Incidence and risk factors of sepsis mortality in labor, delivery and after birth: Population‐based study in the USA
Bibliographic record
Abstract
AIM: Maternal sepsis is one of the leading causes of maternal mortality around the world. The aim of this study was to estimate the incidence and mortality rate of sepsis, and the associated risk factors for their development during pregnancy, labor, delivery and the post-partum period. METHODS: We conducted a population-based cohort study consisting of 5 million births that occurred in the USA. Data were obtained from the Healthcare Cost and Utilization Project-Nationwide Inpatient Sample (HCUP-NIS) database from 1998 to 2008. Logistic regression was used to calculate the adjusted odds ratio and corresponding 95% confidence intervals (95%CI) for sepsis development and sepsis-related death during admission for delivery. RESULTS: The overall incidence of maternal sepsis was 29.4 per 100 000 births (95%CI: 28.0-30.9) with a sepsis case fatality rate of 4.4 per 100 births (95%CI: 3.5-5.6). Both the incidence of maternal sepsis and sepsis-related death rate have increased over the last decade. Women who are black, older than 35 years and who smoke were more likely to experience maternal sepsis. An association was also found between maternal sepsis and diabetes mellitus, cardiovascular disease, eclampsia, preterm birth, hysterectomy, puerperal infection, post-partum hemorrhage, transfusion and chorioamnionitis. CONCLUSIONS: Mortality from maternal sepsis during labor and delivery is an increasing and important problem in westernized countries. Initiatives aimed at improving early recognition and effective management may help reduce the occurrence and outcomes of maternal sepsis at time of labor and delivery.
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How this classification was reachedexpand
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 | 0.003 | 0.003 |
| 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".