Evidence map›Paper›PMID 41716847›Full record

ArticleProceedings. IEEE International Conference on Bioinformatics and Biomedicine2025

Uncovering the Role of Neuropsychiatric Symptoms in Cognitive Impairment Progression.

Eunji Jeon, Muskan Garg, Xingyi Liu, Maria Vassilaki, Jennifer St Sauver, Ronald C Petersen, Sunghwan Sohn

Abstract read
In one paragraph

Article in Proceedings. IEEE International Conference on Bioinformatics and Biomedicine, 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

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Eunji JeonDepartment of Artificial Intelligence and Informatics, Mayo Clinic, Rochester, USA.
Muskan GargDepartment of Artificial Intelligence and Informatics, Mayo Clinic, Rochester, USA.
Xingyi LiuDepartment of Artificial Intelligence and Informatics, Mayo Clinic, Rochester, USA.
Maria VassilakiDepartment of Quantitative Health Sciences, Mayo Clinic, Rochester, USA.
Jennifer St SauverDepartment of Quantitative Health Sciences, Mayo Clinic, Rochester, USA.
Ronald C PetersenDepartment of Neurology, Mayo Clinic, Rochester, USA.
Sunghwan SohnDepartment of Artificial Intelligence and Informatics, Mayo Clinic, Rochester, USA.

Funding

SUPPLEMENT TO ALZHEIMERS DISEASE PATIENT REGISTRYU01AG006786 · NIA · MAYO CLINIC ROCHESTER · PI GRAFF-RADFORD, JONATHAN, JACK, CLIFFORD R. · 1986 to 2023
$49.6M
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 AG090341NIA NIH HHS U01 AG006786
6 · The paper itself

Abstract

With the growing prevalence of cognitive impairment, early detection has become increasingly critical. Prior studies have examined the association between neuropsychiatric symptoms (NPS) and cognitive impairment, identifying potential predictive relationships. However, they hardly evaluated the heterogeneous relationships between serial patterns of NPS and evolving cognition status of the patients. To address this limitation, we investigate the statistical causal relationship between NPS and cognitive impairment, as well as the dynamic changes in their predictive effects over time, with a specific focus on sex differences. Our approach accounts for the fluctuating nature of NPS and varying follow-up durations across participants by implementing a bootstrap strategy that repeatedly samples a fixed number of visits per participant in a temporal order. Then, we apply causal discovery techniques and counterfactual framework-based causal inference methods to estimate the independent effects of NPS over time. Our findings highlight apathy as a key predictive symptom of cognitive impairment. Moreover, its predictive effect peaks earlier in females than in males, indicating that early-stage tracking is particularly informative in female participants. This suggests sex-specific monitoring strategies may improve early detection and intervention of cognitive impairment.

Indexed as

causal discoverycausal inferencecognitive impairmentneuropsychiatric symptom

Identifiers

PMID41716847
PMCPMC12914708

What Socratic holds

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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.