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Record W2322030568 · doi:10.1177/0891988716640378

Quetiapine for Psychosis in Parkinson Disease and Neurodegenerative Parkinsonian Disorders

2016· review· en· W2322030568 on OpenAlexaff
Philippe Desmarais, Fadi Massoud, Josée Filion, Quôc Dinh Nguyên, Paulina Bajsarowicz

Bibliographic record

VenueJournal of Geriatric Psychiatry and Neurology · 2016
Typereview
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsDouglas Mental Health University InstituteHôpital Charles-Le MoyneCentre Hospitalier de l’Université de Montréal
Fundersnot available
KeywordsQuetiapineDementia with Lewy bodiesPsychosisPsychiatryDementiaRating scaleLewy bodyMedicineParkinson's diseasePsychologyPlaceboDiseaseClinical psychologySchizophrenia (object-oriented programming)Internal medicinePathology

Abstract

fetched live from OpenAlex

We performed a systematic review of randomized controlled trials to assess the high-level evidence regarding the role of quetiapine in the treatment of psychosis in patients with neurodegenerative parkinsonian disorders. Studies were included in the qualitative review if they (1) enrolled participants with diagnosis of Parkinson disease, Lewy body dementia, or any other neurodegenerative parkinsonian disorders; (2) assessed the efficacy of quetiapine; and (3) evaluated psychotic and motor outcomes using validated tools. Of the 341 manuscripts identified, 7 studies fulfilled our inclusion criteria. The studies' risk of bias was considered low. A total of 241 participants enrolled in these trials. Heterogeneity was high due to inclusion criteria, user definitions, assessment tools, and study design. Although not causing any motor deterioration, quetiapine failed to significantly reduce psychotic symptoms compared to placebo when objectively assessed on the Brief Psychotic Rating Scale, the most frequently reported scale in these studies. High loss to follow-up and dropout rates as well as significant improvement in psychotic symptoms in the placebo groups may have affected measurements of possible positive medication effects.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.972
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.000
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 head0.018
GPT teacher head0.304
Teacher spread0.287 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations35
Published2016
Admission routes1
Has abstractyes

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