New Sepsis Definition (Sepsis-3) and Community-acquired Pneumonia Mortality. A Validation and Clinical Decision-Making Study

Severe Community-Acquired Pneumonia: Noninvasive Mechanical Ventilation, Intubation, and HFNT

Severe acute respiratory failure (ARF) is a major issue in patients with severe community-acquired pneumonia (CAP). Standard oxygen therapy is the first-line therapy for ARF in the less severe cases. However, respiratory supports may be delivered in more severe clinical condition. In cases with life-threatening ARF, invasive mechanical ventilation (IMV) will be required. Noninvasive strategies such as high-flow nasal therapy (HFNT) or noninvasive ventilation (NIV) by either face mask or helmet might cover the gap between standard oxygen and IMV. The objective of all the supporting measures for ARF is to gain time for the antimicrobial treatment to cure the pneumonia. There is uncertainty regarding which patients with severe CAP are most likely to benefit from each noninvasive support strategy. HFNT may be the first-line approach in the majority of patients. While NIV may be relatively contraindicated in patients with excessive secretions, facial hair/structure resulting in air leaks or poor compliance, NIV may be preferable in those with increased work of breathing, respiratory muscle fatigue, and congestive heart failure, in which the positive pressure of NIV may positively impact hemodynamics. A trial of NIV might be considered for select patients with hypoxemic ARF if there are no contraindications, with close monitoring by an experienced clinical team who can intubate patients promptly if they deteriorate. In such cases, individual clinician judgement is key to choose NIV, interface, and settings. Due to the paucity of studies addressing IMV in this population, the protective mechanical ventilation strategies recommended by guidelines for acute respiratory distress syndrome can be reasonably applied in patients with severe CAP.

Enhancing predictions with a stacking ensemble model for ICU mortality risk in patients with sepsis-associated encephalopathy

OBJECTIVE

We identified predictive factors and developed a novel machine learning (ML) model for predicting mortality risk in patients with sepsis-associated encephalopathy (SAE).

METHODS

In this retrospective cohort study, data from the Medical Information Mart for Intensive Care IV (MIMIC-IV) and eICU Collaborative Research Database were used for model development and external validation. The primary outcome was the in-hospital mortality rate among patients with SAE; the observed in-hospital mortality rate was 14.74% (MIMIC IV: 1112, eICU: 594). Using the least absolute shrinkage and selection operator (LASSO), we built nine ML models and a stacking ensemble model and determined the optimal model based on the area under the receiver operating characteristic curve (AUC). We used the Shapley additive explanations (SHAP) algorithm to determine the optimal model.

RESULTS

The study included 9943 patients. LASSO identified 15 variables. The stacking ensemble model achieved the highest AUC on the test set (0.807) and 0.671 on external validation. SHAP analysis highlighted Glasgow Coma Scale (GCS) and age as key variables. The model (https://sic1.shinyapps.io/SSAAEE/) can predict in-hospital mortality risk for patients with SAE.

CONCLUSIONS

We developed a stacked ensemble model with enhanced generalization capabilities using novel data to predict mortality risk in patients with SAE.

Decision Curve Analysis of In-Hospital Mortality Prediction Models: The Relative Value of Pre- and Intraoperative Data For Decision-Making

BACKGROUND

Clinical prediction modeling plays a pivotal part in modern clinical care, particularly in predicting the risk of in-hospital mortality. Recent modeling efforts have focused on leveraging intraoperative data sources to improve model performance. However, the individual and collective benefit of pre- and intraoperative data for clinical decision-making remains unknown. We hypothesized that pre- and intraoperative predictors contribute equally to the net benefit in a decision curve analysis (DCA) of in-hospital mortality prediction models that include pre- and intraoperative predictors.

METHODS

Data from the VitalDB database featuring a subcohort of 6043 patients were used. A total of 141 predictors for in-hospital mortality were grouped into preoperative (demographics, intervention characteristics, and laboratory measurements) and intraoperative (laboratory and monitor data, drugs, and fluids) data. Prediction models using either preoperative, intraoperative, or all data were developed with multiple methods (logistic regression, neural network, random forest, gradient boosting machine, and a stacked learner). Predictive performance was evaluated by the area under the receiver-operating characteristic curve (AUROC) and under the precision-recall curve (AUPRC). Clinical utility was examined with a DCA in the predefined risk preference range (denoted by so-called treatment threshold probabilities) between 0% and 20%.

RESULTS

AUROC performance of the prediction models ranged from 0.53 to 0.78. AUPRC values ranged from 0.02 to 0.25 (compared to the incidence of 0.09 in our dataset) and high AUPRC values resulted from prediction models based on preoperative laboratory values. A DCA of pre- and intraoperative prediction models highlighted that preoperative data provide the largest overall benefit for decision-making, whereas intraoperative values provide only limited benefit for decision-making compared to preoperative data. While preoperative demographics, comorbidities, and surgery-related data provide the largest benefit for low treatment thresholds up to 5% to 10%, preoperative laboratory measurements become the dominant source for decision support for higher thresholds.

CONCLUSIONS

When it comes to predicting in-hospital mortality and subsequent decision-making, preoperative demographics, comorbidities, and surgery-related data provide the largest benefit for clinicians with risk-averse preferences, whereas preoperative laboratory values provide the largest benefit for decision-makers with more moderate risk preferences. Our decision-analytic investigation of different predictor categories moves beyond the question of whether certain predictors provide a benefit in traditional performance metrics (eg, AUROC). It offers a nuanced perspective on for whom these predictors might be beneficial in clinical decision-making. Follow-up studies requiring larger datasets and dedicated deep-learning models to handle continuous intraoperative data are essential to examine the robustness of our results.

The Predictive Value of Sepsis Scores for In-Hospital Mortality in Patients with Left-Sided Infective Endocarditis

BACKGROUND

As infective endocarditis has particular characteristics compared to other infectious diseases, it is not clear if sepsis scores are reported with good accuracy in these patients. The aim of this study is to evaluate the accuracy of the qSOFA and SOFA scores to predict mortality in patients with infective endocarditis.

METHODS

Between January 2010 and June 2019, 867 patients with suspected left-sided endocarditis were evaluated; 517 were included with left-sided infective endocarditis defined as "possible" or "definite" endocarditis, according to the Modified Duke Criteria. ROC curves were constructed to assess the accuracy of qSOFA and SOFA sepsis scores for the prediction of in-hospital mortality.

RESULTS

The median age was 57 years, 65% were male, 435 (84%) had pre-existing heart valve disease, and the overall mortality was 28%. The most frequent etiologies were Streptococcus spp. (36%), Enterococcus spp. (10%), and Staphylococcus aureus (9%). The sepsis scores from the ROC curves used to predict in-hospital mortality were qSOFA 0.601 (CI95% 0.522-0.681) and SOFA score 0.679 (CI95% 0.602-0.756). A sub-group analysis in patients with and without pre-existing valve disease for SOFA ≥ 2 showed ROC curves of 0.627 (CI95% 0.563-0.690) and 0.775 (CI95% 0.594-0.956), respectively.

CONCLUSIONS

qSOFA and SOFA scores were associated with increased in-hospital mortality in patients with infective endocarditis. However, as accuracy was relatively lower compared to other sites of bacterial infections, we believe that this score may have lower accuracy when predicting the prognosis of patients with IE, because, in this disease, the patient's death may be more frequently linked to valvular and cardiac dysfunction, as well as embolic events, and less frequently directly associated with sepsis.

Clinical Evaluation of Metagenomic Next-Generation Sequencing and Identification of Risk Factors in Patients with Severe Community-Acquired Pneumonia

Purpose

Severe community-acquired pneumonia (SCAP) is the leading cause of death among patients with infectious diseases worldwide. This study aimed to evaluate the effectiveness of metagenomic next-generation sequencing (mNGS) through detecting pathogens in bronchoalveolar lavage fluid (BALF) and identifying risk factors for recovery in SCAP patients.

Patients and Methods

This prospective study recruited 158 SCAP patients admitted to respiratory intensive care unit that were randomly divided into control and study groups, with receiving conventional tests and the same conventional tests plus mNGS, respectively. The diagnostic efficiency of mNGS was evaluated by comparing with conventional tests. Furthermore, univariate and multivariate logistic regression analyses were performed to determine the independent risk factors for recovery in SCAP patients, and a nomogram prediction model was established based on these factors.

Results

Within the study group, the pathogen detection rate was significantly higher with mNGS than that with conventional tests (84.81% vs 45.57%, P < 0.001), with a positive coincidence rate of 94.44%. Acinetobacter baumannii (21.52%, 17/79), Candida albicans (17.72%, 14/79), and Klebsiella pneumonia (15.19%, 12/79) were the top three common pathogens detected by mNGS. Of note, the improvement rate of patients in the study group was significantly higher than that in the control group. The further analysis revealed that the increased levels of interleukin-6, blood urea nitrogen, procalcitonin, the longer length of hospital stay, and bacterial infection were independent risk factors for recovery of SCAP patients, while mNGS detection status was a protective factor. The predictive model showed a good performance for the modeling and validation sets.

Conclusion

Early mNGS exhibited a superior diagnostic efficiency to conventional tests in SCAP patients, which can reduce the risk of death in SCAP patients. Moreover, the clinical factors could also be used for the management and prognosis prediction of SCAP patients.

The Battle of the Pneumonia Predictors: A Comprehensive Meta-Analysis Comparing the Pneumonia Severity Index (PSI) and the CURB-65 Score in Predicting Mortality and the Need for ICU Support

The CURB-65 (confusion, uremia, respiratory rate, blood pressure, age ≥ 65 years) score and the pneumonia severity index (PSI) are widely used and recommended in predicting 30-day mortality and the need for intensive care support in community-acquired pneumonia. This study aims to compare the performance of these two severity scores in both mortality prediction and the need for intensive care support. A systematic review and meta-analysis was carried out, following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) 2020 guidelines, and PubMed, Scopus, ScienceDirect, and Google Scholar were searched for articles published from 2012 to 2022. The reference lists of the included studies were also searched to retrieve possible additional studies. Twenty-five studies reporting prognostic information for CURB 65 and PSI were identified. ReviewManager (RevMan) 5.4.1 was used to produce risk ratios, and a random effects model was used to pool them. Both PSI and CURB-65 showed a high strength in identifying high-risk patients. However, CURB-65 was slightly better in early mortality prediction and had more sensitivity (96.7%) and specificity (89.3%) in predicting admission to intensive care support. Thus, CURB-65 seems to be the preferred tool in predicting mortality and the need for admission into intensive care support.

