The associations between central serous chorioretinopathy and muscle relaxants
Bibliographic record
Abstract
PURPOSE: To evaluate the role of muscle-relaxants as risk factors for the development of central serous chorioretinopathy (CSC) - the second most common retinopathy in our settings; despite multiple risk factors seen in our patients, 21% were initially labelled as idiopathic. MATERIALS AND METHODS: Retrospective case-control study at a tertiary hospital in the United Arab Emirates, where we reviewed the medical records of 273 patients with CSC examined between 2010 and 2019 for use of muscle-relaxants including tolperisone/eperisone, carisoprodol and gabapentin/pregabalin within a year of onset/recurrence of the disease. Intake of drugs with known association with CSC (including corticosteroids/sympathomimetics) was also recorded. Two hundred eighty-six subjects with adverse events seen at the same institute during the same study period served as controls. Odds ratios, Chi-Square tests and multivariate logistic regression were carried out to determine any associations with the muscle-relaxants and other pharmacological confounders - corticosteroids/sympathomimetics. RESULTS: Muscle relaxants may increase the risk of CSC as evident on multivariate regression analysis (OR: 2.55; confidence interval [CI]: 1.208-5.413); the significance was retained on removing the 6 subjects who had corticosteroids/sympathomimetics (OR: 2.30; CI: 1.073-4.939). Univariate analysis yielded an OR of 2.52 for muscle relaxants (CI: 1.2149-5.2276), 2.96 for eperisone/tolperisone (CI: 1.3531-6.5038), and 6.26 for eperisone as an individual agent (CI: 1.8146-21.6252). CONCLUSION: < 0.05). The vascular smooth muscle relaxation could be the possible mechanism that affects the choroidal blood flow and indirectly predisposes to CSC.
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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 | 0.004 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".