Mauro Giuffrè1, Daniele Macor2, Flora Masutti3, Cristiana Abazia3, Fabio Tinè3, Giorgio Bedogni4, Claudio Tiribelli4, Lory Saveria Crocè5. 1. Dipartimento Universitario Clinico Di Scienze Mediche Chirurgiche e Della Salute, Università Degli Studi Di Trieste, Italy. Electronic address: gff.mauro@gmail.com. 2. Dipartimento Universitario Clinico Di Scienze Mediche Chirurgiche e Della Salute, Università Degli Studi Di Trieste, Italy. 3. Clinica Patologie Fegato, Azienda Sanitaria Universitaria Integrata Di Trieste, Italy. 4. Fondazione Italiana Fegato, Italy. 5. Dipartimento Universitario Clinico Di Scienze Mediche Chirurgiche e Della Salute, Università Degli Studi Di Trieste, Italy; Clinica Patologie Fegato, Azienda Sanitaria Universitaria Integrata Di Trieste, Italy; Fondazione Italiana Fegato, Italy.
Abstract
INTRODUCTION AND OBJECTIVES: Recent findings pointed out that even low-risk esophageal varices (EVs) are markers of severe prognosis. Accordingly, we analyzed spleen stiffness (SS) as a non-invasive method to predict EVs of any grade in a cohort of patients with compensated liver cirrhosis. METHOD: We measured SS and liver stiffness (LS) using point-Shear-Wave Elastography (pSWE) with Philips Affiniti 70 system in 210 cirrhotic patients who had undergone endoscopic screening for EVs. We compared SS and LS predictive capability for EVs of any grade. RESULTS: SS was higher in cirrhotic patients with EVs if compared to patients without EVs (p<0.001). The cut-off analysis detected 31kPa (100% sensitivity and negative predictive value) as the value to rule-out EVs and 69kPa (100% specificity and positive predictive value) to rule-in EVs. Besides, we developed the Spleen Stiffness Probability Index (SSPI), that can provide a probability of presence/absence of EVs. SSPI was the best model according to all discriminative and calibration metrics (AIC=120, BIC=127, AUROC=0.95, Pseudo-R2=0.74). SS demonstrated higher correlation with spleen bipolar diameter and spleen surface (r=0.52/0.55) if compared to LS (r=0.30/0.25) - and with platelet count as well (r=0.67 vs r=0.4). CONCLUSION: SS showed significantly higher performance than other parameters, proving to be the best non-invasive test in the screening of EVs: by directly applying SS cut-off of 31kPa, our department could have safely avoided endoscopy in 36% of patients. Despite cut-off analyses, it was possible to create a probability model that could further stratify low-risk from high-risk patients (for any grade of EVs).
INTRODUCTION AND OBJECTIVES: Recent findings pointed out that even low-risk esophageal varices (EVs) are markers of severe prognosis. Accordingly, we analyzed spleen stiffness (SS) as a non-invasive method to predict EVs of any grade in a cohort of patients with compensated liver cirrhosis. METHOD: We measured SS and liver stiffness (LS) using point-Shear-Wave Elastography (pSWE) with Philips Affiniti 70 system in 210 cirrhoticpatients who had undergone endoscopic screening for EVs. We compared SS and LS predictive capability for EVs of any grade. RESULTS: SS was higher in cirrhoticpatients with EVs if compared to patients without EVs (p<0.001). The cut-off analysis detected 31kPa (100% sensitivity and negative predictive value) as the value to rule-out EVs and 69kPa (100% specificity and positive predictive value) to rule-in EVs. Besides, we developed the Spleen Stiffness Probability Index (SSPI), that can provide a probability of presence/absence of EVs. SSPI was the best model according to all discriminative and calibration metrics (AIC=120, BIC=127, AUROC=0.95, Pseudo-R2=0.74). SS demonstrated higher correlation with spleen bipolar diameter and spleen surface (r=0.52/0.55) if compared to LS (r=0.30/0.25) - and with platelet count as well (r=0.67 vs r=0.4). CONCLUSION: SS showed significantly higher performance than other parameters, proving to be the best non-invasive test in the screening of EVs: by directly applying SS cut-off of 31kPa, our department could have safely avoided endoscopy in 36% of patients. Despite cut-off analyses, it was possible to create a probability model that could further stratify low-risk from high-risk patients (for any grade of EVs).
Authors: Marten Schulz; Moritz Kleinjans; Pavel Strnad; Münevver Demir; Theresa M Holtmann; Frank Tacke; Alexander Wree Journal: Diagnostics (Basel) Date: 2021-03-31