Consensus Methodology for the Canadian Brain and Heart Clinical Practice Guidelines
Bibliographic record
Abstract
Brain and heart diseases are leading causes of morbidity and mortality globally. Emerging evidence suggests a close interplay between brain and heart conditions, due to overlapping risk factors, common mechanistic pathways, and genetic factors. Therefore, a call has been made for the use of more interdisciplinary approaches to the prevention and treatment of brain and heart conditions. In this paper, we report on the consensus methodology used for the development of the first Canadian brain and heart clinical practice guidelines. The consensus panel included 10 expert subgroups, to develop research questions and recommendations for specific brain-heart conditions, the McMaster Evidence Review and Synthesis Team, to support the literature search, review, and critical appraisal, and an evidence review team to ensure the rigor and consistent application of the methodology. The consensus process followed the Appraisal of Guidelines for Research and Evaluation II (AGREE II) framework, with the following 4 key stages: (i) the McMaster Evidence Review and Synthesis Team conducted systematic reviews and provided subgroups with data extraction and evaluation tools; (ii) A consensus conference was held, with evidence and recommendations evaluated and voted on by all subgroups; (iii) the evidence review team conducted a final review of evidence for each subgroup and determined the level and strength of each recommendation; and (iv) final recommendations and evidence levels were submitted to all subgroups for ratification and approval by the steering committee. This paper summarizes and describes the consensus methods used to evaluate and integrate evidence from both the cardiac and neurological medical literature for the development of the first Canadian brain and heart clinical practice guidelines.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.017 | 0.344 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".