Dataset Information

Clinical Features Predicting Mortality Risk in Patients With Viral Pneumonia: The MuLBSTA Score.

ABSTRACT: Objective:The aim of this study was to further clarify clinical characteristics and predict mortality risk among patients with viral pneumonia. Methods:A total of 528 patients with viral pneumonia at RuiJin hospital in Shanghai from May 2015 to May 2019 were recruited. Multiplex real-time RT-PCR was used to detect respiratory viruses. Demographic information, comorbidities, routine laboratory examinations, immunological indexes, etiological detections, radiological images and treatment were collected on admission. Results:76 (14.4%) patients died within 90 days in hospital. A predictive MuLBSTA score was calculated on the basis of a multivariate logistic regression model in order to predict mortality with a weighted score that included multilobular infiltrates (OR = 5.20, 95% CI 1.41-12.52, p = 0.010; 5 points), lymphocyte ? 0.8?109/L (OR = 4.53, 95% CI 2.55-8.05, p < 0.001; 4 points), bacterial coinfection (OR = 3.71, 95% CI 2.11-6.51, p < 0.001; 4 points), acute-smoker (OR = 3.19, 95% CI 1.34-6.26, p = 0.001; 3 points), quit-smoker (OR = 2.18, 95% CI 0.99-4.82, p = 0.054; 2 points), hypertension (OR = 2.39, 95% CI 1.55-4.26, p = 0.003; 2 points) and age ?60 years (OR = 2.14, 95% CI 1.04-4.39, p = 0.038; 2 points). 12 points was used as a cut-off value for mortality risk stratification. This model showed sensitivity of 0.776, specificity of 0.778 and a better predictive ability than CURB-65 (AUROC = 0.773 vs. 0.717, p < 0.001). Conclusion:Here, we designed an easy-to-use clinically predictive tool for assessing 90-day mortality risk of viral pneumonia. It can accurately stratify hospitalized patients with viral pneumonia into relevant risk categories and could provide guidance to make further clinical decisions.

SUBMITTER: Guo L

PROVIDER: S-EPMC6901688 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Clinical Features Predicting Mortality Risk in Patients With Viral Pneumonia: The MuLBSTA Score.

Guo Lingxi L Wei Dong D Zhang Xinxin X Wu Yurong Y Li Qingyun Q Zhou Min M Qu Jieming J

Frontiers in microbiology 20191203

<h4>Objective</h4>The aim of this study was to further clarify clinical characteristics and predict mortality risk among patients with viral pneumonia.<h4>Methods</h4>A total of 528 patients with viral pneumonia at RuiJin hospital in Shanghai from May 2015 to May 2019 were recruited. Multiplex real-time RT-PCR was used to detect respiratory viruses. Demographic information, comorbidities, routine laboratory examinations, immunological indexes, etiological detections, radiological images and trea ...[more]

PMID: 31849894

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Project description:AimsThis study aimed to develop and validate a simple method for predicting long-term all-cause mortality in ambulatory patients with chronic heart failure (CHF) residing in an area where Chagas disease is endemic, which will be important not only for patients living in Latin America but also to those living in developed non-endemic countries.Methods and resultsA total of 677 patients with a wide spectrum of aetiologies for left ventricular systolic dysfunction and receiving optimized evidence-based treatment for CHF were prospectively followed for approximately 11 years. We established a risk score using Cox proportional hazard regression models. After multivariable analysis, four variables were independently associated with mortality and included in the CALL Risk Score: Chagas cardiomyopathy aetiology alone [hazard ratio, 3.36; 95% confidence interval (CI), 2.61-4.33; P < 0.001], age ≥60 years (hazard ratio, 1.36; 95% CI, 1.06-1.74; P = 0.016), left anterior fascicular block (hazard ratio, 1.64; 95% CI, 1.27-2.11; P < 0.001), and left ventricular ejection fraction <40% (hazard ratio, 1.73; 95% CI, 1.30-2.28; P < 0.001). The internal validation considered the bootstrapping, a resampling technique recommended for prediction model development. Hence, we established a scoring system attributing weights according to each risk factor: 3 points for Chagas cardiomyopathy alone, 1 point for age ≥60 years, and 2 points each for left anterior fascicular block and left ventricular ejection fraction <40%. Three risk groups were identified: low risk (score ≤2 points), intermediate risk (score of 3 to 5 points), and high risk (score ≥6 points). High-risk patients had more than two-fold increase in mortality (26.9 events/100 patient-years) compared with intermediate-risk patients (10.1 events/100 patient-years) and almost seven-fold increase compared with low-risk patients (4.3 events/100 patient-years). The CALL Risk Score data sets from the development and internal validation cohorts both displayed suitable discrimination c-index of 0.689 (95% CI, 0.688-0.690; P < 0.001) and 0.687 (95% CI, 0.686-0.688; P < 0.001), respectively, and satisfactory calibration [Greenwood-Nam-D'Agostino test (8) = 7.867; P = 0.447] and [Greenwood-Nam-D'Agostino test (8) = 10.08; P = 0.273], respectively.ConclusionsThe CALL Risk Score represents a simple and validated method with a limited number of non-invasive variables that successfully predicts long-term all-cause mortality in a real-world cohort of patients with CHF. Patients with CHF stratified as high risk according to the CALL Risk Score should be monitored and aggressively managed, including those with CHF secondary to Chagas disease.

Dataset Information

Clinical Features Predicting Mortality Risk in Patients With Viral Pneumonia: The MuLBSTA Score.

Publications

Clinical Features Predicting Mortality Risk in Patients With Viral Pneumonia: The MuLBSTA Score.

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