The added value of ECG on the PREVENT CVD risk score for the prediction of subclinical cardiac disease - insights from Project Baseline Health Study

Q: What are the key findings of this study?

Adding ECG parameters to the PREVENT CVD risk score improved model fit for detecting left ventricular hypertrophy (p 0.

Q: What is the clinical evidence from this study?

Study design: Observational. Population: Subclinical cardiovascular disease (n=1143). Intervention: ECG parameters added to PREVENT CVD risk score vs. PREVENT CVD risk score alone. Primary outcome: Detection of subclinical CVD (LVH or LVDD on ECHO, or CAC score >0) (p=<0.01).

Q: What does this research mean for the field?

The addition of ECG parameters to the PREVENT CVD risk score significantly improves detection of left ventricular hypertrophy and diastolic dysfunction in individuals at risk. Novelty: ClaimNovelty.NOVEL_FINDING. Consensus alignment: ConsensusAlignment.SUPPORTS_CONSENSUS.

Q: What question did this study set out to answer?

This research aims to assess the ability of the PREVENT CVD risk score to identify subclinical heart factors and evaluate the additional benefits of integrating ECG data.

Diona Gjermeni; Gracia Fahed; E Santana; B Celestin; Nicholas Cauwenberghs; S P Bagherzadeh; S H Shah; Tatiana Kusnetsova; P S Douglas; M A Daubert; K W Mahaffey; F Haddad

doi:10.1093/eurheartj/ehaf784.1412

November 1, 2025European Heart Journal

The added value of ECG on the PREVENT CVD risk score for the prediction of subclinical cardiac disease - insights from Project Baseline Health Study

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Key result

Adding ECG parameters to the PREVENT score improves detection of LVH and LVDD, but not CAC.

P<0.01
n=1,143

Why the study?

Detecting subclinical CVD is a prevention guideline priority, but whether the PREVENT CVD risk score detects subclinical HF and elevated CAC, and whether ECG adds value, was unknown.

Does the addition of ECG parameters to the PREVENT CVD risk score improve the detection of subclinical cardiovascular disease in community participants without known CVD?

Key Points

This research aims to assess the ability of the PREVENT CVD risk score to identify subclinical heart factors and evaluate the additional benefits of integrating ECG data.
Analyzed data from 1,143 adults without known cardiovascular diseases who underwent echocardiograms and ECGs.
Defined subclinical cardiovascular disease based on echocardiogram findings and coronary artery calcium scores.
Conducted univariate and multivariable regression analyses to evaluate associations between PREVENT CVD scores and heart conditions.
The PREVENT CVD risk score demonstrated good discrimination for diastolic dysfunction and elevated calcium scores.
Increased likelihood ratios were found for left ventricular hypertrophy and diastolic dysfunction when ECG parameters were included in the analysis.
Routine ECG was associated with significant improvements in detecting left ventricular hypertrophy and diastolic dysfunction.

Study Design

Type

Observational (n=1,143)

Structured PICO

Does the addition of ECG parameters to the PREVENT CVD risk score improve the detection of subclinical cardiovascular disease in community participants without known CVD?

P

Population

1,143 community participants without evidence of cardiovascular disease (CAD, HF, atrial fibrillation or vascular disease) from the Project Baseline Health Study, mean age 52.6 years, 57% female.

I

Intervention

Addition of ECG parameters (chamber enlargements and QRS duration) to the PREVENT CVD risk score

C

Comparator

PREVENT CVD risk score alone

O

Outcome

Detection of subclinical CVD defined as left ventricular hypertrophy (LVH) or diastolic dysfunction (LVDD) on ECHO or CAC score >0surrogate

Main Result

p-value: p=<0.01

Routine ECG parameters provide incremental value over the PREVENT CVD risk score for detecting subclinical left ventricular hypertrophy and diastolic dysfunction in individuals without known cardiovascular disease.

Implication

May enhance PREVENT detection of subclinical LVH and diastolic dysfunction; leaves open prospective validation before clinical use.

Abstract

Background The American Heart Association PREVENT cardiovascular disease (CVD) risk score predicts heart failure (HF) and coronary artery disease (CAD) events. Detecting subclinical CVD has been identified as a priority in the new prevention guidelines. Purpose The study had two aims: first to evaluate whether PREVENT CVD can detect subclinical HF and elevated coronary artery calcium (CAC) and second, to determine the added value of electrocardiogram (ECG) to the PREVENT score. Methods From the 2,502 Project Baseline Health Study (PBHS) community participants, a total of 1,143 (47%) without evidence of cardiovascular disease (CAD, HF, atrial fibrillation or vascular disease) had echocardiography (ECHO) readings, CAC score, and data to calculate the PREVENT CVD risk score. Subclinical CVD was defined as left ventricular hypertrophy (LVH) or diastolic dysfunction (LVDD) on ECHO using the American Society of Echocardiography guidelines or CAC score >0.Univariate and backward multivariable regression analyses were performed to determine the association between the PREVENT risk score LVH, LVDD and CAC score >0. Further analysis were conducted to assess the incremental value of ECG parameters of chamber enlargements and QRS duration. The log-likelihood ratio test was used to determine the incremental value of the nested models. Results 57% were females, mean age was 52.6 years, 35% had hypertension, 46% had dyslipidemia and 14% had diabetes mellitus. The PREVENT CVD risk categories were low/borderline (n=800, 70%), intermediate (n=274, 24%) and high risk (n=69, 6%).LVH by ECHO was present in 32 (3%), LVDD by ECHO in 66 (6%) participants and CAC score was >0 in 482 (42%) participants. LVH by ECG was was present in 26 (2%) participants. The PREVENT CVD risk score provided good discrimination for LVDD (AUC 0.79, p<0.001) and CAC > 0 (AUC 0.79, p<0.001) and to a lesser extent for LVH (AUC 0.65, p<0.001). In multivariable regression analysis adjusted for the PREVENT CVD, LVH on ECG and QRS width were significantly associated with LVH on ECHO ((OR 3.90 [95%CI: 1.08-14.13] and (OR 1.02 [95%CI 1.01-1.05]) per 1 msec., respectively) (Table1). LVH and LAE on ECG were also independently associated with LVDD (OR 3.99, 95%CI 1.44-11.30 and OR 7.49, 95%CI 1.73-32.47), respectively (Table 1). LVH on ECG was associated with CAC score >0 (OR 2.91 [95%CI1.09-7.79]) . The likelihood ratio test showed that the addition of ECG parameters to the PREVENT CVD risk score improved the model fit for LVH (p<0.01) and LVDD (p<0.01) but not for CAC score >0 (p=0.08). Conclusion PREVENT CVD risk score was associated with detection of subclinical CVD. Routine ECG may have added value for the detection of LVH or LV diastolic dysfunction in individuals at risk.

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Cite This Study

Gjermeni et al. (2025) conducted an observational in Subclinical cardiovascular disease (n=1,143). ECG parameters added to PREVENT CVD risk score vs. PREVENT CVD risk score alone was evaluated on Detection of subclinical CVD (LVH or LVDD on ECHO, or CAC score >0) (p=<0.01). Adding ECG parameters to the PREVENT CVD risk score improved model fit for detecting left ventricular hypertrophy (p<0.01) and diastolic dysfunction (p<0.01), but not CAC >0.

synapsesocial.com/papers/698585aa8f7c464f23009442 https://doi.org/10.1093/eurheartj/ehaf784.1412