Prediction risk chart for scleroderma digital ulcers: A composite predictive model based on capillaroscopic, demographic and clinico-serological parameters

BACKGROUND: Digital ulcers (DU) affect 50% of systemic sclerosis (SSc) patients, representing a challenging clinical problem. Despite a high negative predictive value, capillaroscopic scores proposed to select patients at risk for DU show an inadequate positive predictive value, especially in patients without previous DU. AIM OF THIS STUDY: To increase the predictive value for DU development of capillaroscopy, through a predictive risk chart taking into account capillaroscopic, demographic, and clinico-serological parameters. PATIENTS AND METHODS: Two hundred and nineteen unselected SSc patients from 8 Italian Rheumatology Centers were consecutively enrolled during a 6-month period. Demographic, clinical, serological and instrumental data and capillaroscopy skin ulcers risk index (CSURI) were collected. RESULTS: A multivariate logistic regression analysis showed a significant positive association between DU appearance and male gender, DU history, altered CSURI, and ESR. A prediction risk chart of the development of DU within 6 months were built on the basis of the above parameters. According to the risk level, four risk classes were identified: low (≤19.3%); medium (>19.3%, ≤58.6%); high (>58.6%, ≤89.2%), and very high risk (>89.2%). CONCLUSIONS: The systematic evaluation of the above parameters can be helpful to identify patients at risk to develop DU optimizing preventive vasoactive therapy.