The Vibration Quantitation Scale (VQS): A Simple, Reproducible Bedside Measure of Sensory Function in Multiple Sclerosis
Bibliographic record
Abstract
OBJECTIVES: To assess the utility of a bedside measure of sensation (the Vibration Quantitation Scale (VQS)) in patients with multiple sclerosis (MS) and in normal controls. To correlate the VQS with the Kurtzke Expanded Disability Severity Score (EDSS) and sensory abnormalities in these patients. METHODS: We developed the VQS and tested its performance in patients with MS of various ages, MS types, and EDSS scores. We compared this with controls (normal volunteers or patients with other neurological diseases) who did not have sensory symptoms. In a subgroup, two examiners measured VQS independently at the same patient visit. A standard C-128 tuning fork was used for the VQS measurement. RESULTS: The VQS had a good inter-observer reproducibility (r=0.920, p<0.001). The VQS fell with increasing age in normals consistent with declining sensory function. The VQS was significantly lower in the multiple sclerosis patients compared with age - matched controls (p<0.001). Abnormalities in VQS were present in patients with brief duration of MS (<5 years) and low EDSS scores, correlating with the presence of sensory abnormalities early in the disease course in some patients. There was a strong correlation between the VQS and EDSS (r=-.509). The VQS correlated with abnormal sensation in the hands (r=0.310), but did not meet statistical significance for abnormal sensation in the feet or face. A second cohort of MS patients was studied using a modified VQS measure (single stimulation, omitting forehead measurement). This reconfirmed the correlation between the modified VQS and EDSS as well as with age. The modified VQS may be useful in clinical practice since it takes little time and is strongly correlated with the EDSS (r=0.578). CONCLUSIONS: The VQS provides a continuous sensory scale applicable in most patients with MS, which is measurable with standard bedside equipment, and which may avoid some of the pitfalls of sensory scoring in 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".