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

Lingxi Guo, Dong Wei, Xinxin Zhang, Yurong Wu, Qingyun Li, Min Zhou, Jieming Qu, Lingxi Guo, Dong Wei, Xinxin Zhang, Yurong Wu, Qingyun Li, Min Zhou, Jieming Qu

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.

Keywords: bacterial coinfection; clinical feature; predicting mortality; predictive score model; virus pneumonia.

Copyright © 2019 Guo, Wei, Zhang, Wu, Li, Zhou and Qu.

Figures

FIGURE 1
FIGURE 1
Study flowchart. RT-PCR: reverse-transcription polymerase chain reaction.
FIGURE 2
FIGURE 2
Distribution of respiratory virus and proportion of bacterial infection detected by sputum or blood culture for each virus. The number of patients infected by each virus is presented on the right side of the corresponding horizontal axis.
FIGURE 3
FIGURE 3
Multivariate analysis associated with mortality of virus-infected pneumonia patients.
FIGURE 4
FIGURE 4
Survival of viral pneumonia patients by different levels of MuLBSTA score (p < 0.001). For inhospital mortality: MuLBSTA 0–11 = Low risk; ≥12 = High risk.
FIGURE 5
FIGURE 5
Characteristic curves for prediction of patients with viral pneumonia (n = 528). C-index of MuLBSTA score and CURB-65 score are 0.811 and 0.735 separately. The bootstrapped (n = 2000) c-index of MuLBSTA and CURB-65 are 0.803 and 0.743.

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