{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,21]],"date-time":"2026-09-21T10:38:41Z","timestamp":1789987121613,"version":"4.0.1"},"reference-count":51,"publisher":"American Society of Tropical Medicine and Hygiene","issue":"4","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,4,2]]},"abstract":"<jats:title>ABSTRACT.<\/jats:title>\n                  <jats:p>\n                    There is uncertainty regarding the usefulness of predictive models for dengue prognosis. We performed a systematic review to identify and evaluate prognostic models in patients with dengue. We conducted a literature search in PubMed, Embase, and Literatura Latinoamericana y del Caribe en Ciencias de la Salud (LILACS) up to May 24, 2023. We included case\u2013control and cohort studies that developed or validated multivariable prognostic models related to severity, hospitalization, intensive care unit (ICU) admission, or mortality in patients of any age with a laboratory-based diagnosis of dengue. A narrative synthesis of the performance measures of the prognostic models evaluated in each study was performed. Of the 4,211 articles, a total of 35 studies reporting information on 43 prognostic models were included. Among these, 35 were developmental and 8 were for external validation. Most models were designed to predict severity (\n                    <jats:italic>n<\/jats:italic>\n                    = 30), followed by mortality (\n                    <jats:italic>n<\/jats:italic>\n                    = 10), hospitalization (\n                    <jats:italic>n<\/jats:italic>\n                    = 2), and ICU admission (\n                    <jats:italic>n<\/jats:italic>\n                    = 1). The reported C-statistic in the models ranged from 0.70 to 0.95 for severity, 0.83 to 0.99 for mortality, 0.87 for hospitalization, and 0.92 for ICU admission. Calibration measures were poorly reported in the vast majority of models. According to the Prediction Study Risk of Bias Assessment Tool, the risk of bias was considered high for all included models, and applicability was of low concern for most models. Our study identified multiple prognostic models, particularly for predicting severity and mortality in patients with dengue. Although most models demonstrated acceptable discriminative ability, calibration measures were poorly reported, and the overall methodological design was poor.\n                  <\/jats:p>","DOI":"10.4269\/ajtmh.24-0653","type":"journal-article","created":{"date-parts":[[2025,2,11]],"date-time":"2025-02-11T11:23:21Z","timestamp":1739273001000},"page":"898-908","source":"Crossref","is-referenced-by-count":3,"title":["Prognostic Models in Patients with Dengue: A Systematic Review"],"prefix":"10.4269","volume":"112","author":[{"given":"Carlos","family":"Diaz-Arocutipa","sequence":"first","affiliation":[{"name":"Unidad de Revisiones Sistem\u00e1ticas y Meta-an\u00e1lisis (URSIGET), Vicerrectorado de Investigaci\u00f3n, Universidad San Ignacio de Loyola, Lima, Peru;"},{"name":"Instituto de Evaluaci\u00f3n de Tecnolog\u00edas en Salud e Investigaci\u00f3n \u2013 EsSalud, Lima, Peru;"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mar\u00eda","family":"Chumbiauca","sequence":"additional","affiliation":[{"name":"Facultad de Ciencias de la Salud, Universidad San Ignacio de Loyola, Lima, Peru"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Percy","family":"Soto-Becerra","sequence":"additional","affiliation":[{"name":"Instituto de Evaluaci\u00f3n de Tecnolog\u00edas en Salud e Investigaci\u00f3n \u2013 EsSalud, Lima, Peru;"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"2795","reference":[{"key":"b1","series-title":"Lancet","first-page":"350","article-title":"Dengue","volume":"393","author":"Wilder-Smith","year":"2019"},{"key":"b2","series-title":"Expert Rev Anti Infect Ther","first-page":"67","article-title":"Current management of severe dengue infection","volume":"15","author":"Lee","year":"2017"},{"key":"b3","series-title":"PLoS One","first-page":"e0262096","article-title":"Prognostic indicators associated