Gestational Hypertension and Preeclampsia in Living Kidney Donors
Bibliographic record
Abstract
Currently, the majority of living kidney donors are women, and these young-women donors are often concerned about the possible effect of kidney donation on future pregnancies. Animal studies have shown evidence of higher blood pressure and urinary protein excretion in animals with 1 kidney compared with animals with 2. However, human studies that have compared donors with healthy nondonors during pregnancy have yielded conflicting results. In this retrospective, matched-cohort study, the authors compared kidney donors to matched, healthy nondonors with regard to risk of developing gestational hypertension or preeclampsia, as well as other maternal and fetal outcomes. They used databases in Ontario to compare pregnancy outcomes in 85 eligible women who donated a kidney between 1992 and 2010 with 510 healthy, nondonors. Baseline characteristics compared were age at the time of cohort entry, urban or rural location, income, the number of pregnancies at 20 weeks’ gestation at cohort entry, and time to first pregnancy after cohort entry. The primary outcome was obtained from diagnostic codes for gestational hypertension or preeclampsia; secondary outcomes examined more specifically other maternal and fetal outcomes. Over an approximately 11-year period, 595 women were followed up through their pregnancies. Donors and nondonors had the same number of doctor visits during pregnancy, but gestational hypertension or preeclampsia was higher among donors (11% vs 5%; odds ratio for donors, 2.4; 95% confidence interval, 1.2–5.0; P = 0.01). Secondary outcomes revealed no significant difference in the rate of preterm birth (8% vs 7%) and low birth weight (6% vs 4%). There were no reports of miscarriage, stillbirth, or maternal death in either group. The risks of gestational hypertension or preeclampsia are higher in kidney donors than in nondonors with similar baseline health.
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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 | 0.001 | 0.048 |
| 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) | 0.000 | 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".