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González-Jiménez P, Piqueras M, Latorre A, Tortosa-Carreres J, Mengot N, Alonso R, Reyes S, Amara-Elori I, Martínez-Dolz L, Moscardó A, Menéndez R, Méndez R. Endothelial Biomarkers Are Superior to Classic Inflammatory Biomarkers in Community-Acquired Pneumonia. Biomedicines 2024; 12:2413. [PMID: 39457725 PMCID: PMC11505377 DOI: 10.3390/biomedicines12102413] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2024] [Revised: 10/17/2024] [Accepted: 10/20/2024] [Indexed: 10/28/2024] Open
Abstract
Background: Complications in community-acquired pneumonia (CAP), including cardiovascular events (CVE), can occur during an acute episode and in the long term. We aimed to analyse the role of endothelial damage biomarkers (C-terminal endothelin-1 precursor fragment [CT-proET-1] and mid-regional pro-adrenomedullin [MR-proADM]), in contrast to classic inflammation markers (C Reactive Protein [CRP] and procalcitonin [PCT]) in patients admitted for CAP and their relationship with ICU admission, CVE and mortality in the short and long term; Methods: Biomarkers were analysed in 515 patients with CAP at day 1, 285 at day 5 and 280 at day 30. Traditional inflammatory biomarkers and endothelial damage biomarkers were measured. ICU admission, CVE and mortality (in-hospital and 1-year follow-up) were assessed using receiver operating characteristic (ROC) curve analysis and univariate logistic regression. Results: A statistically significant association was observed between initial, raised CT-proET-1 and MR-proADM levels, the need for ICU admission and the development of in-hospital CVE or in-hospital mortality. Both endothelial markers maintained a strong association at day 30 with 1-year follow-up CVE. At day 1, CRP and PCT were only associated with ICU admission. On day 30, there was no association between inflammatory markers and long-term CVE or death. The odds ratio (OR) and area under the curve (AUC) of endothelial biomarkers were superior to those of classic biomarkers for all outcomes considered. Conclusions: Endothelial biomarkers are better indicators than classic ones in predicting worse outcomes in both the short and long term, especially CVE. MR-proADM is the best biomarker for predicting complications in CAP.
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Affiliation(s)
- Paula González-Jiménez
- Pneumology Department, La Fe University and Polytechnic Hospital, 46026 Valencia, Spain
- Respiratory Infections, Health Research Institute La Fe (IISLAFE), 46026 Valencia, Spain
- Medicine Department, University of Valencia, 46010 Valencia, Spain
| | - Mónica Piqueras
- Respiratory Infections, Health Research Institute La Fe (IISLAFE), 46026 Valencia, Spain
- Medicine Department, University of Valencia, 46010 Valencia, Spain
- Laboratory Department, La Fe University and Polytechnic Hospital, 46026 Valencia, Spain
| | - Ana Latorre
- Respiratory Infections, Health Research Institute La Fe (IISLAFE), 46026 Valencia, Spain
| | - Jordi Tortosa-Carreres
- Medicine Department, University of Valencia, 46010 Valencia, Spain
- Laboratory Department, La Fe University and Polytechnic Hospital, 46026 Valencia, Spain
| | - Noé Mengot
- Pneumology Department, La Fe University and Polytechnic Hospital, 46026 Valencia, Spain
| | - Ricardo Alonso
- Laboratory Department, La Fe University and Polytechnic Hospital, 46026 Valencia, Spain
| | - Soledad Reyes
- Pneumology Department, La Fe University and Polytechnic Hospital, 46026 Valencia, Spain