with progresses of severe dengue","volume":"17","author":"Huy","year":"2022"},{"key":"b4","series-title":"Trans R Soc Trop Med Hyg","first-page":"149","article-title":"Comprehensive analysis of multivariable models for predicting severe dengue prognosis: Systematic review and meta-analysis","volume":"117","author":"Lee","year":"2023"},{"key":"b5","series-title":"BMJ","first-page":"e073538","article-title":"Transparent reporting of multivariable prediction models for individual prognosis or diagnosis: Checklist for systematic reviews and meta-analyses (TRIPOD-SRMA)","volume":"381","author":"Snell","year":"2023"},{"key":"b6","series-title":"PLoS Med","first-page":"e1001744","article-title":"Critical appraisal and data extraction for systematic reviews of prediction modelling studies: The CHARMS checklist","volume":"11","author":"Moons","year":"2014"},{"key":"b7","series-title":"Ann Intern Med","first-page":"51","article-title":"PROBAST: A tool to assess the risk of bias and applicability of prediction model studies","volume":"170","author":"Wolff","year":"2019"},{"key":"b8","series-title":"F1000Res","first-page":"446","article-title":"Predictive scoring system for risk of complications in pediatric dengue infection","volume":"11","author":"Bhaskar","year":"2022"},{"key":"b9","series-title":"PLoS Negl Trop Dis","first-page":"e2972","article-title":"Predictive tools for severe dengue conforming to World Health Organization 2009 criteria","volume":"8","author":"Carrasco","year":"2014"},{"key":"b10","series-title":"Trans R Soc Trop Med Hyg","first-page":"705","article-title":"A predictive score for hypotension in patients with confirmed dengue fever in Cayenne Hospital, French Guiana","volume":"110","author":"Djossou","year":"2016"},{"key":"b11","series-title":"BMC Infect Dis","first-page":"676","article-title":"A retrospective cohort study to predict severe dengue in Honduran patients","volume":"17","author":"Fern\u00e1ndez","year":"2017"},{"key":"b12","series-title":"Indian Pediatr","first-page":"359","article-title":"Development and validation of a bedside dengue severity score for predicting severe dengue in children","volume":"60","author":"Gayathri","year":"2023"},{"key":"b13","series-title":"Trans R Soc Trop Med Hyg","first-page":"838","article-title":"Combined score based on arterial lactate, aspartate transaminase and prolonged capillary refill time is a useful diagnostic criterion for identifying severe dengue","volume":"114","author":"Gupta","year":"2020"},{"key":"b14","series-title":"PLoS Negl Trop Dis","first-page":"e0005270","article-title":"A cohort study of adult patients with severe dengue in Taiwanese intensive care units: The elderly and APTT prolongation matter for prognosis","volume":"11","author":"Hsieh","year":"2017"},{"key":"b15","series-title":"J Infect","first-page":"532","article-title":"Dengue fever mortality score: A novel decision rule to predict death from dengue fever","volume":"75","author":"Huang","year":"2017"},{"key":"b16","series-title":"Medicine (Baltimore)","first-page":"e7878","article-title":"Predicting the mortality in geriatric patients with dengue fever","volume":"96","author":"Huang","year":"2017"},{"key":"b17","series-title":"PLoS Negl Trop Dis","first-page":"e0008960","article-title":"Assessing the risk of dengue severity using demographic information and laboratory test results with machine learning","volume":"14","author":"Huang","year":"2020"},{"key":"b18","series-title":"Crit Care","first-page":"R280","article-title":"Development of clinical decision rules to predict recurrent shock in dengue","volume":"17","author":"Huy","year":"2013"},{"key":"b19","series-title":"Travel Med Infect Dis","first-page":"102586","article-title":"Dengue clinical features and harbingers of severity in the diabetic patient: A retrospective cohort study on Reunion Island, 2019","volume":"54","author":"Issop","year":"2023"},{"key":"b20","series-title":"Open Forum Infect Dis","first-page":"ofx056","article-title":"Predictors of dengue-related mortality and disease severity in a tertiary care center in north