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Record W4412934454 · doi:10.1038/s44400-025-00022-2

Risk factors and predictors for Lewy body dementia: a systematic review

2025· review· en· W4412934454 on OpenAlexaboutno aff
Ahalya Ratnavel, Francesca Dino, Sarah Azmy, Kathryn A Wyman‐Chick, Ece Bayram

Bibliographic record

Venuenpj Dementia · 2025
Typereview
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsnot available
FundersNational Institute on AgingLewy Body Dementia AssociationDemensförbundet
KeywordsDementiaDementia with Lewy bodiesLewy bodyGeneralizability theoryMedicinePsychologyClinical psychologyParkinsonismDiseaseGerontologyPsychiatryInternal medicineDevelopmental psychology

Abstract

fetched live from OpenAlex

Abstract Lewy body dementia (LBD), including Parkinson’s disease dementia (PDD) and dementia with Lewy bodies (DLB), is a common and burdensome dementia. Determining risk factors and predictors can provide insights into pathogenesis and guide treatment efforts. In this systematic review, we searched PubMed, Embase, and Web of Science for longitudinal studies assessing risk/prodromal factors; including participants without dementia at baseline; with LBD as the outcome; with good/high quality based on the Newcastle-Ottawa Quality Assessment Scale. Across 167 included studies, more consistently reported factors were older age, male sex, APOEe4 , GBA , changes in cognition, mood, behavior, sleep, gait/posture, speech, parkinsonism, smell loss, autonomic dysfunction, white matter disease on MRI, lower CSF amyloid β42 and higher CSF/blood neurofilament light chain. The majority focused on clinical factors preceding PDD with cohorts from North America and Europe, limiting generalizability. Further efforts with more representative cohorts are needed to better identify people at risk for LBD.

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: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.508
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.001
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 head0.024
GPT teacher head0.320
Teacher spread0.296 · 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 designSystematic review
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

Citations6
Published2025
Admission routes1
Has abstractyes

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