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Record W4407111423 · doi:10.1136/jnnp-2024-bnpa.57

#7078 The impact of psychiatric comorbidity on parkinson’s disease outcomes: a systematic review and meta-analysis

2025· review· en· W4407111423 on OpenAlexaboutno aff
Ella Burchill

Bibliographic record

Venuenot available
Typereview
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMeta-analysisComorbidityPsychiatrySystematic reviewMedicinePsychiatric comorbidityDiseasePsychologyMEDLINEInternal medicinePolitical science

Abstract

fetched live from OpenAlex

Background The burden of psychiatric symptoms in Parkinson’s Disease (PD) includes depression, anxiety, apathy, psychosis, and impulse control disorders. However, the relationship between psychiatric comorbidities and subsequent prognosis and neurological outcomes is not yet well understood. In this systematic review and meta-analysis, in individuals with PD, we aimed to characterise the association between specific psychiatric comorbidities and subsequent prognosis and neurological outcomes: cognitive impairment, death, disability, disease progression, falls or fractures and care home admission. Methods We searched MEDLINE, Embase, PsycINFO and AMED up to 13th November 2023 for longitudinal observational studies which measured disease outcomes in people with PD with and without specific psychiatric comorbidities, and a minimum of two authors extracted summary data. For each exposure-outcome pair, a random-effects meta-analysis was conducted based on standardised mean difference, using adjusted effect sizes - where available - in preference to unadjusted effect sizes. Study quality was assessed using the Newcastle-Ottawa Scale. Between-study heterogeneity was assessed using the I2 statistic and publication bias was assessed using funnel plots. PROSPERO Study registration number CRD42022373072. Findings There were 55 eligible studies for inclusion in meta-analysis (n = 165,828). Data on participants’ sex was available for 164,514, of whom 99,182 (60.3%) were male and 65,460 (39.7%) female. Study quality was mostly high (84%). Significant positive associations were found between psychosis and cognitive impairment (SMD 0.44, [95% CI 0.23 - 0.66]), psychosis and disease progression (SMD 0.46, [95% CI 0.12 - 0.80]), depression and cognitive impairment (SMD 0.37 [95% CI 0.10 - 0.65]), depression and disease progression (SMD 0.46 [95% CI 0.18 - 0.74]), depression and disability (SMD 0.42 [95% CI 0.25 - 0.60]), and apathy and cognitive impairment (SMD 0.60 [95% CI 0.02 - 1.19]). Between-study heterogeneity was moderately high. Interpretation Psychosis, depression, and apathy in Parkinson’s disease are all associated with at least one adverse outcome. Whether this relationship is causal is not clear, but the mechanisms underlying these associations require exploration. Clinicians should consider these psychiatric comorbidities to be markers of a poorer prognosis in people with Parkinson’s disease. Future studies should investigate the underlying mechanisms and which treatments for these comorbidities may affect PD outcomes.

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)0.017
metaresearch head score (Gemma)0.043
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.020
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.043
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0170.033
Bibliometrics0.0080.009
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0030.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0200.001

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 head0.092
GPT teacher head0.410
Teacher spread0.318 · 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 designMeta-analysis
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

Citations5
Published2025
Admission routes1
Has abstractyes

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