La frappe au clavier induit-elle des modifications morphologiques du nerf médian, constituant un facteur de risque du syndrome du canal carpien ?
Bibliographic record
Abstract
Context: Carpal tunnel syndrome (CTS) is a common condition, affecting 3% of the general population, with a particularly high incidence among working adults. Moreover, computer use is on the rise : in 2019, 79% of employees used a computer, compared to 60% in 2005. This widespread usage is not without health consequences. Objective: This review aims to determine whether typing can induce morphological changes in the median nerve within the carpal tunnel, which could represent a risk factor for CTS. Method: A bibliographic search was conducted on PubMed, ScienceDirect, and the Cochrane Library. Among the 155 references initially identified, 4 studies were included (3 cohort studies and 1 cross-sectional study). The main outcome was the cross-sectional area (CSA) of the median nerve, measured by ultrasound. The risk of bias in the studies was assessed using the Newcastle-Ottawa Scale. Results: The three cohort studies report a significant increase in the CSA of the median nerve after typing, which is reversible after rest. No study showed a significant increase in the number of participants exceeding the pathological threshold of 11 mm², although a trend was observed after 60 minutes of typing. On the contrary, the cross-sectional study reports a slight non-significant decrease in CSA among intensive users (>4 hours/day). Discussion : The limited number of studies and their heterogeneity are significant limits. According to the AMSTAR-2 tool, this review presents a very low level of confidence. Controlled cohort studies with prospective follow-up would better attribute the effects to keyboard exposure. It would also be relevant to explore differences between desktop and laptop keyboards. Conclusion: Although typing may temporarily modify the characteristics of the median nerve, no statistically significant association with pathological damage was demonstrated, suggesting that typing alone is not an established risk factor.
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".