The Neurosurgical Treatment of Depression: Can it Supersede Psychopharmacology?
Bibliographic record
Abstract
Psychosurgery has a controversial history in the treatment of psychiatric disorders, but in recent years there has been mounting evidence for the potential of chronic electrical deep brain stimulation (DBS) of several neuroanatomical targets in managing treatment-resistant depression (TRD), a debilitating mental illness with limited therapeutic options. Achieving optimal clinical outcome with DBS involves characterizing the heterogeneous neuronal circuits responsible for the variable clinical course of depression and selecting nodes within these circuits for stimulation. A number of exciting preliminary studies have used DBS in several discrete brain areas to treat patients with depression. Despite ongoing controversies about the mechanisms responsible for the therapeutic effects of DBS, the clinical results to date show strong promise for this technique as a feasible treatment choice in TRD. The full therapeutic potential of DBS in psychiatric practice will be revealed as future clinical studies focus on careful ethical approaches and the use of long-term placebo controlled comparisons. Nöroşirürjikal depresyon tedavisi: Psikofarmakolojinin yerini alabilir mi? Psikiyatrik hastalıkların tedavisinde psikocerrahi’nin tartışmalı bir geçmişi vardır. Fakat son yıllarda tedavi seçenekleri sınırlı olan dirençli depresyonun (DD) yönetiminde, bazı nöroanotomik hedeflerin kronik derin beyin uyarımı (DBU) ile uyarılma potansiyelini destekleyen deliller mevcuttur. DBU ile ideal klinik sonuca ulaşmak, depresyonun değişken klinik sürecinden sorumlu heterojen sinir döngülerini belirlemeyi ve bu döngülerin içinde uyarılacak düğümleri seçmeyi içerir. Bir dizi heyecan verici ön çalışma DBU’ını depresyonlu hastaların tedavisinde bir kaç farklı beyin bölgesinde kullanmıştır. DBU’nın terapotik etkilerinden sorumlu mekanizmaları hakkında süregiden tartışmalara rağmen, bugüne kadarki klinik sonuçlar bu tekniği DD’da uygun bir tedavi seçeneği olarak güçlü bir şekilde işaret etmektedir. DBU’nın psikiyatri’deki tam terapotik potensiyeli dikkatli etik yaklaşımlar ve uzun dönem plasebo kontrollü karşılaştırmalara odaklanmış gelecek klinik çalışmalarla açıklanacaktır.
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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 | 0.010 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.003 | 0.008 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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".