Predicting 6‐week treatment response to escitalopram pharmacotherapy in late‐life major depressive disorder
Bibliographic record
Abstract
OBJECTIVE: Approximately half of older patients treated for major depressive disorder (MDD) do not achieve symptomatic remission and functional recovery with first-line pharmacotherapy. This study aims to characterize sociodemographic, clinical, and neuropsychologic correlates of full, partial, and non-response to escitalopram monotherapy of unipolar MDD in later life. METHODS: One hundred and seventy-five patients aged 60 and older were assessed at baseline on demographic variables, depression severity, hopelessness, anxiety, cognitive functioning, co-existing medical illness burden, social support, and quality of life (disability). Subjects received 10 mg/d of open-label escitalopram and were divided into full (n = 55; 31%), partial (n = 75; 42.9%), and non-responder (n = 45; 25.7%) groups based on Hamilton depression scores at week 6. Univariate followed by multivariate analyses tested for differences between the three groups. RESULTS: Non-responders to treatment were found to be more severely depressed and anxious at baseline than both full and partial responders, more disabled, and with lower self-esteem than full responders. In general partial responders resembled full responders more than they resembled non-responders. In multivariate models, more severe anxiety symptoms (both psychological and somatic) and lower self-esteem predicted worse response status at 6 weeks. CONCLUSION: Among treatment-seeking elderly persons with MDD, higher anxiety symptoms and lower self-esteem predict poorer response after six weeks of escitalopram treatment.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".