Management of Treatment-Resistant Depression: Challenges and Strategies
Bibliographic record
Abstract
Daphne Voineskos, 1, 2 Zafiris J Daskalakis, 1, 2 Daniel M Blumberger 1, 2 1Centre for Addiction and Mental Health, Toronto, Ontario, Canada; 2Department of Psychiatry, University of Toronto, Toronto, Ontario, CanadaCorrespondence: Daniel M BlumbergerCentre for Addiction and Mental Health, 1001 Queen Street West, Unit 4-1, Toronto, Ontario M6J1H4, CanadaTel +1 416 535-8501Fax +1 416 583-1358Email daniel.blumberger@camh.caAbstract: Treatment-resistant depression (TRD) is a subset of Major Depressive Disorder which does not respond to traditional and first-line therapeutic options. There are several definitions and staging models of TRD and a consensus for each has not yet been established. However, in common for each model is the inadequate response to at least 2 trials of antidepressant pharmacotherapy. In this review, a comprehensive analysis of existing literature regarding the challenges and management of TRD has been compiled. A PubMed search was performed to assemble meta-analyses, trials and reviews on the topic of TRD. First, we address the confounds in the definitions and staging models of TRD, and subsequently the difficulties inherent in assessing the illness. Pharmacological augmentation strategies including lithium, triiodothyronine and second-generation antipsychotics are reviewed, as is switching of antidepressant class. Somatic therapies, including several modalities of brain stimulation (electroconvulsive therapy, repetitive transcranial magnetic stimulation, magnetic seizure therapy and deep brain stimulation) are detailed, psychotherapeutic strategies and subsequently novel therapeutics including ketamine, psilocybin, anti-inflammatories and new directions are reviewed in this manuscript. Our review of the evidence suggests that further large-scale work is necessary to understand the appropriate treatment pathways for TRD and to prescribe effective therapeutic options for patients suffering from TRD.Keywords: treatment resistant depression, major depressive disorder, pharmacotherapy, psychotherapy, brain stimulation, novel therapies
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.018 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".