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Predictors of mortality among hospitalized COVID-19 patients and risk score formulation for prioritizing tertiary care—An experience from South India

BACKGROUND: We retrospectively data-mined the case records of Reverse Transcription Polymerase Chain Reaction (RT-PCR) confirmed COVID-19 patients hospitalized to a tertiary care centre to derive mortality predictors and formulate a risk score, for prioritizing admission. METHODS AND FINDINGS: Data...

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Autores principales: Gopalan, Narendran, Senthil, Sumathi, Prabakar, Narmadha Lakshmi, Senguttuvan, Thirumaran, Bhaskar, Adhin, Jagannathan, Muthukumaran, Sivaraman, Ravi, Ramasamy, Jayalakshmi, Chinnaiyan, Ponnuraja, Arumugam, Vijayalakshmi, Getrude, Banumathy, Sakthivel, Gautham, Srinivasalu, Vignes Anand, Rajendran, Dhanalakshmi, Nadukkandiyil, Arunjith, Ravi, Vaishnavi, Hifzour Rahamane, Sadiqa Nasreen, Athur Paramasivam, Nirmal, Manoharan, Tamizhselvan, Theyagarajan, Maheshwari, Chadha, Vineet Kumar, Natrajan, Mohan, Dhanaraj, Baskaran, Murhekar, Manoj Vasant, Ramalingam, Shanthi Malar, Chandrasekaran, Padmapriyadarsini
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8812932/
https://www.ncbi.nlm.nih.gov/pubmed/35113971
http://dx.doi.org/10.1371/journal.pone.0263471
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author Gopalan, Narendran
Senthil, Sumathi
Prabakar, Narmadha Lakshmi
Senguttuvan, Thirumaran
Bhaskar, Adhin
Jagannathan, Muthukumaran
Sivaraman, Ravi
Ramasamy, Jayalakshmi
Chinnaiyan, Ponnuraja
Arumugam, Vijayalakshmi
Getrude, Banumathy
Sakthivel, Gautham
Srinivasalu, Vignes Anand
Rajendran, Dhanalakshmi
Nadukkandiyil, Arunjith
Ravi, Vaishnavi
Hifzour Rahamane, Sadiqa Nasreen
Athur Paramasivam, Nirmal
Manoharan, Tamizhselvan
Theyagarajan, Maheshwari
Chadha, Vineet Kumar
Natrajan, Mohan
Dhanaraj, Baskaran
Murhekar, Manoj Vasant
Ramalingam, Shanthi Malar
Chandrasekaran, Padmapriyadarsini
author_facet Gopalan, Narendran
Senthil, Sumathi
Prabakar, Narmadha Lakshmi
Senguttuvan, Thirumaran
Bhaskar, Adhin
Jagannathan, Muthukumaran
Sivaraman, Ravi
Ramasamy, Jayalakshmi
Chinnaiyan, Ponnuraja
Arumugam, Vijayalakshmi
Getrude, Banumathy
Sakthivel, Gautham
Srinivasalu, Vignes Anand
Rajendran, Dhanalakshmi
Nadukkandiyil, Arunjith
Ravi, Vaishnavi
Hifzour Rahamane, Sadiqa Nasreen
Athur Paramasivam, Nirmal
Manoharan, Tamizhselvan
Theyagarajan, Maheshwari
Chadha, Vineet Kumar
Natrajan, Mohan
Dhanaraj, Baskaran
Murhekar, Manoj Vasant
Ramalingam, Shanthi Malar
Chandrasekaran, Padmapriyadarsini
author_sort Gopalan, Narendran
collection PubMed
description BACKGROUND: We retrospectively data-mined the case records of Reverse Transcription Polymerase Chain Reaction (RT-PCR) confirmed COVID-19 patients hospitalized to a tertiary care centre to derive mortality predictors and formulate a risk score, for prioritizing admission. METHODS AND FINDINGS: Data on clinical manifestations, comorbidities, vital signs, and basic lab investigations collected as part of routine medical management at admission to a COVID-19 tertiary care centre in Chengalpattu, South India between May and November 2020 were retrospectively analysed to ascertain predictors of mortality in the univariate analysis using their relative difference in distribution among ‘survivors’ and ‘non-survivors’. The regression coefficients of those factors remaining significant in the multivariable logistic regression were utilised for risk score formulation and validated in 1000 bootstrap datasets. Among 746 COVID-19 patients hospitalised [487 “survivors” and 259 “non-survivors” (deaths)], there was a slight male predilection [62.5%, (466/746)], with a higher mortality rate observed among 40–70 years age group [59.1%, (441/746)] and highest among diabetic patients with elevated urea levels [65.4% (68/104)]. The adjusted odds ratios of factors [OR (95% CI)] significant in the multivariable logistic regression were SaO(2)<95%; 2.96 (1.71–5.18), Urea ≥50 mg/dl: 4.51 (2.59–7.97), Neutrophil-lymphocytic ratio (NLR) >3; 3.01 (1.61–5.83), Age ≥50 years;2.52 (1.45–4.43), Pulse Rate ≥100/min: 2.02 (1.19–3.47) and coexisting Diabetes Mellitus; 1.73 (1.02–2.95) with hypertension and gender not retaining their significance. The individual risk scores for SaO(2)<95–11, Urea ≥50 mg/dl-15, NLR >3–11, Age ≥50 years-9, Pulse Rate ≥100/min-7 and coexisting diabetes mellitus-6, acronymed collectively as ‘OUR-ARDs score’ showed that the sum of scores ≥ 25 predicted mortality with a sensitivity-90%, specificity-64% and AUC of 0.85. CONCLUSIONS: The ‘OUR ARDs’ risk score, derived from easily assessable factors predicting mortality, offered a tangible solution for prioritizing admission to COVID-19 tertiary care centre, that enhanced patient care but without unduly straining the health system.
