Effect of gastric bypass surgery on azithromycin oral bioavailability
Bibliographic record
Abstract
OBJECTIVES: Azithromycin is used widely for community-acquired infections. The timely administration of azithromycin in adequate doses minimizes treatment failure. Gastric bypass, a procedure that circumvents the upper gut, may compromise azithromycin plasma levels. We hypothesized that azithromycin concentrations would be reduced following gastric bypass. METHODS: A single-dose pharmacokinetic study in 14 female post-gastric bypass patients and 14 sex- and body mass index (BMI)-matched controls (mean age 44 years and BMI 36.4 kg/m(2)) was performed. Subjects were administered two 250 mg azithromycin tablets at time 0 and plasma azithromycin levels were sampled at 0.5, 1, 1.5, 2, 3, 5, 7 and 24 h. The AUC of the plasma azithromycin concentrations from time 0 to 24 h (AUC(0-24)) was the primary outcome. RESULTS: Azithromycin concentrations were lower in gastric bypass patients compared with controls throughout the entire duration of sampling. Compared with controls, the AUC(0-24) was reduced in gastric bypass subjects by 32% [1.41 (SD 0.51) versus 2.07 (0.75) mg · h/L; P = 0.008], and dose-normalized AUC(0-24) was reduced by 33% [0.27 (0.12) versus 0.40 (0.13) kg · h/L; P = 0.009]. Peak azithromycin concentrations were 0.260 (0.115) in bypass subjects versus 0.363 (0.200) mg/L in controls (P = 0.08), and were reached at 2.14 (0.99) h in gastric bypass subjects and 2.36 (1.17) h in controls (P = 0.75). CONCLUSIONS: Azithromycin AUC was reduced by one-third in gastric bypass subjects compared with controls. The potential for early treatment failure exists, and dose modification and/or closer clinical monitoring of gastric bypass patients receiving azithromycin should be considered.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".