Methods

Study Population

This registry was a prospective, multicenter registry enrolling patient receiving de novo pacemaker implantations at 28 centers in Japan from April 2015 to September 2016. Consenting patients were enrolled if they were at least 20 years old and had a pacemaker indication according to the Japanese guidelines.6 Patients were excluded if they refused participation in this study. Informed consent was obtained from all patients prior to participation, and the study protocol was approved by each institutional Human Investigations Committee. The investigation was performed in accordance with the ethical standards as laid down in the 1964 Declaration of Helsinki and its later amendments.

Data Collection and Definitions

The patient characteristics and baseline and follow-up data were obtained through a review of their hospital charts. The anonymized patient data were collected in spreadsheet format by the physicians or clinical research coordinators at each institution. We examined the demographics, etiology of the pacemaker implantation, class of the JCS guideline indication,6 and history of heart failure. The history of heart failure was determined as acute heart failure or worsening of chronic heart failure requiring hospitalization. The FC was estimated from the interview of the activities of daily living using a questionnaire, 7, 8 and it was a prioriclassified into a poor FC (<2 METs), moderate FC (2< METs<4), and good FC (> 4 METs) (Supplementary file ).

Follow-up and Endpoints

After the implantation, the patients were followed up at each hospital once every few months for 6 months, and thereafter once every 6 months. The FC was recorded at 3 months, 6 months, and 1 year after the pacemaker implantation. The endpoints were cardiovascular hospitalization and all-cause mortality.

Statistical Analysis

Continuous variables are expressed as the mean ± SD or median with the interquartile range. Continuous and categorical variables were compared with a Student’s t-test and χ2 test, respectively. Univariate and multivariate analyses with a Cox proportional hazard regression model was used to identify the significant predictors of the outcomes. The multivariate Cox proportional hazard analysis adjusted for the age, sex, and significant variables in the univariate analyses, and a history of heart failure and atrial fibrillation. The event-free curves were computed using the Kaplan-Meier method and compared with a log-rank test. A P < 0.05 was considered statistically significant. We used JMP version 11.0 software (SAS Institute Inc., Cary, NC, USA).