Prognostic Models in Patients with Dengue: A Systematic Review.

Abstract

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-control 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 = 30), followed by mortality (n = 10), hospitalization (n = 2), and ICU admission (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.