Interventions to improve outcomes in community-acquired pneumonia

INTRODUCTION

Community-acquired pneumonia (CAP) is a common infection associated with high morbimortality and a highly deleterious impact on patients' quality of life and functionality. We comprehensively review the factors related to the host, the causative microorganism, the therapeutic approach and the organization of health systems (e.g. setting for care and systems for allocation) that might have an impact on CAP-associated outcomes. Our main aims are to discuss the most controversial points and to provide some recommendations that may guide further research and the management of patients with CAP, in order to improve their outcomes, beyond mortality.

AREA COVERED

In this review, we aim to provide a critical account of potential measures to improve outcomes of CAP and the supporting evidence from observational studies and clinical trials.

EXPERT OPINION

CAP is associated with high mortality and a highly deleterious impact on patients' quality of life. To improve CAP-associated outcomes, it is important to understand the factors related to the patient, etiology, therapeutics, and the organization of health systems.

Lung infection by Pseudomonas aeruginosa induces neuroinflammation and blood-brain barrier dysfunction in mice

BACKGROUND

Severe lung infection can lead to brain dysfunction and neurobehavioral disorders. The mechanisms that regulate the lung-brain axis of inflammatory response to respiratory infection are incompletely understood. This study examined the effects of lung infection causing systemic and neuroinflammation as a potential mechanism contributing to blood-brain barrier (BBB) leakage and behavioral impairment.

METHODS

Lung infection in mice was induced by instilling Pseudomonas aeruginosa (PA) intratracheally. We determined bacterial colonization in tissue, microvascular leakage, expression of cytokines and leukocyte infiltration into the brain.

RESULTS

Lung infection caused alveolar-capillary barrier injury as indicated by leakage of plasma proteins across pulmonary microvessels and histopathological characteristics of pulmonary edema (alveolar wall thickening, microvessel congestion, and neutrophil infiltration). PA also caused significant BBB dysfunction characterized by leakage of different sized molecules across cerebral microvessels and a decreased expression of cell-cell junctions (VE-cadherin, claudin-5) in the brain. BBB leakage peaked at 24 h and lasted for 7 days post-inoculation. Additionally, mice with lung infection displayed hyperlocomotion and anxiety-like behaviors. To test whether cerebral dysfunction was caused by PA directly or indirectly, we measured bacterial load in multiple organs. While PA loads were detected in the lungs up to 7 days post-inoculation, bacteria were not detected in the brain as evidenced by negative cerebral spinal fluid (CSF) cultures and lack of distribution in different brain regions or isolated cerebral microvessels. However, mice with PA lung infection demonstrated increased mRNA expression in the brain of pro-inflammatory cytokines (IL-1β, IL-6, and TNF-α), chemokines (CXCL-1, CXCL-2) and adhesion molecules (VCAM-1 and ICAM-1) along with CD11b + CD45+ cell recruitment, corresponding to their increased blood levels of white cells (polymorphonuclear cells) and cytokines. To confirm the direct effect of cytokines on endothelial permeability, we measured cell-cell adhesive barrier resistance and junction morphology in mouse brain microvascular endothelial cell monolayers, where administration of IL-1β induced a significant reduction of barrier function coupled with tight junction (TJ) and adherens junction (AJ) diffusion and disorganization. Combined treatment with IL-1β and TNFα augmented the barrier injury.

CONCLUSIONS

Lung bacterial infection is associated with BBB disruption and behavioral changes, which are mediated by systemic cytokine release.

Comparing In-Hospital Mortality Prediction by Senior Emergency Resident's Judgment and Prognostic Models in the Emergency Department

Background

A comparison of emergency residents' judgments and two derivatives of the Sequential Organ Failure Assessment (SOFA), namely, the mSOFA and the qSOFA, was conducted to determine the accuracy of predicting in-hospital mortality among critically ill patients in the emergency department (ED).

Methods

A prospective cohort research was performed on patients over 18 years of age presented to the ED. We used logistic regression to develop a model for predicting in-hospital mortality by using qSOFA, mSOFA, and residents' judgment scores. We compared the accuracy of prognostic models and residents' judgment in terms of the overall accuracy of the predicted probabilities (Brier score), discrimination (area under the ROC curve), and calibration (calibration graph). Analyses were carried out using R software version R-4.2.0.

Results

In the study, 2,205 patients with median age of 64 (IQR: 50-77) years were included. There were no significant differences between the qSOFA (AUC 0.70; 95% CI: 0.67-0.73) and physician's judgment (AUC 0.68; 0.65-0.71). Despite this, the discrimination of mSOFA (AUC 0.74; 0.71-0.77) was significantly higher than that of the qSOFA and residents' judgments. Additionally, the AUC-PR of mSOFA, qSOFA, and emergency resident's judgments was 0.45 (0.43-0.47), 0.38 (0.36-0.40), and 0.35 (0.33-0.37), respectively. The mSOFA appears stronger in terms of overall performance: 0.13 vs. 0.14 and 0.15. All three models showed good calibration.

Conclusion

The performance of emergency residents' judgment and the qSOFA was the same in predicting in-hospital mortality. However, the mSOFA predicted better-calibrated mortality risk. Large-scale studies should be conducted to determine the utility of these models.

New paradigms on antibiotic recommendations for community-acquired infections in Spain

Over the last years, the susceptibility activity of the most common microorganisms causing community-acquired infections has significantly changed in Spain. Based on the susceptibility rates of Streptococcus pyogenes, Streptococcus pneumoniae, Haemophilus influenzae, Escherichia coli, and Klebsiella pneumoniae collected from outpatients aged 15 or older with symptoms of respiratory or urinary tract infections in several Microbiology Departments in Catalonia in 2021, penicillin V should be first choice for most respiratory tract infections, amoxicillin and clavulanate for chronic obstructive pulmonary disease exacerbations and a single dose of fosfomycin or a short-course nitrofurantoin should remain first-line treatments for uncomplicated urinary tract infections. Updated information on antimicrobial resistance for general practitioners is crucial for achieving appropriate empirical management of the most common infections by promoting more rational antibiotic use.

Prognostic value of the qSOFA in patients with acute exacerbation of idiopathic pulmonary fibrosis

BACKGROUND

Patients with idiopathic pulmonary fibrosis (IPF) have a slowly progressive clinical course, although some develop acute exacerbations (AEs). An easily obtained composite score is desirable for predicting the survival rate in patients with AE of IPF (AE-IPF). We investigated the quick sequential organ failure assessment (qSOFA), originally developed to identify sepsis, as a predictor of mortality in patients with AE-IPF and compared it to other composite assessments.

METHODS

Consecutive patients with IPF admitted for their first AE between 2008 and 2019 were recruited retrospectively. The association between the qSOFA score obtained at admission and mortality was investigated.

RESULTS

During the study period, 97 patients with AE-IPF were hospitalized. The hospital mortality was 30.9%. Multivariate logistic regression analysis revealed that both the qSOFA and the Japanese Association for Acute Medicine (JAAM)-disseminated intravascular coagulation (DIC) scores were significant predictors of hospital mortality (odds ratio [OR] 3.86, 95% confidence interval [CI] 1.43-10.3; p = 0.007 and OR 2.71, 95% CI 1.56-4.67; p = 0.0004; respectively). Kaplan-Meier survival curves showed that both scores were consistently associated with survival. Furthermore, the sum of the two scores was a more effective predictor than the individual scores.

CONCLUSIONS

The qSOFA score of patients admitted with AE-IPF was associated with both in-hospital and long-term mortality, which was also true for the JAAM-DIC score. The qSOFA score plus the JAAM-DIC score should be determined during the diagnostic evaluation of a patient with AE-IPF. Both scores combined may be more effective at predicting outcomes than individual scores.

Liposomes loaded with quercetin for resolution of lung inflammation in a lipopolysaccharide-induced mouse model of sepsis

Quercetin (QU) has been widely used as a dietary supplement and proved useful to treat lung diseases. However, the therapeutic potential of QU may be restricted because of its low bioavailability and poor water solubility. In this study, we investigated the effects of developed QU-loaded liposomes on macrophage-mediated lung inflammation.In vivo, a mouse model of sepsis induced by lipopolysaccharide challenge was used to detect the anti-inflammatory effects of liposomal QU. Hematoxylin/eosin staining and immunostaining were utilized to reveal pathological damage and leukocyte infiltration into the lung tissues. Quantitative reverse transcription-polymerase chain reaction and immunoblotting were used to determine cytokine production in the mouse lungs.In vitro, mouse RAW 264.7 macrophages were treated with free QU and liposomal QU. Cell viability assay and immunostaining were utilized to detect cytotoxicity and distribution of QU in the cells. Thein vivoresults showed that liposomal encapsulation promoted the inhibitory effects of QU on lung inflammation. Liposomal QU decreased mortality in septic mice with no obvious toxicity on vital organs. Mechanistically, the anti-inflammatory effects of liposomal QU were associated with inhibition of nuclear factor-kappa B-dependent cytokine production and inflammasome activation in macrophages. Collectively, the results showed that QU liposomes mitigated lung inflammation in septic mice through inhibition of macrophage inflammatory signaling.

Association of admission lactate with mortality in adult patients with severe community-acquired pneumonia

PURPOSE

The present study was conducted to investigate the association of admission lactate with mortality in severe community-acquired pneumonia (SCAP).

METHODS

We performed a retrospective, observational, cohort study on adult SCAP patients admitted to intensive care unit (ICU) in West China Hospital of Sichuan University between December 2011 and December 2018. The primary outcome was hospital mortality. Univariate and then multivariate analysis were performed to identify independent risk factors for hospital mortality. The association of admission lactate categories with hospital mortality was examined in three logistic regression models and Kaplan-Meier plots. We also applied restricted cubic splines to estimate the potential non-linear associations.

