Optimizing Treatment Outcomes of Dorsomedial Prefrontal Cortex Repetitive Transcranial Magnetic Stimulation in Major Depressive Disorder.
Bibliographic record
Abstract
Major depressive disorder (MDD) continues to challenge the field of psychiatry with its suboptimal treatment outcomes. In cases of partial or non-response to first-line treatments, alternative treatment options are available. Unfortunately, even with these pharmacological advances, there remains a proportion of patients who experience minimal relief from their depressive symptoms. Repetitive transcranial magnetic stimulation (rTMS) is an emerging form of brain stimulation used in the treatment of refractory psychiatric and neurological disorders. The most widely used target for rTMS in MDD is the dorsolateral prefrontal cortex (DLPFC); however, the treatment outcomes it yields are moderate. Over recent years, alternative stimulation targets have emerged as a potential solution to this issue; among them is the dorsomedial prefrontal cortex (DMPFC). To our knowledge, the DMPFC has not been systematically investigated like its adjacent prefrontal counterpart, the DLPFC. Therefore, the primary aim of the present thesis is to examine, and to further optimize treatment outcomes of DMPFC-rTMS in MDD. We addressed this research question using multiple cohorts of MDD patients receiving DMPFC-rTMS. First, we explored the safety and tolerability of DMPFC-rTMS, focusing primarily on its cognitive profile (Study I). Second, we compared treatment outcomes for DMPFC-rTMS between individuals undergoing concurrent antipsychotic pharmacotherapy versus those receiving rTMS alone (Study II). Finally, Experiments III and IV were untaken to investigate accelerated rTMS; that is, whether the pace of symptom improvement can be increased through the use of a more intensive protocol consisting of multiple daily rTMS sessions. Encouragingly, results from this body of work demonstrate that DMPFC-rTMS is a safe and well-tolerated, treatment for MDD (Study I), even in patients undergoing concurrent antipsychotic therapy (Study II). Congruent with existing literature on accelerated rTMS, we found that the rate of improvement can be rapidly increased in some patients, by administering multiple daily sessions of rTMS (Study III), regardless of the intersession interval (Study IV). Collectively, this thesis provides support for the notion that the safety and efficacy of rTMS in MDD applies not only to the standard target, the DLPFC, but also to the DMPFC, a target of stimulation that is entering use.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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".