Should glutamatergic modulators be considered preferential treatments for adults with major depressive disorder and a reported history of trauma? Conceptual and clinical implications
Bibliographic record
Abstract
Major depressive disorder (MDD) is a chronic, highly prevalent, and debilitating mental disorder associated with significant illness and economic burden globally. Exposure to trauma (eg, physical, sexual, emotional abuse, and/or physical, and emotional neglect) is common among individuals with MDD. Persons with MDD and a history of trauma often exhibit an attenuated response to conventional serotonergic antidepressants compared to those with non-traumatized depression. Emerging evidence indicates that exposure to trauma is associated with increased inflammatory markers [eg, C-reactive protein (CRP), interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α)] as well as glutamatergic dysregulation in the central nervous system (CNS). It is hypothesized that individuals with MDD and a history of trauma may be conceptualized as a distinct bio-phenotype compared to non-traumatized depression. Furthermore, preliminary evidence positions select glutamatergic modulators as potential, novel, mechanistically-informed therapeutic strategies that may provide benefit to persons with elevated inflammation and glutamatergic dysregulation.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".