RESULTS

In total, 2275 SCAP patients were included. Admission lactate remained a significant factor for mortality after multivariate regression (OR: 1.085; 95% CI: 1.033,1.141; by continuous variable). After lactate was categorized into quartiles and the confounders were fully adjusted, compared with the quartile 1, ORs (95% CIs) of hospital mortality for quartile 2, quartile 3 and quartile 4 were 1.001 (0.759-1.321), 1.153 (0.877-1.516) and 1.593 (1.202-2.109), respectively (P for trend =0.001). Survival curves indicated that elevated lactate was associated with poor prognosis (P < 0.001). Moreover, this association was non-linear, indicating that increased lactate has the most notable impact on mortality within the range of 1.5 to 4 mmol/L (P non-linear: 0.029 for hospital mortality; 0.004 for ICU mortality).

CONCLUSION

Elevated admission lactate has a significant, independent, and potentially non-linear association with increased mortality in SCAP patients.

A Gap of Patients with Infective Endocarditis between Clinical Trials and the Real World

Introduction: A randomized control trial (RCT) is considered to be the highest level in the Evidence-Based Medicine (EBM) pyramid. While EBM is essential to make a practical tool such as a prognostic guideline, it has been unclear how many patients in the real world can be eligible for a randomized control trial (RCT). Patients and method: This study was performed to clarify if there is a difference in patients' profiles and clinical outcomes between the patients eligible and not eligible for any RCT. We reviewed all IE patients at our institute between 2007 and 2019. The patients were divided into two groups: those eligible for RCTs (RCT appropriate group) and those who were not (RCT inappropriate group). Exclusion criteria for clinical trials were set based on previous clinical trials. Results: A total of 66 patients were enrolled in the study. The median age was 70 years (range 18 to 87 years), and 46 (70%) were male. Seventeen (26%) of the patients were eligible for RCTs. Comparing the two groups, patients in the RCT appropriate group were younger and had fewer comorbidities. The disease severity was milder in the RCT appropriate groups than in the RCT inappropriate groups. Patients in the RCT appropriate group showed significantly longer overall survival times than those in the RCT inappropriate group (Log-Rank test, p < 0.001). Conclusions: We found a significant gap in patients' characteristics and clinical outcomes between the groups. Physicians should be aware that RCT can never reflect the real-world population.

Lung infection by P. aeruginosa induces neuroinflammation and blood-brain barrier dysfunction in mice

Background Severe lung infection can lead to brain dysfunction and neurobehavioral disorders. The mechanisms that regulate the lung-brain axis of inflammatory response to respiratory infection are incompletely understood. This study examined the effects of lung infection causing systemic and neuroinflammation as a potential mechanism contributing to blood-brain barrier (BBB) leakage and behavioral impairment. Methods Pneumonia was induced in adult C57BL/6 mice by intratracheal inoculation of Pseudomonas aeruginosa (PA). Solute extravasation, histology, immunofluorescence, RT-PCR, multiphoton imaging and neurological testing were performed in this study. Results Lung infection caused alveolar-capillary barrier injury as indicated by leakage of plasma proteins across pulmonary microvessels and histopathological characteristics of pulmonary edema (alveolar wall thickening, microvessel congestion, and neutrophil infiltration). PA also caused significant BBB dysfunction characterized by leakage of different sized molecules across cerebral microvessels and a decreased expression of cell-cell junctions (VE-cadherin, claudin-5) in the brain. BBB leakage peaked at 24 hours and lasted for 7 days post-inoculation. Additionally, mice with lung infection displayed hyperlocomotion and anxiety-like behaviors. To test whether cerebral dysfunction was caused by PA directly or indirectly, we measured bacterial load in multiple organs. While PA loads were detected in the lungs up to 7 days post-inoculation, bacteria were not detected in the brain as evidenced by negative cerebral spinal fluid (CSF) cultures and lack of distribution in different brain regions or isolated cerebral microvessels. However, mice with PA lung infection demonstrated increased mRNA expression in the brain of pro-inflammatory cytokines (IL-1β, IL-6, and TNF-α), chemokines (CXCL-1, CXCL-2) and adhesion molecules (VCAM-1 and ICAM-1) along with CD11b + cell recruitment, corresponding to their increased blood levels of white cells (polymorphonuclear cells) and cytokines. To confirm the direct effect of cytokines on endothelial permeability, we measured cell-cell adhesive barrier resistance and junction morphology in mouse brain microvascular endothelial cell monolayers, where administration of IL-1β induced a significant reduction of barrier function coupled with tight junction (TJ) diffusion and disorganization. Combined treatment with IL-1β and TNFα augmented the barrier injury. Conclusions These results suggest that lung bacterial infection causes cerebral microvascular leakage and neuroinflammation via a mechanism involving cytokine-induced BBB injury.

Clarithromycin for community-acquired pneumonia in adults: focus on anti-inflammatory properties

Aim. To evaluate clinical efficacy, anti-inflammatory and immunomodulatory activity of clarithromycin in adults with severe community-acquired pneumonia (sCAP). Materials and methods. A prospective observational study recruited adult hospitalized patients with verified sCAP. Clarithromycin was prescribed as a component of combination antibiotic therapy (ABT) with a -lactam antibiotic (AB). The choice of -lactam AB was carried out by the attending physician in accordance with national clinical guidelines and routine practice of the medical institution. Along with assessment clinical efficacy, the dynamics of inflammatory markers in blood serum was recorded: C-reactive protein, procalcitonin (PCT), tumor necrosis factor , interleukins 1-beta (IL-1) and interleukin 6 (IL-6). The total duration of ABT was 714 days. Results. Altogether 20 patients (13 males, 7 females) aged from 18 to 84 years old were enrolled. As a result of the use of combined ABT with -lactam AB and clarithromycin, a significant decrease in the level of C-reactive protein was noted by the 35th day of therapy (from 74.6 to 14.1 mg/l). An increase in serum PCT was observed in half of the patients; during treatment, the level of PCT significantly decreased. Similar dynamics was detected for IL-6 its content in the blood serum decreased by the time of the end of ABT by 6.8 times compared with the baseline. A decrease in the level of tumor necrosis factor to the reference value was observed in most patients already in the early stages by 35 days of ABT. The majority of patients showed positive dynamics of clinical signs and symptoms with resolution of respiratory failure and other complications of sCAP. In almost half of the patients, the criteria for clinical stability were achieved in the early stages, which made it possible to switch to oral ABT. Conclusion. The results of the study are consistent with literature data indicating a rapid decrease in inflammatory markers when clarithromycin is administered to patients with sCAP. Its results can be a starting point for comparative randomized trials assessing both clinical outcomes and immunological parameters when using different classes of antibiotics for the treatment of sCAP.

Machine-Learning Model for Mortality Prediction in Patients With Community-Acquired Pneumonia: Development and Validation Study

BACKGROUND

Artificial intelligence tools and techniques such as machine learning (ML) are increasingly seen as a suitable manner in which to increase the prediction capacity of currently available clinical tools, including prognostic scores. However, studies evaluating the efficacy of ML methods in enhancing the predictive capacity of existing scores for community-acquired pneumonia (CAP) are limited. We aimed to apply and validate a causal probabilistic network (CPN) model to predict mortality in patients with CAP.

RESEARCH QUESTION

Is a CPN model able to predict mortality in patients with CAP better than the commonly used severity scores?

STUDY DESIGN AND METHODS

This was a derivation-validation retrospective study conducted in two Spanish university hospitals. The ability of a CPN designed to predict mortality in sepsis (SepsisFinder [SeF]), and adapted for CAP (SeF-ML), to predict 30-day mortality was assessed and compared with other scoring systems (Pneumonia Severity Index [PSI], Sequential Organ Failure Assessment [SOFA], quick Sequential Organ Failure Assessment [qSOFA], and CURB-65 criteria [confusion, urea, respiratory rate, BP, age ≥ 65 years]). The SeF models are proprietary software. Differences between receiver operating characteristic curves were assessed by the DeLong method for correlated receiver operating characteristic curves.

RESULTS

The derivation cohort comprised 4,531 patients, and the validation cohort consisted of 1,034 patients. In the derivation cohort, the areas under the curve (AUCs) of SeF-ML, CURB-65, SOFA, PSI, and qSOFA were 0.801, 0.759, 0.671, 0.799, and 0.642, respectively, for 30-day mortality prediction. In the validation study, the AUC of SeF-ML was 0.826, concordant with the AUC (0.801) in the derivation data (P = .51). The AUC of SeF-ML was significantly higher than those of CURB-65 (0.764; P = .03) and qSOFA (0.729, P = .005). However, it did not differ significantly from those of PSI (0.830; P = .92) and SOFA (0.771; P = .14).

INTERPRETATION

SeF-ML shows potential for improving mortality prediction among patients with CAP, using structured health data. Additional external validation studies should be conducted to support generalizability.

Comparative Effectiveness of Ampicillin/Sulbactam versus Cefazolin as Targeted Therapy for Bacteremia Caused by Beta-Lactamase-Producing Methicillin-Sensitive Staphylococcus aureus: A Single-Center Retrospective Study

Cefazolin (CFZ) is the first-line treatment for beta-lactamase-producing methicillin-sensitive Staphylococcus aureus (BP-MSSA) infection. In 2019, Japan experienced a CFZ shortage because of foreign object inclusion in a batch. Ampicillin/sulbactam (SAM) was preferred in many cases as definitive therapy for the treatment of BP-MSSA bacteremia to preserve broad-spectrum antibiotic stock. However, there are no previous studies reporting the clinical efficacy of SAM for BP-MSSA bacteremia. We aimed to compare the clinical efficacy and adverse effects of SAM versus CFZ in patients with BP-MSSA bacteremia. In total, 41 and 30 patients treated with SAM and CFZ, respectively, were identified. The baseline characteristics were similar in both groups. No significant differences were observed in length of hospital stay and all 30-day mortality between the two groups (p = 0.270 and 0.643, respectively). Moreover, no intergroup difference in 90-day mortality was found (hazard ratio 1.02, 95% confidential interval 0.227-4.53). Adverse effects, such as liver dysfunction, were less in the CFZ group than in the SAM group (p = 0.030). Therefore, in cases of poor CFZ supply or in patients allergic to CFZ and penicillinase-stable penicillins, SAM can be an effective therapeutic option for bacteremia due to BP-MSSA with attention of adverse effects, such as liver dysfunction.

