Coronary revascularization in end-stage renal disease

2007 ◽  
Vol 9 (5) ◽  
pp. 389-395 ◽  
Author(s):  
Khaled M. Ziada
Keyword(s):  
Renal Disease ◽  
End Stage Renal Disease ◽  
Coronary Revascularization ◽  
Stage Renal Disease ◽  
End Stage

scholarly journals Coronary Revascularization Improves Long-Term Prognosis in Diabetic and Nondiabetic End-Stage Renal Disease

2002 ◽  
Vol 66 (6) ◽  
pp. 595-595 ◽  
Author(s):  
Jiro Aoki ◽  
Yuji Ikari ◽  
Hiroyoshi Nakajima ◽  
Tokuichiro Sugimoto ◽  
Kazuhiro Hara
Keyword(s):  
Renal Disease ◽  
End Stage Renal Disease ◽  
Coronary Revascularization ◽  
Long Term Prognosis ◽  
Stage Renal Disease ◽  
End Stage

Abstract 317: The Role of Age in Adult Patients with End-Stage Renal Disease Referred for Coronary Revascularization: Insights from Methodological Differences when Modeling a Continuous Variable

2013 ◽  
Vol 6 (suppl_1) ◽  
Author(s):  
Ashok Krishnaswami ◽  
Charles E McCulloch ◽  
Mark A Hlatky ◽  
Thomas K Leong ◽  
Alan Go
Keyword(s):  
Renal Disease ◽  
End Stage Renal Disease ◽  
Odds Ratio ◽  
Primary Outcome ◽  
Coronary Revascularization ◽  
Continuous Variable ◽  
Loss Of Information ◽  
Repeat Revascularization ◽  
Stage Renal Disease ◽  
End Stage

Background: Prior cardiovascular studies have often dichotomized the continuous variable age at a certain pre-specified cutoff which is thought to lead to a loss of information. Methods: To further understand this loss of information we conducted a retrospective cohort study within Kaiser Permanente Northern California and identified 1015 adults with end-stage renal disease who underwent an index coronary revascularization procedure between 1996 and 2008. We used logistic regression analysis and obtained odds ratios for the primary predictor age when age was a. dichotomized at at a cutoff of ≥ 65 years b. categorized as ≤ 55 (reference), 55-64, 65-74, & ≥ 75 years c. modeled as a continuous predictor with a clinically relevant scale (every 5 years ) and d. when age was transformed to a restricted cubic spline (RCS) with four knots. We chose to report in this abstract only the primary outcome repeat revascularization due to the ease in graphically appreciating the various modeling strategies noted above. Results: For the primary outcome repeat revascularization, the unadjusted odds ratio for age ≥ 65 years was 0.64 (95% CI: 0.49-0.82). Categorized age 55-64 years was 0.73 (95% CI: 0.55-0.99), 65-74 years was 0.46 (95% CI: 0.33-0.64), and ≥ 75 years was 0.75 (95% CI: 0.50-1.14), p<0.0002 (departure of trend). The odds ratio for age as a continuous variable every 5 years was 0.87 (95% CI: 0.82-0.92). Figure 1 is a graphical representation of the four different modeling methods of age as noted above. Conclusions: Qualitatively, these four modeling strategies led to different conclusions. When age was dichotomized, there was a significant loss of information. Linearized age did not sufficiently address either the increase in repeat revascularization at both ends of age nor the nadir but appeared to have an adequate fit. Categorized age was able to note the nadir in repeat revascularization around the age of 65 years with a subsequent increase at both ends but the current age categories underrepresented the increased revascularization in the early years. Age transformed to a RCS was visually appealing but lacked adequate quantitative assessment. Therefore, when modeling a continuous variable such as age, there is an imperative to balance the issues of overfitting, residual confounding, flexibility and appropriate interpretation.

Coronary Revascularization in Chronic and End-Stage Renal Disease

2016 ◽  
Vol 23 (1) ◽  
pp. e16-e28 ◽  
Author(s):  
Arun Kannan ◽  
Chithra Poongkunran ◽  
Raul Medina ◽  
Vendhan Ramanujam ◽  
Mugilan Poongkunran ◽  
...  
Keyword(s):  
Renal Disease ◽  
End Stage Renal Disease ◽  
Coronary Revascularization ◽  
Stage Renal Disease ◽  
End Stage
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