Clinical characteristics of patients with or without tolvaptan
In this study, we divided the 113 LC patients into tolvaptan treatment group or non-treatment group. Table 1 shows the comparison of baseline clinical characteristics and laboratory variables between patients with and without tolvaptan treatment. In the tolvaptan treatment group, dose of diuretic drugs, the Child-Pugh score, ALBI score, and serum copeptin, NGAL and L-FABP levels were significantly increased, while BMI, PMI, serum albumin levels were reduced, suggesting that patients treated with tolvaptan demonstrated more advanced liver diseases. In contrast, there were no obvious differences in age, gender, prevalence of HCC, creatinine, BUN, eGFR, ZAG and cystatin C between the two groups (Table 1).
Correlation of copeptin, ZAG, cystatin C, NGAL and L-FABP to clinical parameters in all patients
The correlations between copeptin, ZAG, cystatin C, NGAL or L-FABP and clinical parameters in LC patients are shown in Table 2. Copeptin was strongly correlated with mainly hepatic function including albumin (p=0.007; Figure 1-D), Child-Pugh score (p<0.001), ALBI score (p=0.0003) and CRP (p=0.0047; Figure 1-C). In contrast, ZAG was more strongly correlated with renal function including creatinine (p<0.0001), BUN (p=0.0001) and eGFR (p=0.001) (Table 2; Figure 1-K and L). In addition, ZAG was correlated with bodyweight (p=0.0092; Figure 1-G) and BMI (p=0.0001; Figure 1-H) and CRP (p<0.0001; Figure 1-I). Cystatin C was signiﬁcantly correlated with age (p=0.0191), renal parameters (creatinine and BUN: p<0.0001 and eGFR: p=0.001), copeptin (p=0.008), NGAL (p<0.0001) and L-FABP (p<0.0001) (Table 2). NGAL and L-FABP were signiﬁcantly correlated with indicators of both renal function and hepatic function (Table 2). MELD score significantly correlated with all, copeptin (p=0.001), ZAG (p=0.0003), cystatin C (p<0.0001), NGAL (p<0.0001) and L-FABP (p=0.0024).
Background comparison between Responders and Non-responders to tolvaptan
In this study, we excluded 7 from 45 cases for which tolvaptan efficacy could not be determined because of transferring hospitals, lack of weight data or with other treatment such as albumin transfusion, ascites puncture, and cell-free and concentrated ascites reinfusion therapy (Supplementary Figure 1). We enrolled 38 decompensated LC patients with ascites (24 males and 14 females) with a mean age of 67.1 ± 9.7 years. We divided the 38 patients into two tolvaptan treatment groups: Responders and Non-responders. The Non-responder group was defined as patients with weight loss of <1.5 kg/week after receiving tolvaptan or performing paracentesis within the first week 12. All patients continued to take the same prescribed doses of furosemide and spironolactone within the first week. There were no obvious differences in age, gender, bodyweight, BMI, PMI, presence of HCC, dose of diuretic drugs, albumin, total bilirubin, Child-Pugh score, ALBI score, FIB4-index, MELD score, creatinine, eGFR, serum sodium, cystatin C, NGAL and L-FABP between the two groups (Table 3; Figure 2-D, E and F). In contrast, BUN, copeptin and ZAG levels were significantly higher in Non-responders when compared to the Responders group (respectively, p=0.0014, p=0.0265, p=0.0142) (Table 3; Figure 2-A, B and C). We calculated the cutoff values, area under the ROC curve, sensitivity and speciﬁcity of BUN, copeptin and ZAG using ROC analysis. The cutoff values ascertained from our analyses of BUN, copeptin and ZAG were 18.3mg/dL, 10.1pmol/L and 32.4 μg/mL, respectively (Table 3).
Predictors contributing to the effect of tolvaptan in treatment for ascites
Using multivariate logistic regression analysis, we found BUN (odds ratio 7.43, p=0.0306), serum copeptin levels (odds ratio 9.12, p=0.013) and ZAG (odds ratio 7.43, p=0.0306) to be the signiﬁcant predictors contributing to the efficacy of tolvaptan in the treatment for ascites (Table 4).