Emergency department (ED) visits and hospitalizations in survivors of childhood cancer in the Childhood Cancer Survivor Study.
Bibliographic record
Abstract
10056 Background: Chronic health conditions are frequent among childhood cancer survivors and lead to increased health care resource utilization. We compared rates of ED visits and hospitalizations between survivors and siblings. Methods: Analyses included 10,762 ≥5-year survivors and 2,069 siblings who completed a questionnaire from 2014-2016. We calculated ED visits and non-obstetric hospitalizations in the last 12 months per 1,000 person-years (PY) and evaluated cause-specific hospitalization rates using ICD-10 categories. Multivariable Poisson regression models evaluated predictors of survivor visits. Results: Median age in survivors and siblings was 35.3 years (interquartile range [IQR] 29.0-43.1) and 42.9 years (IQR 35.6-50.2), respectively; time from cancer diagnosis was 27.8 years (IQR 21.7-34.1). 24.2% of survivors and 16.2% of siblings had ≥1 ED visit (p < 0.001); rates were 521/1,000 PY for survivors and 246/1,000 PY for siblings (age/sex-adjusted relative rate [RR] 2.0; 95% confidence interval [CI] 1.7 - 2.3). Factors associated with increased survivor ED visits were black race (RR 1.6, CI 1.2-2.0), being obese (RR 1.4, CI 1.2-1.7) or underweight (RR 1.9, CI 1.2-3.0), female sex (RR 1.3, CI 1.1-1.5), younger age (p = 0.02) or abdomen/pelvis (RR 1.2, CI 1.1-1.4) or brain irradiation (RR 1.2, CI 1.0-1.4). 13.3% of survivors and 8.3% of siblings had ≥1 hospitalization (p < 0.001); rates were 219/1,000 PY for survivors and 130/1,000 PY for siblings (RR 1.9; CI 1.3 - 2.9). Factors associated with increased survivor hospitalizations were female sex (RR 1.3, 1.1-1.5), younger age (p < 0.0001), being obese (RR 1.3, CI 1.0-1.6) or underweight (RR 1.5, 95% CI 1.1-2.2) or platinum chemotherapy exposure (RR 1.6, CI 1.3-2.0). The most common indications for hospitalization were diseases of the digestive (21.9/1,000 PY; CI 18.7 - 25.7) and circulatory (20.9/1,000 PY; CI 17.8 – 24.4) systems. Leukemia survivors had the highest ED visit and hospitalization rates. Conclusions: Childhood cancer survivors had a 2-fold increased likelihood of an ED visit or hospitalization compared with their siblings. This increases the economic burden on survivors and the health care system.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".