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Zhang W, Gu Y, Zhou J, Wang J, Zhao X, Deng X, Li H, Yan L, Jiao X, Shao F. Clinical value of soluble urokinase-type plasminogen activator receptor in predicting sepsis-associated acute kidney injury. Ren Fail 2024; 46:2307959. [PMID: 38289005 PMCID: PMC10829810 DOI: 10.1080/0886022x.2024.2307959] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Accepted: 01/16/2024] [Indexed: 02/01/2024] Open
Abstract
BACKGROUND Sepsis-associated acute kidney injury (S-AKI) is a critical illness and is often associated with high morbidity and mortality rates. The soluble urokinase-type plasminogen activator receptor (suPAR) is an important immune mediator and is involved in kidney injury. However, its diagnostic value in S-AKI patients remains unclear. Therefore, we assessed the early predictive value of suPAR for S-AKI patients. METHODS We prospectively enrolled adult patients, immediately after fulfilling the sepsis-3 criteria. Plasma suPAR levels at 0-, 12-, 24-, and 48-h post-sepsis diagnosis were measured. S-AKI development was the primary outcome. S-AKI risk factors were analyzed using logistic regression, and the value of plasma suPAR for early S-AKI diagnosis was assessed using receiver operating characteristic (ROC) curves. RESULTS Of 179 sepsis patients, 63 (35.2%) developed AKI during hospitalization. At 12-, 24-, and 48-h post-sepsis diagnosis, plasma suPAR levels were significantly higher in patients with S-AKI than in patients without S-AKI (p < 0.05). The plasma suPAR had the highest area under the ROC curve of 0.700 (95% confidence interval (CI), 0.621-0.779) at 24-h post-sepsis diagnosis, at which the best discrimination ability for S-AKI was achieved with suPAR of ≥6.31 ng/mL (sensitivity 61.9% and specificity 71.6%). Logistic regression analysis showed that suPAR at 24-h post-sepsis diagnosis remained an independent S-AKI risk factor after adjusting for mechanical ventilation, blood urea nitrogen, and pH. CONCLUSIONS The findings suggest that plasma suPAR may be a potential biomarker for early S-AKI diagnosis.
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Affiliation(s)
- Wenwen Zhang
- Department of Nephrology, Zhengzhou University People’s Hospital, Henan Provincial People’s Hospital, Zhengzhou, China
| | - Yue Gu
- Department of Nephrology, Henan Provincial Clinical Research Center for Kidney Disease, Henan Key Laboratory for Kidney Disease and Immunology, Zhengzhou University People’s Hospital, Henan Provincial People’s Hospital, Zhengzhou, China
- Department of Nephrology, Henan University People’s Hospital, Henan Provincial People’s Hospital, Zhengzhou, China
| | - Jing Zhou
- Department of Nephrology, Henan Provincial Clinical Research Center for Kidney Disease, Henan Key Laboratory for Kidney Disease and Immunology, Zhengzhou University People’s Hospital, Henan Provincial People’s Hospital, Zhengzhou, China
| | - Juntao Wang
- Department of Nephrology, The First People’s Hospital of Shangqiu, Shangqiu, China
| | - Xiaoru Zhao
- Department of Nephrology, Zhengzhou University People’s Hospital, Henan Provincial People’s Hospital, Zhengzhou, China
| | - Xiaoyu Deng
- Department of Nephrology, Zhengzhou University People’s Hospital, Henan Provincial People’s Hospital, Zhengzhou, China
| | - Han Li
- Department of Nephrology, Henan University People’s Hospital, Henan Provincial People’s Hospital, Zhengzhou, China
| | - Lei Yan
- Department of Nephrology, Henan Provincial Clinical Research Center for Kidney Disease, Henan Key Laboratory for Kidney Disease and Immunology, Zhengzhou University People’s Hospital, Henan Provincial People’s Hospital, Zhengzhou, China
| | - Xiaojing Jiao
- Department of Nephrology, Henan Provincial Clinical Research Center for Kidney Disease, Henan Key Laboratory for Kidney Disease and Immunology, Zhengzhou University People’s Hospital, Henan Provincial People’s Hospital, Zhengzhou, China
| | - Fengmin Shao
- Department of Nephrology, Henan Provincial Clinical Research Center for Kidney Disease, Henan Key Laboratory for Kidney Disease and Immunology, Zhengzhou University People’s Hospital, Henan Provincial People’s Hospital, Zhengzhou, China
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Peng Y, Wang Q, Jin F, Tao T, Qin Q. Assessment of urine CCL2 as a potential diagnostic biomarker for acute kidney injury and septic acute kidney injury in intensive care unit patients. Ren Fail 2024; 46:2313171. [PMID: 38345000 PMCID: PMC10863526 DOI: 10.1080/0886022x.2024.2313171] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Accepted: 01/27/2024] [Indexed: 02/15/2024] Open
Abstract
Acute kidney injury (AKI) is a prevalent and serious condition in the intensive care unit (ICU), associated with significant morbidity and mortality. Septic acute kidney injury (SAKI) contributes substantially to AKI cases in the ICU. However, current diagnostic methods have limitations, necessitating the exploration of novel biomarkers. In this study, we investigated the potential of plasma and urine CCL2 levels as diagnostic markers for AKI and SAKI in 216 ICU patients. Our findings revealed significant differences in plasma (p < 0.01) and urine CCL2 (p < 0.0001) levels between AKI and non-AKI patients in the ICU. Notably, urine CCL2 demonstrated promising predictive value for AKI, exhibiting high specificity and sensitivity (AUC = 0.8976; p < 0.0001). Furthermore, we observed higher urine CCL2 levels in SAKI compared to non-septic AKI (p < 0.001) and urine CCL2 could also differentiate SAKI from non-septic AKI (AUC = 0.7597; p < 0.0001). These results suggest that urine CCL2 levels hold promise as early biomarkers for AKI and SAKI, offering valuable insights for timely intervention and improved management of ICU patients.
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Affiliation(s)
- Yuan Peng
- Intensive Care Unit, The First People’s Hospital of Kunshan Affiliated to Jiangsu University, Kunshan, PR China
| | - Qin Wang
- Intensive Care Unit, The First People’s Hospital of Kunshan Affiliated to Jiangsu University, Kunshan, PR China
| | - Fang Jin
- Intensive Care Unit, The First People’s Hospital of Kunshan Affiliated to Jiangsu University, Kunshan, PR China
| | - Tao Tao
- Intensive Care Unit, The First People’s Hospital of Kunshan Affiliated to Jiangsu University, Kunshan, PR China
| | - Qihong Qin
- Department of Emergency, Suzhou Hospital Affiliated to Nanjing Medical University, Suzhou, PR China
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Cohen M, Banerjee D. Biomarkers in Sepsis: A Current Review of New Technologies. J Intensive Care Med 2024; 39:399-405. [PMID: 37593782 DOI: 10.1177/08850666231194535] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/19/2023]
Abstract
Sepsis syndromes have been recognized since antiquity yet still pose significant challenges to modern medicine. One of the biggest challenges lies in the heterogeneity of triggers and its protean clinical manifestations, as well as its rapidly progressive and lethal nature. Thus, there is a critical need for biomarkers that can quickly and accurately detect sepsis onset and predict treatment response. In this review, we will briefly describe the current consensus definitions of sepsis and the ideal features of a biomarker. We will then delve into currently available and in-development markers of pathogens, hosts, and their interactions that together comprise the sepsis syndrome.
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Affiliation(s)
- Maya Cohen
- Division of Pulmonary, Critical Care, and Sleep Medicine, Alpert/Brown Medical School, Providence, RI, USA
| | - Debasree Banerjee
- Division of Pulmonary, Critical Care, and Sleep Medicine, Alpert/Brown Medical School, Providence, RI, USA
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Lin SP, Xu XJ, Liao C, Zhao N, Chen YY, Tang YM. Prognostic performance of IL-6 and IL-10 in febrile pediatric hematology/oncology patients with normal procalcitonin. J Infect Chemother 2024; 30:387-392. [PMID: 37972690 DOI: 10.1016/j.jiac.2023.11.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Revised: 10/23/2023] [Accepted: 11/11/2023] [Indexed: 11/19/2023]
Abstract
INTRODUCTION It is important to predict adverse outcomes in febrile children with hematology/oncology diseases. Procalcitonin (PCT) is a promising biomarker for the prediction of infection severity, but further studies have revealed its performance in excluding adverse outcomes of infection. IL-6 and IL-10 were reported to have a close association with those infection outcomes. The aim of the study was to investigate the performance of IL-6 and IL-10 in febrile pediatric hematology/oncology patients with normal PCT. METHODS This was a retrospective study conducted in a tertiary children's hospital in China over the past ten years. Inflammatory biomarkers, including IL-6, IL-10, PCT and C-reactive protein (CRP), were detected at the onset of infection. Separate analyses were conducted in patients with neutropenia and without neutropenia. RESULTS In total, 5987 febrile cases were enrolled. For patients with neutropenia, IL-6, IL-10 and PCT were significantly increased in patients with bloodstream infection (BSI), gram-negative bacteremia (GNB) and severe sepsis (SS), but only IL-6 and IL-10 were predictive of GNB and SS. For patients without neutropenia, IL-6, IL-10 and PCT were significantly increased in patients with BSI, GNB and SS, but no biomarkers were predictive of adverse outcomes. All biomarkers failed to exclude patients with fever of unknown origin or upper respiratory infection/bronchitis in patients with neutropenia. CONCLUSIONS IL-6 and IL-10 could be predictors for GNB and SS in febrile patients with neutropenia and had some association with unfavorable outcomes in febrile patients without neutropenia. All biomarkers failed to exclude patients with fever of unknown origin or upper respiratory infection/bronchitis.
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Affiliation(s)
- Shu-Peng Lin
- Division Center of Pediatric Hematology-Oncology, Children's Hospital of Zhejiang University School of Medicine, Research Center of Pediatric Leukemia Diagnostic and Therapeutic Technology of Zhejiang Province, National Medical Research Center for Child Health, Hangzhou, 310003, PR China
| | - Xiao-Jun Xu
- Division Center of Pediatric Hematology-Oncology, Children's Hospital of Zhejiang University School of Medicine, Research Center of Pediatric Leukemia Diagnostic and Therapeutic Technology of Zhejiang Province, National Medical Research Center for Child Health, Hangzhou, 310003, PR China
| | - Chan Liao
- Division Center of Pediatric Hematology-Oncology, Children's Hospital of Zhejiang University School of Medicine, Research Center of Pediatric Leukemia Diagnostic and Therapeutic Technology of Zhejiang Province, National Medical Research Center for Child Health, Hangzhou, 310003, PR China
| | - Ning Zhao
- Division Center of Pediatric Hematology-Oncology, Children's Hospital of Zhejiang University School of Medicine, Research Center of Pediatric Leukemia Diagnostic and Therapeutic Technology of Zhejiang Province, National Medical Research Center for Child Health, Hangzhou, 310003, PR China
| | - Yuan-Yuan Chen
- Division Center of Pediatric Hematology-Oncology, Children's Hospital of Zhejiang University School of Medicine, Research Center of Pediatric Leukemia Diagnostic and Therapeutic Technology of Zhejiang Province, National Medical Research Center for Child Health, Hangzhou, 310003, PR China
| | - Yong-Min Tang
- Division Center of Pediatric Hematology-Oncology, Children's Hospital of Zhejiang University School of Medicine, Research Center of Pediatric Leukemia Diagnostic and Therapeutic Technology of Zhejiang Province, National Medical Research Center for Child Health, Hangzhou, 310003, PR China.
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Heineman T, Orrick C, Phan TK, Denke L, Atem F, Draganic K. Clinical decision support tools useful for identifying sepsis risk. Nursing 2024; 54:50-56. [PMID: 38517502 DOI: 10.1097/01.nurse.0001007628.31606.ee] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/24/2024]
Abstract
PURPOSE Evaluate the effectiveness of the clinical decision support tools (CDSTs), POC Advisor (POCA), and Modified Early Warning System (MEWS) in identifying sepsis risk and influencing time to treatment for inpatients, comparing their respective alert mechanisms. METHODS This study was conducted at two academic university medical center hospitals. Data from adult inpatients in medical-surgical and telemetry units were analyzed from January 1, 2020, to December 31, 2020. Criteria included sepsis-related ICD-10 codes, antibiotic administration, and ordered sepsis labs. Subsequent statistical analyses utilized Fisher's exact test and Wilcoxon Rank Sum test, focusing on mortality differences by age, sex, and race/ethnicity. RESULTS Among 744 patients, 143 sepsis events were identified, with 83% already receiving treatment upon CDST alert. Group 1 (POCA alert) showed reduced response time compared with MEWS, while Group 3 (MEWS) experienced longer time to treatment. Group 4 included sepsis events missed by both systems. Mortality differences were not significant among the groups. CONCLUSION While CDSTs play a role, nursing assessment and clinical judgment are crucial. This study recognized the potential for alarm fatigue due to a high number of CDST-driven alerts, while emphasizing the importance of a collaborative approach for prompt sepsis treatment and potential reduction in sepsis-related mortality.
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Affiliation(s)
- Theresa Heineman
- At the University of Texas Southwestern Medical Center in Dallas, Tx., Theresa Heineman is a rapid response RN, Cary Orrick is a performance improvement coordinator with the Office of Quality and Operational Excellence, Teresa K. Phan is a research manager, Linda Denke is a nurse scientist, Folefac Atem is an adjunct associate professor, and Keri Draganic is an NP with the Cardiovascular and Thoracic Surgery Department
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Machado Lessa CL, Branchini G, Moreira Delfino I, Ramos Voos MH, Teixeira C, Hoher JA, Nunes FB. Comparison of Sepsis-1, 2 and 3 for Predicting Mortality in Septic Patients of a Middle-Income Country: A Retrospective Observational Cohort Study. J Intensive Care Med 2024; 39:349-357. [PMID: 37899601 DOI: 10.1177/08850666231208368] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/31/2023]
Abstract
INTRODUCTION The diagnosis of sepsis is based on expert consensus and does not yet have a "gold standard." With the aim of improving and standardizing diagnostic methods, there have already been three major consensuses on the subject. However, there are still few studies in middle-income countries comparing the methods. This study describes the characteristics of patients diagnosed with sepsis and evaluates and compares the performance of Sepsis-1, 2, and 3 criteria in predicting 28 days, and in-hospital mortality. PATIENTS AND METHODS A retrospective observational cohort study was conducted in the intensive care unit of a tertiary hospital. All admissions between January 1, 2018, and December 31, 2019, were reviewed. Patients diagnosed with sepsis were included. RESULTS During the study period, 653 patients diagnosed with sepsis (by any of the studied criteria) were included in the study. The 28 days mortality rate was 45.8%, and the in-hospital mortality rate was 59.7%. We observed that 72.1% of patients met the minimum criteria for diagnosing sepsis according to the three protocols, and this group also had the highest mortality rate. Age and comorbidities such as cancer and liver cirrhosis were significantly associated with in-hospital mortality. The most common microorganisms were Escherichia coli, Klebsiella spp., and Staphylococcus spp. CONCLUSIONS The study found that most patients met the diagnostic criteria for sepsis using the three methods. Sepsis-2 showed greater sensitivity to predict mortality, while Sequential Organ Failure Assessment showed low accuracy, but was the only significant one. Furthermore, quick Sequential Organ Failure Assessment (qSOFA) had the highest specificity for mortality. Overall, these findings suggest that, although all three methods contribute to the diagnosis and prognosis of sepsis, Sepsis-2 is particularly sensitive in predicting mortality. Sepsis-3 shows some accuracy but requires improvement, and qSOFA exhibits the highest specificity. More research is needed to improve predictive capabilities and patient outcomes.
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Affiliation(s)
| | - Gisele Branchini
- Graduate Program in Pathology, Universidade Federal de Ciências da Saúde de Porto Alegre, Brazil
| | - Isabela Moreira Delfino
- Graduate Program in Health Sciences, Universidade Federal de Ciências da Saúde de Porto Alegre, Brazil
| | | | - Cassiano Teixeira
- Department of Clinical Medicine, Universidade Federal de Ciências da Saúde de Porto Alegre, Brazil
| | - Jorge Amilton Hoher
- Department of Clinical Medicine, Universidade Federal de Ciências da Saúde de Porto Alegre, Brazil
- Central-intensive Care Unit, Complexo Hospitalar Santa Casa de Misericórdia de Porto Alegre, Brazil
| | - Fernanda Bordignon Nunes
- Graduate Program in Pathology, Universidade Federal de Ciências da Saúde de Porto Alegre, Brazil
- School of Health and Life Sciences, Pontifícia Universidade Católica do Rio Grande do Sul, Brazil
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Williams B, Zou L, Pittet JF, Chao W. Sepsis-Induced Coagulopathy: A Comprehensive Narrative Review of Pathophysiology, Clinical Presentation, Diagnosis, and Management Strategies. Anesth Analg 2024; 138:696-711. [PMID: 38324297 PMCID: PMC10916756 DOI: 10.1213/ane.0000000000006888] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/28/2023] [Indexed: 02/08/2024]
Abstract
Physiological hemostasis is a balance between pro- and anticoagulant pathways, and in sepsis, this equilibrium is disturbed, resulting in systemic thrombin generation, impaired anticoagulant activity, and suppression of fibrinolysis, a condition termed sepsis-induced coagulopathy (SIC). SIC is a common complication, being present in 24% of patients with sepsis and 66% of patients with septic shock, and is often associated with poor clinical outcomes and high mortality. 1 , 2 Recent preclinical and clinical studies have generated new insights into the molecular pathogenesis of SIC. In this article, we analyze the complex pathophysiology of SIC with a focus on the role of procoagulant innate immune signaling in hemostatic activation--tissue factor production, thrombin generation, endotheliopathy, and impaired antithrombotic functions. We also review clinical presentations of SIC, the diagnostic scoring system and laboratory tests, the current standard of care, and clinical trials evaluating the efficacies of anticoagulant therapies.
