Pretreatment anxious depression as a predictor of side effect frequency and severity in escitalopram and aripiprazole adjunctive therapy
Bibliographic record
Abstract
OBJECTIVE: To report side effect frequency and severity in patients with major depressive disorder (MDD) receiving escitalopram and aripiprazole adjunctive therapy and to examine whether pretreatment anxious depression is associated with the number and presence of specific side effects. METHODS: 188 of the 211 trial participants provided information on side effects during treatment with escitalopram (10-20 mg) for 8 weeks, and nonresponders received further augmentation on aripiprazole (2-10 mg) adjunctive therapy for another 8 weeks, whereas responders remained on escitalopram. Participants completed the Toronto Side Effects Scale at weeks 2, 4, 10, and 12. Covariate-adjusted negative binomial regression and Wilcoxon tests examined the association between anxious depression (GAD-7 ≥ 10) and number of side effects. Covariate-adjusted logistic regression and chi-square tests explored the association between anxious depression and specific side effects. RESULTS: For both therapies, the most frequent side effects were also the most severe. They mostly related to the central nervous system (CNS) (i.e., drowsiness and nervousness). Between baseline and week 2, the number of side effects participants experienced (incidence rate ratio [IRR] = 1.38, p = .010) or had trouble with (IRR = 1.34, p = .026) was significantly higher among those with anxious depression for escitalopram but not adjunctive aripiprazole. Further, odds of experiencing and having trouble with nervousness and agitation were also significantly higher in anxious depression for escitalopram only (p < .05). CONCLUSION: Patients on escitalopram and aripiprazole adjunctive therapy may experience and have trouble with CNS side effects. Pretreatment anxious depression may predispose escitalopram recipients with MDD to developing side effects, especially those related to anxiety.
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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 | 0.000 | 0.000 |
| 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 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".