Machine learning predicts portal vein thrombosis after splenectomy in patients with portal hypertension: Comparative analysis of three practical models

Figure 1 Flow chart and correlation chart. A: Flow diagram of patient selection and study design; B: Correlation matrix between candidate variables. The size and color of the circle in the matrix reflect the correlation between the corresponding variables. The darker the blue, the stronger the positive correlation between variables, and the darker the red, the stronger the negative correlation between variables. HCV: Hepatitis C virus; HBV: Hepatitis B virus; PLT1 and PLT3: Platelet counts on the first and third days after operation; PVT: Portal vein thrombosis; GLM: Generalized linear model; LSM: Least absolute shrinkage and selection operator model; RFM: Random forest model; RBC: Red blood cells; HLB: Hemoglobin; WBC: White blood cells; N: Neutrophil count; L: Lymphocyte count; NLR: Neutrophil to lymphocyte ratio; PLT: Platelet count; PLR: Platelet to lymphocyte ratio; PT: Prothrombin time; PTA: Prothrombin activity; INR: International normalized ratio; FIB: Fibrinogen; APTT: Activated partial thromboplastin time; ALT: Alanine aminotransaminase; AST: Aspartate aminotransaminase; ALB: Serum albumin; TBIL: Total serum bilirubin; Child: Child-Pugh grade; EGV: Esophageal and gastric varices; SPT: Spleen thickness; DPV: Diameter of the portal vein; PBT: Preoperative blood transfusion; De: Devascularization; PPER1: Platelet elevation rate at postoperative day 1; PPER3: Platelet elevation rate at postoperative day 3.