Multidisciplinary ALS care improves quality of life in patients with ALS
Bibliographic record
Abstract
OBJECTIVE: To examine the effect of multidisciplinary ALS care on the quality-of-life (QoL) in patients with ALS and their caregivers. METHODS: In a cross-sectional study, 208 patients with ALS and their caregivers were interviewed. QoL was assessed using the 36-item Short Form Health Survey (SF-36) and two visual analogue scales (VAS). Criteria for multidisciplinary ALS care were: an ALS team headed by a consultant in rehabilitation medicine and consisting of at least a physical therapist, occupational therapist, speech pathologist, dietician and a social worker; use of the Dutch ALS consensus guidelines for ALS care; and at least six incident ALS patients per year. RESULTS: Clinical characteristics and functional loss of the 133 patients receiving multidisciplinary ALS care and the 75 patients receiving general ALS care were similar. The percentage of patients with adequate aids and appliances was higher in those with multidisciplinary ALS care (93.1 vs 81.3%, p = 0.008), whereas the number of visits to professional caregivers was similar in both groups. Patients in the multidisciplinary ALS care group had a better mental QoL on the SF-36 Mental Summary Score than those in the general care group (p = 0.01). The difference in QoL was most pronounced in the domains of Social Functioning and Mental Health, and was independent of the presence of aids and appliances. No significant differences were found in the SF-36 Physical Summary Score, VAS, or in QoL of caregivers of patients with ALS. CONCLUSION: High standard of care improves mental quality-of-life in patients with ALS.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".