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spelling pubmed-88129322022-02-04 Predictors of mortality among hospitalized COVID-19 patients and risk score formulation for prioritizing tertiary care—An experience from South India Gopalan, Narendran Senthil, Sumathi Prabakar, Narmadha Lakshmi Senguttuvan, Thirumaran Bhaskar, Adhin Jagannathan, Muthukumaran Sivaraman, Ravi Ramasamy, Jayalakshmi Chinnaiyan, Ponnuraja Arumugam, Vijayalakshmi Getrude, Banumathy Sakthivel, Gautham Srinivasalu, Vignes Anand Rajendran, Dhanalakshmi Nadukkandiyil, Arunjith Ravi, Vaishnavi Hifzour Rahamane, Sadiqa Nasreen Athur Paramasivam, Nirmal Manoharan, Tamizhselvan Theyagarajan, Maheshwari Chadha, Vineet Kumar Natrajan, Mohan Dhanaraj, Baskaran Murhekar, Manoj Vasant Ramalingam, Shanthi Malar Chandrasekaran, Padmapriyadarsini PLoS One Research Article BACKGROUND: We retrospectively data-mined the case records of Reverse Transcription Polymerase Chain Reaction (RT-PCR) confirmed COVID-19 patients hospitalized to a tertiary care centre to derive mortality predictors and formulate a risk score, for prioritizing admission. METHODS AND FINDINGS: Data on clinical manifestations, comorbidities, vital signs, and basic lab investigations collected as part of routine medical management at admission to a COVID-19 tertiary care centre in Chengalpattu, South India between May and November 2020 were retrospectively analysed to ascertain predictors of mortality in the univariate analysis using their relative difference in distribution among ‘survivors’ and ‘non-survivors’. The regression coefficients of those factors remaining significant in the multivariable logistic regression were utilised for risk score formulation and validated in 1000 bootstrap datasets. Among 746 COVID-19 patients hospitalised [487 “survivors” and 259 “non-survivors” (deaths)], there was a slight male predilection [62.5%, (466/746)], with a higher mortality rate observed among 40–70 years age group [59.1%, (441/746)] and highest among diabetic patients with elevated urea levels [65.4% (68/104)]. The adjusted odds ratios of factors [OR (95% CI)] significant in the multivariable logistic regression were SaO(2)<95%; 2.96 (1.71–5.18), Urea ≥50 mg/dl: 4.51 (2.59–7.97), Neutrophil-lymphocytic ratio (NLR) >3; 3.01 (1.61–5.83), Age ≥50 years;2.52 (1.45–4.43), Pulse Rate ≥100/min: 2.02 (1.19–3.47) and coexisting Diabetes Mellitus; 1.73 (1.02–2.95) with hypertension and gender not retaining their significance. The individual risk scores for SaO(2)<95–11, Urea ≥50 mg/dl-15, NLR >3–11, Age ≥50 years-9, Pulse Rate ≥100/min-7 and coexisting diabetes mellitus-6, acronymed collectively as ‘OUR-ARDs score’ showed that the sum of scores ≥ 25 predicted mortality with a sensitivity-90%, specificity-64% and AUC of 0.85. CONCLUSIONS: The ‘OUR ARDs’ risk score, derived from easily assessable factors predicting mortality, offered a tangible solution for prioritizing admission to COVID-19 tertiary care centre, that enhanced patient care but without unduly straining the health system. Public Library of Science 2022-02-03 /pmc/articles/PMC8812932/ /pubmed/35113971 http://dx.doi.org/10.1371/journal.pone.0263471 Text en © 2022 Gopalan et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Gopalan, Narendran
Senthil, Sumathi
Prabakar, Narmadha Lakshmi
Senguttuvan, Thirumaran
Bhaskar, Adhin
Jagannathan, Muthukumaran
Sivaraman, Ravi
Ramasamy, Jayalakshmi
Chinnaiyan, Ponnuraja
Arumugam, Vijayalakshmi
Getrude, Banumathy
Sakthivel, Gautham
Srinivasalu, Vignes Anand
Rajendran, Dhanalakshmi
Nadukkandiyil, Arunjith
Ravi, Vaishnavi
Hifzour Rahamane, Sadiqa Nasreen
Athur Paramasivam, Nirmal
Manoharan, Tamizhselvan
Theyagarajan, Maheshwari
Chadha, Vineet Kumar
Natrajan, Mohan
Dhanaraj, Baskaran
Murhekar, Manoj Vasant
Ramalingam, Shanthi Malar
Chandrasekaran, Padmapriyadarsini
Predictors of mortality among hospitalized COVID-19 patients and risk score formulation for prioritizing tertiary care—An experience from South India
title Predictors of mortality among hospitalized COVID-19 patients and risk score formulation for prioritizing tertiary care—An experience from South India
title_full Predictors of mortality among hospitalized COVID-19 patients and risk score formulation for prioritizing tertiary care—An experience from South India
title_fullStr Predictors of mortality among hospitalized COVID-19 patients and risk score formulation for prioritizing tertiary care—An experience from South India
title_full_unstemmed Predictors of mortality among hospitalized COVID-19 patients and risk score formulation for prioritizing tertiary care—An experience from South India
title_short Predictors of mortality among hospitalized COVID-19 patients and risk score formulation for prioritizing tertiary care—An experience from South India
title_sort predictors of mortality among hospitalized covid-19 patients and risk score formulation for prioritizing tertiary care—an experience from south india
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8812932/
https://www.ncbi.nlm.nih.gov/pubmed/35113971
http://dx.doi.org/10.1371/journal.pone.0263471
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