Primary care-based integrated disease management for heart failure: a study protocol for a cluster randomised controlled trial
Bibliographic record
Abstract
INTRODUCTION: Heart failure (HF) is a common chronic disease that increases in prevalence with age. It is associated with high hospitalisation rates, poor quality of life and high mortality. Management is complex with most interactions occurring in primary care. Disease management programmes implemented during or after an HF hospitalisation have been shown to reduce hospitalisation and mortality rates. Evidence for integrated disease management (IDM) serving the primary care HF population has been investigated but is less conclusive. The aim of this study is to evaluate the efficacy of IDM, focused on, optimising medication, self-management and structured follow-up, in a high-risk primary care HF population. METHODS AND ANALYSIS: 100 family physician clusters will be recruited in this Canadian primary care multicentre cluster randomised controlled trial. Physicians will be randomised to IDM or to care as usual. The IDM programme under evaluation will include case management, medication management, education, and skills training delivered collaboratively by the family physician and a trained HF educator. The primary outcome will measure the combined rate (events/patient-years) of all-cause hospitalisations, emergency department visits and mortality over a 12-month follow-up. Secondary outcomes include other health service utilisation, quality of life, knowledge assessments and acute HF episodes. Two to three HF patients will be recruited per physician cluster to give a total sample size of 280. The study has 90% power to detect a 35% reduction in the primary outcome. The difference in primary outcome between IDM and usual care will be modelled using a negative binomial regression model adjusted for baseline, clustering and for individuals experiencing multiple events. ETHICS AND DISSEMINATION: The study has obtained approval from the Research Ethics Board at the University of Western Ontario, London, Canada (ID 114089). Findings will be disseminated through local reports, presentations and peer-reviewed publications. TRIAL REGISTRATION NUMBER: NCT04066907.
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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 | 0.049 | 0.042 |
| Meta-epidemiology (narrow) | 0.008 | 0.003 |
| Meta-epidemiology (broad) | 0.017 | 0.007 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.009 | 0.008 |
| Insufficient payload (model declined to judge) | 0.083 | 0.013 |
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".