ABSTRACT
Background: To assess whether hydrostatic pressure gradients caused by coronary height differences in supine versus prone positioning during invasive physiological stenosis assessment affect resting and hyperaemic pressure-based indices or coronary flow. Methods: Twenty-three coronary stenoses were assessed in twenty-one patients with stable coronary artery disease. All patients had a stenosis of at least 50% visually defined on previous coronary angiography. Pd/Pa, iFR, FFR, and coronary flow velocity (APV) measured using a Doppler were recorded across the same stenosis, with the patient in the prone position, followed by repeat measurements in the standard supine position. Results: When comparing prone to supine measurements in the same stenosis, in the LAD, there was a significant change in mean Pd/Pa of 0.08 ± 0.04 (p = 0.0006), in the iFR of 0.06 ± 0.07 (p = 0.02), and in the FFR of 0.09 ± 0.07 (p = 0.003). In the Cx, there was a change in mean Pd/Pa of 0.05 ± 0.04 (p = 0.009), iFR of 0.07 ± 0.04 (p = 0.01), and FFR of 0.05 ± 0.03 (p = 0.006). In the RCA, there was a change in Pd/Pa of 0.05 ± 0.04 (p = 0.032), iFR of 0.04 ± 0.05 (p = 0.19), and FFR of 0.04+-0.03 (p = 0.004). Resting and hyperaemic coronary flow did not change significantly (resting delta APV = 1.6 cm/s, p = 0.31; hyperaemic delta APV = 0.9 cm/s, p = 0.85). Finally, 36% of iFR measurements and 26% of FFR measurements were re-classified across an ischaemic threshold when prone and supine measurements were compared across the same stenosis. Conclusions: Pd/Pa, iFR, and FFR were affected by hydrostatic pressure variations caused by coronary height differences in prone versus supine positioning. Coronary flow did not change signifying a purely pressure-based phenomenon.
ABSTRACT
INTRODUCTION: Cardiac arrest leaves witnesses, survivors, and their relatives with a multitude of questions. When a young or a public figure is affected, interest around cardiac arrest and cardiopulmonary resuscitation (CPR) increases. ChatGPT allows everyone to obtain human-like responses on any topic. Due to the risks of accessing incorrect information, we assessed ChatGPT accuracy in answering laypeople questions about cardiac arrest and CPR. METHODS: We co-produced a list of 40 questions with members of Sudden Cardiac Arrest UK covering all aspects of cardiac arrest and CPR. Answers provided by ChatGPT to each question were evaluated by professionals for their accuracy, by professionals and laypeople for their relevance, clarity, comprehensiveness, and overall value on a scale from 1 (poor) to 5 (excellent), and for readability. RESULTS: ChatGPT answers received an overall positive evaluation (4.3 ± 0.7) by 14 professionals and 16 laypeople. Also, clarity (4.4 ± 0.6), relevance (4.3 ± 0.6), accuracy (4.0 ± 0.6), and comprehensiveness (4.2 ± 0.7) of answers was rated high. Professionals, however, rated overall value (4.0 ± 0.5 vs 4.6 ± 0.7; p = 0.02) and comprehensiveness (3.9 ± 0.6 vs 4.5 ± 0.7; p = 0.02) lower compared to laypeople. CPR-related answers consistently received a lower score across all parameters by professionals and laypeople. Readability was 'difficult' (median Flesch reading ease score of 34 [IQR 26-42]). CONCLUSIONS: ChatGPT provided largely accurate, relevant, and comprehensive answers to questions about cardiac arrest commonly asked by survivors, their relatives, and lay rescuers, except CPR-related answers that received the lowest scores. Large language model will play a significant role in the future and healthcare-related content generated should be monitored.
