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Record W4205672243 · doi:10.1002/alz.055542

Sex differences in neuropsychiatric symptoms in Alzheimer’s disease dementia: A meta‐analysis

2021· article· en· W4205672243 on OpenAlexaff
Willem S. Eikelboom, Michel Pan, Rik Ossenkoppele, Michiel Coesmans, Jennifer R. Gatchel, Zahinoor Ismail, Krista L. Lanctôt, Corinne E. Fischer, Moyra E. Mortby, Esther van den Berg, Janne M. Papma

Bibliographic record

VenueAlzheimer s & Dementia · 2021
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsSt. Michael's HospitalUniversity of TorontoSunnybrook Health Science CentreHealth Sciences CentreHotchkiss Brain InstituteUniversity of Calgary
Fundersnot available
KeywordsDementiaMeta-analysisDiseaseMedicineInternal medicineAlzheimer's diseasePublication biasDemographyPsychologyClinical psychology

Abstract

fetched live from OpenAlex

Abstract Background Although the majority of individuals with Alzheimer’s disease (AD) dementia exhibit neuropsychiatric symptoms (NPS), there is substantial heterogeneity in NPS manifestation. Sex is increasingly recognized as an important factor in explaining clinical variability within AD; yet, prior studies on sex differences in NPS have reported mixed findings. Therefore, we aimed to review the existing literature on sex differences in NPS in AD dementia using a meta‐analytic approach. Method Effect sizes were extracted from 54 studies (N=19,730; N=12,092 females [61.3%], N=7,638 males [38.7%]). Random‐effects models were used to investigate sex differences in both NPS prevalence and severity for all studies combined, NPS total scores, and for specific NPS separately. Furthermore, meta‐regression analyses were conducted to examine the effects of study characteristics and demographic and clinical variables. Result The majority of the included studies were of fair quality and we found no indications of publication bias. When combining all studies, female sex was associated with overall greater NPS severity (k=17, g=0.07[0.01–0.14], p<0.05), while no sex‐related differences were observed for NPS prevalence (k=41, OR =1.07[0.89–1.28], p=0.46). Meta‐regression analyses showed that younger age (QM =6.44, p<0.05) and longer disease duration (QM =4.27, p<0.05) were associated with more prevalent NPS for females with AD dementia. Regarding specific NPS, female sex was associated with more prevalent psychotic symptoms (k=4, OR=1.62[1.12–2.33], p<0.01), aberrant motor behaviors (AMB; k=5, OR=1.61[1.15–2.25], p<0.01), depressive symptoms (k=18, OR=1.56 [1.22–1.99], p<0.001), and delusions (k=11, OR=1.56 1.27–1.92], p<0.001). In addition, female sex was related to more severe depressive symptoms (k=10, g =0.20[0.08–0.29], p<0.001), disinhibition (k=6, g=0.16[0.03–0.28], p<0.05), and AMB (k=6, g=0.14[0.01–0.27], p<0.05). Conclusion Female sex was associated with more severe overall and specific NPS in AD dementia and a higher prevalence of specific NPS. These associations are generally not affected by study setting, measurement type, age, education, disease duration, MMSE score, and APOE status. These findings support the existing literature on sex differences in the clinical manifestation of AD, which could reflect sex‐related differences in neurobiological and psychosocial factors. Determining sex differences in NPS may guide personalized assessment and tailored treatment.

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)0.014
metaresearch head score (Gemma)0.027
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: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.027
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0150.058
Bibliometrics0.0050.005
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.049
GPT teacher head0.318
Teacher spread0.270 · 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
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

Citations13
Published2021
Admission routes1
Has abstractyes

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