Best Standards of Care for Patients with Late-Onset Pompe Disease – A Canadian Perspective
Bibliographic record
Abstract
Although ERT has become the standard of care for patients with Pompe disease, careful monitoring of patients is also essential for optimal care.Guidelines for the care of patients with Pompe disease have been published by a number of countries and the goal of the presentation is to highlight some of the consensus recommendations.The goal of guidelines is to provide a general framework of evidence or consensus-based standards of care for the team caring for patients with Pompe disease.It is important to remember that the guidelines should be fl exibly contextualised for the available clinic resources and must cater to the needs of the individual patient.Enrolment in a patient registry (i.e., http://www.pomperegistry.com/)may help in clinically relevant research; offering external support through various support groups (i.e., http://www.worldpompe.org;http://www.unitedpompe.com,etc.) is of interest to some, but not all, patients.Depression and anxiety may be part of the disease process and support via counselling and psychiatry may be needed.A team approach is recommended and members may include; neurology, medical genetics, respirology, cardiology, physiatry, psychiatry, speech and language pathology, occupational therapy, physiotherapy,
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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 | 0.018 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.007 | 0.005 |
| Research integrity | 0.007 | 0.010 |
| Insufficient payload (model declined to judge) | 0.009 | 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".