Sex Hormone Status in Women With Chronic Kidney Disease: Survey of Nephrologists’ and Renal Allied Health Care Providers’ Perceptions
Bibliographic record
Abstract
Background: Chronic kidney disease (CKD) in reproductive-age women is accompanied by menstrual and fertility disorders and premature menopause. Objective: We sought to determine nephrologists’ and allied health care providers’ perceptions on management of sex hormone status in women with CKD. Methods: An anonymous, Internet-based survey was sent to nephrology society members from Canada, Australia, New Zealand, and the United Kingdom, and the Canadian Association of Nephrology Nurses and Technologists (February-November 2015). We assessed reported perceptions and management of sex hormone status in women with CKD. Results: One hundred seventy-five nephrologists (21% response rate) and 121 allied health care providers (30%; 116 nurses, 5 pharmacists) responded. Sixty-eight percent of nephrologists and 46% of allied providers were between the ages of 30 and 50 years, and 38% of nephrologists and 89% of allied workers were female. Ninety-five percent of nephrologists agreed that kidney function impacts sex hormone status, although only a minority of nephrologists reported often discussing fertility (35%, female vs male nephrologists, P = .06) and menstrual irregularities with their patients (15%, female vs male nephrologists, P = .02). Transplant nephrologists reported discussing fertility more often than did nontransplant nephrologists (53% vs 30%, P = .03). Physicians were more likely to report discussing fertility (33% vs 7.5%, P < .001) and menstrual irregularities (15% vs 9%, P = .04) with patients than allied health care providers. Forty-three percent of physicians reported uncertainty about the role for postmenopausal hormone therapy in women with CKD. Conclusion: Nephrologists and allied health care providers recognize an impact of CKD on sex hormones in women but report not frequently discussing sex hormone–related issues with patients. Our international survey highlights an important knowledge gap in nephrology.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".