Informative Censoring-A Cause of Bias in Estimating COVID-19 Mortality Using Hospital Data
(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 plas...
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Published in | Life (Basel, Switzerland) Vol. 13; no. 1; p. 210 |
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Main Authors | , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Switzerland
MDPI AG
01.01.2023
MDPI |
Subjects | |
Online Access | Get full text |
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Summary: | (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. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 2075-1729 2075-1729 |
DOI: | 10.3390/life13010210 |