Exploration of prognostic factors for prediction of mortality in elderly CAP population using a nomogram model

Background

The incidence and mortality rate of community-acquired pneumonia (CAP) in elderly patients were higher than the younger population. The assessment tools including CURB-65 and qSOFA have been applied in early detection of high-risk patients with CAP. However, several disadvantages exist to limit the efficiency of these tools for accurate assessment in elderly CAP. Therefore, we aimed to explore a more comprehensive tool to predict mortality in elderly CAP population by establishing a nomogram model.

Methods

We retrospectively analyzed elderly patients with CAP in Minhang Hospital, Fudan University. The least absolute shrinkage and selection operator (LASSO) logistic regression combined with multivariate analyses were used to select independent predictive factors and established nomogram models via R software. Calibration plots, decision curve analysis (DCA) and receiver operating characteristic curve (ROC) were generated to assess predictive performance.

Results

LASSO and multiple logistic regression analyses showed the age, pulse, NLR, albumin, BUN, and D-dimer were independent risk predictors. A nomogram model (NB-DAPA model) was established for predicting mortality of CAP in elderly patients. In both training and validation set, the area under the curve (AUC) of the NB-DAPA model showed superiority than CURB-65 and qSOFA. Meanwhile, DCA revealed that the predictive model had significant net benefits for most threshold probabilities.

Conclusion

Our established NB-DAPA nomogram model is a simple and accurate tool for predicting in-hospital mortality of CAP, adapted for patients aged 65 years and above. The predictive performance of the NB-DAPA model was better than PSI, CURB-65 and qSOFA.

Enhanced bedside mortality prediction combining point-of-care lactate and the quick Sequential Organ Failure Assessment (qSOFA) score in patients hospitalised with suspected infection in southeast Asia: a cohort study

Background

Simple, bedside prediction of infection-related mortality in low-resource settings is crucial for triage and resource-utilisation decisions. We aimed to evaluate mortality prediction by combining point-of-care venous lactate with the quick Sequential Organ Failure Assessment (qSOFA) score in adult patients admitted to hospital with suspected infection in southeast Asia.

Methods

We performed a cohort study by prospectively enrolling patients aged 18 years or older who had been admitted to hospital within the previous 24 h for suspected infection (with at least three documented systemic manifestations of infection according to the 2012 Surviving Sepsis Campaign) at Sunpasitthiprasong Hospital in Ubon Ratchathani, Thailand (derivation cohort). Venous lactate concentration was determined by a point-of-care device and multiple scores were developed. We then evaluated candidate 28-day mortality prediction models combining qSOFA and the lactate scores. A final model was compared with the qSOFA score, a lactate score, and a modified Sequential Organ Failure Assessment (SOFA) score for mortality discrimination using the area under the receiver operating characteristic curve (AUROC). Mortality discrimination of the qSOFA-lactate score was then verified in an external, prospectively enrolled, multinational cohort in southeast Asia.

Findings

Between March 1, 2013, and Jan 26, 2017, 5001 patients were enrolled in the derivation cohort; 4980 had point-of-care lactate data available and were eligible for analysis, and 816 died within 28 days of enrolment. The discrimination for 28-day mortality prediction of a qSOFA-lactate score combining the qSOFA score and a lactate score was superior to that of the qSOFA score alone (AUROC 0·78 [95% CI 0·76–0·80] vs 0·68 [0·67–0·70]; p<0·0001) and similar to a modified SOFA score (0·77 [0·75–0·78]; p=0·088). A lactate score alone had superior discrimination compared with the qSOFA score (AUROC 0·76 [95% CI 0.74–0.78]; p<0·0001). 815 patients were enrolled in the external validation cohort and 792 had point-of-care lactate data and were included in the analysis; the qSOFA-lactate score (AUROC 0·77 [95% CI 0·73–0·82]) showed significantly improved 28-day mortality discrimination compared with the qSOFA score alone (0·69 [0·63–0·74]; p<0·0001).

Interpretation

In southeast Asia, rapid, bedside assessments based on point-of-care lactate concentration combined with the qSOFA score can identify patients at risk of sepsis-related mortality with greater accuracy than the qSOFA score alone, and with similar accuracy to a modified SOFA score.

Funding

National Institutes of Health, Wellcome Trust.

MuLBSTA skorunun SARS-CoV-2 pnömonili hospitalize hastalarda kritik klinik sonuçları öngörmedeki prediktif değerinin incelenmesi

Giriş:MuLBSTA (Multilobar infiltrasyon, Lenfositopeni, Bakteriyel koenfeksiyon, Sigara öyküsü, hiperTansiyon ve Yaş> 65) skoru, viral pnömonisi olan hastaları beklenen mortaliteye göre sınıflandırmak için kullanılan bir klinik tahmin kuralıdır. Hastanede yatan Sars-Cov-2 hastalarında kötü klinik sonuçlar için MuLBSTA'nın prediktif performansını PSI, CURB-65 ve qSOFA ile karşılaştırdık. Metot:Bu çalışma 11 Mart 2020 ile 31 Mayıs 2020 tarihleri arasında üçüncü basamak bir üniversite hastanesinde yatan Sars-Cov-2'li hastalar üzerinde geriye dönük yapıldı. SARS-Cov-2 testi pozitif çıkan 900 hastadan 271'i çalışmaya dahil edildi. Tüm hastalarda 30 günlük mortalite, YBÜ ihtiyacı, mekanik ventilasyon gereksinimi ve ARDS gelişimini değerlendirmek için MuLBSTA, PSI, CURB65 ve qSOFA skoru kullanıldı. 30 günlük mortalite için prognostik faktörler de analiz edildi. Bulgular:Hastanede yatan 271 hastanın 150'si (%55.3) erkekti. Ortalama yaş 54.2 ± 15.4 yıldı. 30 günlük ölüm oranı %10,7 idi. Çalışmaya dahil edilen hastalardan; 39 hasta (%14,3) yoğun bakıma yatırıldı, 32 hasta (%11,8) mekanik ventilatör desteği aldı ve 23 hasta (%8,4) ARDS tanısı aldı. Mortaliteyi tahmin etmede MuLBSTA, PSI, CURB-65 ve qSOFA skorlarının alıcı işletim karakteristik eğrisi altında kalan alan(AUROC) değerleri sırasıyla 0.877 (%95 CI 0.832 0.914), 0.853 (%95 CI 0.806-0.893), 0.769 (95% CI 0,714-0,817) ve 0,769 (95% CI 0,715-0,818). MuLBSTA puanı, diğer tahmin puanlarına kıyasla daha yüksek bir AUROC değeri gösterdi. MuLBSTA ve PSI skorları, YBÜ ihtiyacı, mekanik ventilasyon gereksinimive ARDS gelişimi olan hastaları belirlemede CURB-65 ve qSOFA skorlarından daha iyi performans gösterdi. Sonuç:MuLBSTA skoru, hastanede yatan Sars-Cov-2 hastalarında kötü klinik sonuçları tahmin etmek için etkili bir araçtır. Kullanımını doğrulamak için daha fazla çalışmaya ihtiyaç vardır.

Septic shock 3.0 criteria application in severe COVID-19 patients: An unattended sepsis population with high mortality risk

BACKGROUND

Coronavirus disease 2019 (COVID-19) can be associated with life-threatening organ dysfunction due to septic shock, frequently requiring intensive care unit (ICU) admission, respiratory and vasopressor support. Therefore, clear clinical criteria are pivotal for early recognition of patients more likely to need prompt organ support. Although most patients with severe COVID-19 meet the Sepsis-3.0 criteria for septic shock, it has been increasingly recognized that hyperlactatemia is frequently absent, possibly leading to an underestimation of illness severity and mortality risk.

AIM

To identify the proportion of severe COVID-19 patients with vasopressor support requirements, with and without hyperlactatemia, and describe their clinical outcomes and mortality.

METHODS

We performed a single-center prospective cohort study. All adult patients admitted to the ICU with COVID-19 were included in the analysis and were further divided into three groups: Sepsis group, without both criteria; Vasoplegic Shock group, with persistent hypotension and vasopressor support without hyperlactatemia; and Septic Shock 3.0 group, with both criteria. COVID-19 was diagnosed using clinical and radiologic criteria with a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) positive RT-PCR test.

RESULTS

118 patients (mean age 63 years, 87% males) were included in the analysis (n = 51 Sepsis group, n = 26 Vasoplegic Shock group, and n = 41 Septic Shock 3.0 group). SOFA score at ICU admission and ICU length of stay were different between the groups (P < 0.001). Mortality was significantly higher in the Vasoplegic Shock and Septic Shock 3.0 groups when compared with the Sepsis group (P < 0.001) without a significant difference between the former two groups (P = 0.713). The log rank tests of Kaplan-Meier survival curves were also different (P = 0.007). Ventilator-free days and vasopressor-free days were different between the Sepsis vs Vasoplegic Shock and Septic Shock 3.0 groups (both P < 0.001), and similar in the last two groups (P = 0.128 and P = 0.133, respectively). Logistic regression identified the maximum dose of vasopressor therapy used (AOR 1.046; 95%CI: 1.012-1.082, P = 0.008) and serum lactate level (AOR 1.542; 95%CI: 1.055-2.255, P = 0.02) as the major explanatory variables of mortality rates (R² 0.79).

CONCLUSION

In severe COVID-19 patients, the Sepsis 3.0 criteria of septic shock may exclude approximately one third of patients with a similarly high risk of a poor outcome and mortality rate, which should be equally addressed.

Prognostic Accuracy of qSOFA and SIRS for Mortality in the Emergency Department: A Meta-Analysis and Systematic Review of Prospective Studies

Objective

This meta-analysis aimed to determine the prognostic performance of quick sequential organ failure assessment (qSOFA) score in comparison to systemic inflammatory response syndrome (SIRS) in predicting in-hospital mortality in the emergency department (ED) patients.

Methods

Eligible studies comparing the performance of qSOFA and SIRS in predicting in-hospital death of ED patients were identified from searching PubMed, Embase, and Cochrane. Raw data were collected, and the pooled sensitivity and specificity were calculated for qSOFA and SIRS. The summary receiver operating curve was also plotted to calculate the area under the curve.

