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Propensity score adjustment was performed to adjust for potential confounders.
In addition, binary logistic regression was used to adjust for potential confounding variables.
Poisson regression analysis was used to adjust for potential confounders.
The analysis conducted allowed to adjust for potential confounders.
Logistic and linear regression analyses were used to adjust for potential confounders.
Multivariable logistic regression was used to adjust for potential differences in data source.
We used Cox proportional-hazards models to adjust for potential confounding variables.
We used two multivariate models to adjust for potential confounders.
However, this study did not adjust for potential confounders [ 6].
Multivariable analysis was performed to adjust for potential confounders.
All studies used multivariate models to adjust for potential confounders.
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