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Record W2028836952 · doi:10.1177/026988110101500206

The ‘Dalhousie Serotonin cocktail’ for treatment-resistant major depressive disorder

2001· article· en· W2028836952 on OpenAlexafffundabout
Sivakumaran Devarajan, Stan Kutcher

Bibliographic record

VenueJournal of Psychopharmacology · 2001
Typearticle
Languageen
FieldMedicine
TopicTreatment of Major Depression
Canadian institutionsDalhousie University
FundersDalhousie University
KeywordsNefazodonePindololMajor depressive disorderAntidepressantDoseMajor depressive episodePsychologyAdverse effectInternal medicineMedicinePharmacologySerotoninPsychiatryMoodFluoxetine

Abstract

fetched live from OpenAlex

We describe the successful treatment of five patients with treatment-resistant major depressive disorder (TR-MDD) with a combination pharmacotherapy of pindolol, tryptophan and nefazodone. Five TR-MDD outpatients who had previously not responded to at least four different antidepressant medication trials were initiated on 300 mg/day of nefazodone, 7.5 mg/day of pindolol and 1 g/day of tryptophan. Pindolol doses remained the same throughout the 20 weeks, while tryptophan and nefazodone dosages were gradually increased to 8 g/day and 450 mg/day, respectively. The Hamilton Depression Rating Scale (HAM-D) was used to evaluate outcome. By week 4, all cases demonstrated at least 50% decrease in HAM-D scores. At the end of the trial, the group mean HAM-D score had significantly decreased from 26.8 (+/- 1.9) to 1.8 (+/- 0.8) (p < 0.001). No significant adverse effects were reported. These results suggest that if serotonin availability and release is further enhanced by tryptophan in the presence of nefazodone and pindolol, an antidepressant effect may be produced in patients who are otherwise treatment-resistant. Due to limited sample size, an open design and an 'unusually' high successful efficacy rate of this preliminary study, controlled studies are required to confirm the efficacy of this treatment strategy.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.663
Threshold uncertainty score0.553

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.019
GPT teacher head0.354
Teacher spread0.335 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2001
Admission routes3
Has abstractyes

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