Results

A total of 16 prospective studies with 35,756 patients and 2,285 deaths were included. The pooled sensitivity was 0.43 (95% CI: 0.32–0.54) and 0.8 (95% CI: 0.73–0.86) for qSOFA and SIRS, respectively. The pooled specificity was 0.89 (95% CI: 0.84–0.93) and 0.39 (95% CI: 0.3–0.5) for qSOFA and SIRS, respectively. The area under the summary receiver operating curve was 0.76 (95% CI: 0.72–0.8) and 0.67 (95% CI: 0.62–0.72) for qSOFA and SIRS, respectively. A significant heterogeneity was observed for both qSOFA and SIRS studies.

Conclusion

The present meta-analysis suggested that qSOFA had a higher specificity but a lower sensitivity as compared with SIRS in predicting in-hospital mortality in the ED patients. qSOFA appeared to be a more concise and simple way to recognize patients at high risk for death. However, the use of SIRS in the ED cannot be completely replaced since the sensitivity of qSOFA was relatively lower.

A Large Gap in Patients' Characteristics and Outcomes between the Real-World and Clinical Trial Settings in Community-Acquired Pneumonia and Healthcare-Associated Pneumonia

(1) Introduction: Evidence-based medicine (EBM) is necessary to standardize treatments for infections because EBM has been established based on the results of clinical trials. Since entry criteria for clinical trials are very strict, it may cause skepticism or questions on whether the results of clinical trials reflect the real world of medical practice. (2) Methods: To examine how many patients could join any randomized clinical trials for the treatment of community-acquired pneumonia (CAP) and healthcare-associated pneumonia (HCAP). We reviewed all the pneumonia patients in our institute during 2014–2017. The patients were divided into two groups: patients who were eligible for clinical trials (participation-possible group), and those who were not (participation-impossible group). Exclusion criteria for clinical trials were set based on previous clinical trials. (3) Results: A total of 406 patients were enrolled in the present study. Fifty-seven (14%) patients were categorized into the participation-possible group, while 86% of patients belonged to the participation-impossible group. Patients in the participation-possible group had less comorbidities and more favorable outcomes than those with the participation-impossible group. As for the outcomes, there were significant differences in the 30-day and in-hospital mortality rates between the two groups. In addition, the participation-possible group showed a longer overall survival time than the participation-impossible group (p < 0.001 by Log-Rank test). (4) Conclusion: There is a difference in patients’ profile and outcomes between clinical trials and the real world. Though EBM is essential to advance medicine, we should acknowledge the facts and the limits of the clinical trials.

Update on Pediatric Sepsis in Mexico

The main objective of this work was to determine and update the causal agents’ antibiotic sensitivity and resistance patterns on pediatric sepsis in a population of northeast Mexico. It is a cross-sectional study showing the results of blood cultures of pediatric patients with a presumptive diagnosis of sepsis were reviewed according to the SOFA criteria during 2020 in a public hospital in Mexico. A total of 207 blood cultures were performed and analyzed. The main isolated microorganisms were Staphylococcus, followed by Klebsiella and Escherichia. Several microorganisms showed 100% of sensitivity to different antibiotics or antifungals, some of them include Vancomycin, Voriconazole, Meropenem, Ciprofloxacin, and Cefotaxime. Bacteria of genre Staphylococcus showed its highest sensitivity rate to Tigecycline with 63.3%. Too Staphylococcus showed the highest resistance rate to Oxacillin with 50%. Although the patterns of sepsis-causing germs are similar to those previously reported, the development of new drugs with greater efficacy is the main contribution.

Development and Validation of a Prognostic Risk Score System for COVID-19 Inpatients: A Multi-Center Retrospective Study in China

Coronavirus disease 2019 (COVID-19) has become a worldwide pandemic. Hospitalized patients of COVID-19 suffer from a high mortality rate, motivating the development of convenient and practical methods that allow clinicians to promptly identify high-risk patients. Here, we have developed a risk score using clinical data from 1479 inpatients admitted to Tongji Hospital, Wuhan, China (development cohort) and externally validated with data from two other centers: 141 inpatients from Jinyintan Hospital, Wuhan, China (validation cohort 1) and 432 inpatients from The Third People's Hospital of Shenzhen, Shenzhen, China (validation cohort 2). The risk score is based on three biomarkers that are readily available in routine blood samples and can easily be translated into a probability of death. The risk score can predict the mortality of individual patients more than 12 d in advance with more than 90% accuracy across all cohorts. Moreover, the Kaplan-Meier score shows that patients can be clearly differentiated upon admission as low, intermediate, or high risk, with an area under the curve (AUC) score of 0.9551. In summary, a simple risk score has been validated to predict death in patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); it has also been validated in independent cohorts.

IL-6 and IL-10 Are Associated With Gram-Negative and Gram-Positive Bacteria Infection in Lymphoma

To investigate the Th1/Th2 cytokine profile in patients with lymphoma during the myelosuppression stage of infection. 52 patients with gram-negative bacterial infection (G- group), 49 patients with gram-positive bacterial infection (G+ group), 51 uninfected patients with lymphoma (uninfected group) and 20 healthy controls (healthy group) were enrolled in this study. We evaluated the quantification of Th1/Th2 cytokines with flow cytometry bead assay (CBA) in the sera to explore a rapid diagnostic method to determine the type of infection and anti-infective effect. The levels of procalcitonin (PCT) were also detected simultaneously. The four groups did not differ with regard to IL-2 and IL-4 (P>0.05). The IFN-γ and TNF-α levels of patients with lymphoma were higher than those of healthy controls (P<0.05). There was significantly upregulated IL-6 and IL-10 expression in the G- group (P<0.001). A similar trend was reflected in the IL-6 of the G+ group, which was significantly increased (P<0.001). However, no significant upregulation was observed for IL-10 in the G+ group. According to the different degrees of increased IL-6 and IL-10 levels, We proposed to use the G- Bacterial Infection Cytokine Profile (G- BICP) and the G+ Bacterial Infection Cytokine Profile (G+ BICP) for the first time to differentiate between Gram-negative and Gram-positive (G-/G+) bacterial infection in adults with lymphoma in the myelosuppression stage after chemotherapy. The IL-6, IL-10 and PCT in the G- group and the IL-6, PCT in the G+ group were significantly decreased at day 4 and day 8 compared with those at day 1. IL-6 and IL-10 are closely associated with the severity and treatment efficacy in adults with lymphomas who develop infections after chemotherapy and can help distinguish between G- and G+ bacterial infections at an early stage.

Utility of severity assessment tools in COVID-19 pneumonia: a multicentre observational study

BACKGROUND

Severity scores in pneumonia and sepsis are being applied to SARS-CoV-2 infection. We aimed to assess whether these severity scores are accurate predictors of early adverse outcomes in COVID-19.

METHODS

We conducted a multicentre observational study of hospitalised SARS-CoV-2 infection. We assessed risk scores (CURB65, qSOFA, Lac-CURB65, MuLBSTA and NEWS2) in relation to admission to intensive care or death within 7 days of admission, defined as early severe adverse events (ESAE). The 4C Mortality Score was also assessed in a sub-cohort of patients.

FINDINGS

In 2,387 participants, the overall mortality was 18%. In all scores examined, increasing score was associated with increased risk of ESAE. Area under the curve (AUC) to predict ESAE for CURB65, qSOFA, Lac-CURB65, MuLBSTA and NEWS2 were 0.61, 0.62, 0.59, 0.59 and 0.68, respectively. AUC to predict ESAE was 0.60 with ISARIC 4C Mortality Score.

CONCLUSION

None of the scores examined accurately predicted ESAE in SARS-CoV-2 infection. Non-validated scores should not be used to inform clinical decision making in COVID-19.

Management of pneumonia in critically ill patients

Severe pneumonia is associated with high mortality (short and long term), as well as pulmonary and extrapulmonary complications. Appropriate diagnosis and early initiation of adequate antimicrobial treatment for severe pneumonia are crucial in improving survival among critically ill patients. Identifying the underlying causative pathogen is also critical for antimicrobial stewardship. However, establishing an etiological diagnosis is challenging in most patients, especially in those with chronic underlying disease; those who received previous antibiotic treatment; and those treated with mechanical ventilation. Furthermore, as antimicrobial therapy must be empiric, national and international guidelines recommend initial antimicrobial treatment according to the location's epidemiology; for patients admitted to the intensive care unit, specific recommendations on disease management are available. Adherence to pneumonia guidelines is associated with better outcomes in severe pneumonia. Yet, the continuing and necessary research on severe pneumonia is expansive, inviting different perspectives on host immunological responses, assessment of illness severity, microbial causes, risk factors for multidrug resistant pathogens, diagnostic tests, and therapeutic options.

The timing of use of risk stratification tools affects their ability to predict mortality from sepsis. A meta-regression analysis

Background: Risk stratification tools (RSTs) are used in healthcare settings to identify patients at risk of sepsis and subsequent adverse outcomes. In practice RSTs are used on admission and thereafter as ‘trigger’ tools prompting sepsis management. However, studies investigating their performance report scores at a single timepoint which varies in relation to admission. The aim of this meta-analysis was to determine if the predictive performance of RSTs is altered by the timing of their use. Methods: We conducted a systematic review and meta-regression analysis of studies published from inception to 31 October 2018, using EMBASE and PubMed databases. Any cohort studies investigating the ability of an RST to predict mortality in adult sepsis patients admitted to hospital, from which a 2x2 table was available or could be constructed, were included. The diagnostic performance of RSTs in predicting mortality was the primary outcome. Sensitivity, specificity, positive predictive value, negative predictive value and area under the receiver-operating curve (AUROC) were the primary measures, enabling further meta-regression analysis. Results: 47 studies were included, comprising 430,427 patients. Results of bivariate meta-regression analysis found tools using a first-recorded score were less sensitive than those using worst-recorded score (REML regression coefficient 0.57, 95% CI 0.07-1.08). Using worst-recorded score led to a large increase in sensitivity (summary sensitivity 0.76, 95% CI 0.67-0.83, for worst-recorded scores vs. 0.64 (0.57-0.71) for first-recorded scores). Scoring system type did not have a significant relationship with studies’ predictive ability. The most analysed RSTs were qSOFA (n=37) and EWS (n=14). Further analysis of these RSTs also found timing of their use to be associated with predictive performance. Conclusion: The timing of any RST is paramount to their predictive performance. This must be reflected in their use in practice, and lead to prospective studies in future.

qSOFA predicted pneumonia mortality better than minor criteria and worse than CURB-65 with robust elements and higher convergence

BACKGROUND

Limited data are available on the discriminatory capacity of quick sequential [sepsis-related] organ failure assessment (qSOFA) versus IDSA/ATS minor criteria for predicting mortality in patients with community-acquired pneumonia (CAP).