India","volume":"4","author":"Jain","year":"2017"},{"key":"b21","series-title":"J Crit Care","first-page":"449","article-title":"Clinical profile, intensive care unit course, and outcome of patients admitted in intensive care unit with dengue","volume":"26","author":"Juneja","year":"2011"},{"key":"b22","series-title":"PLoS Negl Trop Dis","first-page":"e0005498","article-title":"The value of daily platelet counts for predicting dengue shock syndrome: Results from a prospective observational study of 2301 Vietnamese children with dengue","volume":"11","author":"Lam","year":"2017"},{"key":"b23","series-title":"J Clin Med","first-page":"396","article-title":"Prognostic factors in adult patients with dengue: Developing risk scoring models and emphasizing factors associated with death \u22647 days after illness onset and \u22643 days after presentation","volume":"7","author":"Lee","year":"2018"},{"key":"b24","series-title":"PLoS ONE","first-page":"e0154772","article-title":"Development of a simple clinical risk score for early prediction of severe dengue in adult patients","volume":"11","author":"Lee","year":"2016"},{"key":"b25","series-title":"J Clin Virol","first-page":"34","article-title":"Predictive value of simple clinical and laboratory variables for dengue hemorrhagic fever in adults","volume":"42","author":"Lee","year":"2008"},{"key":"b26","series-title":"Pathog Glob Health","first-page":"334","article-title":"The predictive and diagnostic accuracy of vascular endothelial growth factor and pentraxin-3 in severe dengue","volume":"112","author":"Low","year":"2018"},{"key":"b27","series-title":"BMC Infect Dis","first-page":"470","article-title":"Development of a bedside score to predict dengue severity","volume":"21","author":"Marois","year":"2021"},{"key":"b28","series-title":"BMC Infect Dis","first-page":"232","article-title":"Prediction of mortality in severe dengue cases","volume":"18","author":"Md-Sani","year":"2018"},{"key":"b29","series-title":"PLoS ONE","first-page":"e0155993","article-title":"Discovery and validation of prognostic biomarker models to guide triage among adult dengue patients at early infection","volume":"11","author":"Pang","year":"2016"},{"key":"b30","series-title":"BMC Infect Dis","first-page":"649","article-title":"Early clinical and laboratory risk factors of intensive care unit requirement during 2004\u20132008 dengue epidemics in Singapore: A matched case-control study","volume":"14","author":"Pang","year":"2014"},{"key":"b31","series-title":"BMC Pediatr","first-page":"109","article-title":"Predicting the severity of dengue fever in children on admission based on clinical features and laboratory indicators: Application of classification tree analysis","volume":"18","author":"Phakhounthong","year":"2018"},{"key":"b32","series-title":"PLoS One","first-page":"e0161884","article-title":"Mortality predictors in patients with severe dengue in the state of Amazonas, Brazil","volume":"11","author":"Pinto","year":"2016"},{"key":"b33","series-title":"Risk Manag Healthc Policy","first-page":"45","article-title":"Validation of dengue infection severity score","volume":"7","author":"Pongpan","year":"2014"},{"key":"b34","series-title":"ISRN Pediatr","first-page":"845876","article-title":"Development of dengue infection severity score","volume":"2013","author":"Pongpan","year":"2013"},{"key":"b35","series-title":"PLoS Negl Trop Dis","first-page":"e769","article-title":"Prediction of dengue disease severity among pediatric Thai patients using early clinical laboratory indicators","volume":"4","author":"Potts","year":"2010"},{"key":"b36","series-title":"Indian J Pediatr","first-page":"433","article-title":"Development of a prognostic prediction model to determine severe dengue in children","volume":"85","author":"Sreenivasan","year":"2018"},{"key":"b37","series-title":"Trop Med Infect Dis","first-page":"162","article-title":"Prognostic indicators for the early prediction of severe dengue infection: A retrospective study in a university hospital in Thailand","volume":"7","author":"Srisuphanunt","year":"2022"},{"key":"b38","series-title":"PLoS