Type 2 & other diabetes

Artificial intelligence identifies individuals with prediabetes using single-lead electrocardiograms

Cardiovasc DiabetolPublished Diagnostic accuracy study

Authors' conclusion

This study establishes that an AI model, DiaCardia, can accurately identify individuals with prediabetes from an ECG alone, with performance that is robust across different patient cohorts and independent of major clinical confounders. Our highly generalizable, single-lead DiaCardia model offers a promising solution for scalable prediabetes screening via wearable devices, potentially enabling early, home-based detection and transforming diabetes prevention strategies.

Study context

Population
Health checkup records; prediabetes/diabetes defined as FPG ≥ 110 mg/dL, HbA1c ≥ 6.0%, or ongoing diabetes treatmentprimary cohort
Participants
16,766 health checkup records
Comparison
DiaCardia vs Single-lead DiaCardia
Outcome
Identification of prediabetes from ECG (AUROC)
Methodological detailsArtificial intelligence (AI) model development and validation, internal held-out test dataset, independent external validation cohort
  • AI model development and validation
  • Internal held-out test dataset
  • Independent external validation cohort

Performance

As reported in the abstract

Prediabetes identification, internal test dataset
Test or modelAUROCSensitivitySpecificity
DiaCardia0.85185.7%70.0%
Single-lead DiaCardia0.84482.3%70.2%

AUROC

DiaCardia0.851
Single-lead DiaCardia0.844

Sensitivity

DiaCardia85.7%
Single-lead DiaCardia82.3%

Specificity

DiaCardia70.0%
Single-lead DiaCardia70.2%

Further findings

OutcomeDiaCardia
External validation cohort (n = 2,456)
AUROC0.785
After adjustment for six major confounders by propensity score matching
AUROC0.789

Prominent predictors (SHAP)

Higher R-wave amplitude in leads aVL and I, and smaller peak interval dispersion were prominent predictors

Original publication

Artificial intelligence identifies individuals with prediabetes using single-lead electrocardiograms. Cardiovasc Diabetol. Published 11 November 2025. doi:10.1186/s12933-025-02982-4

Composed by AI from the published abstract and checked against it. How Briefs are made →

Get them every week

New studies on this topic in My Week and in your Monday e-mail.

We e-mail you a sign-in link and a code. No password, no spam.