Abstract 14430: The Corcare Heart Function Optimization Protocol: A Structured Quality Improvement Intervention to Improve Goal Directed Targets for Patients With Reduced Ejection Fraction
Bibliographic record
Abstract
Introduction: Reduced ejection fraction (REF) in patients is prevalent, utilizing substantial health care resources. Goal Directed Therapy (GDT) reduces hospitalization, morbidity, and mortality but use is suboptimal. Care in subspecialty clinics following discharge reduces readmission, but is not scaled for longitudinal care of the larger REF population. Canadian guidelines support integration of primary, specialist, and non-physician care in systems to improve outcomes. Hypothesis: A protocol-guided intervention will achieve high rates of GDT for REF patients in a community health care setting. Goal: To evaluate a pragmatic quality-of-care intervention to achieve GDT for REF patients and assess barriers to GDT. Methods: Patients referred for imaging and cardiology consultation at a community facility (Jan 1/15-Dec 31/22) were screened. Patients with LVEF <41% on echocardiogram were included if their cardiologist consented to study protocol GDT and were enrolled at the next scheduled, usual care cardiologist visit. 2 project nurses confirmed patient status and assisted GDT management using medical directives at 9 protocol-specified visits between usual care visits over 32 weeks. The primary target was achieving GDT or maximally tolerated GDT (>0 mg). A secondary endpoint, clinical inertia, was defined as not achieving GDT due to physician or patient choice. Results: 864 patients (13 cardiologists) participated: median age 71 (28-102) years, diabetes 25%, hypertension 60%, atrial fibrillation 22%. At intake: NYHA class ≥2 (60%), EF <30% (45%), 30-35% (27%), 36-40% (29%), REF etiology ischemic (47%), non-ischemic (43%), mixed (10%). The majority achieved GDT in each class; inertia, not intolerance predominantly accounted for those who did not achieve GDT. Conclusion: This pragmatic community-based intervention achieved high rates of GDT that could improve longitudinal care for REF patients, and is potentially scalable and generalizable.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".