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Predictors of critical illness and mortality based on symptoms and initial physical examination for patients with SARS-CoV-2: A retrospective cohort study

INTRODUCTION: An unidentified cluster of pneumonia was identified in Wuhan city of China in the last week of December 2019, named Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-COV-2). The current study explored the predictors associated with critical illness and mortality based on symptoms a...

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Detalles Bibliográficos
Autores principales: Bairwa, Mukesh, Kumar, Rajesh, Ajmal, Mohammed, Bahurupi, Yogesh, Kant, Ravi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Authors. Published by Elsevier Ltd on behalf of King Saud Bin Abdulaziz University for Health Sciences. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8213400/
https://www.ncbi.nlm.nih.gov/pubmed/34153728
http://dx.doi.org/10.1016/j.jiph.2021.06.010
Descripción
Sumario:INTRODUCTION: An unidentified cluster of pneumonia was identified in Wuhan city of China in the last week of December 2019, named Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-COV-2). The current study explored the predictors associated with critical illness and mortality based on symptoms at the time of admission and initial physical examination findings in patients with SARS-CoV-2. MATERIAL AND METHODS: A total of 249 records of laboratory-confirmed SARS-COV-2 patients were analyzed. Demographic profile and findings of initial physical examination were collected and analyzed. Bivariate logistic and multivariable stepwise forward regression analysis was used to identify the predictors of critical illness and mortality. RESULTS: A total of 249 records of SARS-COV-2 patients were retrospectively studied, of whom 66 (26.5%) developed a critical illness, and 58 (23.29%) died. The mean age of patients was 45.15 (16.34) years; 171 (68.71%) were men. From 27 potential predictors for developing a critical illness, 15 were reported independent predictors for critical illness, and 13 were for increased risk of mortality. Stepwise forward regression reported dyspnea as a single strongest predictor (OR, 5.800, 95% CI-2.724−12.346; p = 0.001, R(2) = 0.272) to develop critical illness. Likewise, the respiratory rate was alone reported as a strong predictor (OR, 1.381, 95% CI- 1.251−1.525; p = 0.000, R(2) = 0.329) for mortality. CONCLUSIONS: Coronavirus disease is a new challenge to the medical fraternity, leading to significant morbidity and mortality. Knowledge of potential risk factors could help clinicians assess patients' risk with unfavourable outcomes and improve hospitalization decisions in the early stage.