{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,16]],"date-time":"2026-09-16T18:33:47Z","timestamp":1789583627516,"version":"build-2803163510"},"reference-count":43,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2024,10,17]],"date-time":"2024-10-17T00:00:00Z","timestamp":1729123200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003196","name":"Ministero della Salute","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100003196","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Aging"],"abstract":"<jats:sec><jats:title>Background<\/jats:title><jats:p>Once the pandemic ended, SARS-CoV-2 became endemic, with flare-up phases. COVID-19 disease can still have a significant clinical impact, especially in older patients with multimorbidity and frailty.<\/jats:p><\/jats:sec><jats:sec><jats:title>Objective<\/jats:title><jats:p>This study aims at evaluating the main characteristics associated to in-hospital mortality among data routinely collected upon admission to identify older patients at higher risk of death.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>The present study used data from Gerocovid-acute wards, an observational multicenter retrospective-prospective study conducted in geriatric and internal medicine wards in subjects \u226560\u00a0years old during the COVID-19 pandemic. Seventy-one routinely collected variables, including demographic data, living arrangements, smoking habits, pre-COVID-19 mobility, chronic diseases, and clinical and laboratory parameters were integrated into a web-based machine learning platform (Just Add Data Bio) to identify factors with the highest prognostic relevance. The use of artificial intelligence allowed us to avoid variable selection bias, to test a large number of models and to perform an internal validation.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>The dataset was split into training and test sets, based on a 70:30 ratio and matching on age, sex, and proportion of events; 3,520 models were set out to train. The three predictive algorithms (optimized for performance, interpretability, or aggressive feature selection) converged on the same model, including 12 variables: pre-COVID-19 mobility, World Health Organization disease severity, age, heart rate, arterial blood gases bicarbonate and oxygen saturation, serum potassium, systolic blood pressure, blood glucose, aspartate aminotransferase, PaO2\/FiO2 ratio and derived neutrophil-to-lymphocyte ratio.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>Beyond variables reflecting the severity of COVID-19 disease failure, pre-morbid mobility level was the strongest factor associated with in-hospital mortality reflecting the importance of functional status as a synthetic measure of health in older adults, while the association between derived neutrophil-to-lymphocyte ratio and mortality, confirms the fundamental role played by neutrophils in SARS-CoV-2 disease.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fragi.2024.1473632","type":"journal-article","created":{"date-parts":[[2024,10,17]],"date-time":"2024-10-17T05:17:04Z","timestamp":1729142224000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":7,"title":["Prediction of COVID-19 in-hospital mortality in older patients using artificial intelligence: a multicenter study"],"prefix":"10.3389","volume":"5","author":[{"given":"Massimiliano","family":"Fedecostante","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jacopo","family":"Sabbatinelli","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Giuseppina","family":"Dell\u2019Aquila","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fabio","family":"Salvi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anna Rita","family":"Bonfigli","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stefano","family":"Volpato","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Caterina","family":"Trevisan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stefano","family":"Fumagalli","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fabio","family":"Monzani","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Raffaele","family":"Antonelli Incalzi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fabiola","family":"Olivieri","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Antonio","family":"Cherubini","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2024,10,17]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"505","DOI":"10.1080\/14737159.2021.1915773","article-title":"The