Effect of Immunosuppression in Risk of Developing Generalized Symptoms in Ocular Myasthenia Gravis
Bibliographic record
Abstract
BACKGROUNDS AND OBJECTIVES: Early use of immunosuppression has been suggested to prevent generalization of ocular myasthenia gravis (OMG), but high-quality evidence is limited in this regard. We examined whether treatment with prednisone and other immunosuppressants reduce the risk of generalization in OMG. METHODS: This is a retrospective study of consecutive adults with pure OMG who had a minimum 6 months of follow-up. The main outcome was the time to developing generalized symptoms. We used propensity scores to create matched data sets of patients treated with prednisone or any immunosuppressant vs controls. We also used unmatched models with inverse probability of treatment weights (IPTW) and variable exposure times. We used Cox proportional hazards model to estimate hazard ratio (HR) for generalization, comparing treated patients vs controls. RESULTS: A total of 154 patients were included, with a mean follow-up of 87.4 ± 73 months since onset. Forty-three (28%) were generalized, and mean time to generalization from diagnosis was 24.2 ± 24.1 months. Patients who received prednisone had lower risk of generalization than controls, with pooled HR 0.43 (95% CI 0.19-1.06) for the matched model, HR 0.46 (95% CI 0.21-0.89) for the IPTW model, and for HR 0.44 (95% CI 0.23-0.81) for the time-dependent exposure model. Patients who received any immunosuppressant had lower risk of generalization, with HR 0.30 (95% CI 0.11-0.77), 0.32 (95% CI 0.14-0.70), and 0.35 (95% CI 0.15-0.80) for the matched, IPTW, and IPTW-varying exposure models, respectively. DISCUSSION: Our study provides evidence that steroidal and nonsteroidal immunosuppression in patients with OMG is associated with a reduced risk of developing generalized symptoms over time. This supports the early use of immunosuppression in this population. CLASSIFICATION OF EVIDENCE: This study provides Class III evidence that treatment of OMG with corticosteroids or nonsteroidal immunosuppressants reduces the risk of generalization.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".