Medication management and pharmacokinetic changes after bariatric surgery.
Bibliographic record
Abstract
OBJECTIVE: To identify expected pharmacokinetic changes and provide practical recommendations for the medication management of chronic disease states after bariatric surgery. SOURCES OF INFORMATION: . Reference lists of original studies and reviews were also hand searched. Included studies were entered into PubMed and articles under the "Similar articles" heading were also reviewed. Only studies relevant to bariatric surgery types currently available in Canada (ie, Roux-en-Y gastric bypass, sleeve gastrectomy, or gastric banding) were included. MAIN MESSAGE: Pharmacokinetic changes anticipated after bariatric surgery vary by surgery type. There are several guiding principles that might be applied to medication management regimens after bariatric surgery. Practice tips are also presented for medication management of specific chronic disease states. CONCLUSION: Changes to long-term medication regimens after bariatric surgery should be anticipated and managed in an appropriate and timely manner. The provided clinical practice recommendations might be used in conjunction with a patient's clinical picture to adjust chronic medication regimens in an appropriate and evidence-based manner after bariatric surgery.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".