diagnostic and prognostic role of neutrophil-to-lymphocyte ratio in COVID-19: a systematic review and meta-analysis","volume":"21","author":"Alkhatip","year":"2021","journal-title":"Expert Rev. Mol. diagnostics"},{"key":"B2","doi-asserted-by":"publisher","first-page":"326","DOI":"10.1093\/ageing\/afaa258","article-title":"Clinical profile and predictors of in-hospital mortality among older patients hospitalised for COVID-19","volume":"50","author":"Becerra-Mu\u00f1oz","year":"2021","journal-title":"Age Ageing"},{"key":"B3","doi-asserted-by":"publisher","first-page":"26","DOI":"10.1186\/s13613-022-00996-9","article-title":"The association of the Activities of Daily Living and the outcome of old intensive care patients suffering from COVID-19","volume":"12","author":"Bruno","year":"2022","journal-title":"Ann. intensive care"},{"key":"B4","doi-asserted-by":"publisher","first-page":"24522","DOI":"10.18632\/aging.202307","article-title":"Mortality in an Italian nursing home during COVID-19 pandemic: correlation with gender, age, ADL, vitamin D supplementation, and limitations of the diagnostic tests","volume":"12","author":"Cangiano","year":"2020","journal-title":"Aging"},{"key":"B5","doi-asserted-by":"publisher","first-page":"1711","DOI":"10.1007\/s11739-023-03338-0","article-title":"Improving prediction of COVID-19 mortality using machine learning in the Spanish SEMI-COVID-19 registry","volume":"18","author":"Casas-Rojo","year":"2023","journal-title":"Intern. Emerg. Med."},{"key":"B6","doi-asserted-by":"publisher","first-page":"465","DOI":"10.1007\/s41999-023-00790-1","article-title":"Clinical profile of trazodone users in a multisetting older population: data from the Italian GeroCovid Observational study","volume":"14","author":"Coin","year":"2023","journal-title":"Eur. Geriatr. Med."},{"key":"B7","doi-asserted-by":"publisher","first-page":"104383","DOI":"10.1016\/j.archger.2021.104383","article-title":"Predictors of in-hospital mortality AND death RISK STRATIFICATION among COVID-19 PATIENTS aged \u2265 80 YEARs OLD","volume":"95","author":"Covino","year":"2021","journal-title":"Arch. Gerontol. Geriatr."},{"key":"B8","doi-asserted-by":"publisher","first-page":"835","DOI":"10.1186\/s12967-023-04717-z","article-title":"Neutrophil-to-lymphocyte ratio (NLR) predicts mortality in hospitalized geriatric patients independent of the admission diagnosis: a multicenter prospective cohort study","volume":"21","author":"Di Rosa","year":"2023","journal-title":"J. Transl. Med."},{"key":"B9","unstructured":"European centre for disease prevention and control"},{"key":"B10","doi-asserted-by":"publisher","first-page":"184","DOI":"10.1186\/s12877-021-02673-1","article-title":"Age is the main determinant of COVID-19 related in-hospital mortality with minimal impact of pre-existing comorbidities, a retrospective cohort study","volume":"22","author":"Henkens","year":"2022","journal-title":"BMC Geriatr."},{"key":"B11","doi-asserted-by":"publisher","first-page":"497","DOI":"10.1016\/S0140-6736(20)30183-5","article-title":"Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China","volume":"395","author":"Huang","year":"2020","journal-title":"Lancet"},{"key":"B12","unstructured":"Gerocovid_Training_mortality\n          \n          \n          2024"},{"key":"B13","doi-asserted-by":"publisher","first-page":"1798","DOI":"10.1016\/j.jamda.2020.10.002","article-title":"Rapid assessment at hospital admission of mortality risk from COVID-19: the role of functional status","volume":"21","author":"Laosa","year":"2020","journal-title":"J. Am. Med. Dir. Assoc."},{"key":"B14","doi-asserted-by":"publisher","first-page":"602395","DOI":"10.3389\/fimmu.2020.602395","article-title":"Interleukin-8 as a biomarker for disease prognosis of coronavirus disease-2019 patients","volume":"11","author":"Li","year":"2020","journal-title":"Front. Immunol."},{"key":"B15","doi-asserted-by":"publisher","first-page":"206","DOI":"10.1186\/s12967-020-02374-0","article-title":"Neutrophil-to-lymphocyte ratio predicts critical illness patients with 2019 coronavirus disease in the early stage","volume":"18","author":"Liu","year":"2020","journal-title":"J. Transl. Med."