- Respiratory Infections, Health Research Institute La Fe (IISLAFE), 46026 Valencia, Spain
| | - Isabel Amara-Elori
- Pneumology Department, La Fe University and Polytechnic Hospital, 46026 Valencia, Spain
- Respiratory Infections, Health Research Institute La Fe (IISLAFE), 46026 Valencia, Spain
- Medicine Department, University of Valencia, 46010 Valencia, Spain
| | - Luis Martínez-Dolz
- Medicine Department, University of Valencia, 46010 Valencia, Spain
- Cardiology Department, La Fe University and Polytechnic Hospital, 46026 Valencia, Spain
- Centre for Biomedical Research Network in Cardiovascular Diseases (CIBERCV), Instituto de Salud Carlos III, 28029 Madrid, Spain
| | - Antonio Moscardó
- Haemostasis and Thrombosis Unit, La Fe University and Polytechnic Hospital, 46026 Valencia, Spain
| | - Rosario Menéndez
- Respiratory Infections, Health Research Institute La Fe (IISLAFE), 46026 Valencia, Spain
- Centre for Biomedical Research Network in Respiratory Diseases (CIBERES), Instituto de Salud Carlos III, 28029 Madrid, Spain
| | - Raúl Méndez
- Pneumology Department, La Fe University and Polytechnic Hospital, 46026 Valencia, Spain
- Respiratory Infections, Health Research Institute La Fe (IISLAFE), 46026 Valencia, Spain
- Centre for Biomedical Research Network in Respiratory Diseases (CIBERES), Instituto de Salud Carlos III, 28029 Madrid, Spain
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Rombauts A, Abelenda-Alonso G, Cuervo G, Gudiol C, Carratalà J. Role of the inflammatory response in community-acquired pneumonia: clinical implications. Expert Rev Anti Infect Ther 2021; 20:1261-1274. [PMID: 33034228 DOI: 10.1080/14787210.2021.1834848] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
INTRODUCTION Despite adequate antibiotic coverage, community-acquired pneumonia (CAP) remains a leading cause of hospitalization and mortality worldwide. It induces both a local pulmonary and a systemic inflammatory response, particularly significant in severe cases. The intensity of the dysregulated host response varies from patient to patient and has a negative impact on survival and other outcomes. AREAS COVERED This comprehensive review summarizes the pathophysiological aspects of the inflammatory response in CAP, briefly discusses the usefulness of biomarkers, and assesses the clinical evidence for modulating the inflammatory pathways. We searched PubMed for the most relevant studies, reviews, and meta-analysis until August 2020. EXPERT OPINION Notable efforts have been made to identify biomarkers that can accurately differentiate between viral and bacterial etiology, and indeed, to enhance risk stratification in CAP. However, none has proven ideal and no recommended biomarker-guided algorithms exist. Biomarker signatures from proteomic and metabolomic studies could be more useful for such assessments. To date, most studies have produced contradictory results concerning the role of immunomodulatory agents (e.g. corticosteroids, macrolides, and statins) in CAP. Adequately identifying the population who may benefit most from effective modulation of the inflammatory response remains a challenge.
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Affiliation(s)
- Alexander Rombauts
- Department of Infectious Diseases, Hospital Universitari de Bellvitge, Hospitalet de Llobregat, Barcelona, Spain.,Bellvitge Biomedical Research Institute (IDIBELL), Hospitalet de Llobregat, Spain
| | - Gabriela Abelenda-Alonso
