Literature DB >> 27311000

Serum hyaluronic acid predicts protein-energy malnutrition in chronic hepatitis C.

Hiroki Nishikawa1, Hirayuki Enomoto, Kazunori Yoh, Yoshinori Iwata, Kunihiro Hasegawa, Chikage Nakano, Ryo Takata, Kyohei Kishino, Yoshihiro Shimono, Yoshiyuki Sakai, Takashi Nishimura, Nobuhiro Aizawa, Naoto Ikeda, Tomoyuki Takashima, Akio Ishii, Hiroko Iijima, Shuhei Nishiguchi.   

Abstract

Serum hyaluronic acid (HA) is a well-established marker of fibrosis in patients with chronic liver disease (CLD). However, the relationship between serum HA level and protein-energy malnutrition (PEM) in patients with CLD is an unknown. We aimed to examine the relationship between serum HA level and PEM in patients with chronic hepatitis C (CHC) compared with the relationships of other serum markers of fibrosis. A total of 298 CHC subjects were analyzed. We defined patients with serum albumin level of ≤3.5 g/dL and nonprotein respiratory quotient <0.85 using indirect calorimetry as having PEM. We investigated the effect of serum HA level on the presence of PEM. Receiver operating characteristic curve (ROC) analysis was performed for calculating the area under the ROC (AUROC) for serum HA level, platelet count, aspartate aminotransferase (AST) to platelet ratio index, FIB-4 index, AST to alanine aminotransferase ratio, and Forns index for the presence of PEM. The median serum HA level in this study was 148.0 ng/mL (range: 9.0-6340.0 ng/mL). In terms of the degree of liver function (chronic hepatitis, Child-Pugh A, B, and C), the analyzed patients were well stratified according to serum HA level (overall significance, P < 0.0001). The median value (range) of serum HA level in patients with PEM (n = 61) was 389.0 ng/mL (43.6-6340.0 ng/mL) and that in patients without PEM (n = 237) was 103.0 ng/mL (9.0-783.0 ng/mL) (P < 0.0001). Among 6 fibrosis markers, serum HA level yielded the highest AUROC with a level of 0.849 at an optimal cut-off value of 151.0 ng/mL (sensitivity 93.4%; specificity 62.0%; P < 0.0001). In the multivariate analysis, serum HA level was found to be a significant prognostic factor related to the presence of PEM (P = 0.0001).In conclusion, serum HA level can be a useful predictor of PEM in patients with CHC.

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Year:  2016        PMID: 27311000      PMCID: PMC4998486          DOI: 10.1097/MD.0000000000003920

Source DB:  PubMed          Journal:  Medicine (Baltimore)        ISSN: 0025-7974            Impact factor:   1.889


Introduction

The liver is an essential organ for the metabolism of 3 major nutrients: protein, fat, and carbohydrate.[ Liver cirrhosis (LC) is often complicated with protein-energy malnutrition (PEM).[ PEM can be assessed by measuring the serum albumin level for analyzing the degree of protein malnutrition, and by measuring the nonprotein respiratory quotient (npRQ) by using indirect calorimetry for assessing the degree of energy malnutrition; PEM is traditionally defined by observations of body composition (e.g., muscle mass and other anthropometric measurements, body weight, history of poor intake, and/or weight loss).[ RQs reflect what macronutrients are being metabolized; values that approach 1.00 suggest that carbohydrates are largely being burned and values that approach 0.7 suggest that lipids are being consumed.[ Patients with LC often have lower RQs, a phenomenon that has been attributed to limited stores of carbohydrates (e.g., glycogen).[ In general, patients with a serum albumin level ≤3.5 g/dL and npRQ value < 0.85 are considered to have PEM.[ PEM is 1 of the most common complications seen in patients with LC.[ PEM is linked to high morbidity and mortality in patients with LC and it has recently attracted much attention as it is closely associated with sarcopenia.[ Identifying patients with PEM is thus essential for ameliorating prognosis in chronic liver disease (CLD) with PEM. On the other hand, due to the limitations of liver biopsy, such as small size of biopsy specimens or its invasiveness for evaluating the degree of liver fibrosis, various noninvasive tests have been used to assess the liver fibrosis stage.[ In addition to various imaging modalities including fibroscan and acoustic radiation force impulse, there are various serum markers proposed for this purpose and 1 well-known serum marker is hyaluronic acid (HA).[ HA is a high-molecular weight polysaccharide that is distributed in all body tissues and fluids.[ HA is a component of the extra cellular matrix.[ The liver is the essential organ involved in the degradation and synthesis of HA.[ In the liver, HA is synthesized by Ito cells and finally degraded by sinusoidal endothelial cells.[ In general, the serum HA level in patients with LC increases due to the decreased clearance of HA, which is related to the destruction of hepatocytes.[ The usefulness of HA for predicting the degree of liver fibrosis has been well accepted in CLDs with different etiologies such as chronic hepatitis B or C, alcoholic liver disease, and nonalcoholic steatohepatitis.[ This biomarker is worth assessing since it is reliable, easy, inexpensive, and freely available to measure. Physicians and patients prefer to avoid a liver biopsy for fear of complications and evaluate the degree of liver fibrosis noninvasively. As mentioned above, many previous studies have demonstrated that HA is a useful marker for assessing the degree of liver fibrosis and it has been frequently used by some researchers to assess stages of liver fibrosis.[ However, to the best of our knowledge, there have been no studies investigating the relationship between serum HA level and PEM in patients with chronic hepatitis C (CHC). Thus the current study aimed to examine the relationship between serum HA level and PEM in patients with CHC compared with the relationships of other serum fibrotic markers.

