Incidence, Risk Factors, and Consequences of Amniotic Fluid Embolism
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Amniotic fluid embolism (AFE) is a rare but serious cause of maternal mortality whose aetiology remains obscure. Previous population-based studies have reported associations with labour induction and caesarean delivery. METHODS: We updated a previous analysis based on the US Nationwide Inpatient Sample from 1999 to 2008. We adapted a diagnostic validation algorithm to minimise false-positive diagnoses, along with statistical methods that account for the stratified random sampling design. RESULTS: Of the 8 571 209 deliveries recorded in the database, 276 met our case definition of AFE, of which 62 (22.9% of the 274 with known vital status) were fatal. Significant associations with AFE were observed for medical induction {adjusted odds ratio [aOR] = 1.7 [95% confidence interval (CI) 1.2, 2.5]}, caesarean delivery [aOR = 15.0; 95% CI 9.4, 23.9], instrumental vaginal delivery [aOR = 6.6; 95% CI 4.0, 11.1], and cervical/uterine trauma [aOR = 7.4; 95% CI 3.6, 14.9]. AFE was associated with increases in risk of stillbirth, hysterectomy, maternal death, and prolonged maternal length of delivery hospital stay. CONCLUSIONS: AFE remains an extremely serious obstetric complication with high risks of maternal and fetal mortality. The increased risks of AFE associated with labour induction and caesarean delivery have implications for elective use of these interventions.
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Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 it