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Participants with missing baseline values were retained in the analysis by using the missing indicator method [ 37].
Patients with missing baseline values were excluded from these analyses.
This problem was addressed by imputing the missing baseline values before conducting the main analysis.
Sixteen participants with missing baseline values were not included in this analysis.
Missing baseline values were not imputed; that is, participants without a baseline value were excluded from the primary analysis.
There were no missing data in baseline covariates values, and only a few missing baseline values in outcome variables.
Similar(39)
Several different approaches have been suggested to compensate for a missing baseline value including estimation of a glomerular filtration rate (GFR) based on population norms [6], use of the nadir creatinine during hospitalization as baseline; however, these have all been found to result in over- or underestimation of AKI [7].
The missing indicator method [ 21] was used so that patients with a missing baseline value could be included.
Where applicable, the missing indicator method was used [ 18], so that patients with a missing baseline value could be incorporated.
An additional 15 patients per group were added to account for patients with potentially missing baseline HbA1c values or without any on-treatment HbA1c value, resulting in 65 patients per treatment group (25% planned dropout rate).
No imputation of missing baseline QL values was performed.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com