Abstract 085: Discordance in Patient-Physician Perceptions of Angina Experiences and Delivery of Care
Bibliographic record
Abstract
Background: Recent findings from the APPEAR study indicate that physicians under-recognize angina frequency in many patients with coronary artery disease (CAD). We surveyed patients with angina and the physicians who treat them to further explore factors that may contribute to under-recognition and the impact of under-recognition on patients’ experiences. Methods: Surveys were completed by 29 US physicians and 122 of their patients with stable CAD. Patients reported burden of angina and satisfaction with medication. Physicians estimated the average experience of their patients with stable CAD. Results: As with prior studies, physicians under-estimated burden of angina as reported by the patients (physician vs. patient report: weekly of more angina: 24% vs 50%, p=0.014; CCS III/IV: 22% vs 43%, p<0.001). Physicians also over-estimated patients’ satisfaction with control of their angina (70% vs 50%, p<0.001). Over 90% of physicians reported routinely asking patients about the frequency of their angina and adherence to antianginal medications (Figure). Most physicians estimate angina using NYHA or CCS class (59% and 24%, respectively) whereas 7% used a patient-reported assessment. While lack of time was reported as the biggest barrier to accurately assessing patients’ burden of angina, most physicians reported having no challenges to conducting these assessments. Conversely, 68% of patients reported that their physicians effectively communicated with them. Conclusions: Using a detailed survey of patients with stable CAD and their physicians, we found that physicians believe they are communicating effectively and most patients agreed (although to a lesser degree); yet, a substantial discordance between physician and patient perceptions of angina remains. These discordances may contribute to suboptimal treatment decisions, decreased treatment satisfaction, and poor quality of life. The observed discordances may be explained partly by the fact that <10% of physicians reported using a tool to assess angina burden directly from the patients, as physicians appeared to over-estimate their ability to accurately assess angina using traditional interview techniques. Education and use of validated angina assessment tools are essential for aligning perceptions to improve patient care and outcomes.
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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 | 0.008 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".