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Affiliation(s)
- Brittney Williams
- From the Division of Cardiothoracic Anesthesia, Department of Anesthesiology, University of Maryland School of Medicine, Baltimore, Maryland
- Translational Research Program, Department of Anesthesiology & Center for Shock, Trauma and Anesthesiology Research (STAR), University of Maryland School of Medicine, Baltimore, Maryland
| | - Lin Zou
- Translational Research Program, Department of Anesthesiology & Center for Shock, Trauma and Anesthesiology Research (STAR), University of Maryland School of Medicine, Baltimore, Maryland
| | - Jean-Francois Pittet
- Division of Critical Care, Department of Anesthesiology and Perioperative Medicine, University of Alabama at Birmingham, Birmingham, Alabama
| | - Wei Chao
- Translational Research Program, Department of Anesthesiology & Center for Shock, Trauma and Anesthesiology Research (STAR), University of Maryland School of Medicine, Baltimore, Maryland
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Nathan N. Sepsis-Induced Coagulopathy: A Prelude to DIC. Anesth Analg 2024; 138:695. [PMID: 38489789 DOI: 10.1213/ane.0000000000006943] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/17/2024]
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Scarlatescu E, Kim PY, Marchenko SP, Tomescu DR. Validation of the time to attain maximal clot amplitude after reaching maximal clot formation velocity parameter as a measure of fibrinolysis using rotational thromboelastometry and its application in the assessment of fibrinolytic resistance in septic patients: a prospective observational study: communication from the ISTH SSC Subcommittee on Fibrinolysis. J Thromb Haemost 2024; 22:1223-1235. [PMID: 38104723 DOI: 10.1016/j.jtha.2023.12.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Revised: 11/12/2023] [Accepted: 12/04/2023] [Indexed: 12/19/2023]
Abstract
BACKGROUND In sepsis, fibrinolysis resistance correlates with worse outcomes. Practically, rotational thromboelastometry (ROTEM) is used to report residual clot amplitude relative to maximum amplitude at specified times after clot formation clot lysis indices (CLIs). However, healthy individuals can exhibit similar CLIs, thus making it challenging to solely diagnose the low fibrinolytic state. Furthermore, CLI does not include the kinetics of clot formation, which can affect overall fibrinolysis. Therefore, a more nuanced analysis, such as time to attain maximal clot amplitude after reaching maximal clot formation velocity (t-AUCi), is needed to better identify fibrinolysis resistance in sepsis. OBJECTIVES To evaluate the correlation between the degree of fibrinolytic activation and t-AUCi in healthy or septic individuals. METHODS Whole blood (n = 60) from septic or healthy donors was analyzed using tissue factor-activated (EXTEM) and nonactivated (NATEM) ROTEM assays. Lysis was initiated with tissue-type plasminogen activator, and CLI and t-AUCi were calculated. Standard coagulation tests and plasma fibrinolysis markers (D-dimer, plasmin-α2-antiplasmin complex, plasminogen activator inhibitor type 1, and plasminogen) were also measured. RESULTS t-AUCi values decreased with increasing fibrinolytic activity and correlated positively with CLI for different degrees of clot lysis both in EXTEM and NATEM. t-AUCi cutoff value of 1962.0 seconds in EXTEM predicted low fibrinolytic activity with 81.8% sensitivity and 83.7% specificity. In addition, t-AUCi is not influenced by clot retraction. CONCLUSION Whole-blood point-of-care ROTEM analyses with t-AUCi offers a more rapid and parametric evaluation of fibrinolytic potential compared with CLI, which can be used for a more rapid and accurate diagnosis of fibrinolysis resistance in sepsis.
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Affiliation(s)
- Ecaterina Scarlatescu
- Carol Davila University of Medicine and Pharmacy, Bucharest, Romania; Department of Anesthesia and Intensive Care III, Fundeni Clinical Institute, Bucharest, Romania.
| | - Paul Y Kim
- Department of Medicine, McMaster University, Hamilton, Ontario, Canada; Thrombosis and Atherosclerosis Research Institute, Hamilton, Ontario, Canada
| | - Sergey P Marchenko
- Department of Cardiac Surgery, Pavlov First St. Petersburg Medical University, St. Petersburg, Russian Federation
| | - Dana R Tomescu
- Carol Davila University of Medicine and Pharmacy, Bucharest, Romania; Department of Anesthesia and Intensive Care III, Fundeni Clinical Institute, Bucharest, Romania
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Casini F, Valentino MS, Lorenzo MG, Caiazzo R, Coppola C, David D, Di Tonno R, Giacomet V. Use of transcriptomics for diagnosis of infections and sepsis in children: A narrative review. Acta Paediatr 2024; 113:670-676. [PMID: 38243675 DOI: 10.1111/apa.17119] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Revised: 01/08/2024] [Accepted: 01/11/2024] [Indexed: 01/21/2024]
Abstract
AIM The aim of this review was to summarise the most recent evidence about the use of omics-based techniques as an instrument for a more rapid and accurate characterisation of respiratory tract infections, neurological infections and sepsis in paediatrics. METHODS We performed a narrative review using PubMed and a set of inclusion criteria: English language articles, clinical trials, meta-analysis and reviews including only paediatric population inherited to this topic in the last 15 years. RESULTS The examined studies suggest that host gene expression signatures are an effective method to characterise the different types of infections, to distinguish infection from colonisation and, in some cases, to assess the severity of the disease in children. CONCLUSIONS 'Omics-based techniques' may help to define the aetiology of infections in paediatrics, representing a useful tool to choose the most appropriate therapies and limit antibiotic resistance.
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Affiliation(s)
- Francesca Casini
- Pediatric Department, "Vittore Buzzi" Children's Hospital, Milan, Italy
| | - Maria Sole Valentino
- Pediatric Infectious Disease Unit, Luigi Sacco Hospital, University of Milan, Milan, Italy
| | - Marc Garcia Lorenzo
- Pediatric Infectious Disease Unit, Luigi Sacco Hospital, University of Milan, Milan, Italy
| | - Roberta Caiazzo
- Pediatric Infectious Disease Unit, Luigi Sacco Hospital, University of Milan, Milan, Italy
| | - Crescenzo Coppola
- Pediatric Infectious Disease Unit, Luigi Sacco Hospital, University of Milan, Milan, Italy
| | - Daniela David
- Pediatric Infectious Disease Unit, Luigi Sacco Hospital, University of Milan, Milan, Italy
| | - Raffaella Di Tonno
- Pediatric Infectious Disease Unit, Luigi Sacco Hospital, University of Milan, Milan, Italy
| | - Vania Giacomet
- Pediatric Infectious Disease Unit, Luigi Sacco Hospital, University of Milan, Milan, Italy
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11
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Li X, Yu T, Tan J. Letter to the editor: Clinical evaluation of Sepsis-1 and Sepsis-3 in infective endocarditis. Int J Cardiol 2024; 400:131752. [PMID: 38185208 DOI: 10.1016/j.ijcard.2024.131752] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Accepted: 01/03/2024] [Indexed: 01/09/2024]
Affiliation(s)
- Xi Li
- Department of Cardiac Surgery, Sichuan Provincial People's Hospital, school of medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Tao Yu
- Department of Cardiac Surgery, Sichuan Provincial People's Hospital, school of medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Jin Tan
- Department of Cardiac Surgery, Sichuan Provincial People's Hospital, school of medicine, University of Electronic Science and Technology of China, Chengdu, China.
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Jiang Z, Li S, Wang L, Yu F, Zeng Y, Li H, Li J, Zhang Z, Zuo J. A comparison of invasive arterial blood pressure measurement with oscillometric non-invasive blood pressure measurement in patients with sepsis. J Anesth 2024; 38:222-231. [PMID: 38305914 DOI: 10.1007/s00540-023-03304-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Accepted: 12/25/2023] [Indexed: 02/03/2024]
Abstract
PURPOSE This study aimed to compare non-invasive oscillometric blood pressure (NIBP) measurement with invasive arterial blood pressure (IBP) measurement in patients with sepsis. METHODS We conducted a retrospective study to evaluate the agreement between IBP and NIBP using the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. Paired blood pressure measurements of mean arterial pressure (MAP), systolic blood pressure (SBP), and diastolic blood pressure (DBP) were compared using Bland-Altman analysis and paired Student's t test. We also focus on the effect of norepinephrine (NE) on the agreement between the two methods and the association between blood pressure and mortality during intensive care unit (ICU) stay. RESULTS A total of 96,673 paired blood pressure measurements from 6060 unique patients were analyzed in the study. In Bland-Altman analysis, the bias (± SD, 95% limits of agreement) was 6.21 mmHg (± 12.05 mmHg, - 17.41 to 29.83 mmHg) for MAP, 0.39 mmHg (± 19.25 mmHg, - 37.34 to 38.12 mmHg) for SBP, and 0.80 mmHg (± 12.92 mmHg, - 24.52 to 26.12 mmHg) for DBP between the two techniques. Similarly, large limits of agreement were shown in different groups of NE doses. NE doses significantly affected the agreement between IBP and NIBP. SBP between the two methods gave an inconsistent assessment of patients' risk of ICU mortality. CONCLUSION IBP and NIBP were not interchangeable in septic patients. Clinicians should be aware that non-invasive MAP was clinically and significantly underestimated invasive MAP.
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Affiliation(s)
- Ziqing Jiang
- Candidate of Master's Degree, The First Clinical Medical College, Guangzhou University of Chinese Medicine, Baiyun District, Guangzhou, Guangdong Province, China
| | - Shaoying Li
- Candidate of Master's Degree, The First Clinical Medical College, Guangzhou University of Chinese Medicine, Baiyun District, Guangzhou, Guangdong Province, China
| | - Lin Wang
- The First Affiliated Hospital of Guangzhou University of Chinese Medicine, 16 Jichang Road, Baiyun District, Guangzhou, Guangdong Province, China
| | - Feng Yu
- The First Affiliated Hospital of Guangzhou University of Chinese Medicine, 16 Jichang Road, Baiyun District, Guangzhou, Guangdong Province, China
| | - Yanping Zeng
- The First Affiliated Hospital of Guangzhou University of Chinese Medicine, 16 Jichang Road, Baiyun District, Guangzhou, Guangdong Province, China
| | - Hongbo Li
- The First Affiliated Hospital of Guangzhou University of Chinese Medicine, 16 Jichang Road, Baiyun District, Guangzhou, Guangdong Province, China
| | - Jun Li
- The First Affiliated Hospital of Guangzhou University of Chinese Medicine, 16 Jichang Road, Baiyun District, Guangzhou, Guangdong Province, China
| | - Zhanfeng Zhang
- The First Affiliated Hospital of Guangzhou University of Chinese Medicine, 16 Jichang Road, Baiyun District, Guangzhou, Guangdong Province, China
| | - Junling Zuo
- The First Affiliated Hospital of Guangzhou University of Chinese Medicine, 16 Jichang Road, Baiyun District, Guangzhou, Guangdong Province, China.
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Deva A, Juthani R, Kugan E, Balamurugan N, Ayyan M. Utility of ED triage tools in predicting the need for intensive respiratory or vasopressor support in adult patients with COVID-19. Am J Emerg Med 2024; 78:151-156. [PMID: 38281375 DOI: 10.1016/j.ajem.2024.01.034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Revised: 01/16/2024] [Accepted: 01/20/2024] [Indexed: 01/30/2024] Open
Abstract
BACKGROUND Serum and radiological parameters used to predict prognosis in COVID patients are not feasible in the Emergency Department. Due to its damaging effect on multiple organs and lungs, scores used to assess multiorgan damage and pneumonia such as Pandemic Medical Early Warning Score (PMEWS), National Early Warning Score 2 (NEWS2), WHO score, quick Sequential Organ Failure Assessment (qSOFA), and DS-CRB 65 can be used to triage patients in the Emergency Department. They can be used to predict patients with the highest risk of seven-day mortality and need for intensive respiratory or vasopressor support (IRVS). PURPOSE The primary purpose was to find the score with the highest AUC in predicting IRVS and mortality at seven days. Additional objective was to find out any independent factors associated with IRVS and mortality. METHODS The data of adult patients who presented to the Emergency Department (ED) between April 1, 2021 and June 30, 2021 were collected. The WHO score, CRB-65, DS-CRB 65, PMEWS, NEWS2, and qSOFA score were calculated for all patients. Statistical analysis was done and an ROC curve was calculated for all the tools for mortality and need for IRVS at seven days. FINDINGS 677 patients presented to the Emergency Department with COVID-19 during the period above. Presence of Diabetes Mellitus (p = 0.001), Hypertension (p = 0.001), and chronic kidney disease(CKD) (p = 0.04) was significantly associated with need for IRVS. Age, duration of symptoms, pulse rate, respiratory rate, room air saturation, mental status at admission, and time to IRVS need were identified as independent predictors of in-hospital mortality. The longer the time to IRVS need from ED arrival, the higher the likelihood of mortality. PMEWS (0.830) had the highest AUC, followed by NEWS2 (0.805). A PMEWS cut-off of 6.5 was 74.2% sensitive and 78.3% specific in predicting the need for IRVS. ROC analysis to predict 7-day mortality showed that PMEWS had an AUC of 0.802 (0.766-0.839). QSOFA performed poorly in predicting IRVS (AUC 0.645) and 7-day mortality (AUC 0.677). CONCLUSION PMEWS may be used for triaging patients presenting to the Emergency Department with COVID-19 and accurately predicts the need for IRVS and seven day mortality.
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Affiliation(s)
- Anandhi Deva
- Department of Emergency Medicine & Trauma, JIPMER, Puducherry, India
| | - Ronit Juthani
- Department of Medicine, Saint Vincent Hospital, Worcester, MA, United States.
| | - Ezhil Kugan
- Department of Emergency Medicine & Trauma, JIPMER, Puducherry, India
| | - N Balamurugan
- Department of Emergency Medicine & Trauma, JIPMER, Puducherry, India
| | - Manu Ayyan
- Department of Emergency Medicine & Trauma, JIPMER, Puducherry, India
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14
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Dartiguelongue JB. Biological significance and clinical utility of lactate in sepsis. ARCH ARGENT PEDIATR 2024; 122:e202310149. [PMID: 38153988 DOI: 10.5546/aap.2023-10149.eng] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2023]
Abstract
Sepsis is a global health problem; progression to septic shock is associated with a marked increase in morbidity and mortality. In this setting, increased plasma lactate levels demonstrated to be an indicator of severity and a predictor of mortality, and are usually interpreted almost exclusively as a marker of low tissue perfusion. However, a recent paradigm shift has occurred in the exegesis of lactate metabolism and its biological properties. Indeed, metabolic adaptation to stress, even with an adequate oxygen supply, may account for high circulating lactate levels. Likewise, other pathophysiological consequences of sepsis, such as mitochondrial dysfunction, are associated with the development of hyperlactatemia, which is not necessarily accompanied by low tissue perfusion. Interpreting the origin and function of lactate may be of great clinical utility in sepsis, especially when circulating lactate levels are the basis for resuscitative measures.
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Affiliation(s)
- Juan B Dartiguelongue
- Emergency Department, Hospital General de Niños Ricardo Gutiérrez, City of Buenos Aires, Argentina
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15
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Schwarzkopf D, Rose N, Fleischmann-Struzek C, Boden B, Dorow H, Edel A, Friedrich M, Gonnert FA, Götz J, Gründling M, Heim M, Holbeck K, Jaschinski U, Koch C, Künzer C, Le Ngoc K, Lindau S, Mehlmann NB, Meschede J, Meybohm P, Ouart D, Putensen C, Sander M, Schewe JC, Schlattmann P, Schmidt G, Schneider G, Spies C, Steinsberger F, Zacharowski K, Zinn S, Reinhart K. Understanding the biases to sepsis surveillance and quality assurance caused by inaccurate coding in administrative health data. Infection 2024; 52:413-427. [PMID: 37684496 PMCID: PMC10954942 DOI: 10.1007/s15010-023-02091-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Accepted: 08/23/2023] [Indexed: 09/10/2023]
Abstract
PURPOSE Timely and accurate data on the epidemiology of sepsis are essential to inform policy decisions and research priorities. We aimed to investigate the validity of inpatient administrative health data (IAHD) for surveillance and quality assurance of sepsis care. METHODS We conducted a retrospective validation study in a disproportional stratified random sample of 10,334 inpatient cases of age ≥ 15 years treated in 2015-2017 in ten German hospitals. The accuracy of coding of sepsis and risk factors for mortality in IAHD was assessed compared to reference standard diagnoses obtained by a chart review. Hospital-level risk-adjusted mortality of sepsis as calculated from IAHD information was compared to mortality calculated from chart review information. RESULTS ICD-coding of sepsis in IAHD showed high positive predictive value (76.9-85.7% depending on sepsis definition), but low sensitivity (26.8-38%), which led to an underestimation of sepsis incidence (1.4% vs. 3.3% for severe sepsis-1). Not naming sepsis in the chart was strongly associated with under-coding of sepsis. The frequency of correctly naming sepsis and ICD-coding of sepsis varied strongly between hospitals (range of sensitivity of naming: 29-71.7%, of ICD-diagnosis: 10.7-58.5%). Risk-adjusted mortality of sepsis per hospital calculated from coding in IAHD showed no substantial correlation to reference standard risk-adjusted mortality (r = 0.09). CONCLUSION Due to the under-coding of sepsis in IAHD, previous epidemiological studies underestimated the burden of sepsis in Germany. There is a large variability between hospitals in accuracy of diagnosing and coding of sepsis. Therefore, IAHD alone is not suited to assess quality of sepsis care.
