ArticleCureus2025
Patient Perspectives Towards Artificial Intelligence in Heart Failure Care.
Article in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background Artificial intelligence (AI) tools are increasingly being developed to support the management of chronic diseases, including heart failure (HF). Little is known about the views of patients with HF, a population typically older, with high comorbidity, and familiar with close clinician relationships. This study aims to investigate HF patients' perception of AI integration into HF care to help guide a patient-centred adoption. Methods We conducted a cross-sectional survey on consecutive patients with HF with reduced ejection fraction attending follow-up at a clinic. The questionnaire assessed satisfaction with current care, trust in cardiologists, and attitudes toward AI involvement in diagnosis and treatment decisions. Responses were collected on Likert scales and analysed using ordinal and binary logistic regression to test associations with age, sex, education level, smartphone ownership, symptom burden and prior experience with AI. Results A total of 110 patients completed the questionnaire. Attitudes towards AI were mixed. While 38.1% were happy for their doctor to use AI's help in treatment decisions, support fell significantly to 18.2% when AI acted without physician input and to 21.8% when AI remotely adjusted treatment with fewer in-person visits. Even when described as outperforming doctors, half of the patients remained uncomfortable. In direct comparisons, 80.9% preferred cardiologist diagnoses, 84.6% preferred cardiologist treatment plans, and 97.3% would trust their cardiologist over AI in cases of disagreement. No association was found with age, sex, or education. Smartphone ownership, however, predicted greater acceptance of remote AI adjustments. Conclusion HF patients report high satisfaction with care and strong trust in cardiologists, with more cautious attitudes toward AI than seen in general patient populations. Smartphone ownership, rather than demographics or specific experience with AI, predicted openness to AI. Preserving clinician oversight and designing accessible AI tools will be key to equitable adoption in HF care.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.