Systematic review of clinical effectiveness of interventions for treatment resistant late-life depression
Bibliographic record
Abstract
BACKGROUND: Treatment-resistant late-life depression (TRLLD) affects nearly half of older adults with major depression. This systematic review evaluates published evidence of effectiveness of both pharmacological and non-pharmacological treatments for TRLLD. METHODS: A search of MEDLINE, EMBASE, CINAHL, PsycINFO, the Cochrane Library, and online trial registries up to March 2024 was conducted to identify randomized controlled trials (RCTs) evaluating pharmacological and non-pharmacological interventions for TRLLD. RESULTS: Seven studies assessed the effectiveness of pharmacological interventions (antidepressants, antipsychotics, mood stabilizers, or ketamine) and another seven examined non-pharmacological approaches (psychotherapy, electroconvulsive therapy, repetitive transcranial magnetic stimulation (rTMS), and computerized cognitive remediation). Aripiprazole (2 studies), venlafaxine (1 study), ketamine (1 study), and lithium (1 study) were associated with a reduction in depressive symptoms post-treatment compared to the comparator treatment group. rTMS (2 studies), sequential bilateral theta burst stimulation (1 study) and cognitive remediation (1 study) also showed significant improvements in depressive symptoms post-treatment compared to a comparator treatment group. Quality of evidence varied from very low to medium among the included studies. Most studies reported data on small sample sizes. CONCLUSIONS AND IMPLICATIONS: We identified a small number of RCTs evaluating treatments for TRLLD. Aripiprazole augmentation appears to be an effective treatment based on two studies, with an acceptable side effect profile. Other treatments may be effective, but the evidence is based on very low-quality evidence. Future large-scale RCTs are urgently needed to draw firm conclusions.
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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 | 0.020 | 0.139 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.010 | 0.004 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".