Incidence and risk factors for severe preeclampsia, hemolysis, elevated liver enzymes, and low platelet count syndrome, and eclampsia at preterm and term gestation: a population-based study
Bibliographic record
Abstract
BACKGROUND: The majority of previous studies on severe preeclampsia, eclampsia, and hemolysis, elevated liver enzymes, and low platelet count syndrome were hospital-based or included a relatively small number of women. Large, population-based studies examining gestational age-specific incidence patterns and risk factors for these severe pregnancy complications are lacking. OBJECTIVE: This study aimed to assess the gestational age-specific incidence rates and risk factors for severe preeclampsia, hemolysis, elevated liver enzymes, and low platelet count syndrome, and eclampsia. STUDY DESIGN: We carried out a retrospective, population-based cohort study that included all women with a singleton hospital birth in Canada (excluding Quebec) from 2012 to 2016 (N=1,078,323). Data on the primary outcomes (ie, severe preeclampsia, hemolysis, elevated liver enzymes, and low platelet count syndrome, and eclampsia) were obtained from delivery hospitalization records abstracted by the Canadian Institute for Health Information. A Cox regression was used to assess independent risk factors (eg, maternal age and chronic comorbidity) for each primary outcome and to assess differences in the effects at preterm vs term gestation (<37 vs ≥37 weeks). RESULTS: The rates of severe preeclampsia (n=2533), hemolysis, elevated liver enzymes, and low platelet count syndrome (n=2663), and eclampsia (n=465) were 2.35, 2.47, and 0.43 per 1000 singleton pregnancies, respectively. The cumulative incidence of term-onset severe preeclampsia was lower than that of preterm-onset severe preeclampsia (0.87 vs 1.54 per 1000; rate ratio, 0.57; 95% confidence intervals, 0.53-0.62), the rates of hemolysis, elevated liver enzymes, and low platelet count syndrome were similar (1.32 vs 1.23 per 1000; rate ratio, 0.93; 95% confidence interval, 0.86-1.00), and the preterm-onset eclampsia rate was lower than the term-onset rate (0.12 vs 0.33 per 1000; rate ratio, 2.64; 95% confidence interval, 2.16-3.23). For each primary outcome, chronic comorbidity and congenital anomalies were stronger risk factors for preterm- vs term-onset disease. Younger mothers (aged <25 years) were at higher risk for severe preeclampsia at term and for eclampsia at all gestational ages, whereas older mothers (aged ≥35 years) had elevated risks for severe preeclampsia and hemolysis, elevated liver enzymes, and low platelet count syndrome. Regardless of gestational age, nulliparity was a risk factor for all outcomes, whereas socioeconomic status was inversely associated with severe preeclampsia. CONCLUSION: The risk for severe preeclampsia declined at term, eclampsia risk increased at term, and hemolysis, elevated liver enzymes, and low platelet count syndrome risk was similar for preterm and term gestation. Young maternal age was associated with an increased risk for eclampsia and term-onset severe preeclampsia. Prepregnancy comorbidity and fetal congenital anomalies were more strongly associated with severe preeclampsia, hemolysis, elevated liver enzymes, and low platelet count syndrome, and eclampsia at preterm gestation.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| 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".