METHODS

An observational prospective cohort study of 2116 patients with CAP was performed. Construct validity was determined using Cronbach α. Discrimination was assessed using the area under the receiver operating characteristic curve (AUROC) and net reclassification improvement (NRI).

RESULTS

Overall in-hospital mortality was 6.43%. Mortality was 25.96% for patients with a qSOFA score of 2 or higher versus 3.05% for those with a qSOFA score less than 2 (odds ratio for mortality 6.57, P < 0.0001), and 13.85% for patients with at least 3 minor criteria versus 2.03% for those with 2 or fewer minor criteria (odds ratio for mortality 2.27, P < 0.0001). qSOFA had a higher correlation with mortality than minor criteria, as well as higher internal consistency (Cronbach alpha 0.43 versus 0.14) and diagnostic values of individual elements (larger AUROCs and higher Youden's indices). qSOFA ≥2 was less sensitive but more specific for predicting mortality than ≥3 minor criteria (qSOFA sensitivity 59.6%, specificity 88.3% and positive likelihood ratio 5.11 versus ≥3 minor criteria sensitivity 80.1%, specificity 65.8% and positive likelihood ratio 2.34). The predictive validity of qSOFA was good for mortality (AUROC = 0.868), was statistically greater than minor criteria, was equal to pneumonia severity index, and was inferior compared with CURB-65 (AUROC, 0.824, 0.902, 0.919; NRI, 0.088, -0.068, -0.103; respectively).

CONCLUSIONS

The qSOFA predicted mortality in CAP better than IDSA/ATS minor criteria and worse than CURB-65 with robust elements and higher convergence. qSOFA as a bedside prompt might be positioned as a proxy for minor criteria and increase the recognition and thus merit more appropriate management of CAP patients likely to fare poorly, which might have implications for more accurate clinical triage decisions.

Cerebral dysfunctions caused by sepsis during ageing

Systemic inflammation elicited by sepsis can induce an acute cerebral dysfunction known as sepsis-associated encephalopathy (SAE). Recent evidence suggests that SAE is common but shows a dynamic trajectory over time. Half of all patients with sepsis develop SAE in the intensive care unit, and some survivors present with sustained cognitive impairments for several years after initial sepsis onset. It is not clear why some, but not all, patients develop SAE and also the factors that determine the persistence of SAE. Here, we first summarize the chronic pathology and the dynamic changes in cognitive functions seen after the onset of sepsis. We then outline the cerebral effects of sepsis, such as neuroinflammation, alterations in neuronal synapses and neurovascular changes. We discuss the key factors that might contribute to the development and persistence of SAE in older patients, including premorbid neurodegenerative pathology, side effects of sedatives, renal dysfunction and latent virus reactivation. Finally, we postulate that some of the mechanisms that underpin neuropathology in SAE may also be relevant to delirium and persisting cognitive impairments that are seen in patients with severe COVID-19.

In this Review, Manabe and Heneka examine how the systemic inflammation associated with sepsis can lead to acute cerebral dysfunction known as sepsis-associated encephalopathy (SAE). Moreover, they suggest that some of the mechanisms involved in SAE may be relevant for understanding the cognitive impairments that develop in some patients with COVID-19.

A Comprehensive Nomogram Combining CT Imaging with Clinical Features for Prediction of Lymph Node Metastasis in Stage I-IIIB Non-small Cell Lung Cancer

OBJECTIVE

The status of lymph node metastasis (LNM) is highly correlated with the recurrence and survival outcomes of patients with lung cancer. Thus, a tool that predicts LNM could benefit patient treatment and prognosis. The present study established a new radiomic model by combining computed tomography (CT) radiomic features and clinical parameters to predict the LNM status in patients with non-small cell lung cancer (NSCLC).

METHODS

Demographic parameters and clinical laboratory values were analyzed in 217 patients with stage I-IIIB NSCLC; 107 of the patients received CT scanning and radiomic characteristics were used for LNM assessment (76 in the training cohort and 31 in the validation cohort). The minimum redundancy maximum relevance (mRMR) and the least absolute shrinkage and selection operator (LASSO) regression model were used to select the most predictive features on the basis of the 76 patients in the training set. The value of the area under the receiver operator characteristic (ROC) curve (AUC) was adopted to determine the correlation between LN status and the radiomics signature in training cohorts and then validated in the 31 patients of validation set. The radiomics nomogram was analyzed using univariate and multivariate logistic regression. Decision curve analysis (DCA) was performed to evaluate the clinical utility of this model.

RESULTS

This was a retrospective study. Five radiomic characteristics were significantly correlated with LNM in the two cohorts (P < 0.05). The radiomic nomogram that incorporated the above radiomic characteristics, the RDW, and the CT-based LN status had satisfactory discrimination and calibration in the training (AUC, 0.79; 95% CI 0.69-0.89) and validation cohorts (AUC, 0.70; 95% CI 0.50-0.89).The DCA showed that the developed nomogram had promising clinical utility.

CONCLUSIONS

The developed nomogram, combined with preoperative radiomics evidence, the RDW, and the CT-based LN status, has the potential to preoperatively predict LNM with high accuracy and can facilitate the prediction of LN status for NSCLC patients.

The Impact of Risk Factors on Treatment Outcomes of Nosocomial Pneumonia Due to Gram-Negative Bacteria in the Intensive Care Unit

Introduction

Nosocomial pneumonia is a common infection associated with high mortality in hospitalized patients. Nosocomial pneumonia, caused by gram-negative bacteria, often occurs in the elderly and patients with co-morbid diseases.

Methods

Original research using a prospective cross-sectional design was conducted on 281 patients in an intensive care unit setting with nosocomial pneumonia between July 2015 and July 2019. For each nosocomial pneumonia case, data regarding comorbidities, risk factors, patient characteristics, Charlson comorbidity index (CCI), Systemic Inflammatory Response Syndrome (SIRS), and quick Sepsis-Related Organ Failure Assessment (qSOFA) points and treatment outcomes were collected. Data were analyzed by SPSS 22.0.

Results

Nosocomial pneumonia due to gram-negative bacteria occurred in patients with neurological disorders (34.87%), heart diseases (16.37%), chronic renal failure (7.12%), and post-surgery (10.68%). Worse outcomes attributed to nosocomial pneumonia were high at 75.8%. Mechanical ventilation, change of antibiotics, and CCI ≥ 3 and qSOFA ≥ 2 were significantly negative prognostic factors (p < 0.05) on outcomes of nosocomial pneumonia. There was no difference in treatment effects between gender, age, time of onset pneumonia, SIRS score (p > 0.05). The pathogens were significant factors that influence treatment effects, but they weren't independent risk factors for poor outcomes (p = 0.823).

Conclusions

Patients with nosocomial pneumonia hospitalized in intensive care units are usually associated with many underlying diseases, including neurological diseases. Mechanical ventilation, a change in antibiotics, CCI ≥ 3, and qSOFA ≥ 2 are also associated with a worse prognosis of nosocomial pneumonia. CCI and qSOFA might be used in predicting the outcome of nosocomial pneumonia.

Supplementary Information

The online version contains supplementary material available at 10.1007/s41030-021-00175-4.

Prognostic accuracy of Quick SOFA in older adults hospitalised with community acquired urinary tract infection

INTRODUCTION

Quick [Sepsis-related] Sequential Organ Failure Assessment (qSOFA) is a prognostic score based on sepsis-3 definition, easy to carry out, whose application has been studied in older adults with sepsis from different sources and respiratory sepsis. However, to date no study has analysed its prognostic accuracy in older adults admitted to hospital with community urinary tract infection.

METHODS

In a prospective study of 282 older adults admitted to hospital with community acquired urinary tract infection, the application of qSOFA to predict hospital mortality was analysed. The predictive capacity of qSOFA for in-hospital mortality was compared with Systemic Inflammatory Response Syndrome score (SIRS) and Sequential Organ Failure Assessment (SOFA), which require laboratory test in order to be calculated.

RESULTS

In a population with a median age of 81 years, where 51.8% were males and 10.6% had septic shock, qSOFA showed sensibility and specificity of 88.46 and 75.78% and area under the receiver operating characteristic curves (AUROC) of 0.810. AUROC for qSOFA was significantly higher than that of SIRS (AUROC 0.597, P = .005) and with no statistical differences with SOFA (AUROC 0.841, P = .635).

CONCLUSION

qSOFA showed a better predictive prognostic accuracy than SIRS and similar to SOFA in older adults admitted to hospital with community acquired urinary tract infection, having the advantage of not requiring laboratory tests.

Unplanned Transfers From Intermediate Care Units to Intensive Care Units: A Cohort Study

This study evaluated unplanned transfers from the intermediate care unit (IMCU) to the intensive care unit (ICU) among urgent admissions. This retrospective, observational study was conducted in 2 ICUs and 1 IMCU. Three patterns of urgent admission were assessed: admissions to the ICU only, admissions to the IMCU only, and admissions to the IMCU with subsequent transfer to the ICU. Of 5296 admissions analyzed, 1396 patients (26.4%) were initially admitted to the IMCU. Of these, 172 (12.3%) were transferred from the IMCU to the ICU. Mortality was higher in patients transferred from the IMCU to the ICU than in the 3900 ICU-only patients (odds ratio, 3.22; 95% CI, 1.52-6.80). Most transfers from the IMCU to the ICU (135; 78.5%) were due to deterioration of the condition for which the patient was admitted. Patient transfers from the IMCU to the ICU were common, were associated with increased hospital mortality, and were mostly due to deterioration in the condition that was the reason for admission.

