Download PDF
Open Access
CC BY 4.0 · Thromb Haemost
DOI: 10.1055/a-2698-3739
Coagulation and Fibrinolysis

The Impact of NOACS versus VKAS on Absolute and Relative Cognitive Function Decline Over Time: A Machine Learning Approach

Authors

  • Sergio Ferrantelli   ‡

    1   Internal Medicine and Stroke Care Ward, University of Palermo, Palermo, Italy
    2   Department of Health Promotion, Mother and Child Care, Internal Medicine and Medical Specialities, University of Palermo, Palermo, Italy

  • Mario Daidone    ‡

    1   Internal Medicine and Stroke Care Ward, University of Palermo, Palermo, Italy
    2   Department of Health Promotion, Mother and Child Care, Internal Medicine and Medical Specialities, University of Palermo, Palermo, Italy

  • Giuseppe Armentaro   

    3   Department of Medical and Surgical Sciences, University Magna Græcia of Catanzaro, Campus Universitario di Germaneto, Catanzaro, Italy

  • Gaetano Pacinella

    1   Internal Medicine and Stroke Care Ward, University of Palermo, Palermo, Italy
    2   Department of Health Promotion, Mother and Child Care, Internal Medicine and Medical Specialities, University of Palermo, Palermo, Italy

  • Stefania Scaglione

    1   Internal Medicine and Stroke Care Ward, University of Palermo, Palermo, Italy
    2   Department of Health Promotion, Mother and Child Care, Internal Medicine and Medical Specialities, University of Palermo, Palermo, Italy

  • Anna M. Ciaccio

    1   Internal Medicine and Stroke Care Ward, University of Palermo, Palermo, Italy
    2   Department of Health Promotion, Mother and Child Care, Internal Medicine and Medical Specialities, University of Palermo, Palermo, Italy

  • Edoardo Pirera

    1   Internal Medicine and Stroke Care Ward, University of Palermo, Palermo, Italy
    2   Department of Health Promotion, Mother and Child Care, Internal Medicine and Medical Specialities, University of Palermo, Palermo, Italy

  • Carlo D. Maida

    1   Internal Medicine and Stroke Care Ward, University of Palermo, Palermo, Italy
    2   Department of Health Promotion, Mother and Child Care, Internal Medicine and Medical Specialities, University of Palermo, Palermo, Italy

  • Giuseppe Miceli

    1   Internal Medicine and Stroke Care Ward, University of Palermo, Palermo, Italy
    2   Department of Health Promotion, Mother and Child Care, Internal Medicine and Medical Specialities, University of Palermo, Palermo, Italy

  • Giuliana Rizzo

    1   Internal Medicine and Stroke Care Ward, University of Palermo, Palermo, Italy
    2   Department of Health Promotion, Mother and Child Care, Internal Medicine and Medical Specialities, University of Palermo, Palermo, Italy

  • Vittoriano Della Corte

    1   Internal Medicine and Stroke Care Ward, University of Palermo, Palermo, Italy
    2   Department of Health Promotion, Mother and Child Care, Internal Medicine and Medical Specialities, University of Palermo, Palermo, Italy

  • Domenico Di Raimondo

    1   Internal Medicine and Stroke Care Ward, University of Palermo, Palermo, Italy
    2   Department of Health Promotion, Mother and Child Care, Internal Medicine and Medical Specialities, University of Palermo, Palermo, Italy

  • Daniele Pastori   ‡‡

    4   Department of Clinical Internal, Anesthesiological and Cardiovascular Sciences, Sapienza University of Rome, Rome, Italy
    5   IRCCS Neuromed, Pozzilli, Italy

  • Angela Sciacqua   ‡‡

    3   Department of Medical and Surgical Sciences, University Magna Græcia of Catanzaro, Campus Universitario di Germaneto, Catanzaro, Italy

  • Antonino Tuttolomondo   ‡‡

    1   Internal Medicine and Stroke Care Ward, University of Palermo, Palermo, Italy
    2   Department of Health Promotion, Mother and Child Care, Internal Medicine and Medical Specialities, University of Palermo, Palermo, Italy
    • on behalf of MEDIREG (Mediterranean Research Group)
Further Information
  Permissions and Reprints


Graphical Abstract

Abstract

Background

Atrial fibrillation (AF) is the most common arrhythmia in older adults and is associated with an increased risk of cognitive impairment and dementia, even in patients without prior stroke. Nonvitamin K antagonist oral anticoagulants (NOACs) offer a better safety profile than vitamin K antagonists (VKAs), but their cognitive benefit remains uncertain.

Aim

To assess the impact of NOACs versus VKAs on cognitive decline in elderly AF patients using a machine learning approach.

Methods

This multicenter prospective cohort study included 983 AF outpatients enrolled between 2008 and 2022 at the Geriatrics Department, University of Catanzaro, and the ProMISE Department, University of Palermo. Stroke and bleeding risks were assessed using CHA2DS2-VASc and HAS-BLED scores. Cognitive function was evaluated using the Mini-Mental State Examination (MMSE). Cognitive decline was defined as a decrease in MMSE score between baseline and follow-up. Patients with prior anticoagulant therapy (OAT), severe dementia, or comorbidities affecting cognition were excluded. Multivariable logistic regression and a random forest classifier were used to assess whether anticoagulant type independently predicted cognitive decline. Class imbalance was addressed using both class-weighted learning and the synthetic minority over-sampling technique (SMOTE), with model performance evaluated through repeated stratified cross-validation and threshold optimization.

Results

At baseline, cognitive performance was comparable between groups (p = 0.11). After a mean follow-up of 7.2 ± 3.4 years, MMSE scores declined significantly more in VKA-treated patients (−1.7 vs. −0.3 points, p < 0.001). In logistic regression, NOAC use was independently associated with a lower risk of cognitive decline (odds ratio: 0.322; 95% confidence interval: 0.221–0.469; p < 0.0001). The random forest classifier achieved a mean cross-validated AUC of 0.8719 (standard deviation: 0.0273) and a test-set AUC of 0.880. Threshold adjustment and SMOTE improved sensitivity (recall increased: 0.47–0.84), with a precision–recall AUC of 0.763. Permutation importance analysis identified “OAT” as the top predictor. Predicted probabilities of cognitive decline were significantly higher in VKA users (median = 0.70) than in NOAC users (median = 0.09), confirmed by a Kolmogorov–Smirnov test (KS = 0.385, p < 0.001).

Conclusion

NOAC use is associated with a lower predicted probability of cognitive decline, suggesting potential cognitive benefits over VKAs.

Keywords

atrial fibrillation - cognitive impairment - dementia - machine learning - NOAC - VKA

Data Availability Statement

The data and images used in this study are available from the corresponding author upon reasonable request.


Contributors' Statement

S.F., M.D. and G.A. projected the study, coordinated the research group, and contributed to manuscript preparation and revisions, S.F. performed the statistical analysis. G.P., S.S., C.D.M., G.M. and D.D.R. collaborated to collect and process data. D.P., A.S. and A.T. collaborated on supervision and manuscript revisions.


Ethical Approval

All patients gave their informed consent to the study.


Informed Consent

All patients expressed their informed consent to participate in the study and supplied their personal information for publication.


‡ These authors contributed equally to this article.


‡‡ These authors share last authorship.


 




Publication History

Received: 14 March 2025

Accepted: 11 August 2025

Accepted Manuscript online:
10 September 2025

Article published online:
25 September 2025

© 2025. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. (https://creativecommons.org/licenses/by/4.0/)

Georg Thieme Verlag KG
Oswald-Hesse-Straße 50, 70469 Stuttgart, Germany