Prevalence and risk factors associated with self-reported carpal tunnel syndrome (CTS) among office workers in Kuwait
Bibliographic record
Abstract
BACKGROUND: The prevalence of carpal tunnel syndrome (CTS) is not well understood in many Arabian Peninsula countries. The objective of this study was to investigate the prevalence and factors associated with self-reported CTS in Kuwait. FINDINGS: A cross-sectional, self-administered survey of CTS-related symptoms was used in this study. Multivariate logistic regression was also used to estimate adjusted odds ratios for factors of interest. Participants in this study were adult office workers in Kuwait (n = 470, 55.6% males), who worked in companies employing more than 50 people. Self-reported CTS was reported in 18.7% of the group (88/470). CTS was significantly associated with the following demographic factors: female gender, obesity and number of comorbid conditions. Self-identification of CTS was also associated with key symptoms and impairment in daily activities (e.g., wrist pain, numbness, weakness, night pain, difficulty carrying bags, difficulty grasping [Chi-Square Test for Association: P < 0.05 for all symptoms/activities]). However, symptoms such as wrist pain, weakness, and functional disabilities were also frequently reported among those who do not self report CTS (range: 12.1%-38.2%). CONCLUSIONS: Prevalence of self-reported CTS among office workers in Kuwait is 18.7%, and the risk factors for CTS in this population included female gender, obesity and number of related comorbidities. The frequency of symptoms in the sample who did not self report CTS suggest that CTS may be under-recognized, however further research is required to assess the prevalence of clinically diagnosed CTS.
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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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".