{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T01:12:03Z","timestamp":1760058723799,"version":"build-2065373602"},"reference-count":73,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2025,4,26]],"date-time":"2025-04-26T00:00:00Z","timestamp":1745625600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001871","name":"Funda\u00e7\u00e3o para a Ci\u00eancia e a Tecnologia (FCT)","doi-asserted-by":"publisher","award":["DSAIPA\/DS\/0117\/2020","RNEM-LISBOA-01-0145-FEDER-022125","UIDB\/00100\/2020","UIDP\/00100\/2020","LA\/P\/0056\/2020","2023.01951.BD","2024.02043.BD","2021.05553.BD"],"award-info":[{"award-number":["DSAIPA\/DS\/0117\/2020","RNEM-LISBOA-01-0145-FEDER-022125","UIDB\/00100\/2020","UIDP\/00100\/2020","LA\/P\/0056\/2020","2023.01951.BD","2024.02043.BD","2021.05553.BD"]}],"id":[{"id":"10.13039\/501100001871","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Applied Sciences"],"abstract":"<jats:p>Predicting disease states and outcomes\u2014and anticipating the need for specific procedures\u2014enhances the efficiency of patient management, particularly in the dynamic and heterogenous environments of intensive care units (ICUs). This study aimed to develop robust predictive models using small sets of blood analytes to predict disease severity and mortality in ICUs, as fewer analytes are advantageous for future rapid analyses using biosensors, enabling fast clinical decision-making. Given the substantial impact of inflammatory processes, this research examined the serum profiles of 25 cytokines, either in association with or independent of nine routine blood analyses. Serum samples from 24 male COVID-19 patients admitted to an ICU were divided into three groups: Group A, including less severe patients, and Groups B and C, that needed invasive mechanical ventilation (IMV). Patients from Group C died within seven days after the current analysis. Na\u00efve Bayes models were developed using the full dataset or with feature subsets selected either through an information gain algorithm or univariate data analysis. Strong predictive models were achieved for IMV (AUC = 0.891) and mortality within homogeneous (AUC = 0.774) or more heterogeneous (AUC = 0.887) populations utilizing two to nine features. Despite the small sample, these findings underscore the potential for effective prediction models based on a limited number of analytes.<\/jats:p>","DOI":"10.3390\/app15094823","type":"journal-article","created":{"date-parts":[[2025,4,29]],"date-time":"2025-04-29T09:00:39Z","timestamp":1745917239000},"page":"4823","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Predictive Models of Patient Severity in Intensive Care Units Based on Serum Cytokine Profiles: Advancing Rapid Analysis"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-6843-1935","authenticated-orcid":false,"given":"Cristiana P. Von","family":"Rekowski","sequence":"first","affiliation":[{"name":"NMS\u2014NOVA Medical School, FCM\u2014Faculdade de Ci\u00eancias M\u00e9dicas, Universidade NOVA de Lisboa, Campo M\u00e1rtires da P\u00e1tria 130, 1169-056 Lisbon, Portugal"},{"name":"ISEL\u2014Instituto Superior de Engenharia de Lisboa, Instituto Polit\u00e9cnico de Lisboa, Rua Conselheiro Em\u00eddio Navarro 1, 1959-007 Lisbon, Portugal"},{"name":"CHRC\u2014Comprehensive Health Research Centre, Universidade NOVA de Lisboa, 1150-082 Lisbon, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0741-2211","authenticated-orcid":false,"given":"Tiago A. H.","family":"Fonseca","sequence":"additional","affiliation":[{"name":"NMS\u2014NOVA Medical School, FCM\u2014Faculdade