1023 – Therapeutic Drug-monitoring Of Bupropion For Depression
Bibliographic record
Abstract
Introduction Therapeutic Drug-Monitoring (TDM) for bupropion is limited by bupropion's instability at room temperature and by the absence of a well-defined therapeutic reference range. Further it is unclear to what extent bupropion and its metabolites contribute to therapeutic effects, though hydroxybupropion seems to account for the major antidepressant effects. Aim The aim of this examination was to check if measurement of only hydroxybupropion is useful to guide the antidepressant therapy with bupropion. Methods Hydroxybupropion plasma levels were measured by high performance liquid chromatography with ultra violet detection and related to therapeutic effects measured by the Clinical Global Impression Scale for improvement. Results The study included 52 patients (50% female). Patients who were very much improved according to CGI had significantly (p=0.042) higher hydroxybupropion serum levels than patients with moderate or minimal improvement (mean±SD, 1113±576 ng/ml, 825±398 ng/ml and 475±331 ng/ml, respectively). Receiver operating characteristics analysis revealed significant predictive properties of hydroxybupropion serum levels (p=0.002) for improvement with a lower threshold level of 858 ng/ml. Women attained significantly higher serum levels than men and also exhibited a better therapeutic effect (p= 0.018), though they did not receive significantly higher doses. Conclusions Measurement of hydroxybupropion plasma levels can be used to optimize the therapeutic outcome of patients treated with bupropion. Plasma levels between 850 and 1500 ng/ml can be regarded as optimal. Potential sex differences in bupropion pharmacokinetics, probably due to differential activities of CYP2B6, should be taken into account.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.005 | 0.002 |
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".