Severe Maternal Morbidity and Risk of Mortality Beyond the Postpartum Period
Bibliographic record
Abstract
OBJECTIVE: To examine long-term risks of mortality after a pregnancy complicated by severe maternal morbidity. METHODS: We analyzed a longitudinal cohort of 1,229,306 women who delivered in the province of Quebec, Canada from 1989 through 2016. Severe maternal morbidity included conditions such as cerebrovascular accidents, acute renal failure, severe preeclampsia, and other life-threatening complications. The outcome was in-hospital mortality after the last pregnancy, categorized as postpartum (42 days or fewer after delivery) and long-term (43 days to 29 years after delivery). We estimated hazard ratios (HRs) ofr mortality with 95% CI for severe maternal morbidity compared with no severe morbidity, using Cox regression models adjusted for maternal characteristics. RESULTS: Severe maternal morbidity occurred in 2.9% of women. The mortality rate associated with severe maternal morbidity was 0.86 per 1,000 person-years compared with 0.41 per 1,000 person-years for no morbidity. Compared with no morbidity, severe maternal morbidity was associated with two times the rate of death any time after delivery (95% CI 1.81-2.20). Severe cardiac complications (HR 7.00, 85% CI 4.94-9.91), acute renal failure (HR 4.35, 95% CI 2.66-7.10), and cerebrovascular accidents (HR 4.03, 95% CI 2.17-7.48) were the leading morbidities associated with mortality after 42 days. CONCLUSION: Women who experience severe maternal morbidity have an accelerated risk of mortality beyond the postpartum period compared with women who do not experience severe morbidity. More intensive clinical follow-up may be merited for women with serious pregnancy complications.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 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".