Abstract O.53: Occult Coronary Artery Dilatation: An Unrecognized Category Of Coronary Involvement
Bibliographic record
Abstract
Background: The current definition of Coronary artery dilatation (CAD), Z-score >2.5, in KD may omit patients at higher risk of later complications. We propose a category of occult CAD with a Z-score variation ≥ 2 for the same CA on 2 different echocardiograms, but absolute Z-score < 2.5. We compared this new category with cases of CAD and normal CA. >Method: A retrospective review included 337 patients diagnosed with KD in our institution. Echographic data were retrieved for the fist year following diagnosis. Patients were classified in three categories: definite CA dilatation (dCAD) with Z-score ≥ 2.5, occult CA dilatation (oCAD) and normal CA (nCA). We compared inflammatory profile, IVIG treatment resistance, and timing of CA involvement. Results: There were 26.3% patients with nCA, 32.2% with oCAD and 41.1% with dCAD.Patients with KD incomplete diagnostic criteria represented 35%, 14% and 17% for NCAD, OCAD and DCAD groups respectively (p=0.008). Median time for CAD was 7 and 9.5 days for dCAD and oCAD respectively (p=0.2). A Jonckheere trend test identified a progression of inflammatory parameters through the three groups for Platelet count (p< 0.001), Albumin (p = 0.007), ESR (p = 0.04), but not for CRP (p = 0.76) and WBC (p = 0.16). There was a significant difference in treatment resistance, with 5%, 19% and 31% for NCAD, OCAD and DCAD respectively (p=0,002). Conclusion: OCAD group appears like a distinctive subgroup of KD patients showing intermediate inflammatory profiles and treatment respond in the NCAD to DCAD spectrum. Recent Z-score equations, more accurate for young patients’ CA size than former linear equations, may explain the high incidence of dCAD in this report. Further studies are needed to define the profile and propensity to complications of this subpopulation.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".