Host-Microbe Metagenomics: a Lens To Refocus Our Perspective on Infectious and Inflammatory Diseases

A dynamic relationship involving pathogen, host immune response, and microbiome characterizes the biological framework of many infectious and inflammatory diseases. Combined host/microbe metagenomics (mNGS) enables simultaneous assessment of all three features, enabling the study and diagnosis of diverse infectious and inflammatory processes ranging from pneumonia to sepsis to inflammatory diseases such as rheumatoid arthritis. Host/microbe mNGS holds promise for new mechanistic insights, diagnostic approaches, and precision medicine interventions.

Relationship between the prehospital quick Sequential Organ Failure Assessment and prognosis in patients with sepsis or suspected sepsis: a population-based ORION registry

Aim

The quick Sequential Organ Failure Assessment (qSOFA) was proposed for use as a simple screening tool for sepsis. In this study, we evaluated the relationship between the prehospital use of qSOFA and prognosis in patients with sepsis or suspected sepsis using the population‐based Osaka Emergency Information Research Intelligent Operation Network (ORION) registry, which compiles prehospital ambulance data and in‐hospital information.

Methods

The study enrolled 437,974 patients in the ORION registry from January 1 to December 31, 2016. We selected hospitalized patients with sepsis or suspected sepsis using the appropriate codes from the International Classification of Diseases revision 10. We excluded patients with: (i) missing data (outcome, Japan Coma Scale, respiratory rate, and blood pressure); (ii) respiratory rate ≥60/min; and (iii) blood pressure ≥250 mmHg. These measures were evaluated by ambulance personnel when they first contacted the patient in the prehospital setting. The primary end‐point was discharge to death.

Results

In total, 12,646 patients (median age, 78 [interquartile range, 65–85] years; male, n = 6,760 [53.5%]) were eligible for our analysis. In a multivariable logistic regression analysis adjusted for confounding factors, the proportion of patients discharged to death was significantly higher for those evaluated as qSOFA positive (≥2 points) than qSOFA negative (≤1 point) (265/2,250 [11.78%] vs. 415/10,396 [3.99%]; adjusted odds ratio 2.91; 95% confidence interval, 2.47–3.43; P < 0.0001). The specificity and sensitivity were 83.4% and 39.0%, respectively, and the area under the receiver operating characteristic curve for qSOFA positive was 0.61.

Conclusions

The qSOFA evaluated by ambulance personnel in the prehospital setting was significantly associated with prognosis in patients with sepsis or suspected sepsis.

Performance of CURB-65, PSI, and APACHE-II for predicting COVID-19 pneumonia severity and mortality

No prognostic tools for the prediction of COVID-19 pneumonia severity and mortality are available. We explored whether CURB-65, PSI, and APACHE-II could predict COVID-19 pneumonia severity and mortality. We included 167 patients with confirmed COVID-19 pneumonia in this retrospective study. The severity and 30-day mortality of COVID-19 pneumonia were predicted using PSI, CURB-65, and APACHE-II scales. Kappa test was performed to compare the consistency of the three scales. There was a significant difference in the distribution of the scores of the three scales ( P < 0.001). Patients with PSI class ⩽III, CURB-65 ⩽1, and APACHE-II-I all survived. The ROC analysis showed the areas under the curve of the PSI, CURB-65, and APACHE-II scales were 0.83 (95% CI, 0.74–0.93), 0.80 (95% CI, 0.69–0.90), and 0.83 (95% CI, 0.75–0.92), respectively. Our findings suggest that PSI and CURB-65 might be useful to predict the severity and mortality of COVID-19 pneumonia.

The Surviving Sepsis Campaign: research priorities for the administration, epidemiology, scoring and identification of sepsis

Objective

To identify priorities for administrative, epidemiologic and diagnostic research in sepsis.

Design

As a follow-up to a previous consensus statement about sepsis research, members of the Surviving Sepsis Campaign Research Committee, representing the European Society of Intensive Care Medicine and the Society of Critical Care Medicine addressed six questions regarding care delivery, epidemiology, organ dysfunction, screening, identification of septic shock, and information that can predict outcomes in sepsis.

Methods

Six questions from the Scoring/Identification and Administration sections of the original Research Priorities publication were explored in greater detail to better examine the knowledge gaps and rationales for questions that were previously identified through a consensus process.

Results

The document provides a framework for priorities in research to address the following questions: (1) What is the optimal model of delivering sepsis care?; (2) What is the epidemiology of sepsis susceptibility and response to treatment?; (3) What information identifies organ dysfunction?; (4) How can we screen for sepsis in various settings?; (5) How do we identify septic shock?; and (6) What in-hospital clinical information is associated with important outcomes in patients with sepsis?

Conclusions

There is substantial knowledge of sepsis epidemiology and ways to identify and treat sepsis patients, but many gaps remain. Areas of uncertainty identified in this manuscript can help prioritize initiatives to improve an understanding of individual patient and demographic heterogeneity with sepsis and septic shock, biomarkers and accurate patient identification, organ dysfunction, and ways to improve sepsis care.

[Management of Adult Community-Acquired Pneumonia and Prevention - Update 2021 - Guideline of the German Respiratory Society (DGP), the Paul-Ehrlich-Society for Chemotherapy (PEG), the German Society for Infectious Diseases (DGI), the German Society of Medical Intensive Care and Emergency Medicine (DGIIN), the German Viological Society (DGV), the Competence Network CAPNETZ, the German College of General Practitioneers and Family Physicians (DEGAM), the German Society for Geriatric Medicine (DGG), the German Palliative Society (DGP), the Austrian Society of Pneumology Society (ÖGP), the Austrian Society for Infectious and Tropical Diseases (ÖGIT), the Swiss Respiratory Society (SGP) and the Swiss Society for Infectious Diseases Society (SSI)]

The present guideline provides a new and updated concept of the management of adult patients with community-acquired pneumonia. It replaces the previous guideline dating from 2016.The guideline was worked out and agreed on following the standards of methodology of a S3-guideline. This includes a systematic literature search and grading, a structured discussion of recommendations supported by the literature as well as the declaration and assessment of potential conflicts of interests.The guideline has a focus on specific clinical circumstances, an update on severity assessment, and includes recommendations for an individualized selection of antimicrobial treatment.The recommendations aim at the same time at a structured assessment of risk for adverse outcome as well as an early determination of treatment goals in order to reduce mortality in patients with curative treatment goal and to provide palliation for patients with treatment restrictions.

Ceftriaxone versus tazobactam/piperacillin and carbapenems in the treatment of aspiration pneumonia: A propensity score matching analysis

INTRODUCTION

Aspiration pneumonia (AP) accounts for 5.0-53.2% of hospitalized pneumonia and the treatment commonly used is by broad-spectrum antibiotics to cover anaerobes. Since ceftriaxone (CTRX) could generally cover oral streptococcus and anaerobes implicated in AP, it could be a useful option in the treatment of AP, instead of piperacillin-tazobactam/(PIPC/TAZ) or Carbapenems.

PATIENTS AND METHODS

For the purpose of examining whether CTRX is as effective as broad-spectrum antibiotics for the treatment of AP, this retrospective study included consecutive community-onset patients who were admitted to our institute between 2014 and 2017. These patients were divided into two groups, a CTRX group (n = 25) and a PIPC/TAZ or carbapenems group (n = 97) based on the initial antibiotic treatment. Propensity score matching (PSM) was used to balance the potential confounders, and 23 patients were selected from each group. Patients among CTXR group received CTRX, while those among PIPC/TAZ or carbapenems group received PIPC/TAZ, or carbapenems and/or other agents.

RESULTS

Both groups were well-balanced after PSM. There were no differences in 30-day mortality, duration of hospital stay or antibiotic treatments in the between them. The medical costs were much more expensive in the PIPC/TAZ or carbapenems group than in the CTR group (35,582 v. s. 8678 Japanese yen, p < 0.001).

CONCLUSION

CTRX is one of the most useful antibiotic treatment for AP, which is not inferior to broad-spectrum antibiotic treatment. In addition, usage of CTRX in the treatment of AP is more economical than broad-spectrum antibiotic treatment, and could contribute to reduction of medical costs.

An Attention Model With Transfer Embeddings to Classify Pneumonia-Related Bilingual Imaging Reports: Algorithm Development and Validation

BACKGROUND

In the analysis of electronic health records, proper labeling of outcomes is mandatory. To obtain proper information from radiologic reports, several studies were conducted to classify radiologic reports using deep learning. However, the classification of pneumonia in bilingual radiologic reports has not been conducted previously.

OBJECTIVE

The aim of this research was to classify radiologic reports into pneumonia or no pneumonia using a deep learning method.

METHODS

A data set of radiology reports for chest computed tomography and chest x-rays of surgical patients from January 2008 to January 2018 in the Asan Medical Center in Korea was retrospectively analyzed. The classification performance of our long short-term memory (LSTM)-Attention model was compared with various deep learning and machine learning methods. The area under the receiver operating characteristic curve (AUROC), area under the precision-recall curve, sensitivity, specificity, accuracy, and F1 score for the models were compared.

RESULTS

A total of 5450 radiologic reports were included that contained at least one pneumonia-related word. In the test set (n=1090), our proposed model showed 91.01% (992/1090) accuracy (AUROCs for negative, positive, and obscure were 0.98, 0.97, and 0.90, respectively). The top 3 performances of the models were based on FastText or LSTM. The convolutional neural network-based model showed a lower accuracy 73.03% (796/1090) than the other 2 algorithms. The classification of negative results had an F1 score of 0.96, whereas the classification of positive and uncertain results showed a lower performance (positive F1 score 0.83; uncertain F1 score 0.62). In the extra-validation set, our model showed 80.0% (642/803) accuracy (AUROCs for negative, positive, and obscure were 0.92, 0.96, and 0.84, respectively).

CONCLUSIONS

Our method showed excellent performance in classifying pneumonia in bilingual radiologic reports. The method could enrich the research on pneumonia by obtaining exact outcomes from electronic health data.

Severity Scores in COVID-19 Pneumonia: a Multicenter, Retrospective, Cohort Study

BACKGROUND

Identification of patients on admission to hospital with coronavirus infectious disease 2019 (COVID-19) pneumonia who can develop poor outcomes has not yet been comprehensively assessed.

OBJECTIVE

To compare severity scores used for community-acquired pneumonia to identify high-risk patients with COVID-19 pneumonia.

