Nerve conduction studies and current perception thresholds in workers assessed for hand-arm vibration syndrome
Bibliographic record
Abstract
BACKGROUND: Workers exposed to hand-arm vibration are at risk of developing the neurological abnormalities of hand-arm vibration syndrome (HAVS). The Stockholm classification of the neurological component of HAVS is based on history and physical examination. There is a need to determine the association between neurological tests and the Stockholm scale. AIMS: The main objective of this study was to compare the Stockholm neurological scale and the results of current perception threshold (CPT) tests and nerve conduction studies (NCS). METHODS: Detailed physical examinations were done on 162 subjects referred for HAVS assessment at a specialist occupational health clinic. All subjects had NCS and measurement of CPT. The Stockholm neurological classification was carried out blinded to the results of these neurological tests and compared to the test results. RESULTS: The nerve conduction results indicated that median and ulnar neuropathies proximal to the hand are common in workers being assessed for HAVS. Digital sensory neuropathy was found in only one worker. Neither the nerve conduction results nor the current perception results had a strong association with the Stockholm neurological scale. Exposure to vibration in total hours was the main variable associated with the Stockholm neurological scale [right hand: OR 1.30, 95% CI (1.10-1.54); left hand: OR 1.18, 95% CI (1.0-1.39)]. CONCLUSION: Workers being assessed for HAVS should have nerve conduction testing to detect neuropathies proximal to the hand. Quantitative sensory tests such as current perception measurement are insufficient for diagnostic purposes but may have a role in screening workers exposed to vibration.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".