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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:BackgroundThe morbidity and mortality among hospital inpatients with AECOPD and CVDs remains unacceptably high. Currently, no risk score for predicting mortality has been specifically developed in patients with AECOPD and CVDs. We therefore aimed to derive and validate a simple clinical risk score to assess individuals' risk of poor prognosis.Study design and methodsWe evaluated inpatients with AECOPD and CVDs in a prospective, noninterventional, multicenter cohort study. We used multivariable logistic regression analysis to identify the independent prognostic risk factors and created a risk score model according to patients' data from a derivation cohort. Discrimination was evaluated by the area under the receiver-operating characteristic curve (AUC), and calibration was assessed by the Hosmer-Lemeshow goodness-of-fit test. The model was validated and compared with the BAP-65, CURB-65, DECAF and NIVO models in a validation cohort.ResultsWe derived a combined risk score, the ABCDMP score, that included the following variables: age > 75 years, BUN > 7 mmol/L, consolidation, diastolic blood pressure ≤ 60 mmHg, mental status altered, and pulse > 109 beats/min. Discrimination (AUC 0.847, 95% CI, 0.805-0.890) and calibration (Hosmer‒Lemeshow statistic, P = 0.142) were good in the derivation cohort and similar in the validation cohort (AUC 0.811, 95% CI, 0.755-0.868). The ABCDMP score had significantly better predictivity for in-hospital mortality than the BAP-65, CURB-65, DECAF, and NIVO scores (all P < 0.001). Additionally, the new score also had moderate predictive performance for 3-year mortality and can be used to stratify patients into different management groups.ConclusionsThe ABCDMP risk score could help predict mortality in AECOPD and CVDs patients and guide further clinical research on risk-based treatment.Clinical trial registrationChinese Clinical Trail Registry NO.:ChiCTR2100044625; URL: http://www.chictr.org.cn/showproj.aspx?proj=121626 .

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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