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Affiliation(s)
- Daniel Schwarzkopf
- Department of Anesthesiology and Intensive Care Medicine, Jena University Hospital, Am Klinikum 1, 07747, Jena, Germany.
| | - Norman Rose
- Institute of Infectious Diseases and Infection Control, Jena University Hospital, Erlanger Allee 103, 07747, Jena, Germany
| | - Carolin Fleischmann-Struzek
- Institute of Infectious Diseases and Infection Control, Jena University Hospital, Erlanger Allee 103, 07747, Jena, Germany
| | - Beate Boden
- Department of Internal Medicine II-Intensive Care, Klinikum Lippe GmbH, Röntgenstraße 18, 32756, Detmold, Germany
| | - Heike Dorow
- Department of Anesthesiology and Intensive Care Medicine, Jena University Hospital, Am Klinikum 1, 07747, Jena, Germany
| | - Andreas Edel
- Department of Anesthesiology and Operative Intensive Care Medicine (CCM, CVK), Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
| | - Marcus Friedrich
- Berlin Institute of Health, Visiting Professor for the Stiftung Charité, Anna-Louisa-Karsch-Str. 2, 10178, Berlin, Germany
| | - Falk A Gonnert
- Department of Anaesthesiology and Intensive Care Medicine, SRH Wald-Klinikum, Straße des Friedens 122, 07548, Gera, Germany
| | - Jürgen Götz
- Department of Internal Medicine II-Intensive Care, Klinikum Lippe GmbH, Röntgenstraße 18, 32756, Detmold, Germany
| | - Matthias Gründling
- Department of Anaesthesiology, Intensive Care Medicine, Emergency Medicine and Pain Medicine, University Medicine Greifswald, Ferdinand-Sauerbruch-Straße, 17475, Greifswald, Germany
| | - Markus Heim
- Department of Anesthesiology and Intensive Care Medicine, Technical University of Munich, School of Medicine, Ismaninger Straße 22, 81675, Munich, Germany
| | - Kirill Holbeck
- Department of Anesthesiology and Intensive Care Medicine, Technical University of Munich, School of Medicine, Ismaninger Straße 22, 81675, Munich, Germany
| | - Ulrich Jaschinski
- Department of Anaesthesiology and Surgical Intensive Care Medicine, Universitätsklinikum Augsburg, Stenglinstr. 2, 86156, Augsburg, Germany
| | - Christian Koch
- Department of Anesthesiology, Intensive Care Medicine and Pain Therapy, University Hospital Gießen, UKGM, Justus-Liebig University Gießen, Rudolf-Buchheim-Straße 7, 35392, Giessen, Germany
| | - Christian Künzer
- Department of Anesthesiology and Operative Intensive Care Medicine (CCM, CVK), Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
| | - Khanh Le Ngoc
- Department of Anaesthesiology and Intensive Care Medicine, SRH Wald-Klinikum, Straße des Friedens 122, 07548, Gera, Germany
| | - Simone Lindau
- Department of Anaesthesiology, Intensive Care Medicine and Pain Therapy, Goethe University, University Hospital Frankfurt, Theodor-Stern-Kai 7, 60590, Frankfurt am Main, Germany
| | - Ngoc B Mehlmann
- Department of Anaesthesiology and Surgical Intensive Care Medicine, Universitätsklinikum Augsburg, Stenglinstr. 2, 86156, Augsburg, Germany
| | - Jan Meschede
- Department of Anesthesiology and Intensive Care Medicine, Technical University of Munich, School of Medicine, Ismaninger Straße 22, 81675, Munich, Germany
| | - Patrick Meybohm
- Department of Anaesthesiology, Intensive Care, Emergency and Pain Medicine, University Hospital Wuerzburg, Oberduerrbacher Straße 6, 97080, Würzburg, Germany
| | - Dominique Ouart
- Department of Anesthesiology and Intensive Care Medicine, Jena University Hospital, Am Klinikum 1, 07747, Jena, Germany
| | - Christian Putensen
- Department of Anaesthesiology and Intensive Care Medicine, University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Michael Sander
- Department of Anesthesiology, Intensive Care Medicine and Pain Therapy, University Hospital Gießen, UKGM, Justus-Liebig University Gießen, Rudolf-Buchheim-Straße 7, 35392, Giessen, Germany
| | - Jens-Christian Schewe
- Department of Anaesthesiology and Intensive Care Medicine, University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
- Department of Anaesthesiology, Intensive Care Medicine, Emergency Medicine and Pain Medicine, University Medical Centre Rostock, Schillingallee 35, 18057, Rostock, Germany
| | - Peter Schlattmann
- Institute for Medical Statistics, Computer Science and Data Science, Jena University Hospital, Bachstraße 18, 07743, Jena, Germany
| | - Götz Schmidt
- Department of Anesthesiology, Intensive Care Medicine and Pain Therapy, University Hospital Gießen, UKGM, Justus-Liebig University Gießen, Rudolf-Buchheim-Straße 7, 35392, Giessen, Germany
| | - Gerhard Schneider
- Department of Anesthesiology and Intensive Care Medicine, Technical University of Munich, School of Medicine, Ismaninger Straße 22, 81675, Munich, Germany
| | - Claudia Spies
- Department of Anesthesiology and Operative Intensive Care Medicine (CCM, CVK), Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
| | - Ferdinand Steinsberger
- Department of Anesthesiology, Intensive Care Medicine and Pain Therapy, University Hospital Gießen, UKGM, Justus-Liebig University Gießen, Rudolf-Buchheim-Straße 7, 35392, Giessen, Germany
| | - Kai Zacharowski
- Department of Anaesthesiology, Intensive Care Medicine and Pain Therapy, Goethe University, University Hospital Frankfurt, Theodor-Stern-Kai 7, 60590, Frankfurt am Main, Germany
| | - Sebastian Zinn
- Department of Anaesthesiology, Intensive Care Medicine and Pain Therapy, Goethe University, University Hospital Frankfurt, Theodor-Stern-Kai 7, 60590, Frankfurt am Main, Germany
| | - Konrad Reinhart
- Department of Anesthesiology and Operative Intensive Care Medicine (CCM, CVK), Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
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Zheng X, Zhao Y, Wang D, Pan S, Yushuaima, Huang Z, Ye M, Zhang S. A new hematological parameter model for the diagnosis and prognosis of sepsis in emergency department: A single-center retrospective study. Int J Lab Hematol 2024; 46:250-258. [PMID: 37904344 DOI: 10.1111/ijlh.14193] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Accepted: 10/13/2023] [Indexed: 11/01/2023]
Abstract
INTRODUCTION Sepsis, a syndrome of organ dysfunction caused by an unregulated host response to infection. This study aimed to develop a novel sepsis diagnostic model of hematological parameters and evaluate its effectiveness in the early identification and prognosis of sepsis in emergency departments. METHODS A retrospective study was conducted in Emergency Department. Cell population data parameters related to monocytes and neutrophils were obtained using the Mindary BC-6800 plus hematology analyzer. Receiver operating characteristic (ROC) curve analysis, logistic regression analysis was performed to assess the performance of the parameters and establish a diagnostic and prognostic model of sepsis, which was then verified with a validation cohort. RESULTS Mon_XW exhibited the best diagnostic performance (area under the ROC curve [AUC] = 0.848, 95% confidence interval [CI]: 0.810-0.885, p < 0.001), followed by Neu_Y and Neu_YW (AUC = 0.777 95% CI: 0.730-0.824, p < 0.001). Logistic regression analysis identified Mon_XW and Neu_Y as independent predictors, which were used to establish a diagnostic model named hematological parameter for sepsis (HPS). HPS demonstrated the best diagnostic performance with an AUC of 0.862 (95% CI: 0.826-0.898, p < 0.001), sensitivity of 70.0%, and specificity of 87.1%, compared to C-reactive protein (CRP) and procalcitonin (PCT). The validation cohort also found that the positive predictive value of HPS was 70.4% and the negative predictive value was 92.2%. CONCLUSION The developed HPS model showed promising diagnostic efficacy for sepsis in the emergency department, which outperformed CRP and PCT in terms of sensitivity and specificity. By enabling early identification and prognosis of sepsis, that contributes to reducing sepsis-related mortality.
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Affiliation(s)
- Xiaohe Zheng
- Department of Laboratory Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Yating Zhao
- Department of Laboratory Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Dong Wang
- Department of Laboratory Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Shiyao Pan
- Department of Clinical Research and Medical Affairs, Shenzhen Mindray Bio-Medical Electronic Co. Ltd., Shenzhen, China
| | - Yushuaima
- Department of Clinical Research and Medical Affairs, Shenzhen Mindray Bio-Medical Electronic Co. Ltd., Shenzhen, China
| | - Zena Huang
- Yunkang School of Medicine and Health, Nanfang College, Guangzhou, China
| | - Manman Ye
- Department of Laboratory Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Shihong Zhang
- Department of Laboratory Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
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Persson I, Macura A, Becedas D, Sjövall F. Early prediction of sepsis in intensive care patients using the machine learning algorithm NAVOY® Sepsis, a prospective randomized clinical validation study. J Crit Care 2024; 80:154400. [PMID: 38245375 DOI: 10.1016/j.jcrc.2023.154400] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Revised: 08/09/2023] [Accepted: 08/11/2023] [Indexed: 01/22/2024]
Abstract
PURPOSE To prospectively validate, in an ICU setting, the prognostic accuracy of the sepsis prediction algorithm NAVOY® Sepsis which uses 4 h of input for routinely collected vital parameters, blood gas values, and lab values. MATERIALS AND METHODS Patients 18 years or older admitted to the ICU at Skåne University Hospital Malmö from December 2020 to September 2021 were recruited in the study. A total of 304 patients were randomized into one of two groups: Algorithm group with active sepsis alerts, or Standard of care. NAVOY® Sepsis made silent predictions in the Standard of care group, in order to evaluate its performance without disturbing the outcome. The study was blinded, i.e., study personnel did not know to which group patients were randomized. The healthcare provider followed standard practices in assessing possible development of sepsis and intervening accordingly. The patients were followed-up in the study until ICU discharge. RESULTS NAVOY® Sepsis could predict the development of sepsis, according to the Sepsis-3 criteria, three hours before sepsis onset with high performance: accuracy 0.79; sensitivity 0.80; and specificity 0.78. CONCLUSIONS The accuracy, sensitivity, and specificity were all high, validating the prognostic accuracy of NAVOY® Sepsis in an ICU setting, including Covid-19 patients.
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Affiliation(s)
- Inger Persson
- Department of Statistics, Uppsala University, Uppsala, Sweden, AlgoDx AB, Stockholm, Sweden.
| | | | | | - Fredrik Sjövall
- Department of Intensive- and Perioperative Medicine, Skåne University Hospital, Malmö, Sweden
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18
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Kallonen A, Juutinen M, Värri A, Carrault G, Pladys P, Beuchée A. Early detection of late-onset neonatal sepsis from noninvasive biosignals using deep learning: A multicenter prospective development and validation study. Int J Med Inform 2024; 184:105366. [PMID: 38330522 DOI: 10.1016/j.ijmedinf.2024.105366] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Revised: 01/15/2024] [Accepted: 01/31/2024] [Indexed: 02/10/2024]
Abstract
BACKGROUND Neonatal sepsis is responsible for significant morbidity and mortality worldwide. Its accurate and timely diagnosis is hindered by vague symptoms and the urgent necessity for early antibiotic intervention. The gold standard for diagnosing the condition is the identification of a pathogenic organism from normally sterile sites via laboratory testing. However, this method is resource-intensive and cannot be conducted continuously. OBJECTIVE This study aimed to predict the onset of late-onset sepsis (LOS) with good diagnostic value as early as possible using non-invasive biosignal measurements from neonatal intensive care unit (NICU) monitors. METHODS In this prospective multicenter study, we developed a multimodal machine learning algorithm based on a convolutional neural network (CNN) structure that uses the power spectral density (PSD) of recorded biosignals to predict the onset of LOS. This approach aimed to discern LOS-related pathogenic spectral signatures without labor-intensive manual artifact removal. RESULTS The model achieved an area under the receiver operating characteristic score of 0.810 (95 % CI 0.698-0.922) on the validation dataset. With an optimal operating point, LOS detection had 83 % sensitivity and 73 % specificity. The median early detection was 44 h before clinical suspicion. The results highlighted the additive importance of electrocardiogram and respiratory impedance (RESP) signals in improving predictive accuracy. According to a more detailed analysis, the predictive power arose from the morphology of the electrocardiogram's R-wave and sudden changes in the RESP signal. CONCLUSION Raw biosignals from NICU monitors, in conjunction with PSD transformation, as input to the CNN, can provide state-of-the-art prediction performance for LOS without the need for artifact removal. To the knowledge of the authors, this is the first study to highlight the independent and additive predictive potential of electrocardiogram R-wave morphology and concurrent, sudden changes in the RESP waveform in predicting the onset of LOS using non-invasive biosignals.
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Affiliation(s)
- Antti Kallonen
- Faculty of Medicine and Health Technology, Tampere University, FI-33014, Tampere, Finland.
| | - Milla Juutinen
- Faculty of Medicine and Health Technology, Tampere University, FI-33014, Tampere, Finland.
| | - Alpo Värri
- Faculty of Medicine and Health Technology, Tampere University, FI-33014, Tampere, Finland.
| | - Guy Carrault
- Inserm, LTSI - UMR 1099, University of Rennes, F-35000, Rennes, France.
| | - Patrick Pladys
- Inserm, LTSI - UMR 1099, University of Rennes, F-35000, Rennes, France; Pediatric Department, CHU Rennes, F-35000, Rennes, France.
| | - Alain Beuchée
- Inserm, LTSI - UMR 1099, University of Rennes, F-35000, Rennes, France; Pediatric Department, CHU Rennes, F-35000, Rennes, France.
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19
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Wu Q, Ye F, Gu Q, Shao F, Long X, Zhan Z, Zhang J, He J, Zhang Y, Xiao Q. A customised down-sampling machine learning approach for sepsis prediction. Int J Med Inform 2024; 184:105365. [PMID: 38350181 DOI: 10.1016/j.ijmedinf.2024.105365] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Revised: 12/17/2023] [Accepted: 01/29/2024] [Indexed: 02/15/2024]
Abstract
OBJECTIVE Sepsis is a life-threatening condition in the ICU and requires treatment in time. Despite the accuracy of existing sepsis prediction models, insufficient focus on reducing alarms could worsen alarm fatigue and desensitisation in ICUs, potentially compromising patient safety. In this retrospective study, we aim to develop an accurate, robust, and readily deployable method in ICUs, only based on the vital signs and laboratory tests. METHODS Our method consists of a customised down-sampling process and a specific dynamic sliding window and XGBoost to offer sepsis prediction. The down-sampling process was applied to the retrospective data for training the XGBoost model. During the testing stage, the dynamic sliding window and the trained XGBoost were used to predict sepsis on the retrospective datasets, PhysioNet and FHC. RESULTS With the filtered data from PhysioNet, our method achieved 80.74% accuracy (77.90% sensitivity and 84.42% specificity) and 83.95% (84.82% sensitivity and 82.00% specificity) on the test set of PhysioNet-A and PhysioNet-B, respectively. The AUC score was 0.89 for both datasets. On the FHC dataset, our method achieved 92.38% accuracy (88.37% sensitivity and 95.16% specificity) and 0.98 AUC score on the test set of FHC. CONCLUSION Our results indicate that the down-sampling process and the dynamic sliding window with XGBoost brought robust and accurate performance to give sepsis prediction under various hospital settings. The localisation and robustness of our method can assist in sepsis diagnosis in different ICU settings.
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Affiliation(s)
- Qinhao Wu
- Apriko Research, Eindhoven, the Netherlands; Department of Mathematics and Computer Science, Eindhoven University of Technology, De Zaale, Eindhoven, 5612 AZ, Noord Brabant, the Netherlands
| | - Fei Ye
- Apriko Research, Eindhoven, the Netherlands
| | - Qianqian Gu
- Digital, Data and Informatics, Natural History Museum, London, SW7 5BD, United Kingdom
| | - Feng Shao
- Apriko Research, Eindhoven, the Netherlands
| | - Xi Long
- Department of Electrical Engineering, Eindhoven University of Technology, De Zaale, Eindhoven, 5612 AZ, Noord Brabant, the Netherlands
| | - Zhuozhao Zhan
- Department of Mathematics and Computer Science, Eindhoven University of Technology, De Zaale, Eindhoven, 5612 AZ, Noord Brabant, the Netherlands
| | - Junjie Zhang
- E.N.T. Department, the First Hospital of Changsha, University of South China, Changsha, 410005, China
| | - Jun He
- Department of Critical Care Medicine, the First Hospital of Changsha, University of South China, Changsha, 410005, China
| | - Yangzhou Zhang
- Department of Critical Care Medicine, Xiangya Hospital, Central South University, Changsha, Changsha, 410008, China.
| | - Quan Xiao
- E.N.T. Department, the First Hospital of Changsha, University of South China, Changsha, 410005, China.
