Exploring Glutamate Augmentation as a Novel OCD Treatment: A Comparison Between Risperidone and Memantine as SSRI Adjunctive Therapies
Bibliographic record
Abstract
Obsessive Compulsive Disorder (OCD) is a chronic neuropsychiatric disorder characterized by the presence of either obsessions, compulsions, or both. The current FDA-approved treatments for OCD primarily target the serotonergic system and only yield therapeutic effects for ~70% of OCD patients. Thus, augmentation treatments are used to enhance the effects of serotonergic monotherapy or to target additional neurotransmitters, particularly in treatment-resistant patients. Notably, emerging research on glutamate's role in OCD pathology shows promising results for the use of glutamate-modulating medications as SSRI augmentation treatments. This study compares the efficacy of two augmentation treatments: a common treatment using the serotonin and dopamine-modulating medication Risperidone, and a novel treatment using the glutamate-modulating medication Memantine. A PICOS analysis including ten double-blind, randomized, placebo-controlled studies was conducted to compare the efficacy of both medications on OCD symptoms. There were no significant differences between Risperidone and Memantine treatments, though there was a trend towards significance favouring the effectiveness of Memantine. These results indicate that Memantine and Risperidone produce similar effects in the reduction of OCD symptoms, supporting the potential use of Memantine as an augmentation therapy for SSRI-resistant and antipsychotic-augmentation-resistant OCD patients. Further research must be conducted to characterize the potential of novel glutamate-modulating medications for OCD treatment.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".