Improved Outcomes With Early Collaborative Care of Ambulatory Heart Failure Patients Discharged From the Emergency Department
Bibliographic record
Abstract
BACKGROUND: The type of outpatient physician care after an emergency department visit for heart failure may affect patients' outcomes. METHODS AND RESULTS: Using the National Ambulatory Care Reporting System, we examined the care and outcomes of heart failure patients who visited and were discharged from the emergency department in Ontario, Canada (April 2004 to March 2007). Early collaborative care by a cardiologist and primary care (PC) physician within 30 days after discharge was compared with PC alone. Care for 10 599 patients (age, 74.9±11.9 years; 50.2% male) was provided by PC alone (n=6596), cardiologist alone (n=535), or concurrently by both cardiologist and PC (n=1478); 1990 did not visit a physician. Collaborative care patients were more likely to undergo assessment of left ventricular function (57.4% versus 28.7%), noninvasive stress testing (20.1% versus 7.8%), and cardiac catheterization (11.6% versus 2.7%) compared with PC. Drug prescriptions (patients ≥65 years of age) demonstrated higher use of angiotensin-converting enzyme inhibitors (58.8% versus 54.6%), angiotensin receptor blockers (22.7% versus 18.1%), β-adrenoceptor antagonists (63.4% versus 48.0%), loop diuretics (84.2% versus 79.6%), metolazone (4.8% versus 3.4%), and spironolactone (19.8% versus 12.7%) within 100 days after emergency department discharge for collaborative care compared with PC. In a propensity-matched model, mortality was lower with PC compared with no physician visit (hazard ratio, 0.75; 95% confidence interval, 0.64 to 0.87; P<0.001). Collaborative care reduced mortality compared with PC (hazard ratio, 0.79; 95% confidence interval, 0.63 to 1.00; P=0.045). Sole cardiology care conferred a trend to increased mortality (hazard ratio, 1.41 versus collaborative care; 95% confidence interval, 0.98 to 2.03; P=0.067). CONCLUSIONS: Early collaborative heart failure care was associated with increased use of drug therapies and cardiovascular diagnostic tests and better outcomes compared with PC alone.
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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 | 0.006 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".