Sex and Gender Considerations in Randomized Controlled Trials in Adults Receiving Chronic Dialysis: A Meta-Epidemiologic Study
Bibliographic record
Abstract
Background: How sex and gender concepts are incorporated in randomized controlled trials (RCTs) in adults with kidney failure receiving chronic dialysis is unknown. Methods: Meta-epidemiologic study of RCTs in chronic dialysis from the highest impact journals from 2000 to 2020. Meta-regression was performed to identify trial characteristics independently associated with the proportion of female/women participants. Results: Of 561 included RCTs, 69.7% were parallel and 28.0% were crossover in design. 80.6% were in the hemodialysis population. 1/4 were placebo controlled, 1/4 were compared to usual care and 1/2 were compared to an active therapy. 37.6% of RCTs were blinded. The median (IQR) size was 60 participants (26, 151) and the median (IQR) follow-up was 154 days (42, 365). The mean (SD) proportion of female/women participants was 0.40 (0.13). 39.0% of trials reported sex and 26.6% reported gender of participants. 56.2% referred to participants as females, 25.3% referred to participants as women and 15.5% referred to both females and women. No trial characteristic other than region (Asia, ß 0.062 95% CI 0.007-0.117) was associated with the proportion of female/women participants. Considering trial design and conduct, 2.7% used male/female sex and/or man/woman gender as an inclusion criteria, 26.6% as exclusion criteria (e.g. related to pregnancy, contraception, lactation), 4.5% for randomization, 4.8% for subgroup analyses and 15.7% for covariate adjustment. Conclusions: RCTs in dialysis are representative of the general dialysis population with regards to sex/gender but rarely report both sex and gender separately and often do not include either in their reporting or analysis.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | MetaresearchMeta-epidemiology (broad) Domain: Methods · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | MetaresearchMeta-epidemiology (broad) Domain: Methods · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Systematic review | high |
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.030 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.008 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".