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Open AccessJournal ArticleDOI

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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Posted ContentDOI

Can we predict the severe course of COVID-19? A systematic review and meta-analysis of indicators of clinical outcome.

TL;DR: This comprehensive meta-analysis found age, cerebrovascular disease, CRP, LDH and cTnI to be the most important risk-factors in predicting severe COVID-19 outcomes and will inform decision analytical tools to support clinical decision-making.
Journal ArticleDOI

Identification of Parameters Representative of Immune Dysfunction in Patients with Severe and Fatal COVID-19 Infection: a Systematic Review and Meta-analysis

TL;DR: In this paper , the authors conducted an electronic search of PubMed, Scopus, Ovid, Willey, Web of Science, Cochrane library, and CNKI for studies reporting immunological and/or immune related parameters, including hematological, inflammatory, coagulation, and biochemical variables, tested on hospital admission of COVID-19 patients with different severities and outcomes.
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Lymphocyte subsets early predict mortality in a large series of hospitalized COVID-19 patients in Spain.

TL;DR: Reduced counts of CD4+ and CD8+ T cells with proportional expansion of NK lymphocytes at admission were prognostic factors of death in this Spanish series of SARS‐CoV‐2‐infected patients.
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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