Informative Censoring-A Cause of Bias in Estimating COVID-19 Mortality Using Hospital Data.

Autor: Lin HM; Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA., Liu STH; Division of Infectious Diseases, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA., Levin MA; Department of Anesthesiology, Perioperative and Pain Medicine, Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA., Williamson J; Division of Parasitic Diseases and Malaria, Centers for Disease Control and Prevention, Atlanta, GA 30333, USA., Bouvier NM; Division of Infectious Diseases, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA., Aberg JA; Division of Infectious Diseases, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA., Reich D; Department of Anesthesiology, Perioperative and Pain Medicine, Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA., Egorova N; Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
Jazyk: angličtina
Zdroj: Life (Basel, Switzerland) [Life (Basel)] 2023 Jan 11; Vol. 13 (1). Date of Electronic Publication: 2023 Jan 11.
DOI: 10.3390/life13010210
Abstrakt: (1) Background: Several retrospective observational analyzed treatment outcomes for COVID-19; (2) Methods: Inverse probability of censoring weighting (IPCW) was applied to correct for bias due to informative censoring in database of hospitalized patients who did and did not receive convalescent plasma; (3) Results: When compared with an IPCW analysis, overall mortality was overestimated using an unadjusted Kaplan-Meier curve, and hazard ratios for the older age group compared to the youngest were underestimated using the Cox proportional hazard models and 30-day mortality; (4) Conclusions: An IPCW analysis provided stabilizing weights by hospital admission.
Databáze: MEDLINE
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