Prospective study of the changes in pharmacokinetics of immunosuppressive medications after laparoscopic sleeve gastrectomy
Bibliographic record
Abstract
Laparoscopic sleeve gastrectomy induces weight loss via the creation of a restrictive gastric tube for early satiety and is associated with an accelerated gastric transit time. A prospective, single-dose pharmacokinetic study was performed, prior to and after laparoscopic sleeve gastrectomy, for tacrolimus, extended-release tacrolimus, mycophenolate mofetil, and enteric-coated mycophenolate sodium. The study included 12 morbidly obese patients in chronic renal failure. The median decrease in body mass index was 8.8 kg/m 2 with an excess body weight loss of 54.9%. The AUC 24 of all drugs were increased after laparoscopic sleeve gastrectomy by 46%, 55%, 77%, and 74%, respectively. The maximum concentrations were increased for tacrolimus, extended-release tacrolimus, and mycophenolate mofetil by 43%, 46%, and 65%. The apparent total clearances were decreased for tacrolimus, mycophenolate mofetil, and enteric-coated mycophenolate sodium by 36%, 57%, and 38%. Laparoscopic sleeve gastrectomy can be associated with significant changes in pharmacokinetics of the drugs evaluated. The mechanism is likely decreased apparent drug clearance due to an increased drug exposure (from a more distal site of intestinal absorption with decreased intestinal metabolism), or decreased clearance (liver metabolism). Adapting the monitoring of immunosuppression will be important to avoid overdosing and potential side effects.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".