Epidemiology of Cardiac Arrest During Hospitalization for Delivery in Canada: A Nationwide Study
Bibliographic record
Abstract
BACKGROUND: Cardiac arrest in pregnancy is a rare and devastating condition with high mortality and morbidity. The objective of this study was to generate information about maternal cardiac arrest in Canada by examining the frequency, temporal incidence, associated conditions, potential etiologies, and survival rates. METHODS: This retrospective population-based study used hospitalization data from the discharge abstract database of the Canadian Institute for Health Information relating to obstetric deliveries in Canada from April 1, 2002, to March 31, 2015. The data were accessed through the Public Health Agency of Canada's (PHAC) Canadian Perinatal Surveillance System. Cases of cardiac arrest were identified using the diagnostic and intervention codes from the International Statistical Classification of Diseases and the Canadian Classification of Health Interventions, respectively. Data on patient demographics, medical and obstetrical conditions, and potential etiologies of cardiac arrest were collected. Multivariable logistic regression analysis was used to identify conditions associated with cardiac arrest. RESULTS: There were 286 cases of maternal cardiac arrest among 3,568,597 hospitalizations for delivery during the 13-year period. A total of 204 (71.3%) women survived to hospital discharge (95% confidence interval, 65.7%-76.5%). There was no significant variation in the incidence of cardiac arrest or survival from arrest over time or across provinces. Among the pre-existing conditions, hypertensive disorders of pregnancy, gestational diabetes, malignancy, and diseases of the respiratory and nervous system were found to be significantly associated with cardiac arrest. Among the obstetrical conditions, placental abnormalities and polyhydramnios were associated with cardiac arrest. The common potential etiologies included postpartum hemorrhage, heart failure, amniotic fluid embolism, and complications of anesthesia. CONCLUSIONS: In this first Canadian study, the incidence of cardiac arrest during pregnancy was found to be 1:12,500 deliveries. The survival rate reported in our study is higher than reported previously in other countries. Our study findings contribute to better inform the development and implementation of policies and programs in an effort to prevent and manage this condition.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".