Epidemiology, Clinical Features, and Outcomes of Multisystem Inflammatory Syndrome in Children (MIS-C) and Adolescents—a Live Systematic Review and Meta-analysis
Bibliographic record
Abstract
Purpose of Review: A multisystem inflammatory condition occurring in children and adolescents with COVID-19 has become increasingly recognized and widely studied globally. This review aims to investigate and synthesize evolving evidence on its clinical characteristics, management, and outcomes in pediatric patients. Recent Findings: We retrieved data from PubMed, EMBASE, Cochrane Library, WHO COVID-19 Database, Google Scholar, and preprint databases, covering a timeline from December 1, 2019, to July 31, 2021. A total of 123 eligible studies were included in the final descriptive and risk factor analyses. We comprehensively reviewed reported multisystem inflammatory syndrome in children (MIS-C) cases from published and preprint studies of various designs to provide an updated evidence on epidemiology, clinical, laboratory and imaging findings, management, and short-term outcomes. Latest evidence suggests that African black and non-Hispanic white are the two most common ethnic groups, constituting 24.89% (95% CI 23.30-26.48%) and 25.18% (95% CI 23.51-26.85%) of the MIS-C population, respectively. Typical symptoms of MIS-C include fever (90.85%, 95% CI 89.86-91.84%), not-specified gastrointestinal symptoms (51.98%, 95% CI 50.13-53.83%), rash (49.63%, 95% CI 47.80-51.47%), abdominal pain (48.97%, 95% CI 47.09-50.85%), conjunctivitis (46.93%, 95% CI 45.17-48.69%), vomiting (43.79%, 95% CI 41.90-45.68%), respiratory symptoms (41.75%, 95% CI 40.01-43.49%), and diarrhea (40.10%, 95% CI 38.23-41.97%). MIS-C patients are less likely to develop conjunctivitis (OR 0.27, 95% CI 0.11-0.67), cervical adenopathy (OR 0.21, 95% CI 0.07-0.68), and rash (OR 0.44, 95% CI 0.26-0.77), in comparison with Kawasaki disease patients. Our review revealed that the majority of MIS-C cases (95.21%) to be full recovered while only 2.41% died from this syndrome. We found significant disparity between low- and middle-income countries and high-income countries in terms of clinical outcomes. Summary: MIS-C, which appears to be linked to COVID-19, may cause severe inflammation in organs and tissues. Although there is emerging new evidence about the characteristics of this syndrome, its risk factors, and clinical prognosis, much remains unknown about the causality, the optimal prevention and treatment interventions, and long-term outcomes of the MIS-C patients. Supplementary Information: The online version contains supplementary material available at 10.1007/s40124-022-00264-1.
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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 | 0.008 | 0.027 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.022 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".