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    Coronary artery calcification progression and long-term cardiovascular outcomes in renal transplant recipients: an analysis by the joint model
    (Oxford Univ Press, 2022) Seyahi, Nurhan; Alagoz, Selma; Atli, Zeynep; Ozcan, Seyda Gul; Tripepi, Giovanni; Bakir, Alev; Trabulus, Sinan
    Background. Compared with the general population, the risk of death is substantially higher in renal transplant recipients than in age- and sex-matched individuals in the general population. In the general population, coronary artery calcification (CAC) predicts all-cause and cardiovascular mortality. In this study we aimed to analyse these relationships in renal transplant recipients. Methods. We examined 178 renal transplant patients in this prospective observational cohort study. We measured CAC with multidetector spiral computed tomography using the Agatston score at multiple time points. Overall, 411 scans were performed in 178 patients over an average 12.8 years follow-up. The clinical endpoint was a composite including all-cause death and non-fatal cardiovascular events. Data analysis was performed by the joint model. Results. During a follow-up of 12.862.4 years, coronary calcification progressed over time (P < 0.001) and the clinical endpoint occurred in 54 patients. In the analysis by the joint model, both the baseline CAC score and the CAC score progression were strongly associated with the incidence rate of the composite event [hazard ratio 1.261 (95% confidence interval 1.119-1.420), P = 0.0001]. [GRAPHICS] Conclusions. CAC at baseline and coronary calcification progression robustly predict the risk of death and cardiovascular events in renal transplant recipients. These findings support the hypothesis that the link between the calcifying arteriopathy of renal transplant patients and clinical end points in these patients is causal in nature.
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    Estimation of the graft failure by current value joint model, and extension to alternative parameterization structures: Cohort study
    (Lippincott Williams & Wilkins, 2024) Bakir, Alev; Atli, Zeynep; Kaya, Eda; Pekmezci, Salih; Seyahi, Nurhan
    In clinical practice, individuals are followed up to predict the outcome event of interest, and their longitudinal measurements are collected on a regular or irregular basis. We aimed to examine the classical approach, joint model (JM), and alternative parameterization structures using data on the effect of time-varying longitudinal measurements on survival. The motivating cohort dataset included 158 consecutive kidney transplant recipients who had baseline and follow-up data. Although the longitudinal log-transformed estimated glomerular filtration rate (log[eGFR]) measurements and graft failure have an association clinically, the 2 processes are analyzed separately in the classical approach. In addition to the extended Cox model, the current value JM, the weighted cumulative effect JM, and dynamic predictions were performed in the study, by taking advantage of R codes. Of the 158 patients, 34.8% were males. The mean age was 29.8 +/- 10.9 years, and the median age was 26 years at the time of transplantation. The hazard ratio for graft failure was 8.80 for a 1-unit decrease in log(eGFR) in the extended Cox model, 10.58 in the current value JM, and 3.65 in the weighted cumulative effect JM. The presence of coronary heart disease was also found to be associated with log(eGFR): 0.199 (P = .03) for the current value JM and 0.197 (P = .03) for the weighted cumulative effect JM. The current value JM was identified as a better model than the extended Cox model and the weighted cumulative effect JM based on parameter and standard error comparison and goodness of fit criteria. JMs should be preferred, as they facilitate better clinical decisions by accounting for the varying slopes and longitudinal variation of estimated glomerular filtration rate among patients. Suitable types of models should be practiced depending on baseline biomarker levels, their trends over time, the distribution of the biomarkers, and the number of longitudinal biomarkers.