Associations of Pre-Transplant Prescription Narcotic Use with Clinical Complications after Kidney Transplantation
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: The impact of narcotic use before kidney transplantation on post-transplant clinical outcomes is not well described. METHODS: We examined integrated national transplant registry, pharmacy records, and Medicare billing claims to follow 16,322 kidney transplant recipients, of whom 28.3% filled a narcotic prescription in the year before transplantation. Opioid analgesic fills were normalized to morphine equivalents (ME) and expressed as mg/kg exposures (approximate quartiles: 0.1-1.7, 1.8-5.4, 5.5-23.7, and ≥ 23.8 mg/kg, respectively). Post-transplant cardiovascular, respiratory, neurological, accidents, substance abuse, and noncompliance events were identified using diagnosis codes on Medicare billing claims. Adjusted associations of ME level with post-transplant complications were quantified by multivariate Cox regression. RESULTS: The incidence of complications at 3 years post-transplant among those with the highest pre-transplant ME exposure compared to no use included: ventricular arrhythmias, 1.1 vs. 0.2% (p < 0.001); cardiac arrest, 4.7 vs. 2.7% (p < 0.05); hypotension, 14 vs. 8% (p < 0.0001); hypercapnia, 1.6 vs. 0.9% (p < 0.05); mental status changes, 5.3 vs. 2.7% (p < 0.001); drug abuse/dependence, 7.0 vs. 1.7% (p < 0.0001); alcohol abuse, 1.8 vs. 0.6% (p = 0.0001); accidents, 0.9 vs. 0.3% (p < 0.05); and noncompliance, 3.5 vs. 2.3% (p < 0.05). In multivariate analyses, transplant recipients with the highest level of pre-transplant narcotic use had approximately 2 to 4 times the risks of post-transplant ventricular arrhythmias, mental status changes, drug abuse, alcohol abuse, and accidents compared with non-users, and 35-45% higher risks of cardiac arrest and hypotension. CONCLUSION: Although associations may reflect underlying conditions or behaviors, high-level prescription narcotic use before kidney transplantation predicts increased risk of clinical complications after transplantation.
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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 | 0.000 |
| 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 it