Prognostic models in COVID-19 infection that predict severity

Autor: Chepkoech Buttia, Erand Llanaj, Hamidreza Raeisi-Dehkordi, Lum Kastrati, Mojgan Amiri, Renald Meçani, Petek Eylul Taneri, Sergio Alejandro Gómez Ochoa, Peter Francis Raguindin, Faina Wehrli, Farnaz Khatami, Octavio Pano Espínola, Lyda Z. Rojas, Aurélie Pahud de Mortanges, Eric Francis Macharia-Nimietz, Fadi Alijla, Beatrice Minder, Alexander B. Leichtle, Nora Lüthi, Simone Ehrhard, Yok-Ai Que, Laurenz Kopp Fernandes, Wolf Hautz, Taulant Muka
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: European Journal of Epidemiology
Buttia, Chepkoech; Llanaj, Erand; Raeisi-Dehkordi, Hamidreza; Kastrati, Lum; Amiri, Mojgan; Meçani, Renald; Taneri, Petek Eylul; Gomez Ochoa, Sergio Alejandro; Raguindin, Peter Francis; Wehrli, Faina; Khatami, Farnaz; Pano Espinola, Octavio; Rojas, Lyda Z; de Mortanges, Aurélie Pahud; Macharia-Nimietz, Eric Francis; Alijla, Fadi; Minder, Beatrice; Leichtle, Alexander B; Lüthi, Nora; Ehrhard, Simone; ... (2023). Prognostic models in COVID-19 infection that predict severity: a systematic review. European journal of epidemiology, 38(4), pp. 355-372. Springer 10.1007/s10654-023-00973-x
ISSN: 0393-2990
Popis: Current evidence on COVID-19 prognostic models is inconsistent and clinical applicability remains controversial. We performed a systematic review to summarize and critically appraise the available studies that have developed, assessed and/or validated prognostic models of COVID-19 predicting health outcomes. We searched six bibliographic databases to identify published articles that investigated univariable and multivariable prognostic models predicting adverse outcomes in adult COVID-19 patients, including intensive care unit (ICU) admission, intubation, high-flow nasal therapy (HFNT), extracorporeal membrane oxygenation (ECMO) and mortality. We identified and assessed 314 eligible articles from more than 40 countries, with 152 of these studies presenting mortality, 66 progression to severe or critical illness, 35 mortality and ICU admission combined, 17 ICU admission only, while the remaining 44 studies reported prediction models for mechanical ventilation (MV) or a combination of multiple outcomes. The sample size of included studies varied from 11 to 7,704,171 participants, with a mean age ranging from 18 to 93 years. There were 353 prognostic models investigated, with area under the curve (AUC) ranging from 0.44 to 0.99. A great proportion of studies (61.5%, 193 out of 314) performed internal or external validation or replication. In 312 (99.4%) studies, prognostic models were reported to be at high risk of bias due to uncertainties and challenges surrounding methodological rigor, sampling, handling of missing data, failure to deal with overfitting and heterogeneous definitions of COVID-19 and severity outcomes. While several clinical prognostic models for COVID-19 have been described in the literature, they are limited in generalizability and/or applicability due to deficiencies in addressing fundamental statistical and methodological concerns. Future large, multi-centric and well-designed prognostic prospective studies are needed to clarify remaining uncertainties.
Databáze: OpenAIRE
Externí odkaz: