The Ethics of Caring for Pregnant Patients with CKD: A Scoping Review
Bibliographic record
Abstract
Background: Physicians must consider many ethical principles when managing patients with chronic disease before and during pregnancy. An ethical framework could guide joint decision making between physicians and their patients, but does not currently exist. Methods: We performed a scoping literature review to explore the ethical considerations associated with pregnancy in patients with chronic disease. We searched for articles published between 1975 and 2019 using the terms “Ethics” and “High risk Pregnancy/Pregnancy” along with 29 chronic disease-specific MeSH terms (e.g. scleroderma, diabetes, cystic fibrosis). Results: We identified 968 articles and excluded 947 based on their title or abstract. 12 full text articles were included in the final scoping review representing discussions, case reports, and literature reviews on the ethics of high-risk pregnancy in 8 chronic diseases. The extracted data were examined and integrated into analyses of clinical cases in order to develop recommendations for ethically caring for this patient population. Conclusions: Physicians have an ethical duty to their patients to facilitate autonomous decision-making and informed consent. Secondarily, they have a duty to protect the fetus and to use resources judiciously as long as it does not negatively impact the care they provide to their patient.
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 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 | 0.019 | 0.083 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| 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".