Artificial intelligence-guided detection of under-recognised cardiomyopathies on point-of-care cardiac ultrasonography: a multicentre study

Figures

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  Figure 1:. Study overview

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  Figure 2:. Video-level performance of a view-agnostic multi-label POCUS classifier in the Yale–New Haven Health System Video-level performance (AUROC curve with 95% CIs) for discrimination of hypertrophic cardiomyopathy, transthyretin amyloid cardiomyopathy, and severe aortic stenosis, by deploying a POCUS-adapted model to different echocardiographic views obtained across the emergency departments of the Yale–New Haven Health System. Results for all patients (A, B) and for those without known heart failure at the time of their assessment (C, D) are presented, further stratified by the confidence of the automatic view classifier in detecting the corresponding view (all videos [A, C] vs view confidence probability of ≥0·5 [B, D]). The numbers at the bottom of each bar denote the counts of cases out of all eligible video counts in this group. All 95% CIs are derived from bootstrapping with 1000 replications. AUROC=area under the receiver operating characteristic. POCUS=point-of-care ultrasonography.

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  Figure 3:. Saliency maps Activation maps for hypertrophic cardiomyopathy (A, B), transthyretin amyloid cardiomyopathy (C, D), and severe aortic stenosis (E, F) across parasternal long-axis and apical-4-chamber views obtained at the point of care in the emergency department. The colour scale denotes the relative importance of different areas, averaged across time, for each individual label.

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  Figure 4:. Density plot of time between positive artificial intelligence-POCUS screen and eventual confirmatory testing Density plot summarising the time difference between a positive POCUS screen and confirmatory testing by cardiac magnetic resonance or nuclear cardiac amyloid testing for 40 patients and 23 patients with an eventual diagnosis of hypertrophic cardiomyopathy or transthyretin amyloid cardiomyopathy, respectively. POCUS=point-of-care ultrasonography.

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  Figure 5:. Hypertrophic cardiomyopathy and transthyretin amyloid cardiomyopathy-specific probabilities and overall survival among individuals without documented cardiomyopathy in the YNHHS Kaplan–Meier survival curves across quintiles (Q1–5) of the probabilities for hypertrophic cardiomyopathy (A) and transthyretin amyloid cardiomyopathy (B) on point-of-care ultrasonography in the YNHHS. Results are presented for n=25 261 eligible individuals who were never diagnosed with cardiomyopathy during the follow-up period (median of 2·8 [IQR 1·2–6·4] years). We report the p values for comparison of the Kaplan–Meier curves, and also Cox regression-derived HRs (95% CIs) adjusted for age, sex, hypertension, diabetes, ischaemic heart disease, chronic kidney disease, and peripheral arterial disease. HR=hazard ratio. Q=quintile. YNHHS=Yale–New Haven Health System.