Grip strength comparison in immune‐mediated neuropathies: Vigorimeter vs. Jamar
Bibliographic record
Abstract
The Jamar dynamometer and Vigorimeter have been used to assess grip strength in immune-mediated neuropathies, but have never been compared to each other. Therefore, we performed a comparison study between these two devices in patients with immune-mediated neuropathies. Grip strength data were collected in 102 cross-sectional stable and 163 longitudinal (new diagnoses or changing condition) patients with Guillain-Barré syndrome (GBS), chronic inflammatory demyelinating polyradiculoneuropathy (CIDP), gammopathy-related polyneuropathy (MGUSP), and multifocal motor neuropathy (MMN). Stable patients were assessed twice (validity/reliability studies). Longitudinal patients were assessed 3-5 times during 1 year. Responsiveness comparison between the two tools was examined using combined anchor-/distribution-based minimum clinically important difference (MCID) techniques. Patients were asked to indicate their preference for the Jamar or Vigorimeter. Both tools correlated highly with each other (ρ = 0.86, p < 0.0001) and showed good intra-class correlation coefficients (Jamar [Right/Left hands]: ICC 0.997/0.96; Vigori: ICC 0.95/0.98). Meaningful changes were comparable between the two instruments, being higher in GBS compared to CIDP patients. In MGUSP/MMN poor responsiveness was seen. Significant more patients preferred the Vigorimeter. In conclusion, validity, reliability, and responsiveness aspects were comparable between the Jamar dynamometer and Vigorimeter. However, based on patients' preference, the Vigorimeter is recommended in future studies in immune-mediated neuropathies.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".