One","first-page":"e0161696","article-title":"Proposal of a clinical decision tree algorithm using factors associated with severe dengue infection","volume":"11","author":"Tamibmaniam","year":"2016"},{"key":"b39","series-title":"PLoS Negl Trop Dis","first-page":"e196","article-title":"Decision tree algorithms predict the diagnosis and outcome of dengue fever in the early phase of illness","volume":"2","author":"Tanner","year":"2008"},{"key":"b40","series-title":"Clin Infect Dis","first-page":"656","article-title":"An evidence-based algorithm for early prognosis of severe dengue in the outpatient setting","volume":"64","author":"Tuan","year":"2017"},{"key":"b41","series-title":"eLife","first-page":"e67460","article-title":"Combination of inflammatory and vascular markers in the febrile phase of dengue is associated with more severe outcomes","volume":"10","author":"Vuong","year":"2021"},{"key":"b42","series-title":"PLoS Negl Trop Dis","first-page":"e0011161","article-title":"Demographic characteristics, clinical symptoms, biochemical markers and probability of occurrence of severe dengue: A multicenter hospital-based study in Bangladesh","volume":"17","author":"Yang","year":"2023"},{"key":"b43","series-title":"Clinical Prediction Models: A Practical Approach to Development, Validation, and Updating","author":"Steyerberg","year":"2019"},{"key":"b44","series-title":"Virus Res","first-page":"199018","article-title":"Dengue virus infection - a review of pathogenesis, vaccines, diagnosis and therapy","volume":"324","author":"Kok","year":"2023"},{"key":"b45","series-title":"Pathog Glob Health","first-page":"19","article-title":"WHO dengue case classification 2009 and its usefulness in practice: An expert consensus in the Americas","volume":"109","author":"Horstick","year":"2015"},{"key":"b46","series-title":"Nat Rev Dis Primers","first-page":"16055","article-title":"Dengue infection","volume":"2","author":"Guzman","year":"2016"},{"key":"b47","series-title":"PLoS Negl Trop Dis","first-page":"e0010631","article-title":"A systematic review of dengue outbreak prediction models: Current scenario and future directions","volume":"17","author":"Leung","year":"2023"},{"key":"b48","series-title":"Lancet Infect Dis","first-page":"1014","article-title":"Risk predictors of progression to severe disease during the febrile phase of dengue: A systematic review and meta-analysis","volume":"21","author":"Sangkaew","year":"2021"},{"key":"b49","series-title":"BMJ","first-page":"e078276","article-title":"Developing clinical prediction models: A step-by-step guide","volume":"386","author":"Efthimiou","year":"2024"},{"key":"b50","series-title":"BMJ","first-page":"m441","article-title":"Calculating the sample size required for developing a clinical prediction model","volume":"368","author":"Riley","year":"2020"},{"key":"b51","series-title":"Clin Kidney J","first-page":"49","article-title":"External validation of prognostic models: What, why, how, when and where?","volume":"14","author":"Ramspek","year":"2021"}],"container-title":["The American Journal of Tropical Medicine and Hygiene"],"original-title":[],"link":[{"URL":"https:\/\/www.ajtmh.org\/view\/journals\/tpmd\/112\/4\/article-p898.xml","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.ajtmh.org\/downloadpdf\/journals\/tpmd\/112\/4\/article-p898.xml","content-type":"text\/html","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/www.ajtmh.org\/downloadpdf\/journals\/tpmd\/112\/4\/article-p898.xml","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,4,2]],"date-time":"2025-04-02T09:47:28Z","timestamp":1743587248000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ajtmh.org\/view\/journals\/tpmd\/112\/4\/article-p898.xml"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,4,2]]},"references-count":51,"journal-issue":{"issue":"4"},"URL":"https:\/\/doi.org\/10.4269\/ajtmh.24-0653","relation":{},"ISSN":["0002-9637","1476-1645"],"issn-type":[{"value":"0002-9637","type":"print"},{"value":"1476-1645","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,4,2]]}}}