},{"key":"B16","doi-asserted-by":"publisher","first-page":"81","DOI":"10.1016\/j.imj.2022.04.002","article-title":"Clinical characteristics of COVID-19 hospitalized patients associated with mortality: a cohort study in Spain","volume":"1","author":"Lozano","year":"2022","journal-title":"Infect. Med. (Beijing)"},{"key":"B17","doi-asserted-by":"publisher","first-page":"626235","DOI":"10.3389\/fimmu.2021.626235","article-title":"High levels of circulating IL-8 and soluble IL-2R are associated with prolonged illness in patients with severe COVID-19","volume":"12","author":"Ma","year":"2021","journal-title":"Front. Immunol."},{"key":"B18","doi-asserted-by":"publisher","first-page":"2414","DOI":"10.3390\/biomedicines10102414","article-title":"Predicting in-hospital mortality in severe COVID-19: a systematic review and external validation of clinical prediction rules","volume":"10","author":"Maestre-Muniz","year":"2022","journal-title":"Biomedicines"},{"key":"B19","doi-asserted-by":"publisher","first-page":"479","DOI":"10.1093\/cid\/ciab437","article-title":"Increased peripheral blood neutrophil activation phenotypes and neutrophil extracellular trap formation in critically ill coronavirus disease 2019 (COVID-19) patients: a case series and review of the literature","volume":"74","author":"Masso-Silva","year":"2022","journal-title":"Clin. Infect. Dis. official Publ. Infect. Dis. Soc. Am."},{"key":"B20","doi-asserted-by":"publisher","first-page":"864387","DOI":"10.3389\/fimmu.2022.864387","article-title":"Neutrophils in COVID-19: not innocent bystanders","volume":"13","author":"McKenna","year":"2022","journal-title":"Front. Immunol."},{"key":"B21","doi-asserted-by":"publisher","first-page":"1546","DOI":"10.1016\/j.jamda.2020.09.014","article-title":"Predictors of in-hospital mortality in older patients with COVID-19: the COVIDAge study","volume":"21","author":"Mendes","year":"2020","journal-title":"J. Am. Med. Dir. Assoc."},{"key":"B22","doi-asserted-by":"publisher","first-page":"e262","DOI":"10.1016\/S1470-2045(19)30149-4","article-title":"Big data and machine learning algorithms for health-care delivery","volume":"20","author":"Ngiam","year":"2019","journal-title":"Lancet Oncol."},{"key":"B23","doi-asserted-by":"publisher","first-page":"5578","DOI":"10.3390\/jcm11195578","article-title":"Determinants of cause-specific mortality and loss of independence in older patients following hospitalization for COVID-19: the GeroCovid outcomes study","volume":"11","author":"Okoye","year":"2022","journal-title":"J. Clin. Med."},{"key":"B24","doi-asserted-by":"publisher","first-page":"111674","DOI":"10.1016\/j.mad.2022.111674","article-title":"Routine laboratory parameters, including complete blood count, predict COVID-19 in-hospital mortality in geriatric patients","volume":"204","author":"Olivieri","year":"2022","journal-title":"Mech. ageing Dev."},{"key":"B25","doi-asserted-by":"publisher","first-page":"e28","DOI":"10.1093\/gerona\/glaa243","article-title":"Clinical characteristics and risk factors for mortality in very old patients hospitalized with COVID-19 in Spain","volume":"76","author":"Ramos-Rincon","year":"2021","journal-title":"J. Gerontol. A Biol. Sci. Med. Sci."},{"key":"B26","doi-asserted-by":"publisher","first-page":"652470","DOI":"10.3389\/fimmu.2021.652470","article-title":"Neutrophils in COVID-19","volume":"12","author":"Reusch","year":"2021","journal-title":"Front. Immunol."},{"key":"B27","doi-asserted-by":"publisher","first-page":"1617","DOI":"10.1007\/s11739-023-03358-w","article-title":"Artificial intelligence for COVID-19 mortality prediction: improvement of risk stratification and clinical decision-making","volume":"18","author":"Riela","year":"2023","journal-title":"Intern. Emerg. Med."},{"key":"B28","doi-asserted-by":"publisher","first-page":"83","DOI":"10.36150\/2499-6564-N715","article-title":"In-hospital and long-term all-cause mortality in 75 years and older hospitalized patients with and without COVID-19","volume":"72","author":"Rizza","year":"2024","journal-title":"J. Gerontology Geriatrics"},{"key":"B29","doi-asserted-by":"publisher","first-page":"964","DOI":"10.1007\/s12603-021-1664-9","article-title":"Functional, clinical, and sociodemographic variables associated with risk of in-hospital mortality by COVID-19 in people over 80 Years old","volume":"25","author":"Rodriguez-Sanchez","year":"2021","journal-title":"J. Nutr. health and aging"},{"key":"B30","doi-asserted-by":"publisher","first-page":"e043651","DOI":"10.1136\/bmjopen-2020-043651","article-title":"Severity of respiratory failure at admission and in-hospital mortality in patients with COVID-19: a prospective observational multicentre study","volume":"10","author":"Santus","year":"2020","journal-title":"BMJ open"},{"key":"B31","doi-asserted-by":"publisher","first-page":"110","DOI":"10.1016\/j.ajem.2020.11.058","article-title":"Neutrophil to lymphocyte ratio, lymphocyte to monocyte ratio and platelet to lymphocyte ratio to predict the severity of COVID-19","volume":"40","author":"Seyit","year":"2021","journal-title":"Am. J. Emerg. Med."