A retrospective evaluation of patient characteristics and recommendations of a novel multidisciplinary clinic for persons with advanced disability from multiple sclerosis
Bibliographic record
Abstract
CONTEXT: Persons with advanced multiple sclerosis (MS) require care beyond the disease modifying treatments offered in conventional MS clinics to address their complex physical and psychosocial needs. In the novel MS Comprehensive and Palliative Care (MSCPC) Program, an MS neurologist, palliative care specialist, and physiatrist collaborate to identify these needs and improve symptom control. OBJECTIVES: To characterize the medical, physical, and psychosocial concerns of persons with advanced disability from MS and describe the recommended interventions of the MSCPC Program. METHODS: Retrospective chart review of consecutive patients seen in the MSCPC Program from 2019 to 2022. RESULTS: 54 patients were assessed over 74 clinic appointments. Patients' mean age was 59.4 ± 10.8 years (range 37-81) and mean duration of MS was 24.8 ± 11.8 years (range 2-52); 79.7% of patients had secondary progressive MS with median and mode disease severity (EDSS) of 7.5 and 8.5, respectively (range 4-9.5). 70.3% lived at home with a caregiver; the primary caregiver was the spouse for 51.4% of cases. 85.1% of patients received publicly funded in-home assistance for activities of daily living. The most prevalent sequelae of MS were incontinence (89.9%), spasticity (82.6%), and pain (78.3%). ≥1 symptom was addressed at 95.7% of appointments, most often pain (63.8%), spasticity (60.9%), and bowel (59.4%); medication deprescribing was recommended at 29.0% of appointments. Caregiver burnout was identified at 56.5% of appointments. CONCLUSION: This novel program identified high prevalence of symptoms and made recommendations to improve symptom control at >95% of appointments, suggesting unmet symptom control needs in persons with advanced disability from MS.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".