- Department of Infectious Diseases, Hospital Universitari de Bellvitge, Hospitalet de Llobregat, Barcelona, Spain.,Bellvitge Biomedical Research Institute (IDIBELL), Hospitalet de Llobregat, Spain
| | - Guillermo Cuervo
- Department of Infectious Diseases, Hospital Universitari de Bellvitge, Hospitalet de Llobregat, Barcelona, Spain
| | - Carlota Gudiol
- Department of Infectious Diseases, Hospital Universitari de Bellvitge, Hospitalet de Llobregat, Barcelona, Spain.,Bellvitge Biomedical Research Institute (IDIBELL), Hospitalet de Llobregat, Spain.,Spanish Network for Research in Infectious Disease (REIPI), Instituto de Salud Carlos III, Madrid, Spain.,University of Barcelona, Barcelona, Spain.,Institut Català d'Oncologia (ICO), Hospitalet de Llobregat, Barcelona, Spain
| | - Jordi Carratalà
- Department of Infectious Diseases, Hospital Universitari de Bellvitge, Hospitalet de Llobregat, Barcelona, Spain.,Bellvitge Biomedical Research Institute (IDIBELL), Hospitalet de Llobregat, Spain.,Spanish Network for Research in Infectious Disease (REIPI), Instituto de Salud Carlos III, Madrid, Spain.,University of Barcelona, Barcelona, Spain
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Bertsimas D, Lukin G, Mingardi L, Nohadani O, Orfanoudaki A, Stellato B, Wiberg H, Gonzalez-Garcia S, Parra-Calderón CL, Robinson K, Schneider M, Stein B, Estirado A, a Beccara L, Canino R, Dal Bello M, Pezzetti F, Pan A. COVID-19 mortality risk assessment: An international multi-center study. PLoS One 2020; 15:e0243262. [PMID: 33296405 PMCID: PMC7725386 DOI: 10.1371/journal.pone.0243262] [Citation(s) in RCA: 102] [Impact Index Per Article: 20.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2020] [Accepted: 11/19/2020] [Indexed: 01/08/2023] Open
Abstract
Timely identification of COVID-19 patients at high risk of mortality can significantly improve patient management and resource allocation within hospitals. This study seeks to develop and validate a data-driven personalized mortality risk calculator for hospitalized COVID-19 patients. De-identified data was obtained for 3,927 COVID-19 positive patients from six independent centers, comprising 33 different hospitals. Demographic, clinical, and laboratory variables were collected at hospital admission. The COVID-19 Mortality Risk (CMR) tool was developed using the XGBoost algorithm to predict mortality. Its discrimination performance was subsequently evaluated on three validation cohorts. The derivation cohort of 3,062 patients has an observed mortality rate of 26.84%. Increased age, decreased oxygen saturation (≤ 93%), elevated levels of C-reactive protein (≥ 130 mg/L), blood urea nitrogen (≥ 18 mg/dL), and blood creatinine (≥ 1.2 mg/dL) were identified as primary risk factors, validating clinical findings. The model obtains out-of-sample AUCs of 0.90 (95% CI, 0.87-0.94) on the derivation cohort. In the validation cohorts, the model obtains AUCs of 0.92 (95% CI, 0.88-0.95) on Seville patients, 0.87 (95% CI, 0.84-0.91) on Hellenic COVID-19 Study Group patients, and 0.81 (95% CI, 0.76-0.85) on Hartford Hospital patients. The CMR tool is available as an online application at covidanalytics.io/mortality_calculator and is currently in clinical use. The CMR model leverages machine learning to generate accurate mortality predictions using commonly available clinical features. This is the first risk score trained and validated on a cohort of COVID-19 patients from Europe and the United States.
