Concurrent Emergency Department Use by a New Mother With a Disability and Her Newborn
Bibliographic record
Abstract
OBJECTIVES: To assess the risk of concurrent emergency department use (Co-ED) among women with a preexisting disability and their infants. METHODS: This population-based cohort study was completed in Ontario, Canada. Included were all mother-infant pairs with a hospital delivery, 2008-2023. Those with a maternal physical (N = 152 171), sensory (N = 54 716), or intellectual/developmental (N = 2913) disability or multiple disabilities (N = 11 800) were compared with those with no disability (N = 1 548 178). Multinomial logistic regression-generated odds ratios (ORs) and 95% CI for Co-ED (ie, mother and infant both had emergency department (ED) visits within 90 days after hospital discharge), a maternal ED visit only, or an infant ED visit only were calculated, each vs no ED visit. Models were adjusted for maternal age, parity, income quintile, rurality, immigration status, and delivery year. RESULTS: Co-ED was more likely among women with (5.4%) than without (3.4%) a disability (adjusted OR [aOR], 1.66; 95% CI, 1.62-1.71). The median number of days between the first maternal and first infant ED visit was 19 (IQR, 4-41) days, and 18.3% occurred within 24 hours of each other. The aOR for maternal ED visit alone was 1.38 (95% CI, 1.35-1.40) and 1.20 (95% CI, 1.19-1.22) for an infant ED visit alone. CONCLUSIONS: Co-ED was an important outcome for all mother-infant pairs, particularly so for mothers with a disability, of whom about 1 in 20 experienced Co-ED. These dyads may benefit from careful postdischarge planning during the birth hospital stay and enhanced outpatient health 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 | 0.002 |
| 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 | 0.001 | 0.000 |
| 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".