Physician Perspectives on the Diagnosis and Management of Heart Failure With Preserved Ejection Fraction
Why this work is in the frame
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Bibliographic record
Abstract
BackgroundHeart failure (HF) with preserved ejection fraction (HFpEF) carries high morbidity and mortality. Compared with HF with reduced ejection fraction (HFrEF), HFpEF is difficult to diagnose, and lacks evidence-based treatments. In this survey we assessed perceptions of cardiologists, internists, and primary care physicians (PCPs) regarding HFpEF diagnosis and management.MethodsIn total, 159 cardiologists, 89 internists, and 200 PCPs from across Canada completed an online survey, with response rates of 14%-17%.ResultsThe perceived prevalence of HFpEF vs HFrEF was similar across physician types (58% HFrEF, 42% HFpEF). Thirty-seven percent of PCPs did not differentiate HF on the basis of ejection fraction. All physician types ranked symptom and mortality reduction as treatment priorities. Ninety-two percent of specialists believed that HFpEF is best comanaged by PCPs and specialists, whereas one-fifth of PCPs suggested PCP management alone. Compared with specialists, PCPs were more likely to underestimate HFpEF mortality and less aware of sex differences in the prevalence of HFpEF vs HFrEF (all P < 0.001). Fewer PCPs use natriuretic peptides for diagnosis (P < 0.001). All physician types listed cost and availability as barriers to natriuretic peptide use. Ninety-one percent of PCPs incorrectly identified various therapies as effective for improving HFpEF outcomes. Most of all physicians expressed a strong desire to increase knowledge of diagnostic and treatment algorithms for HFpEF.ConclusionsThere are substantial knowledge gaps in the diagnosis and management of HFpEF, particularly among PCPs. Because of the prevalence of HFpEF in primary care, strategies are required to reduce these gaps.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it