SYSTEMIC INFLAMMATION IN CO-MORBID METABOLIC SYNDROME AND VITILIGO. A REGRESSION ANALYSIS OF RISK FACTORS!
Keywords:
Metabolic syndrome, Vitiligo, Logistic RegressionAbstract
Objective: Metabolic syndrome (MetS) often comorbid vitiligo. Why some patients with vitiligo develop MetS while others do not remain to be elucidated. This study aimed to identify independent risk factors for MetS development in vitiligo patients.
Methods: In this prospective study, disease characteristics (disease duration, severity, and subtype) and high-sensitivity c-reactive protein (hs-CRP) were compared between vitiligo patients (n=100) with and without MetS. Age-gender matched subjects (n=150) were controls. Multivariate logistic regression was done to identify independent risk factors for MetS after adjusting for potential confounders (like waist circumference, basal metabolic rate, serum lipids, blood pressure and fasting blood sugar). The performance of these parameters (hs-CRP, age, disease duration and severity) in predicting MetS development was ascertained by the area under the receiver operating characteristic curve (ROC).
Results: Vitiligo patients with MetS had a significantly longer (P<0.001) disease duration as compared to those without MetS (56±16 versus 14±12 months). On regression analysis, inflammatory markers (hs-CRP) had significantly higher odds (OR=5.1) as compared to demographic factors like gender (OR=3.1) and disease factors like disease duration (OR=2.4) and disease severity (OR=1.8) of developing metabolic syndrome. On ROC curve analysis, the performance of these parameters for MetS was hs-CRP>VASI score>disease duration >increasing age (AUC=0.952, 0.905, 0.851 and 0.697, respectively). The cut-off value of hs-CRP was 6.42 ug/mL.
Conclusion: Elevated High-sensitivity C-reactive protein significantly better predicts MetS development in vitiligo as compared to demography (age) and vitiligo disease characteristics (duration and severity).
Downloads
Published
How to Cite
Issue
Section
Copyright (c) 2024 Dr Pavan Kumar Singh, Dr Kanishk Kaushik, Prof Rahul Bhargava
This work is licensed under a Creative Commons Attribution 4.0 International License.
The publication is licensed under CC By and is open access. Copyright is with author and allowed to retain publishing rights without restrictions.