Validation of the Italian version of the Non Motor Symptoms Scale for Parkinson's disease
Bibliographic record
Abstract
OBJECTIVE: To validate the adapted Italian version of the Non-Motor Symptoms Scale (NMSS), a tool to assess non-motor symptoms (NMS) in Parkinson's disease (PD). METHODS: A cross cultural adaptation of the NMSS into Italian and a psychometric analysis of the translated version of the NMSS was carried out in patients with PD from two university centres-affiliated hospitals. The quality of data and the acceptability, reliability and construct validity of NMSS were analyzed. The following standard scales were also applied: Hoehn and Yahr staging, Unified Parkinson's Disease Rating Scale (UPDRS) part III, Montreal Cognitive Assessment, Beck Depression Inventory, Neuropsychiatric Inventory, Epworth Sleepiness Scale, Autonomic Scale for Outcomes in Parkinson's disease-Motor, Movement Disorder Society-Sponsored Revision of the Unified Parkinson's Disease Rating Scale part I and Modified Cumulative Illness Rating Scale (CIRS). Levodopa equivalent daily dose (LEDD) was calculated. RESULTS: Seventy-one patients with PD were assessed (mean age years 69.8 ± 9.6 SD; 31% women; mean length of disease 6.3 ± 4.6 years; H&Y median: 2). Mean NMSS was 39.76 (SD 31.9; skewness 0.95). The total score of NMSS was free of floor or ceiling effects and showed a satisfactory reliability (Cronbach's alpha coefficient on total score was 0.72 [range for domains: 0.64-0.73], SEM value was 3.88 [½ SD = 31.90]). Significant positive correlations were found among total NMSS and other NMS standard tests, but no significant correlation appeared with UPDRS part III, CIRS and LEDD. CONCLUSIONS: The Italian NMSS is a comprehensive and helpful measure for NMS in native Italian patients with PD.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".