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20
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Venkatesan P. Updated criteria for paediatric sepsis and septic shock. Lancet Infect Dis 2024; 24:e225. [PMID: 38521074 DOI: 10.1016/s1473-3099(24)00168-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/25/2024]
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21
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Jeon Y, Kim S, Ahn S, Park JH, Cho H, Moon S, Lee S. Predicting septic shock in patients with sepsis at emergency department triage using systolic and diastolic shock index. Am J Emerg Med 2024; 78:196-201. [PMID: 38301370 DOI: 10.1016/j.ajem.2024.01.029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Revised: 12/19/2023] [Accepted: 01/15/2024] [Indexed: 02/03/2024] Open
Abstract
INTRODUCTION Identifying patients with at a high risk of progressing to septic shock is essential. Due to systemic vasodilation in the pathophysiology of septic shock, the use of diastolic blood pressure (DBP) has emerged. We hypothesized that the initial shock index (SI) and diastolic SI (DSI) at the emergency department (ED) triage can predict septic shock. METHOD This observational study used the prospectively collected sepsis registry. The primary outcome was progression to septic shock. Secondary outcomes were the time to vasopressor requirement, vasopressor dose, and severity according to SI and DSI. Patients were classified by tertiles according to the first principal component of shock index and diastolic shock index. RESULTS A total of 1267 patients were included in the analysis. The area under the receiver operating characteristic curve (AUC) for predicting progression to septic shock for DSI was 0.717, while that for SI was 0.707. The AUC for predicting progression to septic shock for DSI and SI were significantly higher than those for conventional early warning scores. Middle tertile showed adjusted Odd ratio (aOR) of 1.448 (95% CI 1.074-1.953), and that of upper tertile showed 3.704 (95% CI 2.299-4.111). CONCLUSION The SI and DSI were significant predictors of progression to septic shock. Our findings suggest an association between DSI and vasopressor requirement. We propose stratifying lower tertile as being at low risk, middle tertile as being at intermediate risk, and upper tertile as being at high risk of progression to septic shock. This system can be applied simply at the ED triage.
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Affiliation(s)
- Yumin Jeon
- Department of Emergency Medicine, Korea University Ansan Hospital, 15355, Ansan-si, Republic of Korea
| | - Sungjin Kim
- Department of Emergency Medicine, Korea University Ansan Hospital, 15355, Ansan-si, Republic of Korea
| | - Sejoong Ahn
- Department of Emergency Medicine, Korea University Ansan Hospital, 15355, Ansan-si, Republic of Korea
| | - Jong-Hak Park
- Department of Emergency Medicine, Korea University Ansan Hospital, 15355, Ansan-si, Republic of Korea
| | - Hanjin Cho
- Department of Emergency Medicine, Korea University Ansan Hospital, 15355, Ansan-si, Republic of Korea
| | - Sungwoo Moon
- Department of Emergency Medicine, Korea University Ansan Hospital, 15355, Ansan-si, Republic of Korea
| | - Sukyo Lee
- Department of Emergency Medicine, Korea University Ansan Hospital, 15355, Ansan-si, Republic of Korea.
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Kaur M, Bhat SH, Tiwari R, Kale P, Tripathi DM, Sarin SK, Kaur S, Singh N. Rapid Electrochemical Detection of Bacterial Sepsis in Cirrhotic Patients: A Microscaffold-Based Approach for Early Intervention. Anal Chem 2024; 96:4925-4932. [PMID: 38471137 DOI: 10.1021/acs.analchem.3c05754] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/14/2024]
Abstract
Sepsis is a dysregulated inflammatory response leading to multiple organ failure. Current methods of sepsis detection are time-consuming, involving nonspecific clinical signs, biomarkers, and blood cultures. Hence, efficient and rapid sepsis detection platforms are of utmost need for immediate antibiotic treatment. In the current study, a noninvasive rapid monitoring electrochemical sensing (ECS) platform was developed for the detection and classification of plasma samples of patients with liver cirrhosis by measuring the current peak shifts using the cyclic voltammetry (CV) technique. A total of 61 hospitalized cirrhotic patients with confirmed (culture-positive) or suspected (culture-negative) sepsis were enrolled. The presence of bacteria in the plasma was observed by growth kinetics, and for rapidness, the samples were co-encapsulated in microscaffolds with carbon nanodots that were sensitive enough to detect redox changes occurring due to the change in the pH of the surrounding medium, causing shifts in current peaks in the voltammograms within 2 h. The percentage area under the curve for confirmed infections was 94 and that with suspected cases was 87 in comparison to 69 and 71 with PCT, respectively. Furthermore, the charge was measured for class identification. The charge for LPS-absent bacteria ranged from -400 to -600 μC, whereas the charge for LPS-containing bacteria class ranged from -290 to -300 μC. Thus, the developed cost-effective system was sensitive enough to detect and identify bacterial sepsis.
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Affiliation(s)
- Manleen Kaur
- Centre for Biomedical Engineering, Indian Institute of Technology, New Delhi 110016, India
| | - Sadam H Bhat
- Department of Molecular and Cellular Medicine, Institute of Liver and Biliary Sciences, New Delhi 110070, India
| | - Rajnish Tiwari
- Department of Molecular and Cellular Medicine, Institute of Liver and Biliary Sciences, New Delhi 110070, India
| | - Pratibha Kale
- Department of Microbiology, Institute of Liver and Biliary Sciences, New Delhi 110070, India
| | - Dinesh M Tripathi
- Department of Molecular and Cellular Medicine, Institute of Liver and Biliary Sciences, New Delhi 110070, India
| | - Shiv Kumar Sarin
- Department of Hepatology, Institute of Liver and Biliary Sciences, New Delhi 110070, India
| | - Savneet Kaur
- Department of Molecular and Cellular Medicine, Institute of Liver and Biliary Sciences, New Delhi 110070, India
| | - Neetu Singh
- Centre for Biomedical Engineering, Indian Institute of Technology, New Delhi 110016, India
- Biomedical Engineering Unit, All India Institute of Medical Sciences, Ansari Nagar, New Delhi 110029, India
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Harwood A, Pearson S, Howard J, Jones N, Greenlees R, Broms C, Gardiner SJ, Dalton SC. Pre-hospital, pre-antibiotic blood cultures for patients with suspected sepsis-a feasibility study. N Z Med J 2024; 137:108-112. [PMID: 38513210 DOI: 10.26635/6965.6382] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/23/2024]
Affiliation(s)
- Aileen Harwood
- Medical Student, Faculty of Health Sciences, University of Otago, Christchurch
| | - Scott Pearson
- Emergency Medicine Physician, Emergency Department, Christchurch Hospital, Te Whatu Ora - Waitaha Canterbury
| | - Julia Howard
- Clinical Microbiologist, Canterbury Health Laboratories, Christchurch, Te Whatu Ora - Waitaha Canterbury
| | - Nicole Jones
- Project Specialist, Hato Hone St John Tāmaki Makaurau Auckland
| | - Rosie Greenlees
- Technical Lead - Bacteriology, Canterbury Health Laboratories, Christchurch, Te Whatu Ora - Waitaha Canterbury
| | - Charlotte Broms
- Area Operations Manager Canterbury, Hato Hone St John Tāmaki Makaurau Auckland
| | - Sharon J Gardiner
- Antimicrobial Stewardship Pharmacist, Infection Management Service, Christchurch Hospital, Te Whatu Ora - Waitaha Canterbury
| | - Simon C Dalton
- Infectious Diseases Physician, Infection Management Service, Christchurch Hospital, Te Whatu Ora - Waitaha Canterbury
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Tang Y, Zhu Y, You Z. Mycobacterium tuberculosis sepsis with multiple intermuscular abscesses and respiratory failure as the main manifestations: a case report. BMC Infect Dis 2024; 24:340. [PMID: 38515054 PMCID: PMC10956240 DOI: 10.1186/s12879-024-09187-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Accepted: 03/01/2024] [Indexed: 03/23/2024] Open
Abstract
BACKGROUND Tuberculous sepsis is uncommon in individuals without human immunodeficiency virus (HIV) infection, and some patients may not exhibit clinical signs and symptoms of suspected sepsis upon admission, leading to delayed diagnosis and treatment. CASE PRESENTATION This report present the case of a 60-year-old female patient who presented with erythema, edema, and pain in her right upper limb accompanied by fever and chills. Further evaluation revealed multiple intermuscular abscesses caused by suspected gram-positive bacteria. Despite receiving anti-infection treatment, the patient rapidly progressed to septic shock and respiratory failure. Metagenomic next-generation sequencing (mNGS) analysis of blood samples detected Mycobacterium tuberculosis complex groups (11 reads). Additionally, mNGS analysis of fluid obtained from puncture of the abscess in the right upper extremity also suggested Mycobacterium tuberculosis complex groups (221 981 reads). Consequently, the patient was diagnosed with tuberculous sepsis resulting from hematogenous dissemination of Mycobacterium tuberculosis. Following the administration of anti-tuberculosis treatment, a gradual recovery was observed during the subsequent follow-up period. CONCLUSION It is noteworthy that atypical hematogenous disseminated tuberculosis can be prone to misdiagnosis or oversight, potentially leading to septic shock. This case illustrates the importance of early diagnosis and treatment of tuberculosis sepsis. Advanced diagnostic techniques such as mNGS can aid clinicians in the early identification of pathogens for definitive diagnosis.
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Affiliation(s)
- Yingzi Tang
- Department of Infectious Diseases, First Affiliated Hospital, Army Medical University, Chongqing, China
| | - Ying Zhu
- Department of Infectious Diseases, First Affiliated Hospital, Army Medical University, Chongqing, China
| | - Zhonglan You
- Department of Infectious Diseases, First Affiliated Hospital, Army Medical University, Chongqing, China.
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Rhee C, Strich JR, Chiotos K, Classen DC, Cosgrove SE, Greeno R, Heil EL, Kadri SS, Kalil AC, Gilbert DN, Masur H, Septimus EJ, Sweeney DA, Terry A, Winslow DL, Yealy DM, Klompas M. Improving Sepsis Outcomes in the Era of Pay-for-Performance and Electronic Quality Measures: A Joint IDSA/ACEP/PIDS/SHEA/SHM/SIDP Position Paper. Clin Infect Dis 2024; 78:505-513. [PMID: 37831591 DOI: 10.1093/cid/ciad447] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Indexed: 10/15/2023] Open
Abstract
The Centers for Medicare & Medicaid Services (CMS) introduced the Severe Sepsis/Septic Shock Management Bundle (SEP-1) as a pay-for-reporting measure in 2015 and is now planning to make it a pay-for-performance measure by incorporating it into the Hospital Value-Based Purchasing Program. This joint IDSA/ACEP/PIDS/SHEA/SHM/SIPD position paper highlights concerns with this change. Multiple studies indicate that SEP-1 implementation was associated with increased broad-spectrum antibiotic use, lactate measurements, and aggressive fluid resuscitation for patients with suspected sepsis but not with decreased mortality rates. Increased focus on SEP-1 risks further diverting attention and resources from more effective measures and comprehensive sepsis care. We recommend retiring SEP-1 rather than using it in a payment model and shifting instead to new sepsis metrics that focus on patient outcomes. CMS is developing a community-onset sepsis 30-day mortality electronic clinical quality measure (eCQM) that is an important step in this direction. The eCQM preliminarily identifies sepsis using systemic inflammatory response syndrome (SIRS) criteria, antibiotic administrations or diagnosis codes for infection or sepsis, and clinical indicators of acute organ dysfunction. We support the eCQM but recommend removing SIRS criteria and diagnosis codes to streamline implementation, decrease variability between hospitals, maintain vigilance for patients with sepsis but without SIRS, and avoid promoting antibiotic use in uninfected patients with SIRS. We further advocate for CMS to harmonize the eCQM with the Centers for Disease Control and Prevention's (CDC) Adult Sepsis Event surveillance metric to promote unity in federal measures, decrease reporting burden for hospitals, and facilitate shared prevention initiatives. These steps will result in a more robust measure that will encourage hospitals to pay more attention to the full breadth of sepsis care, stimulate new innovations in diagnosis and treatment, and ultimately bring us closer to our shared goal of improving outcomes for patients.
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Affiliation(s)
- Chanu Rhee
- Department of Population Medicine, Harvard Medical School/Harvard Pilgrim Health Care Institute, Boston, Massachusetts, USA
- Division of Infectious Diseases, Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Jeffrey R Strich
- Critical Care Medicine Department, Clinical Center, National Institutes of Health, Bethesda, Maryland, USA
| | - Kathleen Chiotos
- Department of Anesthesiology and Critical Care Medicine, Children's Hospital of Philadelphia and University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - David C Classen
- Division of Epidemiology, Department of Medicine, University of Utah School of Medicine, Salt Lake City, Utah, USA
| | - Sara E Cosgrove
- Division of Infectious Diseases, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Ron Greeno
- Society of Hospital Medicine, Philadelphia, Pennsylvania, USA
| | - Emily L Heil
- Department of Practice, Sciences, and Health Outcomes Research, University of Maryland School of Pharmacy, Baltimore, Maryland, USA
| | - Sameer S Kadri
- Critical Care Medicine Department, Clinical Center, National Institutes of Health, Bethesda, Maryland, USA
| | - Andre C Kalil
- Division of Infectious Diseases, Department of Internal Medicine, University of Nebraska School of Medicine, Omaha, Nebraska, USA
| | - David N Gilbert
- Division of Infectious Diseases, Department of Medicine, Oregon Health and Science University, Portland, Oregon, USA
| | - Henry Masur
- Critical Care Medicine Department, Clinical Center, National Institutes of Health, Bethesda, Maryland, USA
| | - Edward J Septimus
- Department of Population Medicine, Harvard Medical School/Harvard Pilgrim Health Care Institute, Boston, Massachusetts, USA
- Department of Internal Medicine, Texas A&M College of Medicine, Houston, Texas, USA
| | - Daniel A Sweeney
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, University of California San Diego School of Medicine, San Diego, California, USA
| | - Aisha Terry
- Department of Emergency Medicine, George Washington University School of Medicine, Washington D.C., USA
| | - Dean L Winslow
- Division of Infectious Diseases, Department of Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Donald M Yealy
- Department of Emergency Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Michael Klompas
- Department of Population Medicine, Harvard Medical School/Harvard Pilgrim Health Care Institute, Boston, Massachusetts, USA
- Division of Infectious Diseases, Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
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Fu J, Cai W, Pan S, Chen L, Fang X, Shang Y, Xu J. Developments and Trends of Nanotechnology Application in Sepsis: A Comprehensive Review Based on Knowledge Visualization Analysis. ACS Nano 2024; 18:7711-7738. [PMID: 38427687 DOI: 10.1021/acsnano.3c10458] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/03/2024]
Abstract
Sepsis, a common life-threatening clinical condition, continues to have high morbidity and mortality rates, despite advancements in management. In response, significant research efforts have been directed toward developing effective strategies. Within this scope, nanotechnology has emerged as a particularly promising field, attracting significant interest for its potential to enhance disease diagnosis and treatment. While several reviews have highlighted the use of nanoparticles in sepsis, comprehensive studies that summarize and analyze the hotspots and research trends are lacking. To identify and further promote the development of nanotechnology in sepsis, a bibliometric analysis was conducted on the relevant literature, assessing research trends and hotspots in the application of nanomaterials for sepsis. Next, a comprehensive review of the subjectively recognized research hotspots in sepsis, including nanotechnology-enhanced biosensors and nanoscale imaging for sepsis diagnostics, and nanoplatforms designed for antimicrobial, immunomodulatory, and detoxification strategies in sepsis therapy, is elucidated, while the potential side effects and toxicity risks of these nanomaterials were discussed. Particular attention is given to biomimetic nanoparticles, which mimic the biological functions of source cells like erythrocytes, immune cells, and platelets to evade immune responses and effectively deliver therapeutic agents, demonstrating substantial translational potential. Finally, current challenges and future perspectives of nanotechnology applications in sepsis with a view to maximizing their great potential in the research of translational medicine are also discussed.
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Affiliation(s)
- Jiaji Fu
- Department of Critical Care Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
- The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui 230001, China
- Wuhan Jinyintan Hospital, Tongji Medical College of Huazhong University of Science and Technology, Wuhan 430023, China
| | - Wentai Cai
- The First Clinical College, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
| | - Shangwen Pan
- Department of Critical Care Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
| | - Lang Chen
- Department of Critical Care Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
| | - Xiaowei Fang
- The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui 230001, China
| | - You Shang
- Department of Critical Care Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
- Wuhan Jinyintan Hospital, Tongji Medical College of Huazhong University of Science and Technology, Wuhan 430023, China
| | - Jiqian Xu
- Department of Critical Care Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
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Ali J, Johansen W, Ahmad R. Short turnaround time of seven to nine hours from sample collection until informed decision for sepsis treatment using nanopore sequencing. Sci Rep 2024; 14:6534. [PMID: 38503770 PMCID: PMC10951244 DOI: 10.1038/s41598-024-55635-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Accepted: 02/26/2024] [Indexed: 03/21/2024] Open
Abstract
Bloodstream infections (BSIs) and sepsis are major health problems, annually claiming millions of lives. Traditional blood culture techniques, employed to identify sepsis-causing pathogens and assess antibiotic susceptibility, usually take 2-4 days. Early and accurate antibiotic prescription is vital in sepsis to mitigate mortality and antibiotic resistance. This study aimed to reduce the wait time for sepsis diagnosis by employing shorter blood culture incubation times for BD BACTEC™ bottles using standard laboratory incubators, followed by real-time nanopore sequencing and data analysis. The method was tested on nine blood samples spiked with clinical isolates from the six most prevalent sepsis-causing pathogens. The results showed that pathogen identification was possible at as low as 102-104 CFU/mL, achieved after just 2 h of incubation and within 40 min of nanopore sequencing. Moreover, all the antimicrobial resistance genes were identified at 103-107 CFU/mL, achieved after incubation for 5 h and only 10 min to 3 h of sequencing. Therefore, the total turnaround time from sample collection to the information required for an informed decision on the right antibiotic treatment was between 7 and 9 h. These results hold significant promise for better clinical management of sepsis compared with current culture-based methods.
