Sex, Gender, and Quality of Life in Hemodialysis
Bibliographic record
Abstract
Background: Women with kidney failure treated with hemodialysis (HD) report lower quality of life (QoL) compared to men. Decreasing HD frequency is a potential strategy to improve QoL but may result in undertreatment of females compared to males due to biological differences in body water distribution. Methods: Individuals initiating HD in Alberta, Canada were recruited. Sex assigned at birth (SAAB) and gender identity were self-reported and gender score, a measure of social expectations and norms typically associated to a given gender, was calculated using the GENESIS-PRAXY scale. The primary outcomes were the change in Kidney Disease Quality of Life 36 physical (PCS) and mental component scores (MCS) at 3 months, validated markers of mortality, stratified by HD dose (3 vs 2 sessions/week). The associations between SAAB, gender score and change in PCS and MCS by HD dose were measured using non-parametric test and multiple linear regression, respectively. Results: There were 33 participants on 3x/wk HD (14 female, 19 male) and 27 on 2x/wk (12 female, 15 male). PCS increased with 3x/wk (p=0.010) but not 2x/wk (p=0.521) in females, but no differences were observed in MCS. No changes were observed in PCS or MCS in males, irrespective of HD dose. Gender score was positively associated with change MCS on 2x/wk HD (p=0.049) but not 3x/wk HD (p=0.102). While gender score was not associated with change in PCS, HD dose modified the relationship (p=0.035). Conclusions: Higher HD dose was associated with improved physical health in females, but lower HD dose was associated with improved mental health in participants with roles traditionally ascribed to 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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".