Informative Censoring-A Cause of Bias in Estimating COVID-19 Mortality Using Hospital Data.
Life (Basel)
; 13(1)2023 Jan 11.
Article
en En
| MEDLINE
| ID: mdl-36676159
ABSTRACT
(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.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Idioma:
En
Revista:
Life (Basel)
Año:
2023
Tipo del documento:
Article
País de afiliación:
Estados Unidos