Associations of Estradiol With Mortality and Health Outcomes in Patients Undergoing Hemodialysis: A Prospective Cohort Study
Bibliographic record
Abstract
Background:Both lower and higher estradiol (E2) levels have been associated with increased mortality among women with kidney failure. However, robust data are still lacking.Objective:We investigated the interaction of diabetes and age on linear and nonlinear associations between E2 levels, adverse outcomes, and health-related quality of life (HRQOL) in Canadian women undergoing hemodialysis (HD).Design:Population-based cohort study; data from Canadian Kidney Disease Cohort Study (CKDCS).Setting & patients:A total of 427 women undergoing HD enrolled in the CKDCS.Measurements:Baseline E2 (in pmol/L) and E2 tertiles (<38 pmol/L, 38-95 pmol/L, >95 pmol/L).Methods:Cox-proportional hazards used for all-cause and cardiovascular disease (CVD) mortality. Fine-Gray models used for incident CVD. Mixed models used for Health Utilities Index Mark 3 (HUI3), Kidney Disease Quality of Life Physical Component Scores (KDQOL12-PCS), and Mental Component Scores (KDQOL12-MCS).Results:Over a median follow-up of 3.6 (interquartile range [IQR]: 1.6-7.5) years, 250 (58.6%) participants died; 74 deaths (29.6%) were CV-related. Among 234 participants without prior CV events, 80 (34.2%) had an incident CVD event. There were no significant linear associations between E2 and all-cause mortality, CVD mortality, and incident CVD. However, E2 showed a significant concave association with all-cause mortality, but not with CVD mortality and incident CVD. Among patients aged ≥63 years, higher E2 levels were associated with lower HUI3 scores, mean difference (MD) = –0.062 per 1 – SD pmol/L, 95% confidence interval (CI) = –0.112 to –0.012, but the opposite was observed in younger patients (<63 years) in whom higher E2 levels were associated with higher HUI3 scores (MD = 0.032 per 1 – SD pmol/L, 95% CI = 0.008-0.055), Pinteraction = .045. No associations were observed among E2, KDQOL12-PCS (MD = –0.15 per 1 – SD pmol/L, 95% CI = –1.15 to 0.86), and KDQOL12-MCS (MD = –0.63 per 1 – SD pmol/L, 95% CI = –1.82 to 0.57).Limitations:Unmeasured confounding and small sample size.Conclusions:The association between E2 and all-cause mortality may be nonlinear, while no association was observed for CVD mortality, incident CVD, KDQOL12-PCS, and KDQOL12-MCS. Furthermore, the association between serum E2 and HUI3 was modified by age: Higher levels were associated with higher utility among women aged <63 years and the converse observed among older women.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".