Increasing rates of screening and treatment of iron deficiency in ambulatory patients with heart failure with reduced ejection fraction: a quality improvement cohort study
Bibliographic record
Abstract
Introduction Iron deficiency anaemia (IDA) is common in patients with heart failure (HF) and is associated with advanced HF and increased mortality. Intravenous iron supplementation increases exercise tolerance, improves quality of life, and decreases symptoms among patients with HF with reduced ejection fraction (HFrEF) and iron deficiency. Despite this, many patients are not screened or treated for IDA. We aimed to increase rates of screening and treatment of IDA among HF patients through the introduction of curated materials to aid HF clinicians with appropriate screening and treatment. Methods We conducted a retrospective chart review to identify the baseline number of HFrEF patients screened and treated for IDA at two ambulatory cardiology clinics in Toronto, Ontario. A quality improvement initiative was then introduced, which consisted of education and curated materials to aid clinicians in the screening and treatment of IDA among HFrEF patients. The proportion of patients screened and treated for IDA preintervention and postintervention were compared using χ 2 tests of Independence. Results In the preintervention cohort, 36.3% (n=45) of patients with anaemia were screened for IDA. Among those screened, 64.4% (n=29) had IDA. Only 17.2% (n=5) of these were treated with IV iron. After implementation of the quality improvement initiative, 90.9% (n=60) of patients with anaemia were screened for IDA (p<0.001) and 90.3% (n=28) of those with IDA were treated with IV iron (p<0.001). Conclusion The introduction of curated materials to aid clinicians was associated with increased rates of screening and treatment of IDA among ambulatory HFrEF patients. Further work is required to identify barriers and implement strategies to increase screening and treatment rates of IDA among HFrEF patients.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".