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June 12, 2026European Journal of Preventive Cardiology

Development of an integrated PHR-EHR alert system for near-term prevention of sudden cardiac death and cardiovascular events: a preliminary descriptive analysis from a prospective cohort study

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Why the study?

Does an integrated personal health record (PHR) and electronic health record (EHR) alert system using wearable devices predict sudden cardiac death and cardiovascular events in high-risk patients?

Population

229 high-risk patients enrolled from 11 hospitals, mean age 58 ± 13 years, 76% male.

Comparison

Continuous monitoring using commercial wearable… vs Internal comparison between patients who…

Design

Cohort

Authors

TNT NodaTIT ImamuraHMH Makimoto

Discussion

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Overview

Should not yet guide risk stratification in HF or ACS; leaves open validation of integrated personal-EHR models in larger cohorts.

Key Points

  • To develop a predictive model for sudden cardiac death by integrating personal health records with electronic health records.
  • Prospectively enrolling high-risk patients from 11 hospitals, including those with heart failure or acute coronary syndrome.
  • Collecting personal health data through wearable devices and home monitors integrated with electronic health records.
  • Analyzing baseline characteristics and wearable ECG tracings for pre-event indicators.
  • Out of 229 enrolled patients, 23 experienced outcomes including HF and therapy intensification.
  • The Event group showed higher rates of diabetes (61% vs. 27%; p<0.01), HF (83% vs. 51%; p<0.01), and hypertension (65% vs. 40%; p=0.03) compared to controls.
  • A notable ischemic change was detected in ECG tracings 2 days before an acute coronary syndrome event.

Structured PICO

Does an integrated personal health record (PHR) and electronic health record (EHR) alert system using wearable devices predict sudden cardiac death and cardiovascular events in high-risk patients?

P
Population
229 high-risk patients (severe heart failure, acute coronary syndrome, or out-of-hospital cardiac arrest) enrolled from 11 hospitals, mean age 58 ± 13 years, 76% male.
I
Intervention
Continuous monitoring using commercial wearable devices (smartwatches and smart-rings) and home monitors to collect personal health records (body weight, blood pressures, pulse, single-lead ECGs, and patient-reported outcomes) integrated with electronic health records (EHRs).
C
Comparator
Internal comparison between patients who experienced primary or secondary outcomes (Event group, n=23) and those who did not (Control group, n=206).
O
Outcome
Sudden cardiac death (SCD)hard clinical

Preliminary data from a prospective cohort suggests that integrating wearable-derived personal health records with electronic health records can identify high-risk baseline profiles and potentially detect pre-event physiological changes in patients susceptible to cardiovascular events.

Cite This Study

Noda et al. (2026) studied this question.

synapsesocial.com/papers/6a2bd1386550ea4541ffe940https://doi.org/10.1093/eurjpc/zwag249.467
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Using wearable and lifestyle data to predict adverse cardiac events in patients with established coronary artery disease2026
  2. 2Patient Use of mHealth Wearable Devices and their Impact on Healthcare Utilization (Preprint)2025
  3. 3Artificial intelligence-based ascertainment of sudden cardiac death in electronic health records: development, validation and utility across national datasets2026
  4. 4WEARABLE DEVICES IN PREVENTIVE MEDICINE: OPPORTUNITIES AND RISKS OF INTEGRATING TECHNOLOGY INTO CARDIAC CARE2026
  5. 5Cardiology Hospital Admission Risk Prediction (CHARP). Training, internal validation and technical implementation in the Electronic Health Record (EHR)2026