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Affiliation(s)
- Dimitris Bertsimas
- Sloan School of Management, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
- Operations Research Center, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
| | - Galit Lukin
- Operations Research Center, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
| | - Luca Mingardi
- Sloan School of Management, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
- Operations Research Center, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
| | - Omid Nohadani
- Benefits Science Technologies, Boston, Massachusetts, United States of America
| | - Agni Orfanoudaki
- Operations Research Center, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
| | - Bartolomeo Stellato
- Sloan School of Management, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
- Operations Research Center, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
| | - Holly Wiberg
- Operations Research Center, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
| | - Sara Gonzalez-Garcia
- Institute of Biomedicine of Seville (IBIS), Virgen del Rocío University Hospital, CSIC, University of Seville, Seville, Spain
| | - Carlos Luis Parra-Calderón
- Institute of Biomedicine of Seville (IBIS), Virgen del Rocío University Hospital, CSIC, University of Seville, Seville, Spain
| | - Kenneth Robinson
- Hartford HealthCare, Hartford, Connecticut, United States of America
| | | | - Barry Stein
- Hartford HealthCare, Hartford, Connecticut, United States of America
| | | | - Lia a Beccara
- Azienda Socio-Sanitaria Territoriale di Cremona, Cremona, Italy
| | - Rosario Canino
- Azienda Socio-Sanitaria Territoriale di Cremona, Cremona, Italy
| | - Martina Dal Bello
- Physics of Living Systems, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
| | | | - Angelo Pan
- Azienda Socio-Sanitaria Territoriale di Cremona, Cremona, Italy
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Wang S, Zhong H, Lu M, Song G, Zhang X, Lin M, Yang S, Qian M. Higher Serum C Reactive Protein Determined C Reactive Protein Single-Nucleotide Polymorphisms Are Involved in Inherited Depression. Psychiatry Investig 2018; 15:824-828. [PMID: 30048584 PMCID: PMC6111223 DOI: 10.30773/pi.2018.04.03.2] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/24/2017] [Revised: 03/11/2018] [Accepted: 04/03/2018] [Indexed: 02/05/2023] Open
Abstract
OBJECTIVE The pathogenesis of depression is not fully understood yet, but studies have suggested higher circulating C reactive protein (CRP) level might relate to depression occurrence. However, due to high variability of patients' individual condition, the results to date are inconsistent. Considering CRP single-nucleotide polymorphisms (SNPs) could also regulate plasma CRP levels, in the present study, we hypothesized that inherited CRP allelic variations may co-vary with depressive symptomatology. METHODS We recruited 60 depression patients with family depression history and 60 healthy control volunteers into this project. We detected circulation CRP level as well as genome CRP SNPs from participants of this project. RESULTS We have found a significantly higher circulating CRP level in patients with a positive family history. Furthermore, we also identified some certain inherited CRP SNPs (A allele in rs1417938 and C allele in rs1205) could up regulate serum CRP level and distributed more in depression patients with family history. CONCLUSION Our finding may raise new evidence that genetically increased serum CRP level through SNPs variation is likely to induce family inherited depression.
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Affiliation(s)
| | - Hua Zhong
- Huzhou Third People’s Hospital, Zhejiang, China
| | - Meijuan Lu
- Huzhou Third People’s Hospital, Zhejiang, China
| | - Guohua Song
- Huzhou Third People’s Hospital, Zhejiang, China
| | | | - Min Lin
- Huzhou Third People’s Hospital, Zhejiang, China
| | | | - Mincai Qian
- Huzhou Third People’s Hospital, Zhejiang, China
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Yibulaiyin H, Sun H, Yang Y. Depression is Associated with CRP SNPs in Patients with Family History. Transl Neurosci 2017; 8:201-206. [PMID: 29340226 PMCID: PMC5765705 DOI: 10.1515/tnsci-2017-0027] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2017] [Accepted: 10/17/2017] [Indexed: 02/02/2023] Open
Abstract
Objective The pathogenesis of depression is not fully understood, but studies have suggested that higher circulating levels of C reactive protein (CRP) might relate to depression occurrence. However, due to the highly variability of individual patients’ conditions, the results to date are inconsistent. Considering Single nucleotide polymorphisms (SNPs) of CRP gene have also been suggested to predict plasma CRP levels. In the present study, we hypothesize that inherited CRP allelic variations may co-vary with depressive symptomatology. Methods We recruited patients with a diagnosis of depression, with or without family depression history. We then detected serum CRP levels, as well as genome CRP SNPs from participants of this project. Results We found a significantly higher circulating CRP levels in patients with a positive family history. Furthermore, we also identified certain inherited CRP SNPs (A allele in rs1417938 and C allele in rs1205) which could up-regulate serum CRP levels and thus be associated with depression occurrence. Conclusion Our findings raise new evidence for the relationship between circulating CRP level and depression occurrence.
