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A Retrospective Observational Study to Determine the Early Predictors of In-hospital Mortality at Admission with COVID-19

INTRODUCTION: Coronavirus disease-2019 (COVID-19) systemic illness caused by a novel coronavirus severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) has been spreading across the world. The objective of this study is to identify the clinical and laboratory variables as predictors of in-hosp...

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Autores principales: Jain, Aakanksha Chawla, Kansal, Sudha, Sardana, Raman, Bali, Roseleen K, Kar, Sujoy, Chawla, Rajesh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Jaypee Brothers Medical Publishers 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7775949/
https://www.ncbi.nlm.nih.gov/pubmed/33446968
http://dx.doi.org/10.5005/jp-journals-10071-23683
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author Jain, Aakanksha Chawla
Kansal, Sudha
Sardana, Raman
Bali, Roseleen K
Kar, Sujoy
Chawla, Rajesh
author_facet Jain, Aakanksha Chawla
Kansal, Sudha
Sardana, Raman
Bali, Roseleen K
Kar, Sujoy
Chawla, Rajesh
author_sort Jain, Aakanksha Chawla
collection PubMed
description INTRODUCTION: Coronavirus disease-2019 (COVID-19) systemic illness caused by a novel coronavirus severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) has been spreading across the world. The objective of this study is to identify the clinical and laboratory variables as predictors of in-hospital death at the time of admission in a tertiary care hospital in India. MATERIALS AND METHODS: Demographic profile, clinical, and laboratory variables of 425 patients admitted from April to June 2020 with symptoms and laboratory-confirmed diagnosis through real-time polymerase chain reaction (RT-PCR) were studied. Descriptive statistics, an association of these variables, logistic regression, and CART models were developed to identify early predictors of in-hospital death. RESULTS: Twenty-two patients (5.17%) had expired in course of their hospital stay. The median age [interquartile range (IQR)] of the patients admitted was 49 years (21–77 years). Gender distribution was male — 73.38% (mortality rate 5.83%) and female—26.62% (mortality rate 3.34%). The study shows higher association for age (>47 years) [odds ratio (OR) 4.52], male gender (OR 1.78), shortness of breath (OR 2.02), oxygen saturation <93% (OR 9.32), respiratory rate >24 (OR 5.31), comorbidities like diabetes (OR 2.70), hypertension (OR 2.12), and coronary artery disease (OR 3.18) toward overall mortality. The significant associations in laboratory variables include lymphopenia (<12%) (OR 8.74), C-reactive protein (CRP) (OR 1.99), ferritin (OR 3.18), and lactate dehydrogenase (LDH) (OR 3.37). Using this statistically significant 16 clinical and laboratory variables, the logistic regression model had an area under receiver operating characteristic (ROC) curve of 0.86 (train) and 0.75 (test). CONCLUSION: Age above 47 years, associated with comorbidities like hypertension and diabetes, with oxygen saturation below 93%, tachycardia, and deranged laboratory variables like lymphopenia and raised CRP, LDH, and ferritin are important predictors of in-hospital mortality. HOW TO CITE THIS ARTICLE: Jain AC, Kansal S, Sardana R, Bali RK, Kar S, Chawla R. A Retrospective Observational Study to Determine the Early Predictors of In-hospital Mortality at Admission with COVID-19. Indian J Crit Care Med 2020;24(12):1174–1179.
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spelling pubmed-77759492021-01-13 A Retrospective Observational Study to Determine the Early Predictors of In-hospital Mortality at Admission with COVID-19 Jain, Aakanksha Chawla Kansal, Sudha Sardana, Raman Bali, Roseleen K Kar, Sujoy Chawla, Rajesh Indian J Crit Care Med Original Article INTRODUCTION: Coronavirus disease-2019 (COVID-19) systemic illness caused by a novel coronavirus severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) has been spreading across the world. The objective of this study is to identify the clinical and laboratory variables as predictors of in-hospital death at the time of admission in a tertiary care hospital in India. MATERIALS AND METHODS: Demographic profile, clinical, and laboratory variables of 425 patients admitted from April to June 2020 with symptoms and laboratory-confirmed diagnosis through real-time polymerase chain reaction (RT-PCR) were studied. Descriptive statistics, an association of these variables, logistic regression, and CART models were developed to identify early predictors of in-hospital death. RESULTS: Twenty-two patients (5.17%) had expired in course of their hospital stay. The median age [interquartile range (IQR)] of the patients admitted was 49 years (21–77 years). Gender distribution was male — 73.38% (mortality rate 5.83%) and female—26.62% (mortality rate 3.34%). The study shows higher association for age (>47 years) [odds ratio (OR) 4.52], male gender (OR 1.78), shortness of breath (OR 2.02), oxygen saturation <93% (OR 9.32), respiratory rate >24 (OR 5.31), comorbidities like diabetes (OR 2.70), hypertension (OR 2.12), and coronary artery disease (OR 3.18) toward overall mortality. The significant associations in laboratory variables include lymphopenia (<12%) (OR 8.74), C-reactive protein (CRP) (OR 1.99), ferritin (OR 3.18), and lactate dehydrogenase (LDH) (OR 3.37). Using this statistically significant 16 clinical and laboratory variables, the logistic regression model had an area under receiver operating characteristic (ROC) curve of 0.86 (train) and 0.75 (test). CONCLUSION: Age above 47 years, associated with comorbidities like hypertension and diabetes, with oxygen saturation below 93%, tachycardia, and deranged laboratory variables like lymphopenia and raised CRP, LDH, and ferritin are important predictors of in-hospital mortality. HOW TO CITE THIS ARTICLE: Jain AC, Kansal S, Sardana R, Bali RK, Kar S, Chawla R. A Retrospective Observational Study to Determine the Early Predictors of In-hospital Mortality at Admission with COVID-19. Indian J Crit Care Med 2020;24(12):1174–1179. Jaypee Brothers Medical Publishers 2020-12 /pmc/articles/PMC7775949/ /pubmed/33446968 http://dx.doi.org/10.5005/jp-journals-10071-23683 Text en Copyright © 2020; Jaypee Brothers Medical Publishers (P) Ltd. © The Author(s). 2020 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted use, distribution, and non-commercial reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Original Article
Jain, Aakanksha Chawla
Kansal, Sudha
Sardana, Raman
Bali, Roseleen K
Kar, Sujoy
Chawla, Rajesh
A Retrospective Observational Study to Determine the Early Predictors of In-hospital Mortality at Admission with COVID-19
title A Retrospective Observational Study to Determine the Early Predictors of In-hospital Mortality at Admission with COVID-19
title_full A Retrospective Observational Study to Determine the Early Predictors of In-hospital Mortality at Admission with COVID-19
title_fullStr A Retrospective Observational Study to Determine the Early Predictors of In-hospital Mortality at Admission with COVID-19
title_full_unstemmed A Retrospective Observational Study to Determine the Early Predictors of In-hospital Mortality at Admission with COVID-19
title_short A Retrospective Observational Study to Determine the Early Predictors of In-hospital Mortality at Admission with COVID-19
title_sort retrospective observational study to determine the early predictors of in-hospital mortality at admission with covid-19
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7775949/
https://www.ncbi.nlm.nih.gov/pubmed/33446968
http://dx.doi.org/10.5005/jp-journals-10071-23683
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