Prediction models for prognosis of influenza: a systematic review and critical appraisal

Abstract

The influenza epidemic has become an important public health issue throughout the world. Early recognition of potentially terrible outcomes is important in the emergency department (ED). Efficient prognosis of the disease is conducive to reducing the financial burden and providing appropriate care for patients. Prediction models containing several features to estimate the risk of patients with confirmed infection could help clinicians give appropriate treatment when health care resources are limited. We conducted a literature review of studies about influenza published until June 2021 and updated the literature during the creation process. We researched PubMed, Web of Science, and Google Scholar databases to collect articles in English relevant to influenza between Jan 1, 1900, and Dec 30, 2020. The terms used for the search were “influenza”, “diagnostic”, “prognostic”, “prediction”, “score”, “artificial intelligence”, and so on. If the study involved animals, children, pregnant women or the study type was pragmatic and explanatory clinical trial, guideline, protocol, letter, a case report was also excluded. The GRACE checklist in our study was used to assess the 34 studies for quality. Thirty-four articles were included in the review, and relevant data were extracted from the risk prognosis model. Cardiovascular disease and central nervous symptoms play an important role in prognostic models of influenza. In addition, some commonly used scoring systems can also play a certain role in evaluation. This systematic review compared different types of models for predicting the prognosis of influenza infection, informing us of risk factors for the predictive model in predicting the prognosis of influenza in the early stage. The articles were limited to retrospective observational studies, sample size, time limitation, incomplete data, imbalanced prognosis treatment, and so on.