DESIGN

PSI, CURB-65, qSOFA, and MuLBSTA, a new score for viral pneumonia, were calculated on admission to hospital to identify high-risk patients for in-hospital mortality, admission to an intensive care unit (ICU), or use of mechanical ventilation. Area under receiver operating characteristics curve (AUROC), sensitivity, and specificity for each score were determined and AUROC was compared among them.

PARTICIPANTS

Patients with COVID-19 pneumonia included in the SEMI-COVID-19 Network.

KEY RESULTS

We examined 10,238 patients with COVID-19. Mean age of patients was 66.6 years and 57.9% were males. The most common comorbidities were as follows: hypertension (49.2%), diabetes (18.8%), and chronic obstructive pulmonary disease (12.8%). Acute respiratory distress syndrome (34.7%) and acute kidney injury (13.9%) were the most common complications. In-hospital mortality was 20.9%. PSI and CURB-65 showed the highest AUROC (0.835 and 0.825, respectively). qSOFA and MuLBSTA had a lower AUROC (0.728 and 0.715, respectively). qSOFA was the most specific score (specificity 95.7%) albeit its sensitivity was only 26.2%. PSI had the highest sensitivity (84.1%) and a specificity of 72.2%.

CONCLUSIONS

PSI and CURB-65, specific severity scores for pneumonia, were better than qSOFA and MuLBSTA at predicting mortality in patients with COVID-19 pneumonia. Additionally, qSOFA, the simplest score to perform, was the most specific albeit the least sensitive.

Comparing scoring systems for prediction of mortality in patients with bloodstream infection

BACKGROUND

Blood stream infections (BSIs) are associated with significant short-term mortality. There are many different scoring systems for assessing the severity of BSI.

AIM

We studied confusion, urea, respiratory rate, blood pressure, age 65(CURB65), Confusion Respiratory Rate, Blood pressure, age 65(CRB65), quick sequential organ failure assessment (qSOFA), systemic inflammatory response syndrome (SIRS) and National Early Warning Score (NEWS) and assessed how effective they were at predicting 30-day mortality across three separate BSI cohorts.

DESIGN

A retrospective analysis was performed on three established BSI cohorts: (i) All cause BSI, (ii) Escherichia coli and (iii) Streptococcus pneumoniae.

METHODS

The performance characteristics (sensitivity, specificity, positive predictive value, negative predictive value and area under receiver operating curve [AUROC]) for the prediction of 30-day mortality were calculated for the 5 scores using clinically relevant cut-offs.

RESULTS

528 patients were included: All cause BSI-148, E. coli-191 and S. pneumoniae-189. Overall, 30-day mortality was 22%. In predicting mortality, the AUROC for CURB65 and CRB65 were superior compared with qSOFA, SIRS and NEWS in the all cause BSI (0.72, 0.70, 0.66, 0.51 and 0.53) and E. coli cohorts (0.81, 0.76, 0.73, 0.55 and 0.71). In the pneumococcal cohort, CURB65, CRB65, qSOFA and NEWS were broadly equal (0.63, 0.65, 0.66 and 0.62), but all were superior to SIRS (0.57). CURB65, CRB65 and qSOFA had considerably higher accuracy than SIRS or NEWS across all cohorts.

CONCLUSION

CURB65 was superior to other scores in predicting 30-day mortality in the E. coli and all cause BSI cohorts. Further research is required to assess the potential of broadening the application of CURB65 beyond pneumonia.

Community-acquired pneumonia severity assessment tools in patients hospitalized with COVID-19: a validation and clinical applicability study

Objective

To externally validate community-acquired pneumonia (CAP) tools on patients hospitalized with coronavirus disease 2019 (COVID-19) pneumonia from two distinct countries, and compare their performance with recently developed COVID-19 mortality risk stratification tools.

Methods

We evaluated 11 risk stratification scores in a binational retrospective cohort of patients hospitalized with COVID-19 pneumonia in São Paulo and Barcelona: Pneumonia Severity Index (PSI), CURB, CURB-65, qSOFA, Infectious Disease Society of America and American Thoracic Society Minor Criteria, REA-ICU, SCAP, SMART-COP, CALL, COVID GRAM and 4C. The primary and secondary outcomes were 30-day in-hospital mortality and 7-day intensive care unit (ICU) admission, respectively. We compared their predictive performance using the area under the receiver operating characteristics curve (AUC), sensitivity, specificity, likelihood ratios, calibration plots and decision curve analysis.

Results

Of 1363 patients, the mean (SD) age was 61 (16) years. The 30-day in-hospital mortality rate was 24.6% (228/925) in São Paulo and 21.0% (92/438) in Barcelona. For in-hospital mortality, we found higher AUCs for PSI (0.79, 95% CI 0.77–0.82), 4C (0.78, 95% CI 0.75–0.81), COVID GRAM (0.77, 95% CI 0.75–0.80) and CURB-65 (0.74, 95% CI 0.72–0.77). Results were similar for both countries. For the 1%–20% threshold range in decision curve analysis, PSI would avoid a higher number of unnecessary interventions, followed by the 4C score. All scores had poor performance (AUC <0.65) for 7-day ICU admission.

Conclusions

Recent clinical COVID-19 assessment scores had comparable performance to standard pneumonia prognostic tools. Because it is expected that new scores outperform older ones during development, external validation studies are needed before recommending their use.

CAPRL Scoring System for Prediction of 30-day Mortality in 949 Patients with Coronavirus Disease 2019 in Wuhan, China: A Retrospective, Observational Study

Background

Coronavirus disease 2019 (COVID-19) is a serious and even lethal respiratory illness. The mortality of critically ill patients with COVID-19, especially short term mortality, is considerable. It is crucial and urgent to develop risk models that can predict the mortality risks of patients with COVID-19 at an early stage, which is helpful to guide clinicians in making appropriate decisions and optimizing the allocation of hospital resoureces.

Methods

In this retrospective observational study, we enrolled 949 adult patients with laboratory-confirmed COVID-19 admitted to Tongji Hospital in Wuhan between January 28 and February 12, 2020. Demographic, clinical and laboratory data were collected and analyzed. A multivariable Cox proportional hazard regression analysis was performed to calculate hazard ratios and 95% confidence interval for assessing the risk factors for 30-day mortality.

Results

The 30-day mortality was 11.8% (112 of 949 patients). Forty-nine point nine percent (474) patients had one or more comorbidities, with hypertension being the most common (359 [37.8%] patients), followed by diabetes (169 [17.8%] patients) and coronary heart disease (89 [9.4%] patients). Age above 50 years, respiratory rate above 30 beats per minute, white blood cell count of more than10 × 109/L, neutrophil count of more than 7 × 109/L, lymphocyte count of less than 0.8 × 109/L, platelet count of less than 100 × 109/L, lactate dehydrogenase of more than 400 U/L and high-sensitivity C-reactive protein of more than 50 mg/L were independent risk factors associated with 30-day mortality in patients with COVID-19. A predictive CAPRL score was proposed integrating independent risk factors. The 30-day mortality were 0% (0 of 156), 1.8% (8 of 434), 12.9% (26 of 201), 43.0% (55 of 128), and 76.7% (23 of 30) for patients with 0, 1, 2, 3, ≥4 points, respectively.

Conclusions

We designed an easy-to-use clinically predictive tool for assessing 30-day mortality risk of COVID-19. It can accurately stratify hospitalized patients with COVID-19 into relevant risk categories and could provide guidance to make further clinical decisions.

Noninvasive ventilation and high-flow oxygen therapy for severe community-acquired pneumonia

PURPOSE OF REVIEW

We review the evidence on the use of noninvasive respiratory supports (noninvasive ventilation and high-flow nasal cannula oxygen therapy) in patients with acute respiratory failure because of severe community-acquired pneumonia.

RECENT FINDINGS

Noninvasive ventilation is strongly advised for the treatment of hypercapnic respiratory failure and recent evidence justifies its use in patients with hypoxemic respiratory failure when delivered by helmet. Indeed, such interface allows alveolar recruitment by providing high level of positive end-expiratory pressure, which improves hypoxemia. On the other hand, high-flow nasal cannula oxygen therapy is effective in patients with hypoxemic respiratory failure and some articles support its use in patients with hypercapnia. However, early identification of noninvasive respiratory supports treatment failure is crucial to prevent delayed orotracheal intubation and protective invasive mechanical ventilation.

SUMMARY

Noninvasive ventilation is the first-line therapy in patients with acute hypercapnic respiratory failure because of pneumonia. Although an increasing amount of evidence investigated the application of noninvasive respiratory support to hypoxemic respiratory failure, the optimal ventilatory strategy in this setting is uncertain. Noninvasive mechanical ventilation delivered by helmet and high-flow nasal cannula oxygen therapy appear as promising tools but their role needs to be confirmed by future research.

Quick sequential organ failure assessment versus systemic inflammatory response syndrome criteria for emergency department patients with suspected infection

Previous studies have shown inconsistent prognostic accuracy for mortality with both quick sequential organ failure assessment (qSOFA) and the systemic inflammatory response syndrome (SIRS) criteria. We aimed to validate the accuracy of qSOFA and the SIRS criteria for predicting in-hospital mortality in patients with suspected infection in the emergency department. A prospective study was conducted including participants with suspected infection who were hospitalised or died in 34 emergency departments in Japan. Prognostic accuracy of qSOFA and SIRS criteria for in-hospital mortality was assessed by the area under the receiver operating characteristic (AUROC) curve. Of the 1060 participants, 402 (37.9%) and 915 (86.3%) had qSOFA ≥ 2 and SIRS criteria ≥ 2 (given thresholds), respectively, and there were 157 (14.8%) in-hospital deaths. Greater accuracy for in-hospital mortality was shown with qSOFA than with the SIRS criteria (AUROC: 0.64 versus 0.52, difference + 0.13, 95% CI [+ 0.07, + 0.18]). Sensitivity and specificity for predicting in-hospital mortality at the given thresholds were 0.55 and 0.65 based on qSOFA and 0.88 and 0.14 based on SIRS criteria, respectively. To predict in-hospital mortality in patients visiting to the emergency department with suspected infection, qSOFA was demonstrated to be modestly more accurate than the SIRS criteria albeit insufficiently sensitive.Clinical Trial Registration: The study was pre-registered in the University Hospital Medical Information Network Clinical Trials Registry (UMIN000027258).