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Record W4411883198 · doi:10.1186/s41927-025-00538-3

Risk factors and predictive model for mild cognitive impairment in elderly patients with rheumatoid arthritis

2025· article· en· W4411883198 on OpenAlexaboutno aff
Jun Yan, Hua Guo, Pei Chen, Yue Du, Juan Li, Nan Ye

Bibliographic record

VenueBMC Rheumatology · 2025
Typearticle
Languageen
FieldMedicine
TopicRheumatoid Arthritis Research and Therapies
Canadian institutionsnot available
Fundersnot available
KeywordsRheumatoid arthritisMedicineCognitive impairmentCognitionPhysical therapyInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Rheumatoid arthritis (RA) is a chronic autoimmune disorder characterized by joint destruction and systemic inflammation, both of which significantly impair patients' quality of life. Mild cognitive impairment (MCI), a reversible precursor to dementia, is increasingly prevalent among elderly RA patients. Early identification of MCI in this population allows for timely interventions to slow cognitive decline. OBJECTIVE: This study aims to identify independent risk factors for MCI in elderly patients with RA and to develop a predictive nomogram. METHODS: We enrolled 378 elderly RA patients, aged 60 to 80 years, from Xi'an Fifth Hospital between December 2023 and December 2024. Cognitive function was assessed using the Montreal Cognitive Assessment (MoCA), with scores ranging from 20 to 26 indicating MCI. We analyzed demographic, clinical, and laboratory data to identify risk factors through logistic regression and constructed a nomogram. The model's performance was evaluated using receiver operating characteristic (ROC) curves, calibration plots, and decision curve analysis (DCA). RESULTS: Among the 378 patients, 94 (24.87%) were classified in the RA-MCI group. Multivariate analysis identified the course of disease (COD) (OR = 1.07, 95% CI: 1.03-1.10), elevated Disease Activity Score-28 (DAS28) (OR = 1.31, 95% CI: 1.13-1.53), high C-reactive protein (CRP) levels (OR = 1.01, 95% CI: 1.01-1.02), and osteoporosis (OP) (OR = 1.88, 95% CI: 1.14-3.13) as independent risk factors. The nomogram demonstrated moderate discrimination (AUC = 0.750, 95% CI: 0.696-0.805) and clinical utility. CONCLUSION: The COD, OP, DAS28, and CRP levels are key predictors of MCI in elderly RA patients. The proposed nomogram provides a practical tool for early risk stratification, facilitating targeted interventions to delay cognitive decline. TRIAL REGISTRATION: This study conformed to the principles outlined in the Declaration of Helsinki and received approval from the Medical Ethics Committee of Xi'an Fifth Hospital (Approval No.: [2023] Ethics Review 55). Additionally, the trial was registered with the Chinese Clinical Trial Registry (Registration No.: ChiCTR2300077337, Registration Date: 2023-11-01). Written informed consent was obtained from all individual participants included in the study.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.062
Threshold uncertainty score0.944

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.011
GPT teacher head0.262
Teacher spread0.251 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations0
Published2025
Admission routes1
Has abstractyes

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