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ABS0971 (2025)
RISK ESTIMATION FOR SUBCLINICAL HEART FAILURE USING THE PREVENT CALCULATOR IN PATIENTS WITH AUTOIMMUNE RHEUMATIC DISEASES
Keywords: Cardiovascular system, Quality of life, Atherosclerosis, Prognostic factors
V. Gonzalez-Gonzalez1, O. A. Garza-Flores1, D. A. Galarza-Delgado1, J. R. Azpiri-Lopez2, I. J. Colunga-Pedraza1, J. A. Cardenas-de la Garza1, R. I. Arvizu-Rivera1
1Hospital Universitario “Dr. José Eleuterio González”, Rheumatology, Monterrey, Mexico
2Hospital Universitario “Dr. José Eleuterio González”, Cardiology, Monterrey, Mexico

Background: Rheumatoid arthritis (RA), systemic lupus erythematosus (SLE) and psoriatic arthritis (PsA) are heterogeneous autoimmune diseases with established cardiovascular involvement associated with a higher risk of developing heart failure (HF). Studies have shown a greater risk for HF in rheumatologic patients compared to the general population, however, the calculated risk varies among studies. PREVENT is the first cardiovascular risk calculator to predict the risk of HF.


Objectives: To evaluate the performance of the novel PREVENT cardiovascular risk calculator to detect subclinical HF in patients with inflammatory autoimmune diseases.


Methods: Cross-sectional, descriptive study involving RA, SLE, and PsA patients of a single cardiology-rheumatology preventive clinic in a tertiary-care hospital. This cohort includes patients aged 30-79 who met the ACR/EULAR/CASPAR classification criteria for diagnosing RA, SLE, and PsA, respectively. Exclusion criteria included a previous diagnosis of atherosclerotic cardiovascular disease, overlap syndromes, or pregnancy. The risk of heart failure was assessed using the new 10-year PREVENT calculator and patients were categorized as high risk if they had ≥20%. The result was multiplied by 1.5 according to EULAR 2015/2016 recommendations in the patients with RA. A transthoracic echocardiogram was performed on all participants by a board-certified cardiologist. Distribution was assessed by the Kolmogorov-Smirnov test. Results are shown as frequencies (%) for qualitative variables and mean ± SD or median (p25-p75) according to the distribution of quantitative variables. Cohen’s Kappa coefficient was used to evaluate the agreement between the transthoracic echocardiogram and the PREVENT algorithm to detect subclinical HF.


Results: A total of 238 patients with rheumatic diseases were included, mostly women (n = 204, 85.7%) with a mean age of 52.8 ± 10.1 years. Demographic and clinical characteristics are shown in Table 1. The PREVENT calculator classified 4 (1.6%) patients of the 3 rheumatologic diseases as high-risk category. Employing echocardiography, 144 (60.5%) patients with subclinical HF were identified. By Kappa analysis, a slight concordance was found in patients with RA (κ = 0.033) and poor concordance in patients with SLE (κ = -0.049) between the PREVENT algorithm and the echocardiogram for the classification of high-risk subclinical HF patients. No concordance was found in patients with PsA.


Conclusion: Our study demonstrates that the PREVENT risk algorithm failed to detect a high proportion of patients with subclinical HF and that there is no concordance between the two methods. Echocardiography as part of cardiovascular evaluation may help detect those patients with rheumatologic diseases and subclinical HF.


REFERENCES: [1] Kim CH, Al-Kindi SG, Jandali B, Askari AD, Zacharias M, Oliveira GH. Incidence and risk of heart failure in systemic lupus erythematosus. Heart. 2017 Feb;103(3):227-233. doi: 10.1136/heartjnl-2016-309561.

[2] Ahlers, M.J. et al. (2020) ‘Heart failure risk associated with rheumatoid arthritis–related chronic inflammation’, Journal of the American Heart Association, 9(10). doi:10.1161/jaha.119.014661.

[3] Verhoeven F, Prati C, Demougeot C, Wendling D. Cardiovascular risk in psoriatic arthritis, a narrative review. Joint Bone Spine. 2020 Oct;87(5):413-418. doi: 10.1016/j.jbspin.2019.12.004.

Demographic and clinical characteristics of patients with rheumatic diseases.

Characteristics RA patients (n=152) PsA patients (n=41) SLE patients (n=45)
Age, years, ± SD 55.5 ± 9.2 52.6 ± 8.9 44.6 ± 9.2
Women, n (%) 142 (93.4) 23 (56.1) 39 (86.7)
Diabetes, n (%) 23 (15.1) 6 (14.6) 3 (6.7)
Hypertension, n (%) 51 (33.6) 11 (26.8) 10 (22.2)
Dyslipidemia, n (%) 57 (37.5) 19 (46.3) 6 (13.3)
Active smoking, n (%) 14 (9.2) 12 (29.3) 7 (15.6)
Disease duration, years, median (p25-p75) 7.0 (3.0-14.0) 7.0 (2.0-14.0) 7.0 (4.0-11.8)
DAS28-CRP, ± SD 3.2 ± 1.3 - -
DAPSA, median (p25-p75) - 13.6 (6.5-26.0) -
SLEDAI, median (p25-p75) - - 8.0 (2.0-10.0)
PREVENT, %, median (p25-p75) 3.1 (1.6-7.0) 2.3 (1.1-5.4) 0.7 (0.3-2.1)
Classification risk, n (%) - - -
Low risk 99 (65.6) 29 (74.4) 36 (87.8)
Borderline risk 19 (12.6) 5 (12.8) 4 (9.8)
Intermediate risk 30 (19.9) 5 (12.8) 0 (0.0)
High risk 3 (2.0) 0 (0.0) 1 (2.4)
Subclinical heart failure, n (%) 94 (61.8) 23 (56.1) 27 (60.0)
Subclinical SD, n (%) 16 (10.5) 9 (22.0) 13 (28.9)
Subclinical DD, n (%) 88 (57.9) 19 (46.3) 16 (35.6)

RA, rheumatoid arthritis; PsA, psoriatic arthritis; SLE, systemic lupus erythematosus; SD, standard deviation; DAS28-CRP, 28-joint Disease Activity Score based on C-reactive protein; DAPSA, disease activity in psoriatic arthritis, SLEDAI, systemic lupus erythematosus disease activity index; PREVENT, predicting risk of cardiovascular disease EVENTs; DD, diastolic dysfunction; SD, systolic dysfunction.


Acknowledgements: NIL.


Disclosure of Interests: None declared.

© The Authors 2025. This abstract is an open access article published in Annals of Rheumatic Diseases under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/4.0/ ). Neither EULAR nor the publisher make any representation as to the accuracy of the content. The authors are solely responsible for the content in their abstract including accuracy of the facts, statements, results, conclusion, citing resources etc.


DOI: annrheumdis-2025-eular.B3726
Keywords: Cardiovascular system, Quality of life, Atherosclerosis, Prognostic factors
Citation: , volume 84, supplement 1, year 2025, page 1535
Session: Across diseases (Publication Only)