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Affiliation(s)
- Jawad Ali
- Department of Biotechnology, Inland Norway University of Applied Sciences, Holsetgata 22, 2317, Hamar, Norway
| | - Wenche Johansen
- Department of Biotechnology, Inland Norway University of Applied Sciences, Holsetgata 22, 2317, Hamar, Norway
| | - Rafi Ahmad
- Department of Biotechnology, Inland Norway University of Applied Sciences, Holsetgata 22, 2317, Hamar, Norway.
- Institute of Clinical Medicine, Faculty of Health Sciences, UiT - The Arctic University of Norway, Hansine Hansens Veg 18, 9019, Tromsø, Norway.
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28
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Xavier Costa NDS, da Costa Sigrist G, Schalch AS, Belotti L, Dolhnikoff M, da Silva LFF. Lung tissue expression of epithelial injury markers is associated with acute lung injury severity but does not discriminate sepsis from ARDS. Respir Res 2024; 25:129. [PMID: 38500106 PMCID: PMC10949726 DOI: 10.1186/s12931-024-02761-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Accepted: 03/08/2024] [Indexed: 03/20/2024] Open
Abstract
BACKGROUND Acute respiratory distress syndrome (ARDS) is a common cause of respiratory failure in critically ill patients, and diffuse alveolar damage (DAD) is considered its histological hallmark. Sepsis is one of the most common aetiology of ARDS with the highest case-fatality rate. Identifying ARDS patients and differentiate them from other causes of acute respiratory failure remains a challenge. To address this, many studies have focused on identifying biomarkers that can help assess lung epithelial injury. However, there is scarce information available regarding the tissue expression of these markers. Evaluating the expression of elafin, RAGE, and SP-D in lung tissue offers a potential bridge between serological markers and the underlying histopathological changes. Therefore, we hypothesize that the expression of epithelial injury markers varies between sepsis and ARDS as well as according to its severity. METHODS We compared the post-mortem lung tissue expression of the epithelial injury markers RAGE, SP-D, and elafin of patients that died of sepsis, ARDS, and controls that died from non-pulmonary causes. Lung tissue was collected during routine autopsy and protein expression was assessed by immunohistochemistry. We also assessed the lung injury by a semi-quantitative analysis. RESULTS We observed that all features of DAD were milder in septic group compared to ARDS group. Elafin tissue expression was increased and SP-D was decreased in the sepsis and ARDS groups. Severe ARDS expressed higher levels of elafin and RAGE, and they were negatively correlated with PaO2/FiO2 ratio, and positively correlated with bronchopneumonia percentage and hyaline membrane score. RAGE tissue expression was negatively correlated with mechanical ventilation duration in both ARDS and septic groups. In septic patients, elafin was positively correlated with ICU admission length, SP-D was positively correlated with serum lactate and RAGE was correlated with C-reactive protein. CONCLUSIONS Lung tissue expression of elafin and RAGE, but not SP-D, is associated with ARDS severity, but does not discriminate sepsis patients from ARDS patients.
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Affiliation(s)
| | - Giovana da Costa Sigrist
- Departamento de Patologia, Faculdade de Medicina da Universidade de São Paulo, São Paulo, LIM-05, Brazil
| | - Alexandre Santos Schalch
- Departamento de Patologia, Faculdade de Medicina da Universidade de São Paulo, São Paulo, LIM-05, Brazil
| | - Luciano Belotti
- Departamento de Patologia, Faculdade de Medicina da Universidade de São Paulo, São Paulo, LIM-05, Brazil
| | - Marisa Dolhnikoff
- Departamento de Patologia, Faculdade de Medicina da Universidade de São Paulo, São Paulo, LIM-05, Brazil
| | - Luiz Fernando Ferraz da Silva
- Departamento de Patologia, Faculdade de Medicina da Universidade de São Paulo, São Paulo, LIM-05, Brazil
- Serviço de Verificação de Óbitos da Capital, Universidade de São Paulo, São Paulo, Brazil
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29
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Yang M, Chen H, Hu W, Mischi M, Shan C, Li J, Long X, Liu C. Development and Validation of an Interpretable Conformal Predictor to Predict Sepsis Mortality Risk: Retrospective Cohort Study. J Med Internet Res 2024; 26:e50369. [PMID: 38498038 DOI: 10.2196/50369] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Revised: 10/16/2023] [Accepted: 01/24/2024] [Indexed: 03/19/2024] Open
Abstract
BACKGROUND Early and reliable identification of patients with sepsis who are at high risk of mortality is important to improve clinical outcomes. However, 3 major barriers to artificial intelligence (AI) models, including the lack of interpretability, the difficulty in generalizability, and the risk of automation bias, hinder the widespread adoption of AI models for use in clinical practice. OBJECTIVE This study aimed to develop and validate (internally and externally) a conformal predictor of sepsis mortality risk in patients who are critically ill, leveraging AI-assisted prediction modeling. The proposed approach enables explaining the model output and assessing its confidence level. METHODS We retrospectively extracted data on adult patients with sepsis from a database collected in a teaching hospital at Beth Israel Deaconess Medical Center for model training and internal validation. A large multicenter critical care database from the Philips eICU Research Institute was used for external validation. A total of 103 clinical features were extracted from the first day after admission. We developed an AI model using gradient-boosting machines to predict the mortality risk of sepsis and used Mondrian conformal prediction to estimate the prediction uncertainty. The Shapley additive explanation method was used to explain the model. RESULTS A total of 16,746 (80%) patients from Beth Israel Deaconess Medical Center were used to train the model. When tested on the internal validation population of 4187 (20%) patients, the model achieved an area under the receiver operating characteristic curve of 0.858 (95% CI 0.845-0.871), which was reduced to 0.800 (95% CI 0.789-0.811) when externally validated on 10,362 patients from the Philips eICU database. At a specified confidence level of 90% for the internal validation cohort the percentage of error predictions (n=438) out of all predictions (n=4187) was 10.5%, with 1229 (29.4%) predictions requiring clinician review. In contrast, the AI model without conformal prediction made 1449 (34.6%) errors. When externally validated, more predictions (n=4004, 38.6%) were flagged for clinician review due to interdatabase heterogeneity. Nevertheless, the model still produced significantly lower error rates compared to the point predictions by AI (n=1221, 11.8% vs n=4540, 43.8%). The most important predictors identified in this predictive model were Acute Physiology Score III, age, urine output, vasopressors, and pulmonary infection. Clinically relevant risk factors contributing to a single patient were also examined to show how the risk arose. CONCLUSIONS By combining model explanation and conformal prediction, AI-based systems can be better translated into medical practice for clinical decision-making.
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Affiliation(s)
- Meicheng Yang
- State Key Laboratory of Digital Medical Engineering, School of Instrument Science and Engineering, Southeast University, Nanjing, China
| | - Hui Chen
- Department of Critical Care Medicine, Jiangsu Provincial Key Laboratory of Critical Care Medicine, Zhongda Hospital, Southeast University, Nanjing, China
| | - Wenhan Hu
- Department of Critical Care Medicine, Jiangsu Provincial Key Laboratory of Critical Care Medicine, Zhongda Hospital, Southeast University, Nanjing, China
| | - Massimo Mischi
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands
| | - Caifeng Shan
- College of Electrical Engineering and Automation, Shandong University of Science and Technology, Qingdao, China
- School of Intelligence Science and Technology, Nanjing University, Nanjing, China
| | - Jianqing Li
- State Key Laboratory of Digital Medical Engineering, School of Instrument Science and Engineering, Southeast University, Nanjing, China
- School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, China
| | - Xi Long
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands
| | - Chengyu Liu
- State Key Laboratory of Digital Medical Engineering, School of Instrument Science and Engineering, Southeast University, Nanjing, China
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Jamali Z, Mohammadpour N, Sinaei R, Jafari M, Sabzevari F, Hasannejad M. The footprint of SARS-COV-2 infection in neonatal late sepsis. BMC Pediatr 2024; 24:184. [PMID: 38491449 PMCID: PMC10943770 DOI: 10.1186/s12887-024-04665-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Accepted: 02/22/2024] [Indexed: 03/18/2024] Open
Abstract
BACKGROUND Predicting and finding the viral agents responsible for neonatal late-sepsis has always been challenging. METHOD In this cross-sectional study, which has been done from September 2020 to December 2022, 145 hospitalized neonates suspected to late-onset sepsis alongside routine sepsis workup, were also evaluated for severe acute respiratory syndrome-coronavirus-2 (SARS-COV-2) infection, by nasopharyngeal real-time polymerase chain reaction (RT-PCR) or serological tests. RESULT 145 neonates including 81 girls and 64 boys with a mean age of 12.3 ± 5.9 days and an average hospitalization stay of 23.1 ± 15.4 days were enrolled in the study. While 76.6% of them had negative bacterial culture, 63 patients (43.4%) showed evidence of SARS-COV-2 infection in RT-PCR or serology tests. None of the underlying factors including gender, age, and laboratory investigation had a significant relationship with SARS-COV-2 infection. Similarly, the outcomes of death and length of hospitalization were not different between the two groups with positive and negative SARS-COV-2 RT-PCR (P < 0.05). There was only a significant relationship between radiological changes including reticulonodular pattern, consolidation, pleural effusion, and different types of infiltrations and SARS-COV2 infection. CONCLUSION Considering the widespread of coronavirus disease 2019 (COVID-19) in newborns, it seems logical to investigate the SARS-COV-2 infection in late-sepsis.
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Affiliation(s)
- Zahra Jamali
- Department of Pediatrics, School of Medicine, Kerman University of Medical Sciences, Kerman, Iran
| | - Najmeh Mohammadpour
- Clinical Research Development Unit, Afzalipour Hospital, Kerman University of Medical Sciences, Kerman, Iran
| | - Reza Sinaei
- Department of Pediatrics, School of Medicine, Kerman University of Medical Sciences, Kerman, Iran.
- Endocrinology and Metabolism Research Center, Institute of Basic and Clinical Physiology Sciences, Kerman University of Medical Sciences, Kerman, Iran.
| | - Maedeh Jafari
- Department of Pediatrics, School of Medicine, Kerman University of Medical Sciences, Kerman, Iran
| | - Fatemeh Sabzevari
- Department of Pediatrics, Afzalipour Hospital, Kerman University of Medical Sciences, Kerman, Iran
| | - Mohammad Hasannejad
- Department of Laboratory Sciences, School of Medicine, Bam University of Medical Sciences, Bam, Iran
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31
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Ranjit S, Natraj R. Hemodynamic Management Strategies in Pediatric Septic Shock: Ten Concepts for the Bedside Practitioner. Indian Pediatr 2024; 61:265-275. [PMID: 38217271] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2024]
Abstract
The three pathophysiologic contributors to septic shock include varying combinations of hypovolemia (relative > absolute), decreased vascular tone or vasoplegia, and myocardial dysfunction. The three pillars of hemodynamic support include fluid boluses, vasopressors with or without inotrope infusions. The three end-points of hemodynamic resuscitation include an adequate cardiac output (CO), adequate mean arterial pressure (MAP) and diastolic blood pressure (DBP) for organ perfusion, and avoiding congestion (worse filling) parameters. Only 33-50% of septic patients show post-fluid bolus CO improvements; this may be sustained in ≥10% on account of sepsis-mediated glycocalyx injury. A pragmatic approach is to administer a small bolus (10 mL/kg over 20-30 min) and judge the response based on clinical perfusion markers, pressure elements, and congestive features. Vasoplegia marked by low DBP is a major contributor to hypotension in septic shock. Hence, a strategy of restricted fluid bolus with early low-dose norepinephrine (NE) (0.05-0.1 µg/kg/min) can be helpful. NE may also be useful in septic myocardial dysfunction (SMD) as an initial agent to maintain adequate coronary perfusion and DBP while minimizing tachycardia and providing inotropy. Severe SMD may benefit from additional inotropy (epinephrine/dobutamine). Except vasopressin, most vasoactive drugs may safely be administered via a peripheral route. The lowest MAP (5th centile for age) may be an acceptable target, provided end-organ perfusion is satisfactory. A clinical individualized approach combining the history, serial physical examination, laboratory analyses, available monitoring tools, and repeated assessment to individualize circulatory support may to lead to better outcomes than one-size-fits-all algorithms.
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Affiliation(s)
- Suchitra Ranjit
- Pediatric Intensive Care Unit, Apollo Children's Hospitals, Chennai, Tamil Nadu, India. Correspondence to: Dr. Suchitra Ranjit, Apollo Children's Hospital, Chennai, Tamil Nadu, India.
| | - Rajeswari Natraj
- Pediatric Intensive Care Unit, Apollo Children's Hospitals, Chennai, Tamil Nadu, India
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DeMerle KM, Kennedy JN, Chang CCH, Delucchi K, Huang DT, Kravitz MS, Shapiro NI, Yealy DM, Angus DC, Calfee CS, Seymour CW. Identification of a hyperinflammatory sepsis phenotype using protein biomarker and clinical data in the ProCESS randomized trial. Sci Rep 2024; 14:6234. [PMID: 38485953 PMCID: PMC10940677 DOI: 10.1038/s41598-024-55667-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Accepted: 02/26/2024] [Indexed: 03/18/2024] Open
Abstract
Sepsis is a heterogeneous syndrome and phenotypes have been proposed using clinical data. Less is known about the contribution of protein biomarkers to clinical sepsis phenotypes and their importance for treatment effects in randomized trials of resuscitation. The objective is to use both clinical and biomarker data in the Protocol-Based Care for Early Septic Shock (ProCESS) randomized trial to determine sepsis phenotypes and to test for heterogeneity of treatment effect by phenotype comparing usual care to protocolized early, goal-directed therapy(EGDT). In this secondary analysis of a subset of patients with biomarker sampling in the ProCESS trial (n = 543), we identified sepsis phenotypes prior to randomization using latent class analysis of 20 clinical and biomarker variables. Logistic regression was used to test for interaction between phenotype and treatment arm for 60-day inpatient mortality. Among 543 patients with severe sepsis or septic shock in the ProCESS trial, a 2-class model best fit the data (p = 0.01). Phenotype 1 (n = 66, 12%) had increased IL-6, ICAM, and total bilirubin and decreased platelets compared to phenotype 2 (n = 477, 88%, p < 0.01 for all). Phenotype 1 had greater 60-day inpatient mortality compared to Phenotype 2 (41% vs 16%; p < 0.01). Treatment with EGDT was associated with worse 60-day inpatient mortality compared to usual care (58% vs. 23%) in Phenotype 1 only (p-value for interaction = 0.05). The 60-day inpatient mortality was similar comparing EGDT to usual care in Phenotype 2 (16% vs. 17%). We identified 2 sepsis phenotypes using latent class analysis of clinical and protein biomarker data at randomization in the ProCESS trial. Phenotype 1 had increased inflammation, organ dysfunction and worse clinical outcomes compared to phenotype 2. Response to EGDT versus usual care differed by phenotype.
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Affiliation(s)
- Kimberley M DeMerle
- Clinical Research, Investigation, and Systems Modeling of Acute Illness (CRISMA) Center, Pittsburgh, PA, USA
- Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Jason N Kennedy
- Clinical Research, Investigation, and Systems Modeling of Acute Illness (CRISMA) Center, Pittsburgh, PA, USA
- Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Chung-Chou H Chang
- Clinical Research, Investigation, and Systems Modeling of Acute Illness (CRISMA) Center, Pittsburgh, PA, USA
- Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Kevin Delucchi
- Department of Psychiatry, University of California San Francisco, San Francisco, CA, USA
| | - David T Huang
- Clinical Research, Investigation, and Systems Modeling of Acute Illness (CRISMA) Center, Pittsburgh, PA, USA
- Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Emergency Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Multidisciplinary Acute Care Research Organization (MACRO), Pittsburgh, PA, USA
| | - Max S Kravitz
- Department of Emergency Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Nathan I Shapiro
- Department of Emergency Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Center for Vascular Biology Research, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Donald M Yealy
- Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Emergency Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Derek C Angus
- Clinical Research, Investigation, and Systems Modeling of Acute Illness (CRISMA) Center, Pittsburgh, PA, USA
- Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Emergency Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Carolyn S Calfee
- Division of Pulmonary and Critical Care Medicine, Department of Medicine and Anesthesia, University of California San Francisco, San Francisco, CA, USA
| | - Christopher W Seymour
- Clinical Research, Investigation, and Systems Modeling of Acute Illness (CRISMA) Center, Pittsburgh, PA, USA.
- Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
- Department of Emergency Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
- Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh, 3459 Fifth Avenue, NW628, Pittsburgh, PA, 15213, USA.
