Causes of early postpartum complications that result in visits to the emergency department
Bibliographic record
Abstract
OBJECTIVE: This study aimed to review the reasons why postpartum women present to the emergency department (ED) over a short term (≤10 days post-delivery) and to identify the risk factors associated with early visits to the ED. METHODS: This retrospective chart review included all women who delivered at a regional health system (William Osler Health System, WOHS) in 2018 and presented to the WOHS ED within 10 days after delivery. Baseline descriptive statistics were used to examine the patient demographics and identify the timing of the postpartum visit. Univariate tests were used to identify significant predictors for admission. A multivariate model was developed based on backward selection from these significant factors to identify admission predictors. RESULTS: There were 381 visits identified, and the average age of the patients was 31.22 years (SD: 4.83), with median gravidity of 2 (IQR: 1-3). Most patients delivered via spontaneous vaginal delivery (53.0%). The median time of presentation to the ED was 5.0 days, with the following most common reasons: abdominal pain (21.5%), wound-related issues (12.6%), and urinary issues (9.7%). Delivery during the weekend (OR 1.91, 95% CI 1.00-3.65, P = 0.05) was predictive of admission while Group B Streptococcus positive patients were less likely to be admitted (OR 0.22, CI 0.05-0.97, P<0.05). CONCLUSIONS: This was the first study in a busy community setting that examined ED visits over a short postpartum period. Patient education on pain management and wound care can reduce the rate of early postpartum ED visits.
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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 | 0.004 |
| 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 | 0.000 |
| 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".