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Affiliation(s)
- Hasiyeti Yibulaiyin
- 2th affiliated hospital of Xinjiang Medical University, Department of neurology. Xinjiang Provence, Urumqi, China
- E-mail:
| | - Haixia Sun
- 421th hospital of PLA, Department of geriatrics. Urumqi, China
| | - Yue Yang
- 5th affiliated hospital of Xinjiang Medical University, Department of neurology, Urumqi, China
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Liu D, Xie L, Zhao H, Liu X, Cao J. Prognostic value of mid-regional pro-adrenomedullin (MR-proADM) in patients with community-acquired pneumonia: a systematic review and meta-analysis. BMC Infect Dis 2016; 16:232. [PMID: 27230573 PMCID: PMC4881068 DOI: 10.1186/s12879-016-1566-3] [Citation(s) in RCA: 49] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2015] [Accepted: 05/16/2016] [Indexed: 01/31/2023] Open
Abstract
Background The early identification of patients at risk of dying from community-acquired pneumonia (CAP) is critical for their treatment and for defining hospital resource consumption. Mid-regional pro-adrenomedullin (MR-proADM) has been extensively investigated for its prognostic value in CAP. However, the results are conflicting. The purpose of the present meta-analysis was to explore the diagnostic accuracy of MR-proADM for predicting mortality in patients suffering from CAP, particularly emergency department (ED) patients. Method We systematically searched the PubMed, Embase, Web of Knowledge and Cochrane databases. Studies were included if a 2 × 2 contingency table could be constructed based on both the MR-proADM level and the complications or mortality of patients diagnosed with CAP. The prognostic accuracy of MR-proADM in CAP was assessed using the bivariate meta-analysis model. We used the Q-test and I2 index to evaluate heterogeneity. Results MR-proADM displayed moderate diagnostic accuracy for predicting complications in CAP, with an overall area under the SROC curve (AUC) of 0.74 (95 % CI: 0.70–0.78). Eight studies with a total of 4119 patients in the emergency department (ED) were included. An elevated MR-proADM level was associated with increased risk of death from CAP (RR 6.16, 95 % CI 4.71–8.06); the I2 value was 0.0 %, and a fixed-effects model was used to pool RR. The pooled sensitivity and specificity were 0.74 (95 % CI: 0.67–0.79) and 0.73 (95 % CI: 0.70–0.77), respectively. The positive likelihood ratio (PLR) and negative likelihood ratio (NLR) were 2.8 (95 % CI, 2.3–3.3) and 0.36 (95 % CI, 0.29–0.45), respectively. In addition, the diagnostic odds ratio (DOR) was 8 (95 % CI, 5–11), and the overall area under the SROC curve was 0.76 (95 % CI, 0.72–0.80). Conclusions Our study has demonstrated that MR-proADM is predictive of increased complications and higher mortality rates in patients suffering from CAP. Future studies are warranted to determine the prognostic accuracy of MR-proADM in conjunction with severity scores or other biomarkers and to determine an optimal cut-off level. Electronic supplementary material The online version of this article (doi:10.1186/s12879-016-1566-3) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Dan Liu
- Department of Respiratory Medicine, Tianjin Medical University General Hospital, Tianjin, 300070, China
| | - Lixin Xie
- Department of Pulmonary & Critical Care Medicine, Chinese PLA General Hospital, 28 Fuxing Road, Beijing, 100853, China
| | - Haiyan Zhao
- Department of Respiratory Medicine, Tianjin Medical University General Hospital, Tianjin, 300070, China
| | - Xueyao Liu
- Medical School, Nankai University, 94 Weijin Road, Tianjin, 300071, China.,Department of Pulmonary & Critical Care Medicine, Chinese PLA General Hospital, 28 Fuxing Road, Beijing, 100853, China
| | - Jie Cao
- Department of Respiratory Medicine, Tianjin Medical University General Hospital, Tianjin, 300070, China.
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Biomarcadores en la sepsis. ¿Simplificando lo complejo? Enferm Infecc Microbiol Clin 2014; 32:137-9. [DOI: 10.1016/j.eimc.2014.01.001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2014] [Accepted: 01/09/2014] [Indexed: 02/08/2023]
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