Association between Plasma Metabolic Profiles of the Antidepressant Escitalopram and Clinical Response in Subjects with Depression
Bibliographic record
Abstract
Liquid chromatography/electrospray ionization-mass spectrometry revealed plasma metabolic profiles for the antidepressant drug escitalopram (ECTP) and associated clinical responses in subjects with major depressive disorder (MDD). Metabolic profiles contribute to variations in responses to drug treatment of depression. To assess clinical responses and treatment outcomes, we quantified the levels of metabolites, including those of the parent drug, in plasma samples collected at different time points (days 0, 7, 14, and 42) during treatment of seven patients with MDD. Results showed that mean plasma levels of key metabolites and ECTP at day 7 were significantly associated with the clinical response at 42 days after treatment. Statistical analyses, including principal component analysis, of key metabolites and ECTP samples at different time points clearly distinguished the clinical responders from non-responder subjects. Although further validation with a larger cohort is necessary, our results indicate that early improvement and plasma levels of key metabolites and ECTP are predictive of therapeutic treatment outcomes and thus can be used to guide the use of ECTP.
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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 | 0.000 | 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) | 0.000 | 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 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".