Uncovering possible silent acquired long <scp>QT</scp> syndrome using exercise stress testing in long‐term pediatric acute lymphoblastic leukemia survivors
Bibliographic record
Abstract
Abstract An example of chemotherapy‐induced cardiotoxicity in cancer survivors is acquired long QT syndrome (aLQTS), which may cause serious yet preventable life‐threatening consequences. Our objective was to identify and characterize childhood acute lymphoblastic leukemia (ALL) survivors with possible aLQTS using maximal exercise testing. In this cross‐sectional study with exploratory analysis, a total of 250 childhood ALL survivors were evaluated for abnormal QT interval prolongation using the McMaster cycle exercise test. A total of 198 survivors (102 males; 96 females), having reached their peak (mean 32.1 ± 8.4 mL/kg/min; range 15.5–57.8 mL/kg/min), were included in our analyses. Two survivors were excluded for possible congenital LQTS. QT intervals were corrected for heart rate using the Bazett, Fridericia, and Rautaharju formulas at rest (supine, sitting, and standing positions), at the end of each stage of the CPET, and at 1, 3, and 5 minutes into the recovery period. The corrected QT (QTc) of borderline (n = 37) and long QT survivors (n = 20) was significantly longer than normal survivors (n = 141) at rest, exercise, and recovery. Out of 57 survivors presenting an abnormal QTc prolongation, 40 survivors (70%) showed no QT interval anomalies at rest but developed various anomalies during exercise. No significant differences were found between the groups for any of the measured clinical characteristics or cardiac parameters. The standardization of exercise testing in the regular follow‐up of oncology patients is necessary for appropriate cardiac prevention and surveillance to enhance the health and quality of life of the ever‐increasing number of cancer survivors.
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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 | 0.000 | 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) | 0.001 | 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".