de Ci\u00eancias M\u00e9dicas, Universidade NOVA de Lisboa, Campo M\u00e1rtires da P\u00e1tria 130, 1169-056 Lisbon, Portugal"},{"name":"ISEL\u2014Instituto Superior de Engenharia de Lisboa, Instituto Polit\u00e9cnico de Lisboa, Rua Conselheiro Em\u00eddio Navarro 1, 1959-007 Lisbon, Portugal"},{"name":"CHRC\u2014Comprehensive Health Research Centre, Universidade NOVA de Lisboa, 1150-082 Lisbon, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9369-6486","authenticated-orcid":false,"given":"R\u00faben","family":"Ara\u00fajo","sequence":"additional","affiliation":[{"name":"NMS\u2014NOVA Medical School, FCM\u2014Faculdade de Ci\u00eancias M\u00e9dicas, Universidade NOVA de Lisboa, Campo M\u00e1rtires da P\u00e1tria 130, 1169-056 Lisbon, Portugal"},{"name":"ISEL\u2014Instituto Superior de Engenharia de Lisboa, Instituto Polit\u00e9cnico de Lisboa, Rua Conselheiro Em\u00eddio Navarro 1, 1959-007 Lisbon, Portugal"},{"name":"CHRC\u2014Comprehensive Health Research Centre, Universidade NOVA de Lisboa, 1150-082 Lisbon, Portugal"}]},{"given":"Ana","family":"Martins","sequence":"additional","affiliation":[{"name":"ISEL\u2014Instituto Superior de Engenharia de Lisboa, Instituto Polit\u00e9cnico de Lisboa, Rua Conselheiro Em\u00eddio Navarro 1, 1959-007 Lisbon, Portugal"},{"name":"CIMOSM\u2014Centro de Investiga\u00e7\u00e3o em Modela\u00e7\u00e3o e Optimiza\u00e7\u00e3o de Sistemas Multifuncionais, ISEL\u2014Instituto Superior de Engenharia de Lisboa, Instituto Polit\u00e9cnico de Lisboa, Rua Conselheiro Em\u00eddio Navarro 1, 1959-007 Lisbon, Portugal"},{"name":"CIMA\u2014Research Centre for Mathematics and Applications, Rua Conselheiro Em\u00eddio Navarro 1, 1959-007 Lisbon, Portugal"}]},{"given":"Iola","family":"Pinto","sequence":"additional","affiliation":[{"name":"ISEL\u2014Instituto Superior de Engenharia de Lisboa, Instituto Polit\u00e9cnico de Lisboa, Rua Conselheiro Em\u00eddio Navarro 1, 1959-007 Lisbon, Portugal"},{"name":"NOVA Math\u2014Center for Mathematics and Applications, NOVA FCT\u2014NOVA School of Science and Technology, Universidade NOVA de Lisboa, Largo da Torre, 2829-516 Caparica, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3068-4920","authenticated-orcid":false,"given":"M. Concei\u00e7\u00e3o","family":"Oliveira","sequence":"additional","affiliation":[{"name":"Centro de Qu\u00edmica Estrutural\u2014Institute of Molecular Sciences, Instituto Superior T\u00e9cnico, Universidade de Lisboa, Av. Rovisco Pais 1, 1049-001 Lisbon, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4828-4738","authenticated-orcid":false,"given":"Gon\u00e7alo C.","family":"Justino","sequence":"additional","affiliation":[{"name":"Centro de Qu\u00edmica Estrutural\u2014Institute of Molecular Sciences, Instituto Superior T\u00e9cnico, Universidade de Lisboa, Av. Rovisco Pais 1, 1049-001 Lisbon, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0260-003X","authenticated-orcid":false,"given":"Lu\u00eds","family":"Bento","sequence":"additional","affiliation":[{"name":"Intensive Care Department, ULSSJ\u2014Unidade Local de Sa\u00fade de S\u00e3o Jos\u00e9, Rua Jos\u00e9 Ant\u00f3nio Serrano, 1150-199 Lisbon, Portugal"},{"name":"Integrated Pathophysiological Mechanisms, CHRC\u2014Comprehensive Health Research Centre, NMS\u2014NOVA Medical School, FCM\u2014Faculdade de Ci\u00eancias M\u00e9dicas, Universidade NOVA de Lisboa, Campo M\u00e1rtires da P\u00e1tria 130, 1169-056 Lisbon, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5264-9755","authenticated-orcid":false,"given":"Cec\u00edlia R. 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