Infections and Kawasaki Disease: Implications for Coronary Artery Outcome
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: We sought to determine the effect of coincident infection, at time of diagnosis of Kawasaki disease (KD), on treatment response and coronary artery outcome. METHODS: A single-center, retrospective study of 129 consecutive patients diagnosed with typical KD between January 1997 and December 1998 was performed. Standardized clinical assessments, laboratory, microbiology, and imaging test results plus treatment regimens were reviewed. Coronary arteries were visualized by using echocardiography, and coronary artery lesions (CALs) were reported as body surface area-adjusted z scores. Infection-positive and -negative groups were identified, and clinical, laboratory, and treatment data were analyzed. The effect of infections and other outcome variables on CAL development was determined by multivariate regression analysis. RESULTS: (1) Concurrent infections: 33% of children with typical KD had > or =1 confirmed infection at KD diagnosis. (2) Treatment response: the presence of infection did not alter the response to treatment with intravenous immunoglobulin, with resolution of fever in 83% of children after 1 dose of intravenous immunoglobulin together with aspirin administration regardless of presence or absence of infection. (3) Coronary outcome: in total, 31% of the patients developed CALs. Both the proven-infection and no-proven-infection groups had a similar CAL frequency. (4) Multivariate regression analysis: proven infection did not increase the risk of coronary artery involvement even after adjusting for other factors impacting on coronary artery outcomes. CONCLUSIONS: Infections are common at diagnosis of KD. A broad spectrum of infectious agents was found. Infections at diagnosis of KD did not affect the patients' response to treatment and coronary artery outcome when compared with those patients without infections.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 it