Heart Failure Screening in Moose Factory, Ontario: Early Results and Lessons Learned to Facilitate Early Intervention and Specialist Cardiology Care in the James and Hudson Bay region
Bibliographic record
Abstract
The Weeneebayko Area Health Authority (WAHA) and the University Health Network (UHN) worked in collaboration to co-develop a heart failure (HF) screening pathway to bring cardiovascular care closer to home for residents in the Hudson and James Bay region. Building on an established partnership and guided by WAHA’s principles and values, the pathway was implemented and executed over 6 months. Canadian Cardiovascular Society guidelines were applied to a WAHA maintained patient roster. 37 patients were identified as at-risk for HF and further refined down to 28 patients through clinical and co-ordination considerations (such as kidney function and previous follow-up for cardiovascular complaints). Each qualifying patient was contacted by a WAHA nurse clinical coordinator and invited to be screened through brain natriuretic peptide (BNP) testing. 26 of 28 patients agreed to be screened (93% conversion rate). 24 of 26 patients completed their bloodwork. 7 patients were then identified for rapid in-community follow-up, by UHN cardiologists, within two weeks of their positive screen. 4 patients were seen, and 2 were enrolled in a remote management program for HF. This screening pathway increases the capacity of WAHA and UHN teams to provide coordinated, continuous care, focused on prevention and early intervention of HF.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".