Gestational Hypertension and Preeclampsia in Living Kidney Donors
Bibliographic record
Abstract
BACKGROUND: Young women wishing to become living kidney donors frequently ask whether nephrectomy will affect their future pregnancies. METHODS: We conducted a retrospective cohort study of living kidney donors involving 85 women (131 pregnancies after cohort entry) who were matched in a 1:6 ratio with 510 healthy nondonors from the general population (788 pregnancies after cohort entry). Kidney donations occurred between 1992 and 2009 in Ontario, Canada, with follow-up through linked health care databases until March 2013. Donors and nondonors were matched with respect to age, year of cohort entry, residency (urban or rural), income, number of pregnancies before cohort entry, and the time to the first pregnancy after cohort entry. The primary outcome was a hospital diagnosis of gestational hypertension or preeclampsia. Secondary outcomes were each component of the primary outcome examined separately and other maternal and fetal outcomes. RESULTS: Gestational hypertension or preeclampsia was more common among living kidney donors than among nondonors (occurring in 15 of 131 pregnancies [11%] vs. 38 of 788 pregnancies [5%]; odds ratio for donors, 2.4; 95% confidence interval, 1.2 to 5.0; P=0.01). Each component of the primary outcome was also more common among donors (odds ratio, 2.5 for gestational hypertension and 2.4 for preeclampsia). There were no significant differences between donors and nondonors with respect to rates of preterm birth (8% and 7%, respectively) or low birth weight (6% and 4%, respectively). There were no reports of maternal death, stillbirth, or neonatal death among the donors. Most women had uncomplicated pregnancies after donation. CONCLUSIONS: Gestational hypertension or preeclampsia was more likely to be diagnosed in kidney donors than in matched nondonors with similar indicators of baseline health. (Funded by the Canadian Institutes of Health Research and others.).
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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 | 0.000 |
| 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".