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).