P.039 Development of a checklist for treating adults with Myotonic Dystrophy Type 1: a neuromuscular disease network for Canada (NMD4C) Knowledge Translation Tool
Bibliographic record
Abstract
Background: The Neuromuscular Disease Network for Canada (NMD4C) aims to improve the care of Canadians with neuromuscular diseases. It has identified a need to support clinicians in implementing clinical guidelines with the use of checklists for initial evaluation and clinical follow-ups. The objective of the study was to develop a pragmatic management checklist to support clinical guidelines for diagnosis and follow-up of myotonic dystrophy type 1 (DM1). Methods: A practice-based DM1 checklist will be reviewed by a panel of 35 experts using an online survey. The survey has been drafted using the Appraisal of Guidelines Research and Evaluation tool for assessing Recommendation Excellence (AGREE-REX). The experts will rate: (1) the quality of each checklist recommendation, and (2) the applicability of each recommendation based on their clinical setting. Scores will be compiled and discussed among experts to achieve consensus. Results: The compiled checklist items were organized into three sections: (1) initial evaluation, (2) follow-up visit and (3) general treatment recommendations. Feedback from experts across Canada, results on feasibility, and a finalized checklist will be presented. Conclusions: The development of a feasible treatment checklist is a useful KT tool that DM1 experts across Canada could apply in their own clinical settings.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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; both teacher heads agree on what is shown here.
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".