Quality of congestive heart failure treatment at a Canadian teaching hospital.
Bibliographic record
Abstract
BACKGROUND: Practice guidelines for the management of congestive heart failure (CHF) emphasize the need for assessment of left ventricular function and treatment with angiotensin-converting enzyme (ACE) inhibitors. However, previous studies have shown that many patients do not receive these tests or medications. The objective of this study was to evaluate the compliance of physicians at a large Canadian teaching hospital with published CHF management guidelines. METHODS: We conducted a retrospective review of the charts of 200 patients admitted to Sunnybrook & Women's College Health Sciences Centre, Toronto, in 1997 for whom CHF was the diagnosis most responsible for the hospital admission. Quality of care was measured with 3 indicators: the use of left ventricular function testing to determine systolic versus diastolic dysfunction; the prescription of ACE inhibitors to appropriate patients (those with systolic dysfunction, no contraindications to ACE inhibitor therapy and no angiotensin II receptor blocker use); and the prescription of target doses of ACE inhibitors. RESULTS: Of the 200 patients 177 (88.5%) received left ventricular function testing before or during their hospital stay; of the 177, 117 (66.1%) had systolic dysfunction. A total of 100 patients were considered to be ideal candidates for ACE inhibitor treatment. Of the 100, 89 (89.0%) received ACE inhibitors; however, only 23 (23.0%) were prescribed target doses. INTERPRETATION: Most patients who had CHF at this Canadian hospital received left ventricular function testing and ACE inhibitor therapy. Future educational efforts should focus on the importance of adequate dosing of ACE inhibitors.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".