Gender differences in use of prescription narcotic medications among living kidney donors
Bibliographic record
Abstract
Prescription narcotic use among living kidney donors is not well described. Using a unique database that integrates national registry identifiers for living kidney donors (1987-2007) in the United States with billing claims from a private health insurer (2000-2007), we identified pharmacy fills for prescription narcotic medications in periods 1-4 and >4 yr post-donation and estimated relative likelihoods of post-donation narcotic use by Cox regression. We also compared narcotic fill rates and medication possession ratios (MPRs, defined as (days of medication supplied)/(days observed)), between donors and age- and sex-matched non-donors. Overall, rates of narcotic medication fills were 32.3 and 32.4 per 100 person-years in periods 1-4 and >4 yr post-donation. After age and race adjustment, women were approximately twice as likely as men to fill a narcotic prescription in years 1-4 (adjusted hazard ratio, aHR, 2.28; 95% confidence interval, CI, 1.86-2.79) and >4 yr (aHR 1.70; 95% CI 1.50-1.93). MPRs in donors were low (<2.5% days exposed), and lower than among age- and sex-matched non-donors. Prescription narcotic medication use is more common among women than men in the intermediate term after live kidney donation. Overall, total narcotic exposure is low, and lower than among non-donors from the general population.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| 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 | 0.000 | 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, unvalidatedMachine predicted; a candidate call from one teacher head, 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".