Abstract 14167: Cardiac Electrophysiologists' Perspectives on Sleep Apnea
Bibliographic record
Abstract
Introduction: Sleep apnea (SA) is a well-recognized and potentially modifiable factor in the pathophysiology of arrhythmias including atrial fibrillation (AF). The purpose of the study was to evaluate cardiac electrophysiologists’ (EP)’s perception about SA and opinions on management. Methods: Based on semi-structured interviews among conveniently sampled EP (N=4) to narrow preliminary areas of interest for investigation, we created a 27-item online Likert scale-based survey instrument entailing several domains using: 1) the relevance of SA in EP practice and familiarity with it, 2) the practice patterns for SA screening and diagnosis, 3) perception on treatments for SA, 4) opinion on the SA care model. The survey was distributed to 89 academic EP programs in the United States and Canada. Results: A total of 105 cardiologists from 49 institutions responded over a 9-month period, including 63% attending EP and 37% EP fellows in training. The majority of respondents agreed that SA is a major concern in their practice (94%) and that they frequently discussed the connection between SA and the risk of arrhythmia with patients (95%). However, nearly half of respondents (42%) indicated insufficient education on SA during training. In addition, many of them (58%) agreed that they would be comfortable managing SA themselves with proper training and education. Many EPs (53%) were not satisfied with the referral process to a sleep specialist in the area where they practice. The majority (66%) of EP physicians agreed that cardiologists should become more involved in the management of SA than they are now. Additionally, majority (86%) agreed that trained advanced practice providers should be able to assess and manage SA. Many identified time constraints, lack of knowledge, and referral process as major barriers to cardiologists becoming more involved in SA care. Conclusions: There is wide recognition by EP of the importance of SA and its relationship with arrhythmia and AF. However, education and incorporation into cardiology practice appears to lag. Future studies examining the impact of integrating SA care delivery in EP practice on patient outcomes, satisfaction of both patients and EP and healthcare cost are needed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".