Development and validation of a prognostic nomogram for predicting mortality risk in adult rheumatoid arthritis: an analysis of NHANES 1999–2018 data DOI Creative Commons
Xiao Chen,

Haibo Gong,

Jing Chen

и другие.

Frontiers in Immunology, Год журнала: 2025, Номер 16

Опубликована: Апрель 17, 2025

Objective This study aims to identify potential independent risk factors for rheumatoid arthritis (RA)- related mortality and develop a nomogram model predict individualized risk. Methods included 310 RA patients from the National Health Nutrition Examination Survey (NHANES) during 1999 - 2018. We applied LASSO, univariate, multivariate logistic regression analyses determine in training cohort construct model. Calibration plots evaluated nomogram’s accuracy. Finally, we established clinical utility through DCA performed internal validation within cohort. Results Of patients, 140 experienced deaths, corresponding rate of 45.16%. Within cohort, age, heart failure, systemic inflammatory response index (SIRI) emerged as predictors mortality. A model, constructed multivariable analysis, demonstrated an AUC 0. 852 (95% CI: 799 904) 904 846 963) The calibration curve revealed strong agreement between predicted actual probabilities. In both cohorts, highlighted significant net benefits predicting Conclusions demonstrates SIRI’s ability with good discrimination utility. gives clinicians simple tool quickly high promoting early intervention, personalized treatment, better prognosis.

Язык: Английский

NUTRITIONAL STATUS IN PATIENTS WITH LATE-ONSET RHEUMATOID ARTHRITIS: A CROSS-SECTIONAL STUDY DOI Creative Commons
Abdulvahap Kahveci, Sultan Keskin Demircan

Anti-Aging Eastern Europe, Год журнала: 2025, Номер 4(1), С. 34 - 44

Опубликована: Апрель 2, 2025

Introduction. This study aimed to investigate the nutritional status of older patients with rheumatoid arthritis (RA) classified as earlier-onset (EORA) and late-onset (LORA). Methods. The cross-sectional included 145 RA (72 LORA, 73 EORA). Clinical demographic data, were recorded. was determined using Mini-Nutritional Assessment (MNA), Prognostic Nutritional Index (PNI), Controlling Status (CONUT), Geriatric Risk (GNRI) indices. rheumatologic data EORA LORA compared. Patients in both groups divided into two according DAS28-CRP index (cut off= 3.2), cross comparisons made Also, prediction disease activity by malnutrition GNRI scale evaluated ROC analysis. Results. highest prevalence 20.5%, measured CONUT score. mean score statistically higher group than (128.38±15.36 vs. 121.96±21; p=0.040), a significant difference observed between categories, indicating more (p=0.009). In cross-comparisons, showed lower values high compared those without, patient (p = 0.023 for EORA; p 0.011 LORA). However, on analysis, able predict only [AUC (CI):0.594 (0.451-0.737); p=0.041]. Conclusion. present demonstrated that prevalent Furthermore, it revealed time onset should be conjunction during assessment patients.

Язык: Английский

Процитировано

0

Development and validation of a prognostic nomogram for predicting mortality risk in adult rheumatoid arthritis: an analysis of NHANES 1999–2018 data DOI Creative Commons
Xiao Chen,

Haibo Gong,

Jing Chen

и другие.

Frontiers in Immunology, Год журнала: 2025, Номер 16

Опубликована: Апрель 17, 2025

Objective This study aims to identify potential independent risk factors for rheumatoid arthritis (RA)- related mortality and develop a nomogram model predict individualized risk. Methods included 310 RA patients from the National Health Nutrition Examination Survey (NHANES) during 1999 - 2018. We applied LASSO, univariate, multivariate logistic regression analyses determine in training cohort construct model. Calibration plots evaluated nomogram’s accuracy. Finally, we established clinical utility through DCA performed internal validation within cohort. Results Of patients, 140 experienced deaths, corresponding rate of 45.16%. Within cohort, age, heart failure, systemic inflammatory response index (SIRI) emerged as predictors mortality. A model, constructed multivariable analysis, demonstrated an AUC 0. 852 (95% CI: 799 904) 904 846 963) The calibration curve revealed strong agreement between predicted actual probabilities. In both cohorts, highlighted significant net benefits predicting Conclusions demonstrates SIRI’s ability with good discrimination utility. gives clinicians simple tool quickly high promoting early intervention, personalized treatment, better prognosis.

Язык: Английский

Процитировано

0