Heart, Lung and Circulation最新文献

Background

Method

Results

Conclusions

Background

Functional coronary angiography (FCA) for endotype characterisation (vasospastic angina [VSA], coronary microvascular disease [CMD], or mixed) is recommended among patients with angina with non-obstructive coronary arteries. Whilst clear diagnostic criteria for VSA and CMD exist, there is no standardised FCA protocol. Variations in testing protocol may limit the widespread uptake of testing, generalisability of results, and expansion of collaborative research. At present, there are no data describing protocol variation across an entire geographic region. Therefore, we aimed to capture current practice variations in the approach to FCA to improve access and standardisation for diagnosis of coronary vasomotor disorders in Australia and New Zealand.

Method

Between July 2022 and July 2023, we conducted a national survey across all centres in Australia and New Zealand with an active FCA program. The survey captured attitudes towards FCA and protocols used for diagnosis of coronary vasomotor disorders at 33 hospitals across Australia and New Zealand.

Results

Survey responses were received from 39 clinicians from 33 centres, with representation from centres within all Australian states and territories and both North and South Islands of New Zealand. A total of 21 centres were identified as having an active FCA program. In general, respondents agreed that comprehensive physiology testing helped inform clinical management. Barriers to program expansion included cost, additional catheter laboratory time, and the absence of an agreed-upon national protocol. Across the clinical sites, there were significant variations in testing protocol, including the technique used (Doppler vs thermodilution), order of testing (hyperaemia resistance indices first vs vasomotor function testing first), rate and dose of acetylcholine administration, routine use of temporary pacing wire, and routine single vs multivessel testing. Overall, testing was performed relatively infrequently, with very little follow-on FCA performed, despite nearly all respondents believing this would be clinically useful.

Conclusions

This survey demonstrates, for the first time, variations in FCA protocol among testing centres across two entire countries. Furthermore, whilst FCA was deemed clinically important, testing was performed relatively infrequently with little or no follow-on testing. Development and adoption of a standardised national FCA protocol may help improve patient access to testing and facilitate further collaborative research within Australia and New Zealand.

Background

Heart failure requires complex management, and increased patient knowledge has been shown to improve outcomes. This study assessed the knowledge of Chat Generative Pre-trained Transformer (ChatGPT) and its appropriateness as a supplemental resource of information for patients with heart failure.

Method

A total of 107 frequently asked heart failure-related questions were included in 3 categories: “basic knowledge” (49), “management” (41) and “other” (17). Two responses per question were generated using both GPT-3.5 and GPT-4 (i.e., two responses per question per model). The accuracy and reproducibility of responses were graded by two reviewers, board-certified in cardiology, with differences resolved by a third reviewer, board-certified in cardiology and advanced heart failure. Accuracy was graded using a four-point scale: (1) comprehensive, (2) correct but inadequate, (3) some correct and some incorrect, and (4) completely incorrect.

Results

GPT-4 provided 107/107 (100%) responses with correct information. Further, GPT-4 displayed a greater proportion of comprehensive knowledge for the categories of “basic knowledge” and “management” (89.8% and 82.9%, respectively). For GPT-3, there were two total responses (1.9%) graded as “some correct and incorrect” for GPT-3.5, while no “completely incorrect” responses were produced. With respect to comprehensive knowledge, GPT-3.5 performed best in the “management” category and “other” category (prognosis, procedures, and support) (78.1%, 94.1%). The models also provided highly reproducible responses, with GPT-3.5 scoring above 94% in every category and GPT-4 with 100% for all answers.

Conclusions

GPT-3.5 and GPT-4 answered the majority of heart failure-related questions accurately and reliably. If validated in future studies, ChatGPT may serve as a useful tool in the future by providing accessible health-related information and education to patients living with heart failure. In its current state, ChatGPT necessitates further rigorous testing and validation to ensure patient safety and equity across all patient demographics.