Patients and methods

Patients

Between October 2005 and July 2012, nutritional evaluation using indirect calorimetry was performed in a total of 298 patients with CHC at the Division of Hepatobiliary and Pancreatic Disease, Department of Internal Medicine, Hyogo College of Medicine, Hyogo, Japan. In our hospital, nutritional evaluation using indirect calorimetry had been performed on an inpatient basis as a rule. In patients who agreed to be subject to nutritional evaluation using indirect calorimetry, it was routinely conducted in our department. All patients analyzed had detectable HCV-RNA and hepatitis B surface antigen negativity and in all of them, there was no clear evidence of drug-induced or alcoholic liver disease or of severe comorbid diseases such as nephrotic syndrome or severe systemic inflammatory disease that can affect the interpretation of our current data. We defined patients with serum albumin level of ≤3.5 g/dL and npRQ < 0.85 as those with PEM, according to previous reports.[ We prospectively collected clinical data for these patients and retrospectively investigated the effect of serum HA level on the presence of PEM in our cohort by comparing with other fibrosis markers including platelet count, aspartate aminotransferase (AST) to platelet ratio index (APRI), FIB-4 index, AST to alanine aminotransferase (ALT) ratio, and Forns index. In addition, in patients with available stored sera, we performed further analyses using these stored sera (described later). Serum HA level was measured by using a particle-enhanced turbidimetric immunoassay.[ The APRI score was calculated using Wai formula: (AST/upper limit of normal)/platelet count (expressed as platelets × 109/L) × 100.[ The FIB-4 index was calculated using Sterling formula as: age (years) × AST (IU/L)/platelet count (×109/L) × √ALT (IU/L)).[ The Forns index was calculated as reported previously.[ Liver biopsy specimens were obtained using standard methods, and well-experienced pathologists in our hospital evaluated the samples. Fibrosis stages were evaluated according to the METAVIR scoring system and the staging was performed on a degree of F0–F4 (F0—no fibrosis; F1—portal fibrosis without septa; F2—portal fibrosis with rare septa; F3—numerous septa without cirrhosis; F4—LC).[ The pathological findings of the liver biopsy specimens were also routinely assessed in our department. We participated in conferences on the histological findings and final agreements were obtained.[ In patients with poor liver function, after a full explanation of liver biopsy-related adverse events, we routinely used a thinner biopsy needle with great caution so as to avoid biopsy-related bleeding. All analyzed patients had no or minimal ascites on radiologic findings. In performing liver biopsy, procedure-related death was not observed in any of the analyzed cases. The ethics committee of our hospital approved the current study protocol and this study protocol complied with all of the provisions of the Declaration of Helsinki. Written informed consent was obtained from all subjects prior to liver biopsy and assessing nutritional status using indirect calorimetry.

