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A controlled trial of antidepressants in patients with Parkinson disease and depression

2008· article· en· W2042158944 on OpenAlexfundno aff
Matthew Menza, Roseanne D. Dobkin, Humberto Marín, M. H. Mark, Michael A. Gara, Steven Buyske, Karina Bienfait, Allison Dicke

Bibliographic record

VenueNeurology · 2008
Typearticle
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsnot available
FundersNational Institutes of HealthNational Institute of Neurological Disorders and StrokeNational Institute of Mental HealthValeant Pharmaceuticals InternationalSanofiGlaxoSmithKlinePfizerNational Institute on Alcohol Abuse and AlcoholismAllerganEli Lilly and CompanyBristol-Myers Squibb
KeywordsNortriptylineParoxetinePlaceboDepression (economics)Internal medicineMedicinePsychiatryPsychologyAnxietyAntidepressantAmitriptylineAlternative medicine

Abstract

fetched live from OpenAlex

<b>Background:</b> Parkinson disease (PD) is a common neurodegenerative disease affecting up to 1 million individuals in the United States. Depression affects up to 50% of these patients and is associated with a variety of poor outcomes for patients and their families. Despite this, there are few evidence-based data to guide clinical care. <b>Methods:</b> An NIH-funded, randomized, controlled trial of paroxetine CR, nortriptyline, and placebo in 52 patients with PD and depression. The primary outcomes were the change in the Hamilton Depression Rating Scale (HAM-D) and the percentage of depression responders at 8 weeks. <b>Results:</b> Nortriptyline was superior to placebo for the change in HAM-D (<i>p</i> &lt; 0.002); paroxetine CR was not. There was a trend for superiority of nortriptyline over paroxetine CR at 8 weeks (<i>p</i> &lt; 0.079). Response rates favored nortriptyline (<i>p</i> = 0.024): nortriptyline 53%, paroxetine CR 11%, placebo 24%. In planned contrasts of response rates, nortriptyline was superior to paroxetine CR (<i>p</i> = 0.034). Nortriptyline was also superior to placebo in many of the secondary outcomes, including sleep, anxiety, and social functioning, while paroxetine CR was not. Both active drug treatments were well tolerated. <b>Conclusions:</b> Though relatively modest in size, this is the largest placebo-controlled trial done to date in patients with Parkinson disease (PD) and depression. Nortriptyline was efficacious in the treatment of depression and paroxetine CR was not. When compared directly, nortriptyline produced significantly more responders than did paroxetine CR. The trial suggests that depression in patients with PD is responsive to treatment and raises questions about the relative efficacy of dual reuptake inhibitors and selective serotonin reuptake inhibitors. <b>ARR</b> = absolute risk reduction; <b><i>DSM-IV</i></b> = <i>Diagnostic and Statistical Manual of Mental Disorders,</i> 4th edition; <b>HAM-A</b> = Hamilton Anxiety Scale; <b>HAM-D</b> = Hamilton Depression Rating Scale; <b>MMSE</b> = Mini-Mental State Examination; <b>NNT</b> = number needed to treat; <b>PD</b> = Parkinson disease; <b>PDQ</b> = Parkinson’s Disease Questionnaire; <b>PSQI</b> = Pittsburgh Sleep Quality Index; <b>SCID</b> = Structured Clinical Interview; <b>SSRI</b> = selective serotonin reuptake inhibitor; <b>TCA</b> = tricyclic antidepressant; <b>UPDRS</b> = Unified Parkinson’s Disease Rating Scale.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0120.001

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.

Opus teacher head0.011
GPT teacher head0.237
Teacher spread0.226 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
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

Citations408
Published2008
Admission routes1
Has abstractyes

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