Hormone replacement therapy in women and risk of carpal tunnel syndrome: a systematic review and metaanalysis
Bibliographic record
Abstract
BACKGROUND: Carpal tunnel syndrome (CTS) is the most common entrapment mononeuropathy. Menopausal status and/or estrogen level may play a role in CTS. The evidence regarding the association between hormone replacement therapy (HRT) in postmenopausal women and CTS is still conflicting. This meta-analysis aimed to investigate the association between carpal tunnel syndrome (CTS) and women using hormone replacement therapy (HRT). METHODS: A search was conducted in the PubMed/Medline, Scopus, Embase, and Cochrane databases, from their inception through July 2022. Studies which reported on the association between any type of HRT use and the risk of developing CTS in postmenopausal women compared to a control group were included. Studies which did not include a control group were excluded. Of the 1573 articles extracted from database searches, seven studies involving 270,764 women were included of which 10,746 had CTS. The association between CTS and HRT use was evaluated using the pooled odds ratio (OR) with a 95% confidence interval (CI) under random-effects modelling. Risk of bias in each study was assessed using the Newcastle-Ottawa Scale (NOS) and version 2 of the Cochrane tool for assessing risk of bias in randomized trials (RoB 2). RESULTS: 97.0%, Q-test p-value < 0.001). Subgroup analysis of groups in non-randomized controlled studies showed a significantly increased risk of CTS, while groups in randomized controlled studies showed a decreased risk of CTS (pooled OR 1.87, 95% CI 1.24-2.83 versus pooled OR 0.79, 95% CI 0.69-0.92, respectively) with the p-value of group difference < 0.001. The risk of bias in most of the included studies was estimated to be low. CONCLUSIONS: This meta-analysis supports the safety of using HRT in postmenopausal women with potential risk factors for CTS. LEVEL OF EVIDENCE: I, Prognosis. REGISTRATION: INPLASY (202280018).
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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 | 0.010 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.030 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".