Prospective longitudinal evaluation of AI-ECG in newly diagnosed heart failure (PLANE-HF)

* In the United Kingdom, there are one million people suffering from heart failure (HF), with more than 60,000 new cases annually (1).

* Monitoring for declining left ventricular ejection fraction (LVEF) could optimise treatment approaches and avert healthcare episodes.

* Easy home-based tracking of cardiac function would be transformative.

* Previous studies have validated the capability of artificial intelligence-enabled electrocardiogram (AI-ECG) to correlated with changes in LVEF (2).

* We hypothesize that longitudinal changes in AI-ECG probability score is associated with changes in the left ventricular (LV) function.

* A prospective multicentre longitudinal study recruiting newly diagnosed HF with reduced ejection fraction (HFrEF) cases to investigate application of AI-ECG using longitudinal single-lead ECG recordings via patient-administered smart ECG-stethoscope examination – Figure 1.

* A total of 36 patients were included in the analysis, with invitation to return for repeat echocardiography at 6-8 weeks.

* Adjusted logistic regression was performed to analyze changes in LVEF by 10% as the outcome variable, investigating the relationship with the trajectory of AI-ECG probability scores.

This study was approved by the UK Health Research Authority (reference 22/LO/0701).

* Out of 36 patients, 19 patients had ischaemic and 17 had a non-ischaemic HF.

* The mean age was 56.3 years, 97.2% patients were male and 46.6% were White.

* 328 longitudinal single-lead ECGs were captured and used in the analysis.

* 12 (33.3%) patients had an increase of their LVEF by 10%; preceding AI-ECGs was predictive of this recovery (OR 1.36; 95% CI, 1.05 – 1.65, p value = 0.016 – Table 1)

Clinical Importance:

* Individualised predictions of deterioration and improvement

* Proactive medication adjustment

* Enhanced triage for echocardiography

* AI-ECG designed to identify left ventricular systolic dysfunction (LVSD) can predict changes in LVEF% among newly diagnosed HFrEF patients.

* Such results can place AI-ECG as a remote monitoring tool to track improvement or deterioration in patients’ LVEF%, which facilitate a proactive management and prevention strategies.