The GoodHope Ehlers Danlos Syndrome Clinic: development and implementation of the first interdisciplinary program for multi-system issues in connective tissue disorders at the Toronto General Hospital
Bibliographic record
Abstract
Ehlers-Danlos Syndrome (EDS) are a heterogeneous group of genetic connective tissue disorders, and typically manifests as weak joints that subluxate/dislocate, stretchy and/or fragile skin, organ/systems dysfunction, and significant widespread pain. Historically, this syndrome has been poorly understood and often overlooked. As a result, people living with EDS had difficulty obtaining an accurate diagnosis and appropriate treatment, leading to untold personal suffering as well as ineffective health care utilization. The GoodHope EDS clinic addresses systemic gaps in the diagnosis and treatment of EDS. This paper describes a leap forward-from lack of awareness, diagnosis, and treatment-to expert care that is tailored to meet the specific needs of patients with EDS. The GoodHope EDS clinic consists of experts from various medical specialties who work together to provide comprehensive care that addresses the multi-systemic nature of the syndrome. In addition, EDS-specific self-management programs have been developed that draw on exercise science, rehabilitation, and health psychology to improve physical and psychosocial wellbeing and overall quality of life. Embedded into the program are research initiatives to shed light on the clinical presentation, underlying mechanisms of pathophysiology, and syndrome management. We also lead regular educational activities for community health care providers to increase awareness and competence in the interprofessional management of EDS beyond our doors and throughout the province and country.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".