Hormone therapy and clinical and surrogate cardiovascular endpoints in women with chronic kidney disease: a systematic review and meta-analysis
Bibliographic record
Abstract
OBJECTIVE: Women with chronic kidney disease (CKD) experience kidney dysfunction-mediated premature menopause. The role of postmenopausal hormone therapy (HT) in this population is unclear. We sought to summarize current knowledge regarding use of postmenopausal HT and cardiovascular (CV) outcomes, and established surrogate measures of CV risk in women with CKD. METHODS: This is a systematic review and meta-analysis of adult women with CKD. We searched electronic bibliographic databases (MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials) (inception to 2014 December), relevant conference proceedings, tables of contents of journals, and review articles. Randomized controlled trials and observational studies examining postmenopausal HT compared with either placebo or untreated control groups were included. The intervention of interest was postmenopausal HT, and the outcome measures were all-cause and CV mortality, nonfatal CV event (myocardial infarction, stroke), and surrogate measures of CV risk (serum lipids, blood pressure). RESULTS: Of 12,482 references retrieved, four randomized controlled trials and two cohort studies (N = 1,666 participants) were identified. No studies reported on CV outcomes or mortality. Compared with placebo, postmenopausal HT was associated with decreased low-density lipoprotein cholesterol (-13.2 mg/dL [95% CI, -23.32 to -3.00 mg/dL]), and increased high-density lipoprotein (8.73 mg/dL [95% CI, 4.72-12.73 mg/dL]) and total cholesterol (7.96 mg/dL [95% CI, 0.07-15.84 mg/dL]). No associations were observed between postmenopausal HT triglyceride levels and blood pressure. CONCLUSIONS: Studies examining the effect of postmenopausal HT on CV outcomes in women with CKD are lacking. Further prospective study of the role of postmenopausal HT in this high-risk group is required.
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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 | 0.010 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.028 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".