Characteristics and outcomes among pregnant women with end-stage renal disease on hemodialysis
Bibliographic record
Abstract
PURPOSE: Pregnancy among women with end-stage renal disease (ESRD) has risen in frequency, which may be attributed to improvements in hemodialysis care. Our objective was to describe baseline characteristics and pregnancy outcomes among women with ESRD on hemodialysis. METHODS: Using the United States' Healthcare Cost and Utilization Project-Nationwide Inpatient Sample, we created a cohort of women with ESRD on hemodialysis who gave birth between 2005 and 2015. We determined the proportion of adverse maternal and neonatal outcomes among this cohort. Then, we created a composite measure of vascular-mediated adverse pregnancy outcomes. Women who experienced at least one of either preeclampsia, intrauterine growth restriction, or intrauterine fetal death were categorized as having the composite measure. Then, multivariate regression models were used to estimate the associations between maternal baseline demographic and clinical characteristics and the composite measure. RESULTS: Among 8,765,973 deliveries between 2005 and 2015, 307 were to women with ESRD on hemodialysis. Over the study period, the incidence of pregnancies to women with ESRD increased from 0.47 to 5.76/100,000 births. An estimated 28% of pregnancies were complicated by preeclampsia, 8% by placental abruption, 58% delivered by cesarean, and in the postpartum, 28% required blood transfusions and 6% experienced sepsis. About 45% of babies were born preterm and 14% had IUGR. The composite measure of adverse events was not found to be associated with any baseline maternal characteristics. CONCLUSIONS: The frequency of pregnant women with ESRD on hemodialysis has risen, with adverse pregnancy complications for both mother and fetus. Transfer to high-risk centers is suggested for women with ESRD.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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".