Pregnancy Outcomes in Living Kidney Donors: Protocol of a Population-Based Cohort Study in Three Canadian Provinces
Notice bibliographique
Résumé
Background: A substantial proportion of living kidney donors are women of childbearing age. Some prior studies report a higher risk of gestational hypertension and pre-eclampsia in living kidney donors compared with nondonors. Further research is needed to better quantify the risk of adverse maternal, fetal/infant, and neonatal outcomes attributable to living kidney donation. Objective: To determine the risk of hypertensive disorders of pregnancy, including gestational hypertension, pre-eclampsia, and eclampsia, and other maternal and fetal/infant outcomes in living kidney donors compared with a matched group of nondonors of similar baseline health. Design and Setting: Protocol for a population-based, matched cohort study using Canadian administrative health care databases. The protocol will be run separately in 3 provinces, Ontario, Alberta, and British Columbia, and results will be combined statistically using meta-analysis. Participants: The cohort will include women aged 18 to 48 years who donated a kidney between July 1992 and March 2022 and had at least one postdonation singleton pregnancy of ≥20 weeks gestation between January 1993 and February 2023. We expect to include at least 150 living kidney donors with over 200 postdonation pregnancies from Ontario and a similar number of donors and pregnancies across Alberta and British Columbia combined. Nondonors will include women from the general population with at least one pregnancy of ≥20 weeks gestation between January 1993 and February 2023. Nondonors will be randomly assigned cohort entry dates based on the distribution of nephrectomy dates in donors. The sample of nondonors will be restricted to those aged 18 to 48 years on their cohort entry dates with delivery dates at least 6 months after their assigned entry dates. A concern with donor and nondonor comparisons is that donors are healthier than the general population. To reduce this concern, we will also apply 30+ exclusion criteria to further restrict the nondonor group so that they have similar health measures at cohort entry as the donors. Donor and nondonor pregnancies will then be matched (1:4) on 5 potential confounders: delivery date, maternal age at delivery date, time between cohort entry and delivery date, neighborhood income quintile, and parity at delivery date. Measurements: The primary outcome will be a composite of maternal gestational hypertension, preeclampsia, or eclampsia. Secondary maternal outcomes will include components of the primary outcome, early pre-eclampsia, severe maternal morbidity, cesarean section, postpartum hemorrhage, and gestational diabetes. Fetal/infant/neonatal outcomes will include premature birth/low birth weight, small for gestational age, neonatal intensive care unit admission, stillbirth, and neonatal death. Methods: The primary unit of analysis will be the pregnancy. We will compute the risk ratio of the primary composite outcome in donors versus nondonors using a log-binomial mixed regression model with random effects to account for the correlation within women with multiple pregnancies and within matched sets of donors and nondonors. We will perform the statistical analyses within each province and then combine aggregated results using meta-analytic techniques to produce overall estimates of the study outcomes. Limitations: Due to regulations that prevent individual-level records from being sent to other provinces, we cannot pool individual-level data from all 3 provinces. Conclusion: Compared to prior studies, this study will better estimate the donation-attributable risk of adverse maternal, fetal/infant, and neonatal outcomes. Transplant centers can use the results to counsel female living donor candidates of childbearing age and to inform recommended practices for the follow-up and care of living kidney donors who become pregnant.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,015 | 0,014 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,002 |
| Méta-épidémiologie (sens large) | 0,002 | 0,003 |
| Bibliométrie | 0,003 | 0,005 |
| Études des sciences et des technologies | 0,007 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,005 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,011 | 0,002 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».