@article{buttia_prognostic_2023,
	title = {Prognostic models in {COVID}-19 infection that predict severity: a systematic review},
	issn = {0393-2990, 1573-7284},
	url = {https://link.springer.com/10.1007/s10654-023-00973-x},
	doi = {10.1007/s10654-023-00973-x},
	shorttitle = {Prognostic models in {COVID}-19 infection that predict severity},
	abstract = {Abstract
            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.},
	journaltitle = {European Journal of Epidemiology},
	shortjournal = {Eur J Epidemiol},
	author = {Buttia, Chepkoech and Llanaj, Erand and Raeisi-Dehkordi, Hamidreza and Kastrati, Lum and Amiri, Mojgan and Meçani, Renald and Taneri, Petek Eylul and Ochoa, Sergio Alejandro Gómez and Raguindin, Peter Francis and Wehrli, Faina and Khatami, Farnaz and Espínola, Octavio Pano and Rojas, Lyda Z. and de Mortanges, Aurélie Pahud and Macharia-Nimietz, Eric Francis and Alijla, Fadi and Minder, Beatrice and Leichtle, Alexander B. and Lüthi, Nora and Ehrhard, Simone and Que, Yok-Ai and Fernandes, Laurenz Kopp and Hautz, Wolf and Muka, Taulant},
	urldate = {2023-03-09},
	date = {2023-02-25},
	langid = {english},
}