The Role of the Primary-Care Physician in Treating Relapses in Multiple Sclerosis Patients
Bibliographic record
Abstract
Multiple sclerosis (MS) is a common disabling neurologic disease with an overall prevalence in Canada of 240 in 100,000. Multiple sclerosis clinics are located at tertiary-care centers that may be difficult for a patient to access during an acute relapse. Many relapses are evaluated by primary-care physicians in private clinics or emergency departments, but these physicians' familiarity with MS is not known. Therefore, a survey was undertaken to determine the knowledge and experience of primary-care physicians regarding the diagnosis and treatment of MS relapses. A total of 1282 licensed primary-care physicians in the catchment area of the London (Ontario, Canada) Multiple Sclerosis Clinic were identified and mailed a two-page anonymous survey. A total of 237 (18.5%) responses were obtained, but only 216 (16.8%) of these respondents were still in active practice. Of these 216 physicians, only 9% reported having no MS patients in their practice, while 70% had one to five patients, 16.7% had six to ten, and 1.9% had more than ten (3.7% did not respond to this question). Corticosteroids were recognized as an MS treatment by 49.5% of the respondents, but only 43.1% identified them as a treatment for acute relapses. In addition, 31% did not know how to diagnose a relapse, and only 37% identified new signs or symptoms of neurologic dysfunction as indicating a potential relapse. Despite the high prevalence of MS in Canada, primary-care physicians require more education and support from specialists in MS care regarding the diagnosis and treatment of MS relapses.
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 | 0.003 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".