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Nurse-led home-based detection of cardiac dysfunction by ultrasound: results of the CUMIN pilot study.


ABSTRACT:

Aims

Access to echocardiography is a significant barrier to heart failure (HF) care in many low- and middle-income countries. In this study, we hypothesized that an artificial intelligence (AI)-enhanced point-of-care ultrasound (POCUS) device could enable the detection of cardiac dysfunction by nurses in Tunisia.

Methods and results

This CUMIN study was a prospective feasibility pilot assessing the diagnostic accuracy of home-based AI-POCUS for HF conducted by novice nurses compared with conventional clinic-based transthoracic echocardiography (TTE). Seven nurses underwent a one-day training program in AI-POCUS. A total of 94 patients without a previous HF diagnosis received home-based AI-POCUS, POC N-terminal pro-B-type natriuretic peptide (NT-proBNP) testing, and clinic-based TTE. The primary outcome was the sensitivity of AI-POCUS in detecting a left ventricular ejection fraction (LVEF) <50% or left atrial volume index (LAVI) >34 mL/m2, using clinic-based TTE as the reference. Out of seven nurses, five achieved a minimum standard to participate in the study. Out of the 94 patients (60% women, median age 67), 16 (17%) had an LVEF < 50% or LAVI > 34 mL/m2. AI-POCUS provided an interpretable LVEF in 75 (80%) patients and LAVI in 64 (68%). The only significant predictor of an interpretable LVEF or LAVI proportion was the nurse operator. The sensitivity for the primary outcome was 92% [95% confidence interval (CI): 62-99] for AI-POCUS compared with 87% (95% CI: 60-98) for NT-proBNP > 125 pg/mL, with AI-POCUS having a significantly higher area under the curve (P = 0.040).

Conclusion

The study demonstrated the feasibility of novice nurse-led home-based detection of cardiac dysfunction using AI-POCUS in HF patients, which could alleviate the burden on under-resourced healthcare systems.

SUBMITTER: Tromp J 

PROVIDER: S-EPMC10944680 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature

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Publications

Nurse-led home-based detection of cardiac dysfunction by ultrasound: results of the CUMIN pilot study.

Tromp Jasper J   Sarra Chenik C   Nidhal Bouchahda B   Mejdi Ben Messaoud BM   Zouari Fourat F   Hummel Yoran Y   Mzoughi Khadija K   Kraiem Sondes S   Fehri Wafa W   Gamra Habib H   Lam Carolyn S P CSP   Mebazaa Alexandre A   Addad Faouzi F  

European heart journal. Digital health 20231212 2


<h4>Aims</h4>Access to echocardiography is a significant barrier to heart failure (HF) care in many low- and middle-income countries. In this study, we hypothesized that an artificial intelligence (AI)-enhanced point-of-care ultrasound (POCUS) device could enable the detection of cardiac dysfunction by nurses in Tunisia.<h4>Methods and results</h4>This CUMIN study was a prospective feasibility pilot assessing the diagnostic accuracy of home-based AI-POCUS for HF conducted by novice nurses compar  ...[more]

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