Outcomes of myasthenia gravis patients admitted to the Intensive Care Unit: Experience from a tertiary care center in Saudi Arabia.
Bibliographic record
Abstract
BACKGROUND: Myasthenia gravis is an autoimmune disorder that affects the neuromuscular junction resulting in muscle weakness and fatigue. The aim of this study was to investigate the indications for and frequency of intensive care unit admissions in people with myasthenia gravis in addition to exploring the clinical presentations and outcomes during their admission. METHODS AND FINDINGS: This retrospective study included all adult patients diagnosed with myasthenia gravis who were admitted to the intensive care unit in a six year period. Twenty-four patients with a diagnosis of myasthenia gravis were included in this study, with a total of 60 admissions. The median age at their first admission was 45 years with female predominance. Majority of the patients (87.5%) were acetylcholine antibody positive and 66.7% of patients had thymectomy. Myasthenic crisis was the most common reason for intensive care unit admission (63.3%). 80.5% of patients admitted with myasthenic crisis were treated with plasma exchange. During their admission, 45% of patients required mechanical ventilation. Complications during hospitalization were reported in 18.3% of patients, with mortality rate of 5% of all admissions. CONSLUSION: People with myasthenia gravis are commonly admitted to the intensive care unit due to myasthenic crises, however, there were minimal complications reported and a low mortality rate.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".