Echocardiographic Assessment of Cardiac Function in Pediatric Survivors of Anthracycline-Treated Childhood Cancer
Bibliographic record
Abstract
BACKGROUND: Anthracycline-induced cardiotoxicity is a major cause of morbidity and mortality in childhood cancer survivors (CCSs). Echocardiographic myocardial strain imaging is recommended in adult patients with cancer, but its role in pediatric CCSs has not been well established. Aims of this study were to determine the prevalence of abnormalities in left ventricular strain in pediatric CCSs, to compare strain with other echocardiographic measurements and blood biomarkers, and to explore risk factors for reduced strain. METHODS: CCSs ≥3 years from their last anthracycline treatment were enrolled in this multicenter study and underwent a standardized functional echocardiogram and biomarker collection. Regression analysis was used to identify factors associated with longitudinal strain (LS). RESULTS: score, <-2) was found in 0.8% and 7.7% of the CCSs, respectively. LS was significantly lower in CCSs than in controls, but the absolute difference was small (0.7%). Lower LS in CCSs was associated with older current age and higher body surface area. Sex, cumulative anthracycline dose, radiotherapy, and biomarkers were not independently associated with LS. Circumferential strain, diastolic parameters, and biomarkers were not significantly different in pediatric CCSs. CONCLUSIONS: Global systolic function and LS are only mildly reduced in pediatric CCSs, and most LS values are within normal range. This makes single LS measurements of limited added value in identifying CCSs at risk for cardiac dysfunction. The utility of strain imaging in the long-term follow-up of CCS remains to be demonstrated.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".