Indirect calorimetry

Two parameters are measured using indirect calorimetry: carbon dioxide production per minute (VCO2) and oxygen consumption per minute (VO2). Total urinary excretion of nitrogen (UN) was measured as reported previously.[ npRQ, resting energy expenditure (REE), substrate oxidation rates of fat (%F), carbohydrate (%C), and protein (%P) were calculated using the following formulas: npRQ = (1.44 VCO2 − 4.890 UN)/(1.44 VO2 − 6.04 UN); REE (kcal/d) = 5.50 VO2 + 1.76 VCO2 − 1.99 UN; F (g/24 h) = 2.432 VO2 + 2.432 VCO2 − 1.943 UN; C (g/24 h) = 5.926 VO2 + 4.189 VCO2 − 2.539 UN; P (g/24 h) = 6.250 UN; %F = 9.46F/REE × 100; %C = 4.18C/REE × 100; and %P = 4.32P/REE × 100.[ Data for REE were obtained for all subjects in the morning after an overnight fast (12 h).

Statistical analysis

Receiver operating characteristic curve (ROC) analysis was performed for calculating the area under the ROC (AUROC) for serum HA level, platelet count, APRI, FIB-4 index, AST to ALT ratio, and Forns index by selecting the optimal cut-off value that maximized the sum of sensitivity and specificity for the presence of PEM. For continuous variables, the statistical analysis among groups was performed using Student t test, Mann–Whitney U test, Kruskal–Wallis test, or Spearman rank correlation coefficient rs test as appropriate. For categorical variables, the groups were compared using Fisher exact test. Variables with P < 0.05 in the univariate analysis were subjected to a multivariate logistic regression analysis. Data are expressed as means ± standard deviation (SD) or median values (range). Values of P < 0.05 were considered to be statistically significant. Statistical analysis was performed with the JMP 11 (SAS Institute Inc., Cary, NC).

Results

Baseline characteristics

The baseline characteristics of the study participants (n = 298) are shown in Table 1. They included 147 males and 151 females. The mean (±SD) age was 64.0 ± 12.0 years. In terms of degree of liver fibrosis, there are 2 subjects with F0, 60 with F1, 30 with F2, 42 with F3, and 164 with F4. Patients with F4 included 97 with Child-Pugh A, 57 with Child-Pugh B, and 10 with Child-Pugh C. The mean (±SD) serum HA level was 261.4 ± 507.5 ng/mL (median value; 148.0 ng/mL, range; 9.0–6340.0 ng/mL). In this analysis, 236 patients (79.2%) had HCV-RNA ≥5 log copies/mL.
Table 1

Baseline characteristics in the current analysis (n = 298).

Baseline characteristics in the current analysis (n = 298).

Prevalence of PEM in different fibrosis stages (F0–1, F2, F3, and F4) and different Child-Pugh stages (A, B, and C).

The proportions of PEM in different fibrosis stages were 1.6% (1/62) in F0–1, 6.7% (2/30) in F2, 4.8% (2/42) in F3, and 34.1% (56/164) in F4 (overall significance, P < 0.0001; Fig. 1A). The proportions of PEM in different Child-Pugh stages were 16.5% (16/97) in Child-Pugh A, 52.6% (30/57) in Child-Pugh B, and 100% (10/10) in Child-Pugh C (overall significance, P < 0.0001; Fig. 1B).
Figure 1

Prevalence of PEM in different fibrosis stages (F0–1, F2, F3, and F4) and different Child-Pugh stages (A, B, and C). (A) The proportions of PEM in different fibrosis stages were 1.6% (1/62) in F0–1, 6.7% (2/30) in F2, 4.8% (2/42) in F3, and 34.1% (56/164) in F4 (overall significance, P < 0.0001). (B) The proportions of PEM in different Child-Pugh stages were 16.5% (16/97) in Child-Pugh A, 52.6% (30/57) in Child-Pugh B, and 100% (10/10) in Child-Pugh C (overall significance, P < 0.0001). PEM = protein-energy malnutrition.

Prevalence of PEM in different fibrosis stages (F0–1, F2, F3, and F4) and different Child-Pugh stages (A, B, and C). (A) The proportions of PEM in different fibrosis stages were 1.6% (1/62) in F0–1, 6.7% (2/30) in F2, 4.8% (2/42) in F3, and 34.1% (56/164) in F4 (overall significance, P < 0.0001). (B) The proportions of PEM in different Child-Pugh stages were 16.5% (16/97) in Child-Pugh A, 52.6% (30/57) in Child-Pugh B, and 100% (10/10) in Child-Pugh C (overall significance, P < 0.0001). PEM = protein-energy malnutrition.

