Caring for Pregnant Patients With CKD---An Ethical Discussion of 5 Cases
Bibliographic record
Abstract
INTRODUCTION: Pregnancy planning in patients with chronic kidney disease can result in ethical conflicts due to the potential for adverse outcomes. Traditionally, many nephrologists have advised their patients to avoid pregnancy altogether; however, this approach is paternalistic and not patient-centered. An ethical framework could guide joint decision-making between physicians and their patients, but this does not currently exist. METHODS: We performed a literature search to identify the ethical considerations associated with this patient population. We searched for articles published between 1975 and 2019 using the terms "ethics" and "high risk pregnancy," along with 29 chronic disease-specific MeSH terms. Subsequently, we performed a critical evaluation using established ethical theories and adapted anonymized clinical cases from the Pregnancy in Kidney Disease Clinic (PreKid Clinic) at our institution to guide the discussion. RESULTS: We identified 968 articles and excluded 947 based on their title or abstract. Twelve full-text articles were included, representing discussions, case reports, and literature reviews on the ethics of pregnancy in 8 chronic diseases. The extracted data were applied to 5 clinical cases to guide the discussion. CONCLUSIONS: This clinical review focuses on 3 main ethical themes: duty to patient, duty to the fetus, and duty to society, to help physicians explore common scenarios that may arise when counseling patients around pregnancy. Primarily, physicians have a duty to facilitate autonomous decision-making and informed consent. Secondarily, they have a duty to protect the fetus and use resources judiciously as long as it does not impact the care of their patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".