Evidence map›Paper›PMID 41402904›Full record

ArticleBiology of sex differences2025

Sex differences in cognitive decline and impairment: a scoping review in informatics literature.

Muskan Garg, Xingyi Liu, Jie Lin, Maria Vassilaki, Ronald C Petersen, Jennifer St Sauver, Ekta Kapoor, Sunghwan Sohn

Abstract readScoping Review
In one paragraph

Article in Biology of sex differences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Muskan GargDepartment of Artificial Intelligence & Informatics, Mayo Clinic, Rochester, MN, USA.
Xingyi LiuDepartment of Artificial Intelligence & Informatics, Mayo Clinic, Rochester, MN, USA.
Jie LinDepartment of Artificial Intelligence & Informatics, Mayo Clinic, Rochester, MN, USA.
Maria VassilakiDepartment of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA.
Ronald C PetersenDepartment of Neurology, Mayo Clinic, Rochester, MN, USA.
Jennifer St SauverDepartment of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA.
Ekta KapoorDivision of General Internal Medicine, Mayo Clinic, Rochester, MN, USA.
Sunghwan SohnDepartment of Artificial Intelligence & Informatics, Mayo Clinic, Rochester, MN, USA. sohn.sunghwan@mayo.edu.

Funding

Early Detection of Mild Cognitive Impairment, Alzheimer’s Disease and Other Dementias using EHRR01AG068007 · NIA · MAYO CLINIC ROCHESTER · PI Yonas E Geda, Sunghwan Sohn · 2020 to 2026
$3.8M
Advancing women’s care in Alzheimer’s disease and other dementias through EHRRF1AG090341 · NIA · MAYO CLINIC ROCHESTER · PI SOHN, SUNGHWAN · 2025 to 2025
$3.4M
Interdisciplinary Infrastructure for Aging Research: Rochester Epidemiology ProjectR33AG058738 · NIA · MAYO CLINIC ROCHESTER · PI LEBRASSEUR, NATHAN K, OLSON, JANET E · 2020 to 2022
$2.4M
NIA NIH HHS R01 AG068007NIA NIH HHS R33 AG058738NIA NIH HHS RF1 AG090341NIH HHS R01 AG068007 and RF1 AG090341
6 · The paper itself

Abstract

objectivesA scoping review was conducted to investigate knowledge gaps in the informatics research literature regarding sex differences in cognitive decline and impairment, identifying existing studies and areas requiring further exploration. METHODS AND MATERIALS: Our scoping review follows the Preferred Reporting Items for Systematic reviews and Meta-Analysis Extension for Scoping Reviews (PRISMA - ScR) guidelines. We searched Ovid and other databases (APA PsychInfo, EMB Reviews, and Embase) for studies on sex differences in cognitive decline and impairment, focusing on peer-reviewed informatics journals and conference proceedings from 2000 to 2025. The selected manuscripts were analyzed based on metadata statistics, study attributes, and thematic content.

resultsA total of 17 full articles met the inclusion criteria. Most studies were conducted in North America (n = 7) and the European Union (n = 5). More than half of the studies were published after 2020 (n = 10). Our analyses highlight key aspects of selected studies, including bibliometric metadata, study attributes (e.g., study types, methods, and data sources), and thematic findings. Statistical modeling (n = 8) and machine learning (n = 4) are the most widely used study methods. Majority (n = 11) of the publications are single-site studies, while the other multi-site collaborations (n = 6) have emerged among hospitals, academic institutions, and research institutions. DISCUSSION: Sex-specific disparities in cognitive decline and impairment remain a critical issue in healthcare. Most informatics research has primarily concentrated on identifying generic sex differences in cognitive decline and impairment progression, rather than exploring the complex underlying mechanisms such as observational studies with causal analysis. While these studies are valuable, they lack a holistic approach to understanding sex-specific disparities.

conclusionThere is a significant gap in using informatics to understand how biological, social, and behavioral factors contribute to sex-specific disparities in cognitive decline and impairment. This limitation underscores the need for more comprehensive informatics research that goes beyond mere identification to find the root cause of these disparities in healthcare.

Indexed as

Cognitive DysfunctionFemaleHumansMaleSex FactorsAlzheimer’s diseaseClinical decision support systemsCognitive declineCognitive impairmentDementiaSex disparities

Identifiers

PMID41402904
PMCPMC12822129

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.