Serum HA levels among patients with different degrees of liver damage

The median values (range) of serum HA levels among patients with different degrees of liver damage were as follows: 62.5 ng/mL (9.0–568.0 ng/mL) in patients with chronic hepatitis (F0–F3, n = 134), 203.0 ng/mL (22.0–1290.0 ng/mL) in patients with Child-Pugh A (n = 97), 358.0 ng/mL (55.8–3730 ng/mL) in patients with Child-Pugh B (n = 57), and 775.0 ng/mL (165.0–6340.0 ng/mL) in patients with Child-Pugh C (n = 10) (overall significance, P < 0.0001; Fig. 2A).
Figure 2

(A) Serum HA levels among patients with different degree of liver damage. The median values (range) of serum HA levels among patients with different degree of liver damage are 62.5 ng/mL (9.0–568.0 ng/mL) in patients with chronic hepatitis (CH [F0–F3], n = 134), 203.0 ng/mL (22.0–1290.0 ng/mL) in patients with Child-Pugh A (CP-A, n = 97), 358.0 ng/mL (55.8–3730.0 ng/mL) in patients with Child-Pugh B (CP-B, n = 57), and 775.0 ng/mL (165.0–6340.0 ng/mL) in patients with Child-Pugh C (CP-C, n = 10) (overall significance, P < 0.0001). (B) Comparison of serum HA level between patients with serum albumin value of >3.5 g/dL and those with serum albumin value of ≤3.5 g/dL. The median value (range) of serum HA level in patients with serum albumin value of ≤3.5 g/dL (n = 104) was 346.0 ng/mL (43.6–6340.0 ng/mL) and that in patients with serum albumin value of >3.5 g/dL (n = 194) was 87.8 ng/mL (9.0–783.0 ng/mL) (P < 0.0001). (C) Comparison of serum HA level between patients with npRQ value of ≥0.85 g/dL and those with npRQ of <0.85. The median value (range) of serum HA level in patients with npRQ value of <0.85 (n = 141) was 199.0 ng/mL (9.0–6340.0 ng/mL) and that in patients with serum albumin value of ≥0.85 (n = 157) was 102.0 ng/mL (9.0–783.0 ng/mL) (P = 0.0006). (D) Comparison of serum HA level between patients with and without PEM. The median value (range) of serum HA level in patients with PEM (n = 61) was 389.0 ng/mL (43.6–6340.0 ng/mL) and that in patients without PEM (n = 237) was 103.0 ng/mL (9.0–783.0 ng/mL) (P < 0.0001). HA = hyaluronic acid, npRQ = nonprotein respiratory quotient, PEM = protein-energy malnutrition.

(A) Serum HA levels among patients with different degree of liver damage. The median values (range) of serum HA levels among patients with different degree of liver damage are 62.5 ng/mL (9.0–568.0 ng/mL) in patients with chronic hepatitis (CH [F0–F3], n = 134), 203.0 ng/mL (22.0–1290.0 ng/mL) in patients with Child-Pugh A (CP-A, n = 97), 358.0 ng/mL (55.8–3730.0 ng/mL) in patients with Child-Pugh B (CP-B, n = 57), and 775.0 ng/mL (165.0–6340.0 ng/mL) in patients with Child-Pugh C (CP-C, n = 10) (overall significance, P < 0.0001). (B) Comparison of serum HA level between patients with serum albumin value of >3.5 g/dL and those with serum albumin value of ≤3.5 g/dL. The median value (range) of serum HA level in patients with serum albumin value of ≤3.5 g/dL (n = 104) was 346.0 ng/mL (43.6–6340.0 ng/mL) and that in patients with serum albumin value of >3.5 g/dL (n = 194) was 87.8 ng/mL (9.0–783.0 ng/mL) (P < 0.0001). (C) Comparison of serum HA level between patients with npRQ value of ≥0.85 g/dL and those with npRQ of <0.85. The median value (range) of serum HA level in patients with npRQ value of <0.85 (n = 141) was 199.0 ng/mL (9.0–6340.0 ng/mL) and that in patients with serum albumin value of ≥0.85 (n = 157) was 102.0 ng/mL (9.0–783.0 ng/mL) (P = 0.0006). (D) Comparison of serum HA level between patients with and without PEM. The median value (range) of serum HA level in patients with PEM (n = 61) was 389.0 ng/mL (43.6–6340.0 ng/mL) and that in patients without PEM (n = 237) was 103.0 ng/mL (9.0–783.0 ng/mL) (P < 0.0001). HA = hyaluronic acid, npRQ = nonprotein respiratory quotient, PEM = protein-energy malnutrition.

