Kawasaki disease in Kenya and review of the African literature
Bibliographic record
Abstract
BACKGROUND: Kawasaki disease has been described across the globe, although publications from Africa are limited. To our knowledge, there are no publications on Kawasaki disease from Kenya, which triggered this report. METHODS: A retrospective cross-sectional study was undertaken to identify in-patients with a discharge diagnosis of Kawasaki disease, over 2 different 5-year periods, at two pediatric hospitals in Nairobi, Kenya. We reviewed the medical records of all patients and report their clinical findings, diagnostic workup and treatment. In addition, we undertook a detailed review of the literature. RESULTS: Twenty-three patients with Kawasaki disease were identified, of those 12 (52.2%) had incomplete disease. The mean age was 2.3 years (SD+/-2.2) (range 0.3-10.3) with a male to female ratio of 1:1. The mean duration of fever at diagnosis was 8.3 days (SD+/-4.7) (range 2-20). Oral changes were the most common clinical feature and conjunctivitis the least common. Thrombocytosis at diagnosis was seen in 52% (12/23). Twenty-one patients (91.3%) were treated with intravenous immunoglobulin and all except 1 received aspirin. Baseline echocardiograms were performed in 95.7% (22/23) and found to be abnormal in 3 (13.6%). Follow-up data was limited. Our literature review identified 79 publications with documented cases of Kawasaki disease in children from 22 countries across the African continent with a total of 1115 patients including those from this report. Only 153 reported cases, or 13.7%, are from sub-Saharan Africa. CONCLUSIONS: This is the first publication on Kawasaki disease from Kenya and one of the largest reports from sub-Saharan Africa. It is the first to have a complete review of the number of published cases from the African continent. Challenges in the diagnosis and management of Kawasaki disease in many African countries include disease awareness, infectious confounders, access and cost of intravenous immunoglobulin, access to pediatric echocardiography and follow-up. Increasing awareness and health care resources are important for improving outcomes of Kawasaki disease in Africa.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.019 | 0.021 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".