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Kvalvik SA, Zakariassen SB, Overrein S, Rasmussen S, Skrede S, Baghestan E. Obstetric infections and clinical characteristics of maternal sepsis: a hospital-based retrospective cohort study. Sci Rep 2024; 14:6067. [PMID: 38480912 PMCID: PMC10937963 DOI: 10.1038/s41598-024-56486-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Accepted: 03/07/2024] [Indexed: 03/17/2024] Open
Abstract
Sepsis is responsible for 50% of intrahospital maternal deaths worldwide. Incidence is increasing in both low and middle-, and high-income countries. There is little data on incidence and clinical outcomes of obstetric infections including maternal sepsis in the Nordic countries. The aims of this study are to give estimates of the occurrence of obstetric infections and maternal sepsis in a Norwegian hospital cohort, assess the quality of management of maternal sepsis cases, and evaluate the usefulness of diagnostic codes to identify maternal sepsis retrospectively. We conducted a retrospective cohort study of pregnant, labouring, post-abortion, and postpartum women. We assessed the accuracy of the diagnostic code most frequently applied for maternal sepsis, O85. We found 7.8% (95% confidence interval 7.1-8.5) infection amongst pregnant, labouring, and postpartum women. The incidence of maternal sepsis was 0.3% (95% confidence interval 0.2-0.5), and the majority of sepsis cases were recorded in the postpartum period. Two thirds of women were given broad-spectrum antibiotics at the time sepsis was diagnosed, but only 15.4% of women with puerperal sepsis were given antimicrobials in accordance with national guidelines. When used retrospectively, obstetric infection codes are insufficient in identifying both maternal and puerperal sepsis, with only 20.3% positive predictive value for both conditions. In conclusion, obstetric infections contribute significantly to maternal morbidity in Norway's second largest maternity hospital. This study provides incidences of maternal infections for hospitalised patients in temporal relation to pregnancy, labour, abortion and the postpartum period, knowledge which is valuable for planning of health care services and allocation of resources. In addition, the study highlights areas where improvement is needed in clinical handling of maternal sepsis. There is need for studies on the management quality and use of correct diagnostic codes in this patient category.
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Affiliation(s)
- Sedina Atic Kvalvik
- Department of Obstetrics and Gynaecology, Haukeland University Hospital, Pb 1400, 5021, Bergen, Norway.
- Department of Clinical Science, University of Bergen, Pb 7804, 5020, Bergen, Norway.
| | | | - Sofie Overrein
- Department of Clinical Science, University of Bergen, Pb 7804, 5020, Bergen, Norway
| | - Svein Rasmussen
- Department of Clinical Science, University of Bergen, Pb 7804, 5020, Bergen, Norway
| | - Steinar Skrede
- Department of Clinical Science, University of Bergen, Pb 7804, 5020, Bergen, Norway
- Department of Medicine, Haukeland University Hospital, Pb 1400, 5021, Bergen, Norway
| | - Elham Baghestan
- Department of Obstetrics and Gynaecology, Haukeland University Hospital, Pb 1400, 5021, Bergen, Norway
- Department of Clinical Science, University of Bergen, Pb 7804, 5020, Bergen, Norway
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Iyer V, Castro D, Malla B, Panda B, Rabson AR, Horowitz G, Heger N, Gupta K, Singer A, Norwitz ER. Culture-independent identification of bloodstream infections from whole blood: prospective evaluation in specimens of known infection status. J Clin Microbiol 2024; 62:e0149823. [PMID: 38315022 PMCID: PMC10935643 DOI: 10.1128/jcm.01498-23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Accepted: 12/19/2023] [Indexed: 02/07/2024] Open
Abstract
Sepsis caused by bloodstream infection (BSI) is a major healthcare burden and a leading cause of morbidity and mortality worldwide. Timely diagnosis is critical to optimize clinical outcome, as mortality rates rise every hour treatment is delayed. Blood culture remains the "gold standard" for diagnosis but is limited by its long turnaround time (1-7 days depending on the organism) and its potential to provide false-negative results due to interference by antimicrobial therapy or the presence of mixed (i.e., polymicrobial) infections. In this paper, we evaluated the performance of resistance and pathogen ID/BSI, a direct-from-specimen molecular assay. To reduce the false-positivity rate common with molecular methods, this assay isolates and detects genomic material only from viable microorganisms in the blood by incorporating a novel precursor step to selectively lyse host and non-viable microbial cells and remove cell-free genomic material prior to lysis and analysis of microbial cells. Here, we demonstrate that the assay is free of interference from host immune cells and common antimicrobial agents at elevated concentrations. We also demonstrate the accuracy of this technology in a prospective cohort pilot study of individuals with known sepsis/BSI status, including samples from both positive and negative individuals. IMPORTANCE Blood culture remains the "gold standard" for the diagnosis of sepsis/bloodstream infection (BSI) but has many limitations which may lead to a delay in appropriate and accurate treatment in patients. Molecular diagnostic methods have the potential for markedly improving the management of such patients through faster turnaround times and increased accuracy. But molecular diagnostic methods have not been widely adopted for the identification of BSIs. By incorporating a precursor step of selective lysis of host and non-viable microorganisms, our resistance and pathogen ID (RaPID)/BSI molecular assay addresses many limitations of blood culture and other molecular assay. The RaPID/BSI assay has an approximate turnaround time of 4 hours, thereby significantly reducing the time to appropriate and accurate diagnosis of causative microorganisms in such patients. The short turnaround time also allows for close to real-time tracking of pathogenic clearance of microorganisms from the blood of these patients or if a change of antimicrobial regimen is required. Thus, the RaPID/BSI molecular assay helps with optimization of antimicrobial stewardship; prompt and accurate diagnosis of sepsis/BSI could help target timely treatment and reduce mortality and morbidity in such patients.
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Affiliation(s)
- Vidya Iyer
- Department of Obstetrics and Gynecology, Tufts Medical Center, Boston, Massachusetts, USA
- Department of Obstetrics and Gynecology, Tufts University School of Medicine, Boston, Massachusetts, USA
- Division of Clinical Research, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Daniel Castro
- Department of Obstetrics and Gynecology, Tufts Medical Center, Boston, Massachusetts, USA
| | - Bipin Malla
- Department of Obstetrics and Gynecology, Tufts Medical Center, Boston, Massachusetts, USA
| | - Britta Panda
- Department of Obstetrics and Gynecology, Tufts Medical Center, Boston, Massachusetts, USA
| | - Arthur R. Rabson
- Department of Pathology and Laboratory Medicine, Tufts Medical Center, Boston, Massachusetts, USA
| | - Gary Horowitz
- Department of Pathology and Laboratory Medicine, Tufts Medical Center, Boston, Massachusetts, USA
| | - Nicholas Heger
- Department of Pathology and Laboratory Medicine, Tufts Medical Center, Boston, Massachusetts, USA
| | | | - Alon Singer
- HelixBind Inc., Boxborough, Massachusetts, USA
| | - Errol R. Norwitz
- Department of Obstetrics and Gynecology, Tufts Medical Center, Boston, Massachusetts, USA
- Department of Obstetrics and Gynecology, Tufts University School of Medicine, Boston, Massachusetts, USA
- Division of Clinical Research, Massachusetts General Hospital, Boston, Massachusetts, USA
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Mokhtar WA, Sherief LM, Kamal NM, ElSheikh AO, Omran FH, Abdulsaboor A, Sakr MM, El Gebally S, Shehab MMM, Alfaifi J, Turkistani R, Aljuaid F, Oshi MA, Elbekoushi FB, Mokhtar GA. Late onset neonatal sepsis: Can plasma gelsolin be a promising diagnostic marker? Medicine (Baltimore) 2024; 103:e37356. [PMID: 38457556 PMCID: PMC10919505 DOI: 10.1097/md.0000000000037356] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Revised: 01/31/2024] [Accepted: 02/02/2024] [Indexed: 03/10/2024] Open
Abstract
Plasma gelsolin (pGSN) correlates with clinical improvement in septic patients. We aimed to investigate pGSN levels as a diagnostic and prognostic marker of neonatal late-onset-sepsis (LOS). A case-control study was done on 184 neonates (92 with LOS and 92 controls). All participants were subjected to detailed history taking, full clinical evaluation, sepsis workup, and pGSN enzyme-linked immunosorbent-assay measurement. We detected significantly lower pGSN level among cases compared to controls (90.63 ± 20.64 vs 451.83 ± 209.59). It was significantly related to the severity of sepsis and mortality, with significantly lower values among cases with septic shock and multiorgan failure and non-survivors. Follow-up pGSN significantly increased after sepsis improvement in survivors compared to admission values. pGSN might be a reliable diagnostic and prognostic marker for LOS.
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Affiliation(s)
- Wesam A. Mokhtar
- Pediatric Department, Faculty of Medicine, Zagazig University, Zagazig, Egypt
| | - Laila M. Sherief
- Pediatric Department, Faculty of Medicine, Zagazig University, Zagazig, Egypt
| | - Naglaa M. Kamal
- Pediatric Department, Faculty of Medicine, Cairo University, Giza, Egypt
| | - Azza O. ElSheikh
- Medical Microbiology and Immunology Department, Faculty of Medicine, Zagazig University, Zagazig, Egypt
| | - Farida H. Omran
- Medical Microbiology and Immunology Department, Faculty of Medicine, Zagazig University, Zagazig, Egypt
| | - Ahmed Abdulsaboor
- Clinical Pathology Department, Faculty of Medicine, Zagazig University, Zagazig, Egypt
| | - Maha M.H. Sakr
- Clinical Pathology Department, Faculty of Medicine, Zagazig University, Zagazig, Egypt
| | - Shreif El Gebally
- Pediatric Department, Faculty of Medicine, Zagazig University, Zagazig, Egypt
| | | | - Jaber Alfaifi
- Department of Child Health, Faculty of Medicine, University of Bisha, Bisha, Kingdom of Saudi Arabia
| | - Reem Turkistani
- Pediatric Department, Alhada Armed Forces Hospital, Taif, Kingdom of Saudi Arabia
| | - Futun Aljuaid
- Pediatric Department, Taif Children Hospital, Taif, Kingdom of Saudi Arabia
| | - Mohammed A.M. Oshi
- Neurology Division, Pediatric Department, Gaafar Ibnauf Children’s Emergency Hospital, Khartoum, Sudan
| | | | - Ghada A. Mokhtar
- Medical Microbiology and Immunology Department, Faculty of Medicine, Zagazig University, Zagazig, Egypt
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Tsai YW, Zhang B, Chou HY, Chen HJ, Hsu YC, Shiue YL. Clinical impacts of the rapid diagnostic method on positive blood cultures. Lab Med 2024; 55:179-184. [PMID: 37352545 DOI: 10.1093/labmed/lmad057] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/25/2023] Open
Abstract
OBJECTIVE This study aimed to evaluate the impact of short-term incubation (STI) protocol on clinical outcomes of bloodstream infection (BSI) patients. METHODS A total of 1363 positive blood culture records from January 2019 to December 2021 were included. The main clinical outcomes included pathogen identification turnaround time (TAT), antimicrobial susceptibility testing (AST) TAT, and length of total hospital stay. RESULTS The TAT of pathogen identification and AST significantly decreased after implementing the STI protocol (2.2 vs 1.4 days and 3.4 vs 2.5 days, respectively, with P < .001 for both). Moreover, for patients with Gram-negative bacteria (GNB)-infected BSIs, the length of total hospital stay decreased from 31.9 days to 27.1 days, indicating that these patients could be discharged 5 days earlier after implementing the STI protocol (P < .01). CONCLUSION The protocol led to a significant reduction in TAT and improved clinical outcomes, particularly for GNB organisms. The findings suggest that the STI protocol can improve patient outcomes and hospital resource utilization in the management of BSIs.
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Affiliation(s)
- Ya-Wen Tsai
- Center for Integrative Medicine, Tainan City, Taiwan
- Institute of Biomedical Sciences, National Sun Yat-sen University, Kaohsiung, Taiwan
| | - Bin Zhang
- Division of Biostatistics and Epidemiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, US
| | - Hsiu-Yin Chou
- Center for Integrative Medicine, Tainan City, Taiwan
| | - Hung-Jui Chen
- Division of Infectious Diseases, Department of Internal Medicine, Tainan City, Taiwan
| | - Yu-Chi Hsu
- Information Systems Office, Chi Mei Medical Center, Tainan City, Taiwan
| | - Yow-Ling Shiue
- Institute of Biomedical Sciences, National Sun Yat-sen University, Kaohsiung, Taiwan
- Institute of Precision Medicine, National Sun Yat-sen University, Kaohsiung, Taiwan
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37
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Wu M, Deng Y, Wang X, He B, Wei F, Zhang Y. Development of risk prediction nomogram for neonatal sepsis in Group B Streptococcus-colonized mothers: a retrospective study. Sci Rep 2024; 14:5629. [PMID: 38453985 PMCID: PMC10920653 DOI: 10.1038/s41598-024-55783-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Accepted: 02/27/2024] [Indexed: 03/09/2024] Open
Abstract
Neonatal clinical sepsis is recognized as a significant health problem, This study sought to identify a predictive model of risk factors for clinical neonatal sepsis. A retrospective study was conducted from 1 October 2018 to 31 March 2023 in a large tertiary hospital in China. Neonates were divided into patients and controls based on the occurrence of neonatal sepsis. A multivariable model was used to determine risk factors and construct models.The utilization and assessment of model presentation were conducted using Norman charts and web calculators, with a focus on model differentiation, calibration, and clinical applicability (DCA). Furthermore, the hospital's data from 1 April 2023 to 1 January 2024 was utilized for internal validation. In the modelling dataset, a total of 339 pairs of mothers and their newborns were included in the study and divided into two groups: patients (n = 84, 24.78%) and controls (n = 255, 75.22%). Logistic regression analysis was performed to examine the relationship between various factors and outcome. The results showed that maternal age < 26 years (odds ratio [OR] = 2.16, 95% confidence interval [CI] 1.06-4.42, p = 0.034), maternal gestational diabetes (OR = 2.17, 95% CI 1.11-4.27, p = 0.024), forceps assisted delivery (OR = 3.76, 95% CI 1.72-5.21, p = 0.032), umbilical cord winding (OR = 1.75, 95% CI 1.32-2.67, p = 0.041) and male neonatal sex (OR = 1.59, 95% CI 1.00-2.62, p = 0.050) were identified as independent factors influencing the outcome of neonatal clinical sepsis. A main effects model was developed incorporating these five significant factors, resulting in an area under the curve (AUC) value of 0.713 (95% CI 0.635-0.773) for predicting the occurrence of neonatal clinical sepsis. In the internal validation cohort, the AUC value of the model was 0.711, with a 95% CI of 0.592-0.808. A main effects model incorporating the five significant factors was constructed to help healthcare professionals make informed decisions and improve clinical outcomes.
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Affiliation(s)
- Mengqi Wu
- Center for Reproductive Medicine, Department of Pediatrics, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou, 310014, Zhejiang, China
- Department of Postgraduate Education, Jinzhou Medical University, Jinzhou, 121004, Liaoning, China
| | - Yanbing Deng
- Center for Reproductive Medicine, Department of Pediatrics, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou, 310014, Zhejiang, China
| | - Xinye Wang
- Center for Reproductive Medicine, Department of Pediatrics, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou, 310014, Zhejiang, China
| | - Baomei He
- Center for Reproductive Medicine, Department of Pediatrics, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou, 310014, Zhejiang, China
| | - Fangqiang Wei
- General Surgery, Cancer Center, Department of Hepatobiliary & Pancreatic Surgery and Minimally Invasive Surgery, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou, 310014, Zhejiang, China.
| | - Ying Zhang
- Center for Reproductive Medicine, Department of Pediatrics, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou, 310014, Zhejiang, China.
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38
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Harris E. Low Levels of Protein Biomarker Could Predict Sepsis Deaths. JAMA 2024; 331:726. [PMID: 38353958 DOI: 10.1001/jama.2024.0357] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/06/2024]
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Steinbach D, Ahrens PC, Schmidt M, Federbusch M, Heuft L, Lübbert C, Nauck M, Gründling M, Isermann B, Gibb S, Kaiser T. Applying Machine Learning to Blood Count Data Predicts Sepsis with ICU Admission. Clin Chem 2024; 70:506-515. [PMID: 38431275 DOI: 10.1093/clinchem/hvae001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Accepted: 11/16/2023] [Indexed: 03/05/2024]
Abstract
BACKGROUND Timely diagnosis is crucial for sepsis treatment. Current machine learning (ML) models suffer from high complexity and limited applicability. We therefore created an ML model using only complete blood count (CBC) diagnostics. METHODS We collected non-intensive care unit (non-ICU) data from a German tertiary care centre (January 2014 to December 2021). Using patient age, sex, and CBC parameters (haemoglobin, platelets, mean corpuscular volume, white and red blood cells), we trained a boosted random forest, which predicts sepsis with ICU admission. Two external validations were conducted using data from another German tertiary care centre and the Medical Information Mart for Intensive Care IV database (MIMIC-IV). Using the subset of laboratory orders also including procalcitonin (PCT), an analogous model was trained with PCT as an additional feature. RESULTS After exclusion, 1 381 358 laboratory requests (2016 from sepsis cases) were available. The CBC model shows an area under the receiver operating characteristic (AUROC) of 0.872 (95% CI, 0.857-0.887). External validations show AUROCs of 0.805 (95% CI, 0.787-0.824) for University Medicine Greifswald and 0.845 (95% CI, 0.837-0.852) for MIMIC-IV. The model including PCT revealed a significantly higher AUROC (0.857; 95% CI, 0.836-0.877) than PCT alone (0.790; 95% CI, 0.759-0.821; P < 0.001). CONCLUSIONS Our results demonstrate that routine CBC results could significantly improve diagnosis of sepsis when combined with ML. The CBC model can facilitate early sepsis prediction in non-ICU patients with high robustness in external validations. Its implementation in clinical decision support systems has strong potential to provide an essential time advantage and increase patient safety.
