The effect of nurse practitioner (NP-led) care on health-related quality of life in people with multiple sclerosis – a randomized trial
Bibliographic record
Abstract
BACKGROUND: Care for People with Multiple Sclerosis (PwMS) is increasingly complex, requiring innovations in care. Canada has high rates of MS; it is challenging for general neurologists to optimally care for PwMS with busy office practices. The aim of this study was to evaluate the effects of add-on Nurse Practitioner (NP)-led care for PwMS on depression and anxiety (Hospital Anxiety and Depression Scale, HADS), compared to usual care (community neurologist, family physician). METHODS: PwMS followed by community neurologists were randomized to add-on NP-led or Usual care for 6 months. Primary outcome was the change in HADS at 3 months. Secondary outcomes were HADS (6 months), EQ5D, MSIF, CAREQOL-MS, at 3 and 6 months, and Consultant Satisfaction Survey (6 months). RESULTS: We recruited 248 participants; 228 completed the trial (NP-led care arm n = 120, Usual care arm n = 108). There were no significant baseline differences between groups. Study subjects were highly educated (71.05%), working full-time (41.23%), living independently (68.86%), with mean age of 47.32 (11.09), mean EDSS 2.53 (SD 2.06), mean duration since MS diagnosis 12.18 years (SD 8.82) and 85% had relapsing remitting MS. Mean change in HADS depression (3 months) was: -0.41 (SD 2.81) NP-led care group vs 1.11 (2.98) Usual care group p = 0.001, sustained at 6 months; for anxiety, - 0.32 (2.73) NP-led care group vs 0.42 (2.82) Usual care group, p = 0.059. Other secondary outcomes were not significantly different. There was no difference in satisfaction of care in the NP-led care arm (63.83 (5.63)) vs Usual care (62.82 (5.45)), p = 0.194). CONCLUSION: Add-on NP-led care improved depression compared to usual neurologist care and 3 and 6 months in PwMS, and there was no difference in satisfaction with care. Further research is needed to explore how NPs could enrich care provided for PwMS in healthcare settings. TRIAL REGISTRATION: Retrospectively registered on clinicaltrials.gov ( ClinicalTrials.gov Identifier: NCT04388592 , 14/05/2020).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".