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

Hung-Mo LinSean T H LiuMatthew A LevinJohn WilliamsonNicole M BouvierJudith A AbergDavid ReichNatalia Egorova
Published in: Life (Basel, Switzerland) (2023)
(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.
Keyphrases
  • coronavirus disease
  • sars cov
  • cardiovascular events
  • healthcare
  • risk factors
  • emergency department
  • cross sectional
  • cardiovascular disease
  • acute care
  • community dwelling
  • middle aged
  • drug induced