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Affiliation(s)
- Daniel Steinbach
- University Institute for Laboratory Medicine, OWL University Hospital of Bielefeld University, Detmold, Germany
| | - Paul C Ahrens
- University Institute for Laboratory Medicine, OWL University Hospital of Bielefeld University, Detmold, Germany
| | - Maria Schmidt
- University Institute for Laboratory Medicine, OWL University Hospital of Bielefeld University, Detmold, Germany
| | - Martin Federbusch
- University Institute for Laboratory Medicine, OWL University Hospital of Bielefeld University, Detmold, Germany
| | - Lara Heuft
- Institute of Human Genetics, Leipzig University Hospital, Leipzig, Germany
| | - Christoph Lübbert
- Department of Infectious Diseases/Tropical Medicine, Nephrology and Rheumatology, Hospital St. Georg, Leipzig, Germany
- Division of Infectious Diseases and Tropical Medicine, Department of Medicine I, Interdisciplinary Center for Infectious Diseases, Leipzig University Hospital, Leipzig, Germany
| | - Matthias Nauck
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
- DZHK (German Centre for Cardiovascular Research), Partner Site Greifswald, University Medicine Greifswald, Greifswald, Germany
| | - Matthias Gründling
- Anesthesiology and Intensive Care Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Berend Isermann
- University Institute for Laboratory Medicine, OWL University Hospital of Bielefeld University, Detmold, Germany
| | - Sebastian Gibb
- University Institute for Laboratory Medicine, OWL University Hospital of Bielefeld University, Detmold, Germany
- Anesthesiology and Intensive Care Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Thorsten Kaiser
- University Institute for Laboratory Medicine, OWL University Hospital of Bielefeld University, Detmold, Germany
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40
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Yang HS. Machine Learning for Sepsis Prediction: Prospects and Challenges. Clin Chem 2024; 70:465-467. [PMID: 38431277 DOI: 10.1093/clinchem/hvae006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Accepted: 01/11/2024] [Indexed: 03/05/2024]
Affiliation(s)
- He S Yang
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, 10065, United States
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41
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Liu R, Yu ZC, Xiao CX, Xiao SF, He J, Shi Y, Hua YY, Zhou JM, Zhang GY, Wang T, Jiang JY, Xiong DX, Chen Y, Xu HB, Yun H, Sun H, Pan TT, Wang R, Zhu SM, Huang D, Liu YJ, Hu YH, Ren XR, Shi MF, Song SZ, Luo JM, Liu J, Zhang J, Xu F. [Different methods in predicting mortality of pediatric intensive care units sepsis in Southwest China]. Zhonghua Er Ke Za Zhi 2024; 62:204-210. [PMID: 38378280 DOI: 10.3760/cma.j.cn112140-20231013-00282] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 02/22/2024]
Abstract
Objective: To investigate the value of systemic inflammatory response syndrome (SIRS), pediatric sequential organ failure assessment (pSOFA) and pediatric critical illness score (PCIS) in predicting mortality of pediatric sepsis in pediatric intensive care units (PICU) from Southwest China. Methods: This was a prospective multicenter observational study. A total of 447 children with sepsis admitted to 12 PICU in Southwest China from April 2022 to March 2023 were enrolled. Based on the prognosis, the patients were divided into survival group and non-survival group. The physiological parameters of SIRS, pSOFA and PCIS were recorded and scored within 24 h after PICU admission. The general clinical data and some laboratory results were recorded. The area under the curve (AUC) of the receiver operating characteristic curve was used to compare the predictive value of SIRS, pSOFA and PCIS in mortality of pediatric sepsis. Results: Amongst 447 children with sepsis, 260 patients were male and 187 patients were female, aged 2.5 (0.8, 7.0) years, 405 patients were in the survival group and 42 patients were in the non-survival group. 418 patients (93.5%) met the criteria of SIRS, and 440 patients (98.4%) met the criteria of pSOFA≥2. There was no significant difference in the number of items meeting the SIRS criteria between the survival group and the non-survival group (3(2, 4) vs. 3(3, 4) points, Z=1.30, P=0.192). The pSOFA score of the non-survival group was significantly higher than that of the survival group (9(6, 12) vs. 4(3, 7) points, Z=6.56, P<0.001), and the PCIS score was significantly lower than that of the survival group (72(68, 81) vs. 82(76, 88) points, Z=5.90, P<0.001). The predictive value of pSOFA (AUC=0.82) and PCIS (AUC=0.78) for sepsis mortality was significantly higher than that of SIRS (AUC=0.56) (Z=6.59, 4.23, both P<0.001). There was no significant difference between pSOFA and PCIS (Z=1.35, P=0.176). Platelet count, procalcitonin, lactic acid, albumin, creatinine, total bilirubin, activated partial thromboplastin time, prothrombin time and international normalized ratio were all able to predict mortality of sepsis to a certain degree (AUC=0.64, 0.68, 0.80, 0.64, 0.68, 0.60, 0.77, 0.75, 0.76, all P<0.05). Conclusion: Compared with SIRS, both pSOFA and PCIS had better predictive value in the mortality of pediatric sepsis in PICU.
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Affiliation(s)
- R Liu
- Department of Pediatric Critical Care, Children's Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Pediatric Metabolism and Inflammatory Diseases, Chongqing 400014, China
| | - Z C Yu
- Department of Pediatric Critical Care, Children's Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Pediatric Metabolism and Inflammatory Diseases, Chongqing 400014, China
| | - C X Xiao
- Department of Pediatric Critical Care, Children's Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Pediatric Metabolism and Inflammatory Diseases, Chongqing 400014, China
| | - S F Xiao
- Department of Pediatric Critical Care, Kunming Children's Hospital, Kunming 650103, China
| | - J He
- Department of Pediatric Critical Care, Kunming Children's Hospital, Kunming 650103, China
| | - Y Shi
- Department of Pediatric Critical Care, the First People's Hospital of Liangshan Yi Autonomous Prefecture, Xichang 615099, China
| | - Y Y Hua
- Department of Pediatric Critical Care, the First People's Hospital of Liangshan Yi Autonomous Prefecture, Xichang 615099, China
| | - J M Zhou
- Department of Pediatric Critical Care, the First People's Hospital of Liangshan Yi Autonomous Prefecture, Xichang 615099, China
| | - G Y Zhang
- Department of Pediatric Critical Care, Chengdu Women's and Children's Central Hospital, Chengdu 610073, China
| | - T Wang
- Department of Pediatric Critical Care, Chengdu Women's and Children's Central Hospital, Chengdu 610073, China
| | - J Y Jiang
- Department of Pediatric Critical Care, Chongqing University Three Gorges Hospital, Chongqing 400030, China
| | - D X Xiong
- Department of Pediatric Critical Care, Chongqing University Three Gorges Hospital, Chongqing 400030, China
| | - Y Chen
- Department of Pediatric Critical Care, Guizhou Provincial Children's Hospital, Zunyi 563099, China
| | - H B Xu
- Department of Pediatric Critical Care, Guizhou Provincial Children's Hospital, Zunyi 563099, China
| | - H Yun
- Department of Pediatric Critical Care, Guizhou Provincial Children's Hospital, Zunyi 563099, China
| | - H Sun
- Department of Pediatric Critical Care, Affiliated Hospital of Guizhou Medical University, Guiyang 550004, China
| | - T T Pan
- Department of Pediatric Critical Care, Affiliated Hospital of Guizhou Medical University, Guiyang 550004, China
| | - R Wang
- Department of Pediatric Critical Care, Yuxi Children's Hospital, Yuxi 653199, China
| | - S M Zhu
- Department of Pediatric Critical Care, Yuxi Children's Hospital, Yuxi 653199, China
| | - D Huang
- Department of Pediatric Critical Care, Guizhou Provincial People's Hospital, Guiyang 550499, China
| | - Y J Liu
- Department of Pediatric Critical Care, Guizhou Provincial People's Hospital, Guiyang 550499, China
| | - Y H Hu
- Department of Pediatric Critical Care, Sichuan Provincial Maternity and Child Health Hospital, Chengdu 610045, China
| | - X R Ren
- Department of Pediatric Critical Care, Sichuan Provincial Maternity and Child Health Hospital, Chengdu 610045, China
| | - M F Shi
- Department of Pediatric Critical Care, the First People's Hospital of Yibin, Yibin 644099, China
| | - S Z Song
- Department of Pediatric Critical Care, the First People's Hospital of Yibin, Yibin 644099, China
| | - J M Luo
- Department of Pediatric Critical Care, the First People's Hospital of Yibin, Yibin 644099, China
| | - J Liu
- Department of Pediatric Critical Care, Nanchong Central Hospital, Nanchong 637003, China
| | - J Zhang
- Department of Pediatric Critical Care, Nanchong Central Hospital, Nanchong 637003, China
| | - F Xu
- Department of Pediatric Critical Care, Children's Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Pediatric Metabolism and Inflammatory Diseases, Chongqing 400014, China
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See EJ, Russell JA, Bellomo R, Lawler PR. Renin as a Prognostic and Predictive Biomarker in Sepsis: More Questions Than Answers? Crit Care Med 2024; 52:509-512. [PMID: 38381014 DOI: 10.1097/ccm.0000000000006133] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/22/2024]
Affiliation(s)
- Emily J See
- Department of Intensive Care, Royal Melbourne Hospital, Parkville, NSW, Australia
- Department of Critical Care, University of Melbourne, Parkville, NSW, Australia
- Department of Intensive Care, Austin Hospital, Heidelberg, VIC, Australia
- Department of Critical Care, Australian and New Zealand Intensive Care Research Centre, Monash University, Melbourne, VIC, Australia
- Department of Medicine, Centre for Heart Lung Innovation, University of British Columbia and St Paul's Hospital, Vancouver, BC, Canada
- Department of Medicine, McGill University Health Centre and McGill University, Montreal, QC, Canada
- Division of Cardiology and Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, ON, Canada
| | - James A Russell
- Department of Medicine, Centre for Heart Lung Innovation, University of British Columbia and St Paul's Hospital, Vancouver, BC, Canada
| | - Rinaldo Bellomo
- Department of Intensive Care, Royal Melbourne Hospital, Parkville, NSW, Australia
- Department of Critical Care, University of Melbourne, Parkville, NSW, Australia
- Department of Intensive Care, Austin Hospital, Heidelberg, VIC, Australia
- Department of Critical Care, Australian and New Zealand Intensive Care Research Centre, Monash University, Melbourne, VIC, Australia
- Department of Medicine, Centre for Heart Lung Innovation, University of British Columbia and St Paul's Hospital, Vancouver, BC, Canada
- Department of Medicine, McGill University Health Centre and McGill University, Montreal, QC, Canada
- Division of Cardiology and Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, ON, Canada
| | - Patrick R Lawler
- Department of Medicine, McGill University Health Centre and McGill University, Montreal, QC, Canada
- Division of Cardiology and Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, ON, Canada
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Akyol D, Çankayalı İ, Ersel M, Demirağ K, Uyar M, Can Ö, Özçete E, Karbek-Akarca F, Yağdı T, Engin Ç, Özgiray E, Yurtseven T, Yağmur B, Nalbantgil S, Ekren P, Bozkurt D, Şirin H, Çilli F, Sezer ED, Taşbakan M, Yamazhan T, Pullukçu H, Sipahi H, Arda B, Ulusoy S, Sipahi OR. Impact of the empirical therapy timing on the clinical progress of septic shock patients. Diagn Microbiol Infect Dis 2024; 108:116149. [PMID: 38142580 DOI: 10.1016/j.diagmicrobio.2023.116149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2023] [Revised: 11/11/2023] [Accepted: 11/24/2023] [Indexed: 12/26/2023]
Abstract
AIM To evaluate the effect of timing of antimicrobial therapy on clinical progress of patients with septic shock. MATERIALS AND METHOD We included 204 adult patients diagnosed with septic shock according to Sepsis-3 criteria between March 2016 and April 2021. One-month survival was evaluated using univariate and logistic regression analysis. RESULTS Antibiotic treatment was initiated within 1 h of the vasopressors in 26.4 % of patients. One-month mortality did not differ significantly between patients with and without empirical therapy coverage on etiological agents. Univariate factors that significantly affected one-month survival were starting antibiotics at the first hour, the unit where the case was diagnosed with septic shock, SOFA scores, qSOFA scores, and lactate level. In multivariate analysis, diagnosis of septic shock in the Emergency Service, SOFA score ≥11, qSOFA score of three and lactate level ≥4 were significantly associated with one-month mortality. CONCLUSION Training programs should be designed to increase the awareness of septic shock diagnosis and treatment in the Emergency Service and other hospital units. Additionally, electronic patient files should have warning systems for earlier diagnosis and consultation.
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Affiliation(s)
- Deniz Akyol
- Ege University Faculty of Medicine, Department of Infectious Diseases and Clinical Microbiology, Izmir, Turkey.
| | - İlkin Çankayalı
- Ege University Faculty of Medicine, Department of Anesthesiology and Reanimation, Izmir, Turkey
| | - Murat Ersel
- Ege University Faculty of Medicine, Department of Emergency Department, Izmir, Turkey
| | - Kubilay Demirağ
- Ege University Faculty of Medicine, Department of Anesthesiology and Reanimation, Izmir, Turkey
| | - Mehmet Uyar
- Ege University Faculty of Medicine, Department of Anesthesiology and Reanimation, Izmir, Turkey
| | - Özge Can
- Ege University Faculty of Medicine, Department of Emergency Department, Izmir, Turkey
| | - Enver Özçete
- Ege University Faculty of Medicine, Department of Emergency Department, Izmir, Turkey
| | - Funda Karbek-Akarca
- Ege University Faculty of Medicine, Department of Emergency Department, Izmir, Turkey
| | - Tahir Yağdı
- Ege University Faculty of Medicine, Department of Cardiovascular Surgery, Izmir, Turkey
| | - Çağatay Engin
- Ege University Faculty of Medicine, Department of Cardiovascular Surgery, Izmir, Turkey
| | - Erkin Özgiray
- Ege University Faculty of Medicine, Department of Neurosurgery, Izmir, Turkey
| | - Taşkın Yurtseven
- Ege University Faculty of Medicine, Department of Neurosurgery, Izmir, Turkey
| | - Burcu Yağmur
- Ege University Faculty of Medicine, Department of Cardiology, Izmir, Turkey
| | - Sanem Nalbantgil
- Ege University Faculty of Medicine, Department of Cardiology, Izmir, Turkey
| | - Pervin Ekren
- Ege University Faculty of Medicine, Department of Pulmonology, Izmir, Turkey
| | - Devrim Bozkurt
- Ege University Faculty of Medicine, Department of Internal Medicine, Izmir, Turkey
| | - Hadiye Şirin
- Ege University Faculty of Medicine, Department of Neurology, Izmir, Turkey
| | - Feriha Çilli
- Ege University Faculty of Medicine, Department of Medical Microbiology İzmir, Turkey
| | - Ebru Demirel Sezer
- Ege University Faculty of Medicine, Department of Medical Biochemistry, Izmir, Turkey
| | - Meltem Taşbakan
- Ege University Faculty of Medicine, Department of Infectious Diseases and Clinical Microbiology, Izmir, Turkey
| | - Tansu Yamazhan
- Ege University Faculty of Medicine, Department of Infectious Diseases and Clinical Microbiology, Izmir, Turkey
| | - Hüsnü Pullukçu
- Ege University Faculty of Medicine, Department of Infectious Diseases and Clinical Microbiology, Izmir, Turkey
| | - Hilal Sipahi
- Bornova Public Health Directorate, Izmir, Turkey
| | - Bilgin Arda
- Ege University Faculty of Medicine, Department of Infectious Diseases and Clinical Microbiology, Izmir, Turkey
| | - Sercan Ulusoy
- Ege University Faculty of Medicine, Department of Infectious Diseases and Clinical Microbiology, Izmir, Turkey
| | - Oğuz Reşat Sipahi
- Ege University Faculty of Medicine, Department of Infectious Diseases and Clinical Microbiology, Izmir, Turkey; King Hamad University Hospital, Bahrain Oncology Center, Infectious Diseases and Clinical Microbiology, Bahrain
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Fellman V. Biomarkers needed to discriminate early onset sepsis from asphyxia in newborn infants. Acta Paediatr 2024; 113:382-383. [PMID: 38196318 DOI: 10.1111/apa.17094] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/20/2023] [Accepted: 12/27/2023] [Indexed: 01/11/2024]
Affiliation(s)
- Vineta Fellman
- Department of Clinical Sciences, Pediatrics, Lund University, Lund, Sweden
- Children's Hospital, University of Helsinki, Helsinki, Finland
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Doğan NÖ, Özturan İU, Pekdemir M, Yaka E, Yılmaz S. Prognostic value of early warning scores in patients presenting to the emergency department with exacerbation of COPD. Med Klin Intensivmed Notfmed 2024; 119:129-135. [PMID: 37401954 DOI: 10.1007/s00063-023-01036-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2023] [Revised: 05/24/2023] [Accepted: 06/03/2023] [Indexed: 07/05/2023]
Abstract
OBJECTIVE Acute exacerbation of chronic obstructive pulmonary disease (AECOPD) is a condition that frequently presents to the emergency department (ED) and its prognosis is not very well understood. Risk tools that can be used rapidly in the ED are needed to predict the prognosis of these patients. METHODS This study comprised a retrospective cohort of AECOPD patients presenting to a single center between 2015 and 2022. The prognostic accuracy of several clinical early warning scoring systems, Modified Early Warning Score (MEWS), National Early Warning Score (NEWS), NEWS‑2, Systemic Inflammatory Response Syndrome (SIRS) and the quick Sepsis-related Organ Failure Assessment (qSOFA), were compared. The outcome variable was determined as one-month mortality. RESULTS Of the 598 patients, 63 (10.5%) had died within 1 month after presenting to the ED. Patients who died had more often congestive heart failure, altered mental status, and admission to intensive care, and they were older. Although the MEWS, NEWS, NEWS‑2, and qSOFA scores of those who died were higher than those who survived, there was no difference between the SIRS scores of these two groups. The score with the highest positive likelihood ratio for mortality estimation was qSOFA (8.5, 95% confidence interval [CI] 3.7-19.6). The negative likelihood ratios of the scores were similar, the NEWS score had a negative likelihood ratio of 0.4 (95% CI 0.2-0.8) with the highest negative predictive value of 96.0%. CONCLUSION In AECOPD patients, most of the early warning scores that are frequently used in the ED were found to have a moderate ability to exclude mortality and a low ability to predict mortality.
