Where multiple potential confounding variables were present, we used multivariate logistic regression models to determine independent predictors of important outcomes (e.g., delayed presentation).
Multiple potential confounding variables exist.
Moreover, all cohort studies adjusted for multiple potential confounding variables with three cohort studies adjusting for glycaemic control (table 1).
These findings remained robust after adjustment for multiple potential confounding variables, suggesting that NLR may be independently associated with outcomes in critical illness.
We used Cox proportional hazards modelling to assess the effect of aspirin/NSAIDs on mortality risk, adjusting for multiple potential confounding variables as described above.
In Stage 1 (identify independent variables), we identified multiple potential M&A targets within the chaebol and selected cases that reflected combinations of high and low states of uncertainty and controversy, based on information from a series of initial interviews.
After adjusting for potential variables, stepwise backward multiple linear regression analysis revealed that age and alanine aminotransferase levels were positively associated with logarithmic transformation of BCLs (log BCLs), while serum albumin levels were negatively associated with log BCLs in CPD patients.
After adjusting for these potential variables, stepwise backward multiple linear regression analysis revealed that only age and ALT levels were positively and significantly associated with log BCLs and only albumin levels (beta coefficient ± standard error [SE] = -0.167 ± 0.034, P = 0.002) were negatively and significantly associated with log BCLs.
First, it allows clinicians to make treatment decisions informed by global patient prognosis instead of multiple potential clinical factors that may have variable impacts on mortality risk.
To address missing data, we will control for potential variables related to missing data, as well as examine multiple imputation methods for handling missing data (expectation maximisation algorithm).
