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25% of the participants had missing data on our main exposure but analyses using multivariable imputation did not differ from those based on the complete data subset, suggesting that missing data has not importantly biased our findings.
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Imputation did not affect the median values.
However, the imputations did not alter the conclusions.
For these analyses, missing covariate values were imputed using multivariable imputation.
The American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) provides risk-adjusted assessments of surgical programs, traditionally imputing certain missing data points using a single round of multivariable imputation.
Missing data will be interpolated where possible using multivariable imputation.
Our study found an association with ARDS in univariable analysis, but our multivariable analysis did not.
Multivariable analysis did not confirm an association between temperature and change in creatinine clearance (p = 0.87).
Multivariable adjustment did not change these results.
Our multivariable models did adjust for these demographics factors.
Alternative imputation techniques did not affect our results.
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