Comparison of serum HA level between patients with serum albumin value of >3.5 g/dL and those with serum albumin value of ≤3.5 g/dL

The median value (range) of serum HA level in patients with serum albumin value of ≤3.5 g/dL (n = 104) was 346.0 ng/mL (43.6–6340.0 ng/mL) and that in patients with serum albumin value of >3.5 g/dL (n = 194) was 87.8 ng/mL (9.0–783.0 ng/mL) (P < 0.0001; Fig. 2B).

Comparison of serum HA level between patients with npRQ value of ≥0.85 and those with npRQ of <0.85

The median value (range) of serum HA level in patients with npRQ value of <0.85 (n = 141) was 199.0 ng/mL (9.0–6340.0 ng/mL) and that in patients with serum albumin value of ≥0.85 (n = 157) was 102.0 ng/mL (9.0–783.0 ng/mL) (P = 0.0006; Fig. 2C).

Comparison of serum HA levels between patients with and without PEM

The median value (range) of serum HA level in patients with PEM (n = 61) was 389.0 ng/mL (43.6–6340.0 ng/mL) and that in patients without PEM (n = 237) was 103.0 ng/mL (9.0–783.0 ng/mL) (P < 0.0001; Fig. 2D).

ROC analyses of 6 fibrosis markers for the presence of PEM

Serum HA level yielded the highest AUROC, with a level of 0.849, at an optimal cut-off value of 151.0 ng/mL (sensitivity, 93.4%; specificity, 62.0%; P < 0.0001), followed by FIB-4 index (AUROC, 0.802; P < 0.0001), APRI (AUROC, 0.770; P < 0.0001), Forns index (AUROC, 0.762; P < 0.0001), platelet count (AUROC, 0.734; P < 0.0001), and AST to ALT ratio (AUROC, 0.724; P < 0.0001; Fig. 3 and Table 2A). In patients with a serum HA level of ≥151.0 ng/mL (n = 147), the proportion of PEM was 38.8% (57/147), whereas in patients with a serum HA level of <151.0 ng/mL (n = 151), the proportion of PEM was 2.65% (4/151) (P < 0.0001). When cut-off points of serum HA level were set at 300, 500, and 700 ng/mL, the proportions of PEM were 48.7% (38/78) in patients with HA level ≥300 ng/mL, 73.3% (22/30) in patients with HA level ≥500 ng/mL, and 87.5% (14/16) in patients with HA level ≥700 ng/mL. While in limited patients with LC (F4, n = 164), serum HA level also yielded the highest AUROC with a level of 0.771 at an optimal cut-off value of 443.0 ng/mL (sensitivity, 51.8%; specificity, 89.8%; P < 0.0001; Table 2B). In patients with a serum HA level of ≥443.0 ng/mL (n = 40), the proportion of PEM was 72.5% (29/40), whereas in patients with a serum HA level of <443.0 ng/mL (n = 124), the proportion of PEM was 21.8% (27/124) (P < 0.0001). In limited patients with non-LC (n = 134), APRI yielded the highest AUROC (0.854) and AUROC of serum HA level was 0.760 at an optimal cut-off value of 199.0 ng/mL (sensitivity, 60.0%; specificity, 91.5%; P < 0.0001; Table 2C). In patients with a serum HA level of ≥199.0 ng/mL (n = 14), the proportion of PEM was 21.4% (3/14), whereas in patients with a serum HA level of <199.0 ng/mL (n = 120), the proportion of PEM was 1.7% (2/120) (P = 0.0082).
Figure 3

Receiver operating curve analyses of 6 fibrosis markers for the presence of PEM. (A) Serum hyaluronic acid level, (B) AST to platelet ratio index, (C) FIB-4 index, (D) AST to ALT ratio, (E) platelet count, and (F) Forns index. ALT = alanine aminotransferase, AST = aspartate aminotransferase, PEM = protein-energy malnutrition.

Table 2

Receiver operating curve (ROC) analyses of 6 fibrosis markers for the presence of PEM for all patients (A, n = 298), patients with LC (B, n = 164), and patients with non-LC (C, n = 134).

