The Canadian Heart Failure (CAN-HF) Registry: A Canadian Multicentre, Retrospective Study of Outpatients with Heart Failure
Bibliographic record
Abstract
Background: Guideline-directed medical therapy (GDMT) reduces events in patients with heart failure (HF) with reduced ejection fraction (HFrEF). Despite this impact, underutilization of GDMT persists. This report sought to describe HF management in Canadian outpatients treated at specialized HF clinics (HFCs). Methods: The Canadian Heart Failure (CAN-HF) study was retrospective and observational, and it included 1775 patients from 6 Canadian outpatient HFCs, from the period January 2017-April 2020. Results: We observed improvement in prescription rates in patients with HFrEF, between their first visit and their most-recent clinic visit, across all GDMT classes, in those who were followed at the HFC for ≥ 6 months. The largest prescription rate increases were observed for angiotensin receptor-neprilysin inhibitors and mineralocorticoid-receptor antagonists. However, more than half of the patients remained on angiotensin-converting enzyme inhibitors and/or angiotensin-receptor blockers, despite being symptomatic, according to their New York Heart Association class. Most patients (50%) were on triple therapy, as of their most-recent visit, with fewer (36%) on dual therapy, monotherapy (13%), or no GDMT (2%). Our data also suggest that patients who had been managed at the HFC for > 6 months had higher prescription rates of GDMT and were on higher doses of GDMT, compared to those who were new to the clinic. For patients with HF with preserved ejection fraction, few patients were on candesartan and less than half were on a mineralocorticoid-receptor antagonist. Conclusions: Our data from HFCs that in most cases were affiliated with academic centres compare favourably with data from other analyses of ambulatory patients with HFrEF, evidence that supports the use of a specialized patient-care model.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.009 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 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".