ABSTRACT
OBJECTIVES: To estimate digit circumference and the impact of sex and body mass index (BMI) for the calculation of the Leeds Dactylitis Index (LDI) in psoriatic arthritis (PsA) patients with bilateral dactylitis. METHODS: Digit circumference of the hands and the foot were measured with a dactylometer and were studied according to sex and BMI (divided in 4 weight categories) in healthy Portuguese subjects, using Student's t-test and One-way ANOVA, respectively. The effect size of sex and BMI were calculated using Cohen's d test and Eta squared, respectively. Multiple linear regression was used to calculate the effect of sex and BMI, as well as their interaction, to create a formula to predict digit circumference. RESULTS: Fifty-nine participants (33 women, 26 men) with a mean BMI of 24.8 were included. Men's mean digit circumferences were statistically higher than those of women (p<0.001), with a large sex effect size in most of the digits. Differences in the mean circumference between the four BMI categories were statistically significant (p<0.05) for all digits, with a large BMI effect size. Sex and BMI were independent variables to predict mean digit circumference (p<0.001). A new tool (based on regression analysis) allowing to estimate the circumference of digits for males and females of different BMIs is presented. CONCLUSIONS: Our data allows the calculation of digit circumference for males and females of different BMIs in the Portuguese population; and shows that BMI influences digital circumference supporting BMI inclusion in LDI references tables.
Subject(s)
Arthritis, Psoriatic , Male , Humans , Female , Body Mass Index , Arthritis, Psoriatic/diagnosis , Hand , Regression Analysis , Waist CircumferenceABSTRACT
Objective: We aim to study association between neutrophile to lymphocyte (NLR) and platelet to lymphocyte (PLR) ratios and disease activity, and their value to predict bDMARD response. Methods: A set of spondylarthritis (SpA) patients under bDMARD registered in the Reuma.pt registry was studied. Sociodemographic, clinical and laboratorial variables were assessed on bDMARD initiation, 6, 12, 18 and 24 months (M) thereafter. Univariable and multivariable generalized estimation equations models assessed associations with disease activity. The NLR and PLR predictive value was assessed using univariable and multivariable logistic regression models. Results: A total of 170 patients were included. Most were male (54.7%), with a predominantly axial phenotype (84.7%). Significant associations were observed between NLR [B=1.55, 95% confidence interval (CI) = (1.38; 1.74)] and PLR [(B=1.16, 95% CI = (1.09; 1.24)] with ASDAS-CRP (p < 0.001). Both baseline ratios predicted ∆ ASDAS-CRP ≥ 1.1 at 6 months [OR = 2.20, 95% CI = (1.21, 4.00) for NLR; OR = 1.02, 95% CI = (1.01, 1.04) for PLR, p < 0.01)]. PLR was a significant predictor of ∆ ASDAS-CRP ≥ 1.1 in all timepoints [OR (12 M) = 1.02, 95% CI = (1.00, 1.03), p < 0.05; OR (18M) = 1.02, 95% CI = (1.01, 1.03), p < 0.001; OR (24M) = 1.01, 95% CI = (1.01, 1.02), p < 0.01]. Conclusion: NLR and PLR were associated with disease activity during the follow up of these patients. They seem to be significant predictors of therapeutic response to bDMARD in naïve SpA patients.