Temporal trends in severe morbidity and mortality associated with ectopic pregnancy requiring hospitalisation in Washington State, USA: a population-based study
Bibliographic record
Abstract
OBJECTIVE: To examine temporal trend in maternal mortality/severe morbidity associated with hospitalisation due to ectopic pregnancy. DESIGN: A population-based observational study. SETTING AND PARTICIPANTS: All women hospitalised for ectopic pregnancy in Washington State, USA, 1987-2014 (n=20 418). The main composite outcome of severe morbidity/mortality included death, sepsis, need for transfusion, hysterectomy and systemic or organ failure, identified by diagnostic and procedure codes from hospitalisation files. Severe morbidity/mortality due to ectopic pregnancy were expressed as incidence ratios among women of reproductive age (15-64 years) and among women hospitalised for ectopic pregnancy. Comparisons were made between 1987-1991 (reference) and 2010-2014 using ratios of incidence ratios (RR) and ratio differences (RD). The Cochran-Armitage test for trend assessed statistical significance; logistic regression was used to obtain adjusted OR (AOR) and 95% CI, adjusted for demographic factors and comorbidity. RESULTS: Hospitalisation for ectopic pregnancy declined from 0.89 to 0.16 per 1000 reproductive age women between 1987-1991 and 2010-2014 (p<0.001). Among reproductive age women, ectopic pregnancy mortality remained stable (0.03 per 100 000); and mortality/severe morbidity increased among women aged 25-34 years (p=0.022). Among women hospitalised for ectopic pregnancy, mortality increased from 0.29 to 1.65 per 1000 between 1987-1991 and 2010-2015 (p=0.06); severe morbidity/mortality increased from 3.85% to 19.63% (RR=5.10, 95% CI 4.36 to 5.98; RD=15.78 per 100 women, 95% CI 13.90 to 17.66; AOR for 1-year change was 1.08, 95% CI 1.07 to 1.08). CONCLUSIONS: Hospitalisation for ectopic pregnancy declined in Washington State, USA, between 1987 and 2014; however, mortality/severe morbidity associated with ectopic pregnancy increased in female population aged 25-34 years.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".