Survival Analysis of Myasthenia Gravis Patients at a Referral Center in Pará, Brazil (2005-2020)
Bibliographic record
Abstract
Objective: To evaluate the profile and survival of patients diagnosed with Myasthenia Gravis, by reviewing medical records of neurological consultations at a referral service in the interior of Pará (Brazil), between 2005 and 2020. Methods: a historical, observational and retrospective cohort study. 36 participants were included. Survival analysis methods were used to identify prognostic factors for disease remission at the observation time of 36 months. The correlation between the variables and the death outcome was performed using the chi-square test. Results: Most patients were women (66.6%) and had the generalized form of the disease (86.1%). The most prevalent symptoms were: ophthalmoparesis (97.2%), fatigability (75%) and dysphagia (72.2%). Among the complications, 19.4% had myasthenic crisis. The dosage of anti-acetylcholine receptor (AChR) antibody was positive in 58.3% and 69.4% underwent electroneuromyography, and 72% of them had electrodecrement. Most of the patients responded to the staggered standard treatment and achieved remission (83.3%), while 16.6% died. Survival analysis showed through Kaplan-Meier curves and Log-rank test that the variables related to poor control were male gender (p=0.01), thymus disease (p=0.02) and use of cyclosporine (p=0.02). The factors that influenced the death outcome were male gender, cyclosporine and thymectomy. Conclusion: The study showed that the evolution of people with Myasthenia Gravis over 15 years and the poor prognostic factors were equivalent to the international literature.
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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 | 0.000 | 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".