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Affiliation(s)
- Nurettin Özgür Doğan
- Faculty of Medicine, Dept. of Emergency Medicine, Kocaeli University, Kocaeli, Turkey.
| | - İbrahim Ulaş Özturan
- Faculty of Medicine, Dept. of Emergency Medicine, Kocaeli University, Kocaeli, Turkey
| | - Murat Pekdemir
- Faculty of Medicine, Dept. of Emergency Medicine, Kocaeli University, Kocaeli, Turkey
| | - Elif Yaka
- Faculty of Medicine, Dept. of Emergency Medicine, Kocaeli University, Kocaeli, Turkey
| | - Serkan Yılmaz
- Faculty of Medicine, Dept. of Emergency Medicine, Kocaeli University, Kocaeli, Turkey
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Schlapbach LJ, Goertz S, Hagenbuch N, Aubert B, Papis S, Giannoni E, Posfay-Barbe KM, Stocker M, Heininger U, Bernhard-Stirnemann S, Niederer-Loher A, Kahlert CR, Natalucci G, Relly C, Riedel T, Aebi C, Berger C, Agyeman PKA. Organ Dysfunction in Children With Blood Culture-Proven Sepsis: Comparative Performance of Four Scores in a National Cohort Study. Pediatr Crit Care Med 2024; 25:e117-e128. [PMID: 37878412 PMCID: PMC10904004 DOI: 10.1097/pcc.0000000000003388] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/27/2023]
Abstract
OBJECTIVES Previous studies applying Sepsis-3 criteria to children were based on retrospective analyses of PICU cohorts. We aimed to compare organ dysfunction criteria in children with blood culture-proven sepsis, including emergency department, PICU, and ward patients, and to assess relevance of organ dysfunctions for mortality prediction. DESIGN We have carried out a nonprespecified, secondary analysis of a prospective dataset collected from September 2011 to December 2015. SETTING Emergency departments, wards, and PICUs in 10 tertiary children's hospitals in Switzerland. PATIENTS Children younger than 17 years old with blood culture-proven sepsis. We excluded preterm infants and term infants younger than 7 days old. INTERVENTIONS None. MEASUREMENTS AND MAIN RESULTS We compared the 2005 International Pediatric Sepsis Consensus Conference (IPSCC), Pediatric Logistic Organ Dysfunction-2 (PELOD-2), pediatric Sequential Organ Failure Assessment (pSOFA), and Pediatric Organ Dysfunction Information Update Mandate (PODIUM) scores, measured at blood culture sampling, to predict 30-day mortality. We analyzed 877 sepsis episodes in 807 children, with a 30-day mortality of 4.3%. Percentage with organ dysfunction ranged from 32.7% (IPSCC) to 55.3% (pSOFA). In adjusted analyses, the accuracy for identification of 30-day mortality was area under the curve (AUC) 0.87 (95% CI, 0.82-0.92) for IPSCC, 0.83 (0.76-0.89) for PELOD-2, 0.85 (0.78-0.92) for pSOFA, and 0.85 (0.78-0.91) for PODIUM. When restricting scores to neurologic, respiratory, and cardiovascular dysfunction, the adjusted AUC was 0.89 (0.84-0.94) for IPSCC, 0.85 (0.79-0.91) for PELOD-2, 0.87 (0.81-0.93) for pSOFA, and 0.88 (0.83-0.93) for PODIUM. CONCLUSIONS IPSCC, PELOD-2, pSOFA, and PODIUM performed similarly to predict 30-day mortality. Simplified scores restricted to neurologic, respiratory, and cardiovascular dysfunction yielded comparable performance.
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Affiliation(s)
- Luregn J Schlapbach
- Department of Intensive Care and Neonatology, and Children`s Research Center, University Children`s Hospital Zurich, Zurich, Switzerland
- Child Health Research Centre, University of Queensland, Brisbane, QLD, Australia
| | - Sabrina Goertz
- Division of Infectious Diseases, and Children's Research Center, University Children's Hospital Zurich, Zurich, Switzerland
| | - Niels Hagenbuch
- Department of Pediatrics, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Blandine Aubert
- Clinic of Neonatology, Department Mother-Woman-Child, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Sebastien Papis
- Pediatric Infectious Diseases Unit, Department of Woman, Child and Adolescent, Children's Hospital of Geneva, University Hospitals of Geneva and Faculty of Medicine, Geneva, Switzerland
| | - Eric Giannoni
- Clinic of Neonatology, Department Mother-Woman-Child, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Klara M Posfay-Barbe
- Pediatric Infectious Diseases Unit, Department of Woman, Child and Adolescent, Children's Hospital of Geneva, University Hospitals of Geneva and Faculty of Medicine, Geneva, Switzerland
| | | | - Ulrich Heininger
- Infectious Diseases and Vaccinology, University Children's Hospital Basel, Basel, Switzerland
| | | | | | | | | | - Christa Relly
- Division of Infectious Diseases, and Children's Research Center, University Children's Hospital Zurich, Zurich, Switzerland
| | - Thomas Riedel
- Department of Pediatrics, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
- Department of Pediatrics, Cantonal Hospital Graubuenden, Chur, Switzerland
| | - Christoph Aebi
- Department of Pediatrics, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Christoph Berger
- Division of Infectious Diseases, and Children's Research Center, University Children's Hospital Zurich, Zurich, Switzerland
| | - Philipp K A Agyeman
- Department of Pediatrics, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
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Beaumont R, Tang K, Gwee A. The Sensitivity and Specificity of Procalcitonin in Diagnosing Bacterial Sepsis in Neonates. Hosp Pediatr 2024; 14:199-208. [PMID: 38415310 DOI: 10.1542/hpeds.2023-007318] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/29/2024]
Abstract
CONTEXT AND OBJECTIVES Neonatal sepsis accounts for 15% of all neonatal deaths. Early detection enables prompt administration of antibiotic treatment, reducing morbidity and mortality. This study aims to review the sensitivity and specificity of procalcitonin in diagnosing microbiologically-proven sepsis in neonates to determine the optimal procalcitonin cut-off value for use in clinical practice. DATA SOURCES, STUDY SELECTION, AND DATA EXTRACTION Medline, EMBASE and PubMed were searched on 3 May 2023 for original studies in symptomatic neonates in whom both blood culture and procalcitonin levels were taken, and a procalcitonin cut-off with either sensitivity or specificity reported. Studies that included asymptomatic or culture-negative neonates in the proven sepsis group were excluded. Risk of bias was assessed using the Qualitative Assessment of Diagnostic Accuracy Studies 2 tool. RESULTS Nineteen original studies enrolling a total of 1920 symptomatic neonates (721 with proven sepsis) were included. Six studies used a procalcitonin cut-off of 0.5 ng/mL and found a sensitivity of 87% to 100% and specificity of 17% to 89%. Nine studies evaluated higher procalcitonin cut-off values between 0.99 ng/mL and 2 ng/mL, which were 67% to 98% sensitive and 41% to 89% specific. All other procalcitonin thresholds were neither sensitive nor specific. Meta-analysis was not performed because of high risk of bias within the identified studies. CONCLUSIONS This review found that procalcitonin was highly sensitive (87% to 100%) at a cut-off value of 0.5 ng/mL, although specificity varied greatly across all cut-off values reviewed. The variation in diagnostic accuracy between studies suggests that procalcitonin may be useful to guide antibiotic cessation but should not be used alone as a diagnostic marker for neonatal sepsis.
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Affiliation(s)
- Rachael Beaumont
- Department of Paediatrics, The University of Melbourne, Parkville, Australia
- Infectious Diseases Group, Murdoch Children's Research Institute, Parkville, Australia
| | - Kailey Tang
- Department of Paediatrics, The University of Melbourne, Parkville, Australia
| | - Amanda Gwee
- Department of Paediatrics, The University of Melbourne, Parkville, Australia
- Infectious Diseases Group, Murdoch Children's Research Institute, Parkville, Australia
- Infectious Diseases Unit, The Royal Children's Hospital, Melbourne, Parkville, Australia
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Turcato G, Zaboli A, Sibilio S, Parodi M, Mian M, Brigo F. The role of lactate-to-albumin ratio to predict 30-day risk of death in patients with sepsis in the emergency department: a decision tree analysis. Curr Med Res Opin 2024; 40:345-352. [PMID: 38305238 DOI: 10.1080/03007995.2024.2314740] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Accepted: 02/01/2024] [Indexed: 02/03/2024]
Abstract
BACKGROUND Accurately estimating the prognosis of septic patients on arrival in the emergency department (ED) is clinically challenging. The lactate-to-albumin ratio (LAR) has recently been proposed to improve the predictive performance of septic patients admitted to the ICU. OBJECTIVES This study aims to assess whether the LAR could be used as an early prognostic marker of 30-day mortality in patients with sepsis in the ED. METHODS A prospective observational study was conducted in the ED of the Hospital of Merano. All patients with a diagnosis of sepsis were considered. The LAR was recorded on arrival in the ED. The primary outcome measure was mortality at 30 days. The predictive role of the LAR for mortality was evaluated with the area under the ROC curve, logistic regression adjusted for the Charlson Comorbidity Index value, National Early Warning Score, and Sequential Organ Failure score, and with decision tree analysis. RESULTS 459 patients were enrolled, of whom 17% (78/459) died at 30 days. The median LAR of the patients who died at 30 days (0.78 [0.45-1.19]) was significantly higher than the median LAR of survivors (0.42 [0.27-0.65]) (p < 0.001). The discriminatory ability of the LAR for death at 30 days was 0.738, higher than that of lactate alone (0.692), and slightly lower than that of albumin alone (0.753). The decision trees confirmed the role of the LAR as an independent risk factor for mortality. CONCLUSION The LAR can be used as an index to better predict the 30-day risk of death in septic patients.
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Affiliation(s)
- Gianni Turcato
- Department of Internal Medicine, Intermediate Care Unit, Santorso, Italy
| | - Arian Zaboli
- Innovation, Research and Teaching Service (SABES-ASDAA), Teaching Hospital of the Paracelsus Medical Private University (PMU), Bolzano, Italy
| | - Serena Sibilio
- Department of Emergency Medicine, Hospital of Merano-Meran (SABES-ASDAA), Merano-Meran, Italy
- Lehrkrankenhaus der Paracelsus Medizinischen Privatuniversität, Salzburg, Austria
| | - Marta Parodi
- Department of Internal Medicine, Intermediate Care Unit, Santorso, Italy
| | - Michael Mian
- Innovation, Research and Teaching Service (SABES-ASDAA), Teaching Hospital of the Paracelsus Medical Private University (PMU), Bolzano, Italy
- College of Health Care-Professions Claudiana, Bozen, Italy
| | - Francesco Brigo
- Innovation, Research and Teaching Service (SABES-ASDAA), Teaching Hospital of the Paracelsus Medical Private University (PMU), Bolzano, Italy
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van der Weijden BM, Janssen SWCM, Benitz WE, Kuzniewicz MW, Puopolo KM, Plötz FB, Achten NB. Open-source code to extend early-onset sepsis calculator accessibility. Lancet Digit Health 2024; 6:e153. [PMID: 38262801 DOI: 10.1016/s2589-7500(23)00253-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Revised: 11/06/2023] [Accepted: 12/05/2023] [Indexed: 01/25/2024]
Affiliation(s)
- Bo M van der Weijden
- Department of Paediatrics, Tergooi Hospital, Hilversum, Netherlands; Department of Paediatrics, Amsterdam University Medical Centers-Emma Children's Hospital, Amsterdam, Netherlands
| | - Sanne W C M Janssen
- Department of Paediatrics, Amsterdam University Medical Centers-Emma Children's Hospital, Amsterdam, Netherlands
| | - William E Benitz
- Division of Neonatal and Developmental Medicine, Department of Pediatrics, Stanford University School of Medicine, CA, USA
| | - Michael W Kuzniewicz
- Perinatal Research Unit, Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA
| | - Karen M Puopolo
- Division of Neonatology, The Children's Hospital of Philadelphia, Philadelphia, PA, USA; Perelman School of Medicine, University of Pennsylvania, PA, USA
| | - Frans B Plötz
- Department of Paediatrics, Tergooi Hospital, Hilversum, Netherlands; Department of Paediatrics, Amsterdam University Medical Centers-Emma Children's Hospital, Amsterdam, Netherlands
| | - Niek B Achten
- Department of Paediatrics, Erasmus University Medical Centre-Sophia Children's Hospital, Rotterdam 300, Netherlands.
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Meeus M, Beirnaert C, Mahieu L, Laukens K, Meysman P, Mulder A, Van Laere D. Clinical Decision Support for Improved Neonatal Care: The Development of a Machine Learning Model for the Prediction of Late-onset Sepsis and Necrotizing Enterocolitis. J Pediatr 2024; 266:113869. [PMID: 38065281 DOI: 10.1016/j.jpeds.2023.113869] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Revised: 11/24/2023] [Accepted: 12/04/2023] [Indexed: 01/08/2024]
Abstract
OBJECTIVE To develop an artificial intelligence-based software system for predicting late-onset sepsis (LOS) and necrotizing enterocolitis (NEC) in infants admitted to the neonatal intensive care unit (NICU). STUDY DESIGN Single-center, retrospective cohort study, conducted in the NICU of the Antwerp University Hospital. Continuous monitoring data of 865 preterm infants born at <32 weeks gestational age, admitted to the NICU in the first week of life, were used to train an XGBoost machine learning (ML) algorithm for LOS and NEC prediction in a cross-validated setup. Afterward, the model's performance was assessed on an independent test set of 148 patients (internal validation). RESULTS The ML model delivered hourly risk predictions with an overall sensitivity of 69% (142/206) for all LOS/NEC episodes and 81% (67/83) for severe LOS/NEC episodes. The model showed a median time gain of ≤10 hours (IQR, 3.1-21.0 hours), compared with historical clinical diagnosis. On the complete retrospective dataset, the ML model made 721 069 predictions, of which 9805 (1.3%) depicted a LOS/NEC probability of ≥0.15, resulting in a total alarm rate of <1 patient alarm-day per week. The model reached a similar performance on the internal validation set. CONCLUSIONS Artificial intelligence technology can assist clinicians in the early detection of LOS and NEC in the NICU, which potentially can result in clinical and socioeconomic benefits. Additional studies are required to quantify further the effect of combining artificial and human intelligence on patient outcomes in the NICU.
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Affiliation(s)
- Marisse Meeus
- Department of Neonatal Intensive Care, Antwerp University Hospital, Edegem, Belgium; Laboratory of Experimental Medicine and Pediatrics, Faculty of Medicine and Health Sciences, University of Antwerp, Antwerpen, Belgium.
| | - Charlie Beirnaert
- Department of Neonatal Intensive Care, Antwerp University Hospital, Edegem, Belgium; Innocens BV, Antwerpen, Belgium; Department of Computer Science, University of Antwerp, Antwerpen, Belgium
| | - Ludo Mahieu
- Department of Neonatal Intensive Care, Antwerp University Hospital, Edegem, Belgium; Laboratory of Experimental Medicine and Pediatrics, Faculty of Medicine and Health Sciences, University of Antwerp, Antwerpen, Belgium
| | - Kris Laukens
- Department of Computer Science, University of Antwerp, Antwerpen, Belgium
| | - Pieter Meysman
- Department of Computer Science, University of Antwerp, Antwerpen, Belgium
| | - Antonius Mulder
- Department of Neonatal Intensive Care, Antwerp University Hospital, Edegem, Belgium; Laboratory of Experimental Medicine and Pediatrics, Faculty of Medicine and Health Sciences, University of Antwerp, Antwerpen, Belgium
| | - David Van Laere
- Department of Neonatal Intensive Care, Antwerp University Hospital, Edegem, Belgium; Laboratory of Experimental Medicine and Pediatrics, Faculty of Medicine and Health Sciences, University of Antwerp, Antwerpen, Belgium; Innocens BV, Antwerpen, Belgium
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