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We estimate this model using baseline data (seven cities) of the Fragile Families and Child Wellbeing Study.
27 This is a linear model using baseline measures of the primary outcome as a covariate.
We fit the Rosner Colditz log-incidence model and the Gail model using baseline data.
The advantage of a repeated measures approach compared to a model using baseline data only is that the former allows risk to be continually reassessed following each additional cycle of anticancer therapy.
We fit the base model using baseline variables and imputed HT duration without updating exposures and assessed covariates using the CTS comparing their magnitude and direction to the variables in the NHS.
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It should be noted that the model used baseline characteristics for adjustment, however, corticosteroid use could be at any time in the ICU stay, and therefore, it is possible that the baseline characteristics do not reflect the characteristics of the patient treated when they received therapy.
Cox proportional hazards models were also constructed using time-dependent updated means of variables significant in models using baseline characteristics.
Minimally adjusted models using baseline path length to calculate the follow-up PWV again confirmed our findings (Table S5).
Risk models using baseline characteristics provide adequate discrimination between patients with good and poor 6-month outcomes after TBI [ 9, 10].
The Cox Proportional Hazards models using baseline covariates showed the lowest increase in risk, with hazard ratios of 1.19 (95 % CI 1.06 – 1.35) and 1.14 (95 % CI 1.01 – 1.30) in the OS and CT, respectively.
Given that insulin resistance and diabetes correlate highly with current BMI, we examined associations in models with our derived trajectories and baseline weight (which effectively describe an individual's current weight contemporaneous with diabetes-related markers) relative to the models using baseline weight only.
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