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Record W2074828631 · doi:10.1212/wnl.0b013e3182516244

A randomized, double-blind, placebo-controlled trial of antidepressants in Parkinson disease

2012· article· en· W2074828631 on OpenAlexaff
I Richard, M. P. McDermott, Roger Kurlan, Jeffrey M. Lyness, Peter G. Como, N. Shirlene Pearson, Stewart A. Factor, Jorge L. Juncos, Carmen Serrano Ramos, Matthew Brodsky, Carol A. Manning, Laura Marsh, Lisa M. Shulman, Hubert H. Fernandez, Kevin J. Black, Michel Panisset, Chadwick W. Christine, Wei Jiang, Carlos Singer, Sarah R. Horn, Ronald F. Pfeiffer, David A. Rottenberg, John T. Slevin, Lawrence Elmer, Daniel Z. Press, H. Christopher Hyson, William M. McDonald, Irene Hegeman Richard, Michael McDermott, Barbara Sommerfeld, Cheryl Deeley, T. de la Torre, M Barnard, April Wilson, Maryann Lincoln, Paula Damgaard, Melissa Gerstenhaber, Kelly Dustin, Nancy Zappala, Camille Swartz, Mary L. Creech, E. Shipley, Samantha Blankenship, Monica Beland, Jessie Roth, Heather Burnette, Tamara E. Foxworth, Mónica Quesada, Mary Lloyd, Brenda Pfeiffer, Joy Hansen, Joy Folie, Renee Wagner, Julia Spears, Colleen Taylor, Rachel Brown, Lisa Iguchi, Chen Lim, Kori A. LaDonna, Julie Megens, Matthew Menza, Jeffrey L. Cummings, Robert M. Hamer, Kathleen M. Shannon, Joanne Odenkirchen, Robin Conwit, Christopher A. Beck, Donna LaDonna, Jan Bausch, Scott Y. H. Kim, Ron Chismar, Sinéad Quinn, Steve Bean, Susan Daigneault, Patricia Lindsay, Tori Ross, Katie Kompoliti

Bibliographic record

VenueNeurology · 2012
Typearticle
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsLondon Health Sciences CentreHotel Dieu HospitalUniversité de Montréal
FundersNational Institute on AgingMcDonnell Center for Systems NeuroscienceParkinsonfondenNational Center for Research ResourcesWeill Cornell Medical CollegeAllerganNational Institutes of HealthIpsenH. Lundbeck A/SACADIA PharmaceuticalsEisaiNational Parkinson FoundationKyowa Hakko KirinNational Institute of Diabetes and Digestive and Kidney DiseasesMichael J. Fox Foundation for Parkinson's ResearchJohns Hopkins UniversityNational Institute of Mental HealthNorthwestern UniversityNational Institute of Neurological Disorders and StrokeTeva Pharmaceutical IndustriesMerz PharmaceuticalsBiogenGlaxoSmithKline
KeywordsParkinson's diseaseDouble blindMedicinePlaceboRandomized controlled trialPsychiatryDiseaseInternal medicineAlternative medicinePathology

Abstract

fetched live from OpenAlex

OBJECTIVE: To evaluate the efficacy and safety of a selective serotonin reuptake inhibitor (SSRI) and a serotonin and norepinephrine reuptake inhibitor (SNRI) in the treatment of depression in Parkinson disease (PD). METHODS: A total of 115 subjects with PD were enrolled at 20 sites. Subjects were randomized to receive an SSRI (paroxetine; n = 42), an SNRI (venlafaxine extended release [XR]; n = 34), or placebo (n = 39). Subjects met DSM-IV criteria for a depressive disorder, or operationally defined subsyndromal depression, and scored >12 on the first 17 items of the Hamilton Rating Scale for Depression (HAM-D). Subjects were followed for 12 weeks (6-week dosage adjustment, 6-week maintenance). Maximum daily dosages were 40 mg for paroxetine and 225 mg for venlafaxine XR. The primary outcome measure was change in the HAM-D score from baseline to week 12. RESULTS: Treatment effects (relative to placebo), expressed as mean 12-week reductions in HAM-D score, were 6.2 points (97.5% confidence interval [CI] 2.2 to 10.3, p = 0.0007) in the paroxetine group and 4.2 points (97.5% CI 0.1 to 8.4, p = 0.02) in the venlafaxine XR group. No treatment effects were seen on motor function. CONCLUSIONS: Both paroxetine and venlafaxine XR significantly improved depression in subjects with PD. Both medications were generally safe and well tolerated and did not worsen motor function. CLASSIFICATION OF EVIDENCE: This study provides Class I evidence that paroxetine and venlafaxine XR are effective in treating depression in patients with PD.

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)0.001
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: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.665

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.033
GPT teacher head0.305
Teacher spread0.272 · 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 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

Citations334
Published2012
Admission routes1
Has abstractyes

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