For the primary analysis, we categorized patients as aged ≥75 and <75 years. This threshold was chosen based on the known knowledge gaps in health status outcomes in adults ≥75 years, the underrepresentation of adults ≥75 years from prior CTO revascularization studies,10 , 27 and studies demonstrating comparatively fewer adults aged 70 to 79 and ≥80 years being referred for CTO PCI.11 Continuous variables were summarized as means±SDs or medians (interquartile range), and categorical variables as counts (percentage). For descriptive purposes, continuous variables were compared between the 2 groups with the 2‐tailed t test or Wilcoxon Rank Sum test, and categorical variables were compared with χ2 analysis. As a supplementary analysis, we also compared differences in baseline characteristics, procedural characteristics, and health status outcomes among adults aged <65, 65 to 74, and ≥75 years using 1‐way ANOVA or the Kruskal–Wallis test for continuous variables and χ2 analysis for categorical variables.
We examined the association between age category (aged ≥75 and <75 years) and technical success using hierarchical modified Poisson regression with robust error variance to account for clustering of patients within sites.28 Covariates for model adjustment were determined a priori based on clinical experience, and included vessel treated, presence of a bypass graft to the CTO vessel, prior stenting of the CTO vessel, and each component of the Japan CTO score: presence of a blunt proximal cap, vessel calcification, vessel bending ≥45°, CTO length ≥20 mm, and whether the current procedure was a repeat attempt of a previously failed CTO PCI.
For the health status outcomes analysis, we excluded 37 of the 1000 patients enrolled in OPEN‐CTO with missing baseline health status or all 3 follow‐up health status assessments. Unadjusted health status outcomes were compared between adults ≥75 and <75 years at baseline, 1, 6, and 12‐months. Differences in health status between adults aged ≥75 years and adults <75 years were modeled using hierarchical multivariable linear regression with repeated measures, which allowed for better informing of the 12‐month estimate (the primary health status outcome of interest) using 1 and 6‐month estimates. Models were developed for SAQ Summary Score, SAQ Angina Frequency Score, SAQ Physical Limitations, SAQ QOL, and RDS. Each model included age and time as categorical effects, an age by time interaction, and adjusted for the corresponding baseline health status as a restricted cubic spline term. Each model was further adjusted for potential confounders based on clinical experience, including sex, diabetes, congestive heart failure, chronic lung disease, prior myocardial infarction, chronic kidney disease, and whether technical success was achieved. We also included a sex‐by‐age interaction, as sex‐related differences in cardiovascular risk profiles may lead to differential health status benefits in older women as compared with older men.29 In a sensitivity analysis, we repeated the above analysis adjusting for in‐hospital MACCE.
A P value of <0.05 was considered statistically significant. All statistical analyses were performed in SAS version 9.4 (SAS Institute, Cary, NC USA).
We examined the association between age category (aged ≥75 and <75 years) and technical success using hierarchical modified Poisson regression with robust error variance to account for clustering of patients within sites.
For the health status outcomes analysis, we excluded 37 of the 1000 patients enrolled in OPEN‐CTO with missing baseline health status or all 3 follow‐up health status assessments. Unadjusted health status outcomes were compared between adults ≥75 and <75 years at baseline, 1, 6, and 12‐months. Differences in health status between adults aged ≥75 years and adults <75 years were modeled using hierarchical multivariable linear regression with repeated measures, which allowed for better informing of the 12‐month estimate (the primary health status outcome of interest) using 1 and 6‐month estimates. Models were developed for SAQ Summary Score, SAQ Angina Frequency Score, SAQ Physical Limitations, SAQ QOL, and RDS. Each model included age and time as categorical effects, an age by time interaction, and adjusted for the corresponding baseline health status as a restricted cubic spline term. Each model was further adjusted for potential confounders based on clinical experience, including sex, diabetes, congestive heart failure, chronic lung disease, prior myocardial infarction, chronic kidney disease, and whether technical success was achieved. We also included a sex‐by‐age interaction, as sex‐related differences in cardiovascular risk profiles may lead to differential health status benefits in older women as compared with older men.
A P value of <0.05 was considered statistically significant. All statistical analyses were performed in SAS version 9.4 (SAS Institute, Cary, NC USA).
