Pregnancy in Patients Receiving Home Dialysis
Bibliographic record
Abstract
Pregnancy is an important goal for many women with CKD or kidney failure, but important barriers exist, particularly as CKD stage progresses. Women with advanced CKD often have a limited fertility window and may miss their opportunity for a pregnancy if advised to defer until after kidney transplantation. Pregnancy rates in women with advanced kidney failure or receiving dialysis remain low, and despite the improved outcomes in recent years, these pregnancies remain high risk for both mother and baby with high rates of preterm birth due to both maternal and fetal complications. However, with increased experience and advances in models of care, this paradigm may be changing. Intensive hemodialysis regimens have been shown to improve both fertility and live birth rates. Increasing dialysis intensity and individualizing dialysis prescription to residual renal function, to achieve highly efficient clearances, has resulted in improved live birth rates, longer gestations, and higher birth weights. Intensive hemodialysis regimens, particularly nocturnal and home-based dialysis, are therefore a potential option for women with kidney failure desiring pregnancy. Global initiatives for the promotion and uptake of home-based dialysis are gaining momentum and may have advantages in this unique patient population. In this article, we review the epidemiology and outcomes of pregnancy in hemodialysis and peritoneal dialysis recipients. We discuss the role home-based therapies may play in helping women achieve more successful pregnancies and outline the principles and practicalities of management of dialysis in pregnancy with a focus on delivery of home modalities. The experience and perspectives of a patient are also shared.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".