Abstract
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•Esophageal Varices is one complication of chronic liver disease that leads to deaths globally due to hemorrhage.•The prediction of presence the Esophageal Varices is essential to avoid bleeding for patients.•Now the only diagnostic method for Esophageal Varices by the upper gastrointestinal endoscopy but it has many disadvantages.•Only ten variables are the most significant for diagnosing the varices: PLT, Stiffness, PC, liver texture, spleen, HCV-RNA, Albumin, gender, Total bilirubin, and PV diameter.•We Evaluated the effectiveness of several noninvasive markers for predicting Varices.•We Introduced a novel (EVP) index with acceptable performance for diagnosing Varices and compared with the exist, it could save operating the upper endoscopic by nearly 46.5%.
Esophageal Varices (EVs) is one of the major dangerous complications of liver fibrosis. Upper Gastrointestinal (UGI) Endoscopy is necessary for its diagnosis. Repeated examinations for EVs screening severely burden endoscopic units in terms of cost and other side implications; moreover, the lack of public health resources in rural areas and primary hospitals should be considered, particularly in developing countries. So, an accurate noninvasive marker for EV is highly needed for liver disease patients.
This study sought to evaluate the values of several indices to determine how adequate are they in predicting EV and build a novel accurate prediction index.
Five thousand and thirteen patients were enrolled. The laboratory tests, abdominal ultrasonography, liver stiffness measurement using Fibro-scan, and UGI endoscopy were performed. Ten common indices: Fib-4 score, AST-to-platelet ratio index, Fibrosis index, AST/ALT ratio Varices Prediction Rule, Baveno VI, APRI-Fib4 Combo, King score, “Model for End-Stage Liver Disease”, and Lok Score were calculated. The significant predictors for EVs were identified by using “P-value Correlation-based Filter Selection” method, where a novel Egyptian Varices Prediction (EVP) index was developed using binary logistic regression. The diagnostic performance was evaluated by some parameters and the Area Under Curve (AUC).
EVP Index was correlated to EVs at 0.5; it achieved higher performance (AUC 0.788, accuracy 73.3%, and sensitivity 78%) than the other indices at a cutoff point of 0.423.
EVP Index was a good noninvasive predictor. It had an acceptable performance for diagnosing EVs and it was only required regular laboratory tests and imaging data. It can provide a tool for classifying or arranging the patients according to the degree pre-emptive for selective endoscopy and the degree of severity. Also, it will enable clinicians to concentrate on one marker instead of a wide set of parameters.