Kane, Conor

Abstract Aims Heart failure is prevalent; however, there is no cost-effective screening option. Against formal echocardiography, we assessed the diagnostic performance of focused cardiac ultrasound (FoCUS), performed by novice users guided and interpreted by artificial intelligence (AI) for the assessment of left ventricular ejection fraction (LVEF). Methods and results We prospectively enrolled 496 adults referred for diagnostic echocardiography. Novice operators (without clinical or imaging experience) underwent a 4-h imaging workshop, then performed FoCUS using a point-of-care device (Philips Lumify) utilizing real-time AI-image guidance (UltraSight). Images were assessed by AI-image interpretation software (Mayo Clinic), and two expert blinded echocardiologists. Median age was 67, 39% female, and body mass index range 17–56 kg/m2. Forty-one subjects (8.3%) exhibited moderate or greater LV dilatation and 28 (5.6%) had LVEF <40%. The median scan time was 4 min (IQR 3–5). Adequate views were achieved in 95.0% and 97.4% of subjects for AI interpretation and expert analysis, respectively. A two-step diagnostic screening process for low EF in which only abnormal AI reads or uninterpretable scans were reviewed by experts (15.1%) had a sensitivity 96.2%, specificity 95.4%, PPV 54.3%, and NPV 99.8%. A subsequent prospective validation study of 344 subjects demonstrated similar results (sensitivity 100%, specificity 99.4%). Conclusion In this early feasibility investigation, AI-guidance technology embedded on a handheld device, enabled novice users without clinical or imaging experience to acquire sufficient quality images to accurately assess LVEF with minimal training. The technology evaluated in this study may hold promise for AI-guidance and interpretation to facilitate low-cost screening for cardiac dysfunction.

Background: Clinically significant tricuspid regurgitation (TR) is an important contributor to morbidity and mortality. The Tricuspid Regurgitation Impact on Outcomes (TRIO) score based on 8 parameters (age, gender, chronic heart failure, chronic lung disease, heart rate, creatinine, aspartate transaminase level, and TR severity) is used for risk stratification. The performance of the TRIO score in patients with TR secondary to severe pulmonary hypertension (PH) is unknown. Research Questions: To evaluate whether the TRIO score can be applied in patients with TR and pulmonary hypertension (PH), and to identify other predictors of mortality. Methods: Retrospective study including patients with TR ≥ moderate. Severe PH was defined as right ventricular systolic pressure (RVSP) ≥50 mmHg. The impact of clinical, echocardiographic and laboratory variables on mortality was evaluated with the Cox proportional hazard method. Results: A total of 13,482 patients from the TRIO population were included; severe PH was present in 6,530 (48.4%); mean age 73.4 + 13.3, 55.7% females. TRIO score performance was modest (AUC 0.62) in risk stratification (Figure A). PH patients had significantly higher mortality than those without PH at all levels of TRIO score (Figure B); differences were progressively lower with increasing TRIO scores. At multivariate analysis, only TRIO score [HR = 1.54 (1.35-1.77) per unit change], presence of an elevated NT-proBNP [HR = 1.02 (1.02-1.03) per 1000 pg/ml change], RVSP (HR = 1.08 (1.02-1.16) per 10 mmHg change], presence of RV dysfunction [HR = 1.15, (1.05-1.26)] and pulmonary artery pulsatility index (PAPi) ≤ 4 [HR = 1.34 (1.07-1.67)] were significant predictors of mortality (model AUC 0.65). Conclusions: TRIO score allows risk stratification in PH patients, but performance is modest; incorporating additional factors marginally increased model performance. PH patients have higher mortality at all levels of TRIO score, more so at low scores.