Development and validation of prediction models for mechanical ventilation, renal replacement therapy, and readmission in COVID-19 patients

Abstract Objective Coronavirus disease 2019 (COVID-19) patients are at risk for resource-intensive outcomes including mechanical ventilation (MV), renal replacement therapy (RRT), and readmission. Accurate outcome prognostication could facilitate hospital resource allocation. We develop and validate...

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Veröffentlicht in:	Journal of the American Medical Informatics Association : JAMIA Jg. 28; H. 7; S. 1480 - 1488
Hauptverfasser:	Rodriguez, Victor Alfonso, Bhave, Shreyas, Chen, Ruijun, Pang, Chao, Hripcsak, George, Sengupta, Soumitra, Elhadad, Noemie, Green, Robert, Adelman, Jason, Metitiri, Katherine Schlosser, Elias, Pierre, Groves, Holden, Mohan, Sumit, Natarajan, Karthik, Perotte, Adler
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	England Oxford University Press 14.07.2021
Schlagworte:	Adolescent Adult Aged Aged, 80 and over Area Under Curve COVID-19 - complications COVID-19 - therapy Electronic Health Records Female Humans Logistic Models Male Middle Aged Models, Statistical Patient Readmission Prognosis Renal Replacement Therapy Respiration, Artificial Retrospective Studies ROC Curve Statistics, Nonparametric Young Adult COVID-19 supervised machine learning patient readmission renal replacement therapy artificial respiration
ISSN:	1527-974X, 1527-974X
Online-Zugang:	Volltext
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