Receiver operating curve analyses of 6 fibrosis markers for the presence of PEM. (A) Serum hyaluronic acid level, (B) AST to platelet ratio index, (C) FIB-4 index, (D) AST to ALT ratio, (E) platelet count, and (F) Forns index. ALT = alanine aminotransferase, AST = aspartate aminotransferase, PEM = protein-energy malnutrition. Receiver operating curve (ROC) analyses of 6 fibrosis markers for the presence of PEM for all patients (A, n = 298), patients with LC (B, n = 164), and patients with non-LC (C, n = 134).

Variables closely associated with HA value

Based on our results, we further investigated the relationship between HA value and other baseline variables by using Spearman rank correlation coefficient rs test. In inflammatory diseases, the HA level is reported to be enhanced and free fatty acid (FFA) level is reported to be linked to npRQ value.[ Thus we additionally tested high-sensitivity C reactive protein (hCRP) and FFA level using stored sera. In this study, stored sera were available for 230 patients (77.2%). For all cases, the variables significantly correlated with the HA value were as follows: age, white blood cell (WBC), lymphocyte count, AST, ALT, alkaline phosphatase (ALP), gamma glutamyl transpeptidase (GGT), total bilirubin, serum albumin, platelet count, prothrombin time (PT), total cholesterol, triglyceride, REE/body weight, body mass index, hCRP, and FFA. The rs and P values for these variables are detailed in Table 3. For patients with LC (n = 164), the variables significantly correlated with the HA value were as follows: WBC, lymphocyte count, AST, ALP, GGT, total bilirubin, serum albumin, platelet count, PT, total cholesterol, triglyceride, hCRP, and FFA. The rs and P values for these variables are detailed in Table 3.
Table 3

Correlation with serum HA level in each variable.

Correlation with serum HA level in each variable.

ROC analyses of 6 fibrosis markers for the presence of PEM in limited patients whose stored sera were available (n = 230)

In patients whose stored sera were available (n = 230), among the 6 fibrotic markers, serum HA level yielded the highest AUROC with a level of 0.848 (P < 0.0001), followed by FIB-4 index (AUROC, 0.797; P < 0.0001), APRI (AUROC, 0.774; P < 0.0001), Forns index (AUROC, 0.764; P < 0.0001), platelet count (AUROC, 0.730; P = 0.0001), and AST to ALT ratio (AUROC, 0.719; P = 0.0001).

Univariate and multivariate analyses of factors linked to PEM for all cases

Univariate analysis identified the following factors as significantly associated with the presence of PEM: age (P = 0.0009); AST (P < 0.0001); ALP (P < 0.0001); total cholesterol (P < 0.0001); triglyceride (P = 0.0043); total bilirubin (P < 0.0001); WBC (P = 0.0006); lymphocyte count (P = 0.0003); platelet count (P < 0.0001); PT (P < 0.0001); serum HA level (P < 0.0001); APRI (P < 0.0001); FIB-4 index (P < 0.0001); AST to ALT ratio (P < 0.0001); Forns index (P < 0.0001); and BMI (P = 0.0456) (Table 4). The hazard ratios and 95% confidence intervals calculated using multivariate analysis for the 16 factors with P < 0.05 in the univariate analysis are shown in Table 4. Serum HA level (P = 0.0001) and PT (P = 0.0351) were found to be significant prognostic factors related to the presence of PEM.
Table 4

Univariate and multivariate analyses of factors linked to PEM.

Univariate and multivariate analyses of factors linked to PEM.

