Utilization of Prenatal Services by Survivors of Childhood and Adolescent/Young Adult Cancers
Bibliographic record
Abstract
Objectives: To describe utilization of specialised prenatal care by high-risk survivors and evaluate echocardiogram use in echocardiogram-need survivors, as per survivorship guideline recommendations.\n\nMethods: Retrospective population-based matched survivor:control study utilizing Ontario health administrative data. Survivors were classified as high-risk/low-risk for obstetrical outcomes, and as echocardiogram-need (yes/no) for echocardiogram outcomes. Associations were tested using logistic regression.\n\nResults: 11% (n=363) of 3,204 pregnant survivors were classified as high-risk. Over 90% received specialized prenatal care. Living in a rural area was associated with lower use. (AOR 0.51; 95% CI 0.44-0.59). Since 2003, 32% (560/1,737) of survivors had an echocardiogram-need. Only 14% (77/560) had ≥1 echocardiogram, this was not associated with rurality nor neighbourhood income quintile.\n\nConclusions: Although the majority of high-risk survivors receive specialized prenatal care, geographic inequality in care persists. Despite survivorship guidelines, >85% of echocardiogram-need pregnant survivors do not have an echocardiogram performed; future work should address this gap in care.
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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 | 0.001 |
| 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) | 0.002 | 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".