Importance of anatomical dominance in the evaluation of coronary dilatation in Kawasaki disease
Bibliographic record
Abstract
Introduction In Kawasaki disease, although coronary dilatation is attributed to vasculitis, the effect of myocardial inflammation is underestimated. Coronary dilatations are determined by Z-scores, which do not take into account dominance. The aim of the present study was to describe the impact of coronary dominance on dilatation in Kawasaki disease. METHODS: We performed a retrospective analysis of coronary dilatations according to angiography categorisation of dominance. RESULTS: Of 28 patients (2.6 [0.2-10.1] years), right dominance was present in 15 patients and left in 13. Early dilatation was present in all patients, of whom 11 were ipsilateral to the dominant segment and 17 contralateral. Ipsilateral dilatations were present at diagnosis (9/11 versus 6/17, p=0.02) compared with contralateral dilatations, which developed 2 weeks after diagnosis (9/11 versus 16/17, p=0.29). Coronary artery Z-scores of patients with contralateral dilatation increased at 2 weeks, before returning to baseline values (2.0±2.2 at diagnosis, 4.1±1.8 at 2 weeks, 1.8±1.2 at 3-6 months, p=0.001), compared with patients with ipsilateral dilatation in whom Z-scores were maximal at diagnosis and remained stable (3.0±0.9, 2.7±1.1 and 2.6±1.5, respectively, p=0.13). Dominant coronary artery Z-scores were higher compared with non-dominant segments at diagnosis (3.0±0.9 versus 1.0±0.8, p<0.001) and at late follow-up (2.6±1.5 versus 0.4±1.4, p=0.002) in patients with ipsilateral dilatation. CONCLUSION: Progression of coronary dilatation after diagnosis may be a sign of dilatation secondary to vasculitis, as opposed to regression of Z-scores in ipsilateral dilatations, probably related to physiological vasodilatation in response to carditis. This needs to be validated in larger studies against vasculitic and myocardial inflammatory markers.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".