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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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Key result

Continuous wearable monitoring detects cardiovascular events, with baseline HF present in 83% of cases.

  • n=229

Why the study?

Predicting sudden cardiac death using electronic health records remains difficult, but integrating continuous personal health records from wearables with electronic health records may enable early prediction.

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 with severe HF, ACS, or out-of-hospital cardiac arrest from 11 hospitals

Comparison

Patients experiencing primary or secondary outcomes vs patients without events

Design

Prospective multicenter cohort study

Authors

TNT NodaKyoto UniversityTIT ImamuraKyoto UniversityHMH MakimotoJichi Medical University

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.

Study Design

Type

Cohort (n=229)

Multicenter

Yes

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 with severe heart failure, acute coronary syndrome, or out-of-hospital cardiac arrest, mean age 58 years, undergoing continuous wearable monitoring.
E
Exposure
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) conducted a cohort in Severe heart failure, acute coronary syndrome, or out-of-hospital cardiac arrest (n=229). Continuous personal health record (PHR) monitoring using wearable devices was evaluated on Sudden cardiac death (SCD). Continuous personal health record monitoring using wearable devices in 229 high-risk patients detected 23 cardiovascular events, with event patients showing higher baseline heart failure (83% vs 51%).

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. 1Abstract WE403: Development and Implementation of an Artificial Intelligence-Based Predictive Model for Sudden Cardiac Death by Integrating Personal Health Records and Clinical Data2026
  2. 2Abstract TH845: Machine Learning-Based Prediction of Sudden Cardiac Death in the General Population Using EHR Data: An Innovative Approach to Prevention2026
  3. 3Could smart wearables predict individuals who are at risk of Sudden Cardiac Death?2024
  4. 4Using wearable and lifestyle data to predict adverse cardiac events in patients with established coronary artery disease2026
  5. 5Patient Use of mHealth Wearable Devices and their Impact on Healthcare Utilization (Preprint)2025