Diagnostic accuracy of spleen stiffness to evaluate portal hypertension and esophageal varices in chronic liver disease: a systematic review and meta-analysis

Abstract

Objectives To systematically review studies on the diagnostic accuracy of spleen stiffness measurement (SSM) for the detection of clinical significant portal hypertension (CSPH), severe portal hypertension (SPH), esophageal varices (EV), and high-risk esophageal varices (HREV) in patients with chronic liver diseases (CLD). Methods Through a systematic search, we identified 32 studies reporting the accuracy of SSM for the diagnosis of portal hypertension (PH) and/or EV in adults with CLD. A bivariate random-effects model was performed to estimate pooled sensitivity, specificity, likelihood ratio, positive predictive value (PPV), negative predictive value (NPV), and diagnostic odds ratios (DOR). The clinical utility of SSM was evaluated by Fagan plot. Results A total of 32 studies assessing 3952 patients were included in this meta-analysis. The pooled sensitivities of SSM were 0.85 (95% confidence interval (CI), 0.69–0.93) for CSPH; 0.84 (95% CI, 0.75–0.90) for SPH; 0.90 (95% CI, 0.83–0.94) for any EV; and 0.87 (95% CI, 0.77–0.93) for HREV. The pooled specificities of SSM were 0.86 (95% CI, 0.74–0.93) for CSPH; 0.84 (95% CI, 0.72–0.91) for SPH; 0.73 (95% CI, 0.66–0.79) for EV; and 0.66 (95% CI, 0.53–0.77) for HREV. Summary PPV and NPV of SSM for detecting HREV were 0.54 (95% CI, 0.47–0.62) and 0.88 (95% CI, 0.81–0.95), respectively. Conclusions Our meta-analysis suggests that SSM could be used as a helpful surveillance tool in management of CLD patients and was quite useful for ruling out the presence of HREV thereby avoiding unnecessary endoscopy. Key Points • SSM could be used to rule out the presence of HREV in patients with CLD thereby avoiding unnecessary endoscopy. • SSM has significant diagnostic value for CSPH and SPH with high sensitivity and specificity in patients with CLD. • SSM could be used as a helpful surveillance tool for clinicians managing CLD patients.

Features of the immunoreactivity T and B lymphocytes subpopulations and cytokine imbalance in patients with hepatosplenomegaly of different etiology

“…Hepatosplenomegaly is manifested by an increase in the liver and spleen size, occurs often in viral hepatitis, cholestasis, biliary cirrhosis and hereditarily determined storage diseases. Structural and functional disorders of the spleen are caused by pathological changes in the mechanisms of cellular filtration of blood, antigen elimination, hematopoiesis and deposition of blood cells [1,2]. The entry of infectious antigens and cellular debris through the portal vein into the liver from the digestive tract leads to an immediate response of the liver immune cellsmacrophages of the reticuloendothelial system, which are the first line of defense against foreign antigens [3].…”

Management of Portal Hypertension

“…14 Spleen stiffness measurement (SSM) correlates well with the presence of esophageal varices and CSPH, as demonstrated recently in a meta-analysis of 32 studies. 15 This is particularly helpful when liver stiffness is between 15 and 20 kPa. 14 A spleen stiffness <21 kPa rules out CSPH while a value $ 50 kPa rules in CSPH.…”

A Primer to the Diagnostic and Clinical Utility of Spleen Stiffness Measurement in Patients With Chronic Liver Disease

“…Currently, the gold standard for defining CSPH is hepatic venous pressure gradient (HVPG) measurement or esophagogastroduodenoscopy (EGD) to detect the presence of varices. Measurement of the HVPG is invasive and costly 19 . Furthermore, although LSM and platelet count serve as good noninvasive predictors of CSPH, correlation with severity is lost when HVPG is >10 mm Hg, leading to underestimating CSPH and decompensation 17 .…”

“…Measurement of the HVPG is invasive and costly. 19 Furthermore, although LSM and platelet count serve as good noninvasive predictors of CSPH, correlation with severity is lost when HVPG is >10 mm Hg, leading to underestimating CSPH and decompensation. 17 For example, Vermehren et al 7 showed that using ARFI, SSM is more accurate than LSM in predicting large EVs.…”