{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,13]],"date-time":"2026-10-13T23:19:14Z","timestamp":1791933554928,"version":"4.3.4"},"reference-count":48,"publisher":"Public Library of Science (PLoS)","issue":"9","license":[{"start":{"date-parts":[[2022,9,9]],"date-time":"2022-09-09T00:00:00Z","timestamp":1662681600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001411","name":"Indian Council of Medical Research","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001411","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS ONE"],"abstract":"<jats:sec id=\"sec001\">\n<jats:title>Aim<\/jats:title>\n<jats:p>To develop an accurate lab score based on in-hospital patients\u2019 potent clinical and biological parameters for predicting COVID-19 patient severity during hospital admission.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec002\">\n<jats:title>Methods<\/jats:title>\n<jats:p>To conduct this retrospective analysis, a derivation cohort was constructed by including all the available biological and clinical parameters of 355 COVID positive patients (recovered = 285, deceased = 70), collected in November 2020-September 2021. For identifying potent biomarkers and clinical parameters to determine hospital admitted patient severity or mortality, the receiver operating characteristics (ROC) curve and Fischer\u2019s test analysis was performed. Relative risk regression was estimated to develop laboratory scores for each clinical and routine biological parameter. Lab score was further validated by ROC curve analysis of the validation cohort which was built with 50 COVID positive hospital patients, admitted during October 2021-January 2022.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec003\">\n<jats:title>Results<\/jats:title>\n<jats:p>Sensitivity vs. 1-specificity ROC curve (&gt;0.7 Area Under the Curve, 95% CI) and univariate analysis (p&lt;0.0001) of the derivation cohort identified five routine biomarkers (neutrophil, lymphocytes, neutrophil: lymphocytes, WBC count, ferritin) and three clinical parameters (patient age, pre-existing comorbidities, admitted with pneumonia) for the novel lab score development. Depending on the relative risk (p values and 95% CI) these clinical parameters were scored and attributed to both the derivation cohort (n = 355) and the validation cohort (n = 50). ROC curve analysis estimated the Area Under the Curve (AUC) of the derivation and validation cohort which was 0.914 (0.883\u20130.945, 95% CI) and 0.873 (0.778\u20130.969, 95% CI) respectively.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec004\">\n<jats:title>Conclusion<\/jats:title>\n<jats:p>The development of proper lab scores, based on patients\u2019 clinical parameters and routine biomarkers, would help physicians to predict patient risk at the time of their hospital admission and may improve hospital-admitted COVID-19 patients\u2019 survivability.<\/jats:p>\n<\/jats:sec>","DOI":"10.1371\/journal.pone.0273006","type":"journal-article","created":{"date-parts":[[2022,9,9]],"date-time":"2022-09-09T20:56:24Z","timestamp":1662756984000},"page":"e0273006","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":9,"title":["Development of lab score system for predicting COVID-19 patient severity: A retrospective analysis"],"prefix":"10.1371","volume":"17","author":[{"given":"Arnab","family":"Sarkar","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Surojit","family":"Sanyal","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Agniva","family":"Majumdar","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Devendra Nath","family":"Tewari","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Uttaran","family":"Bhattacharjee","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Juhi","family":"Pal","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7611-909X","authenticated-orcid":true,"given":"Alok Kumar","family":"Chakrabarti","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6897-7390","authenticated-orcid":true,"given":"Shanta","family":"Dutta","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2022,9,9]]},"reference":[{"key":"pone.0273006.ref001","doi-asserted-by":"crossref","first-page":"264","DOI":"10.1016\/j.ijid.2020.01.009","article-title":"The continuing 2019-nCoV epidemic threat of novel coronaviruses to global health\u2014The latest 2019 novel coronavirus outbreak in Wuhan, China","volume":"91","author":"I Hui DS","year":"2020","journal-title":"Int J Infect Dis"},{"key":"pone.0273006.ref002","doi-asserted-by":"crossref","first-page":"707","DOI":"10.1001\/jama.2020.0757","article-title":"Coronavirus Infections\u2014More Than Just the Common Cold","volume":"323","author":"CI Paules","year":"2020","journal-title":"JAMA"},{"key":"pone.0273006.ref003","doi-asserted-by":"crossref","first-page":"182","DOI":"10.1080\/1040841X.2020.1739001","article-title":"Emergence of Novel Coronavirus and COVID-19: whether to stay or die out?","volume":"46","author":"A Biswas","year":"2020","journal-title":"Crit Rev Microbiol"},{"key":"pone.0273006.ref004","doi-asserted-by":"crossref","first-page":"181","DOI":"10.1007\/s40258-020-00632-2","article-title":"How Many Intensive Care Beds are Justifiable for Hospital Pandemic Preparedness? 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