Epidemiologic and clinical characteristics of multisystem inflammatory syndrome in adults: a rapid review
Bibliographic record
Abstract
Multisystem inflammatory disease in children (MIS-C) is one of the severe presentations of the coronavirus disease 2019 (COVID-19) that has been described in the literature since the beginning of the pandemic. Although MIS-C refers to children, cases with similar clinical characteristics have been recently described in adults. A description of the epidemiologic and clinical characteristics of multisystem inflammatory disease in adults (MIS-A) is a starting point for better knowledge and understanding of this emerging disease. We identified nine case reports of MIS-A in the literature, five from the United States, two from France and two from the United Kingdom. The case descriptions revealed similarities in clinical features, including occurrence during post-acute disease phase, fever, digestive symptoms, cardiac involvement and elevated inflammatory markers. All the patients were hospitalized, three required admission to the intensive care unit and one died. The most common treatments were intravenous immunoglobulin, prednisolone and aspirin. These findings suggest that MIS-A is a severe complication of COVID-19 disease that can lead to death. Further studies to improve our understanding of the pathogenesis of MIS-A, which will help improve treatment decisions and prevent sequelae or death.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".