Impacts of center and clinical factors in antihypertensive medication use after kidney transplantation
Bibliographic record
Abstract
Hypertension guidelines recommend calcium channel blockers (CCBs), thiazide diuretics, and angiotensin-converting-enzyme inhibitors/angiotensin receptor blockers (ACEi/ARBs) as first-line agents to treat hypertension. Hypertension is common among kidney transplant (KTx) recipients, but data are limited regarding patterns of antihypertensive medication (AHM) use in this population. We examined a novel database that links national registry data for adult KTx recipients (age > 18 years) with AHM fill records from a pharmaceutical claims warehouse (2007-2016) to describe use and correlates of AHM use during months 7-12 post-transplant. For patients filling AHMs, individual agents used included: dihydropyridine (DHP) CCBs, 55.6%; beta-blockers (BBs), 52.8%; diuretics, 30.0%; ACEi/ARBs, 21.1%; non-DHP CCBs, 3.0%; and others, 20.1%. Both BB and ACEi/ARB use were significantly lower in the time period following the 2014 Eighth Joint National Committee (JNC-8) guidelines (2014-2016), compared with an earlier period (2007-2013). The median odds ratios generated from case-factor adjusted models supported variation in use of ACEi/ARBs (1.51) and BBs (1.55) across transplant centers. Contrary to hypertension guidelines for the general population, KTx recipients are prescribed relatively more BBs and fewer ACEi/ARBs. The clinical impact of this AHM prescribing pattern warrants further study.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".