},{"key":"B32","doi-asserted-by":"publisher","first-page":"29","DOI":"10.1016\/j.ejim.2021.01.017","article-title":"Assessing the impact of COVID-19 on the health of geriatric patients: the European GeroCovid Observational Study","volume":"87","author":"Trevisan","year":"2021","journal-title":"Eur. J. Intern Med."},{"key":"B33","doi-asserted-by":"publisher","first-page":"1505","DOI":"10.12688\/f1000research.16216.2","article-title":"Feature selection with the R package MXM","volume":"7","author":"Tsagris","year":"2018","journal-title":"F1000Res"},{"key":"B34","doi-asserted-by":"publisher","first-page":"38","DOI":"10.1038\/s41698-022-00274-8","article-title":"Just Add Data: automated predictive modeling for knowledge discovery and feature selection","volume":"6","author":"Tsamardinos","year":"2022","journal-title":"NPJ Precis. Oncol."},{"key":"B35","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1016\/j.ajem.2020.12.003","article-title":"Increased age, neutrophil-to-lymphocyte ratio (NLR) and white blood cells count are associated with higher COVID-19 mortality","volume":"40","author":"Vafadar Moradi","year":"2021","journal-title":"Am. J. Emerg. Med."},{"key":"B36","doi-asserted-by":"publisher","first-page":"1","DOI":"10.18637\/jss.v045.i03","article-title":"Mice: multivariate imputation by chained equations in R","volume":"45","author":"van Buuren","year":"2011","journal-title":"J. Stat. Softw."},{"key":"B37","doi-asserted-by":"publisher","first-page":"797","DOI":"10.1002\/jmv.25783","article-title":"Clinical features and treatment of COVID-19 patients in northeast Chongqing","volume":"92","author":"Wan","year":"2020","journal-title":"J. Med. virology"},{"key":"B38","doi-asserted-by":"publisher","first-page":"1061","DOI":"10.1001\/jama.2020.1585","article-title":"Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus-infected pneumonia in wuhan, China","volume":"323","author":"Wang","year":"2020","journal-title":"Jama"},{"key":"B39","doi-asserted-by":"publisher","first-page":"978237","DOI":"10.3389\/fpubh.2022.978237","article-title":"The prognostic value of the Barthel Index for mortality in patients with COVID-19: a cross-sectional study","volume":"10","author":"Wang","year":"2022","journal-title":"Front. public health"},{"key":"B40","doi-asserted-by":"publisher","first-page":"101188","DOI":"10.1016\/j.imu.2023.101188","article-title":"Machine learning models for predicting severe COVID-19 outcomes in hospitals","volume":"37","author":"Wendland","year":"2023","journal-title":"Inf. Med. Unlocked"},{"key":"B41","doi-asserted-by":"publisher","first-page":"934","DOI":"10.1001\/jamainternmed.2020.0994","article-title":"Risk factors associated with acute respiratory distress syndrome and death in patients with coronavirus disease 2019 pneumonia in wuhan, China","volume":"180","author":"Wu","year":"2020","journal-title":"JAMA Intern. Med."},{"key":"B42","doi-asserted-by":"publisher","first-page":"m1328","DOI":"10.1136\/bmj.m1328","article-title":"Prediction models for diagnosis and prognosis of covid-19 infection: systematic review and critical appraisal","volume":"369","author":"Wynants","year":"2020","journal-title":"Bmj"},{"key":"B43","doi-asserted-by":"publisher","first-page":"80","DOI":"10.1186\/s12879-021-05796-3","article-title":"Predictive value of the neutrophil to lymphocyte ratio for disease deterioration and serious adverse outcomes in patients with COVID-19: a prospective cohort study","volume":"21","author":"Zeng","year":"2021","journal-title":"BMC Infect. Dis."}],"container-title":["Frontiers in Aging"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fragi.2024.1473632\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,17]],"date-time":"2024-10-17T05:17:07Z","timestamp":1729142227000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fragi.2024.1473632\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,10,17]]},"references-count":43,"alternative-id":["10.3389\/fragi.2024.1473632"],"URL":"https:\/\/doi.org\/10.3389\/fragi.2024.1473632","relation":{},"ISSN":["2673-6217"],"issn-type":[{"value":"2673-6217","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,10,17]]},"article-number":"1473632"}}