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Predictors of mortality for patients with COVID-19 pneumonia caused by SARS-CoV-2: a prospective cohort study.

TLDR
Age ≥65 years, pre-existing concurrent cardiovascular or cerebrovascular diseases, CD3+CD8+ T-cells ≤75 cells·μL−1 and cardiac troponin I ≥0.05 ng·mL−1 were four risk factors predicting high mortality of COVID-19 pneumonia patients.
Abstract
The aim of this study was to identify factors associated with the death of patients with COVID-19 pneumonia caused by the novel coronavirus SARS-CoV-2. All clinical and laboratory parameters were collected prospectively from a cohort of patients with COVID-19 pneumonia who were hospitalised to Wuhan Pulmonary Hospital (Wuhan City, Hubei Province, China) between 25 December 2019 and 7 February 2020. Univariate and multivariate logistic regression was performed to investigate the relationship between each variable and the risk of death of COVID-19 pneumonia patients. In total, 179 patients with COVID-19 pneumonia (97 male and 82 female) were included in the present prospective study, of whom 21 died. Univariate and multivariate logistic regression analysis revealed that age ≥65 years (OR 3.765, 95% CI 1.146‒17.394; p=0.023), pre-existing concurrent cardiovascular or cerebrovascular diseases (OR 2.464, 95% CI 0.755‒8.044; p=0.007), CD3+CD8+ T-cells ≤75 cells·μL−1 (OR 3.982, 95% CI 1.132‒14.006; p We identified four risk factors: age ≥65 years, pre-existing concurrent cardiovascular or cerebrovascular diseases, CD3+CD8+ T-cells ≤75 cells·μL−1 and cardiac troponin I ≥0.05 ng·mL−1. The latter two factors, especially, were predictors for mortality of COVID-19 pneumonia patients.

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Journal ArticleDOI

Predictors of mortality for patients with COVID-19 pneumonia caused by SARS-CoV-2.

TL;DR: In this paper, the authors investigated the predictors of mortality for patients with COVID-19 pneumonia caused by SARS-CoV-2: a prospective cohort study and found that COVID19 pneumonia is associated with higher mortality.
Journal ArticleDOI

Predicting severe outcomes in Covid-19 related illness using only patient demographics, comorbidities and symptoms.

TL;DR: Severe Covid-19 illness can be predicted using data that could be obtained from a remote screening using only presenting symptoms, comorbidities and demographic data, and fair ability to discriminate severe vs non-severe outcomes is demonstrated.
Journal ArticleDOI

Correlation of Pectoralis Muscle Volume and Density with Severity of COVID-19 Pneumonia in Adults.

TL;DR: CT-derived measurements of the pectoralis muscle can be useful in predicting disease severity and mortality rate of COVID-19 pneumonia in adult patients.
Journal ArticleDOI

The association between ambient temperature and mortality of the coronavirus disease 2019 (COVID-19) in Wuhan, China: a time-series analysis.

TL;DR: In this article, a Poisson distributed lag nonlinear model was constructed to evaluate the non-linear delayed effects of ambient temperature on death, by using the daily new death of COVID-19 and ambient temperature data from January 10 to March 31, 2020.
References
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Journal ArticleDOI

A Novel Coronavirus from Patients with Pneumonia in China, 2019.

TL;DR: Human airway epithelial cells were used to isolate a novel coronavirus, named 2019-nCoV, which formed a clade within the subgenus sarbecovirus, Orthocoronavirinae subfamily, which is the seventh member of the family of coronaviruses that infect humans.
Journal ArticleDOI

Clinical Characteristics of 138 Hospitalized Patients With 2019 Novel Coronavirus-Infected Pneumonia in Wuhan, China.

TL;DR: The epidemiological and clinical characteristics of novel coronavirus (2019-nCoV)-infected pneumonia in Wuhan, China, and hospital-associated transmission as the presumed mechanism of infection for affected health professionals and hospitalized patients are described.
Journal ArticleDOI

Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study

TL;DR: Characteristics of patients who died were in line with the MuLBSTA score, an early warning model for predicting mortality in viral pneumonia, and further investigation is needed to explore the applicability of the Mu LBSTA scores in predicting the risk of mortality in 2019-nCoV infection.
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