Discussion

HA is a well-established fibrosis marker in patients with CLD.[ However, the relationship between serum HA level and PEM in patients with CLD remains unclear. As mentioned earlier, PEM is linked to high morbidity and mortality in patients with LC. Thus identifying factors closely associated with PEM are essential for clinicians. Different liver diseases can cause different patterns of liver fibrogenesis. Based on recent reports, there are several controversial results related to the clinical applicability of serum HA level in various liver diseases, including hepatitis B or C, autoimmune liver disease, alcoholic liver disease, NASH, and others.[ Thus, in the current study, we investigated the effect of serum HA level in limited patients with CHC, who are most common among Japanese patients with CLD. To the best of our knowledge, this is the 1st study examining the relationship between serum HA level and PEM as defined by using indirect calorimetry for patients with CHC. In our results, the AUROC of serum HA level for the presence of PEM was the highest among those of the 6 serum fibrosis markers for all cases (AUROC = 0.849) and for patients with LC (AUROC = 0.771), although APRI had the highest AUROC (0.854) for the presence of PEM in patients with non-LC. In the limited patients whose stored sera were available, similar results were obtained. Furthermore, the AUROC of HA level for predicting LC was 0.879 in our analysis and HA level was found to be a significant factor linked to PEM in the multivariate analysis. These results suggest that serum HA level is a useful predictor of not only LC but also PEM. In daily clinical practice, testing serum HA level can be recommended for evaluating PEM in patients with CLD as assessment of HA is an inexpensive, standardized, and noninvasive supplement although indirect calorimetry is expensive and time consuming for testing. Serum HA level may also be a useful indicator for initiating nutritional support for patients with PEM. On the other hand, in our results, serum HA level was significantly correlated with numerous factors including age, biliary enzymes, liver function, immunological function as expressed by WBC and lymphocyte count, and systemic inflammation as expressed by hCRP value. Thus, in a sense, our observations that HA level is a significant predictor for PEM may be associated with complex factors. However, it worth noting that hCRP level was significantly correlated with HA level in the present analysis (rs = 0.252, P = 0.0001) although there are several missing values for hCRP. A is an immune regulator that acts through the release of inflammatory cytokines and it is produced by fibroblasts.[ In inflammatory diseases, fibroblasts are activated in the repair process of inflammation, and thus the production of HA is considered to be enhanced when the failed component is repaired.[ Based on these, we speculate that a higher HA level is linked to systemic inflammation, which eventually leads to energy consumption or malnutrition, as well as protein malnutrition.[ However, further examination will be needed to confirm these results. Hanai et al[ reported that plasma levels of FFA were significantly correlated with npRQ value (n = 146, r = −0.39, P < 0.0001) and FFA is a useful alternative marker to represent npRQ in patients with LC, whereas in our data, in patients with LC (120 patients with available stored sera), although significant correlation was found between FFA level and serum HA level (rs = 0.354, P < 0.0001), no significant correlation was found between FFA level and npRQ (rs = −0.113, P = 0.219). Thus whether serum FFA value significantly correlates with npRQ remains controversial, and this is beyond the aim of the present analysis. We acknowledge several limitations to the present study. First, this is a retrospective observational study. Second, liver biopsy involves a drawback being prone to sampling errors for evaluating the degree of liver fibrosis. Third, there are several missing values for testing several variables. Fourth, npRQ value may be influenced by characteristics of diet or recent physical activity in each patient, leading to bias. Thus caution should be exercised in interpreting our study results. However, in the current analysis, we demonstrated that serum HA level was closely associated with PEM in patients with CHC. In conclusion, serum HA level can be a useful predictor for predicting PEM in patients with CHC.

Acknowledgments

The authors would like to thank all medical staff in our nutritional guidance room for data collection.
  42 in total

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Authors:  Mathias Plauth; Eduard Cabré; Bernard Campillo; Jens Kondrup; Giulio Marchesini; Tatjana Schütz; Alan Shenkin; Julia Wendon
Journal:  Clin Nutr       Date:  2009-06-11       Impact factor: 7.324

4.  Hyaluronic acid, an accurate serum marker for severe hepatic fibrosis in patients with non-alcoholic fatty liver disease.

Authors:  Ayako Suzuki; Paul Angulo; James Lymp; Dave Li; Shinji Satomura; Keith Lindor
Journal:  Liver Int       Date:  2005-08       Impact factor: 5.828

Review 5.  Branched-chain amino acids as pharmacological nutrients in chronic liver disease.

Authors:  Takumi Kawaguchi; Namiki Izumi; Michael R Charlton; Michio Sata
Journal:  Hepatology       Date:  2011-06-23       Impact factor: 17.425

6.  Identification of chronic hepatitis C patients without hepatic fibrosis by a simple predictive model.

Authors:  Xavier Forns; Sergi Ampurdanès; Josep M Llovet; John Aponte; Llorenç Quintó; Eva Martínez-Bauer; Miquel Bruguera; Jose Maria Sánchez-Tapias; Juan Rodés
Journal:  Hepatology       Date:  2002-10       Impact factor: 17.425

Review 7.  Malnutrition in cirrhosis: contribution and consequences of sarcopenia on metabolic and clinical responses.

Authors:  Pranav Periyalwar; Srinivasan Dasarathy
Journal:  Clin Liver Dis       Date:  2012-01-23       Impact factor: 6.126

8.  Protein-calorie malnutrition as a prognostic indicator of mortality among patients hospitalized with cirrhosis and portal hypertension.

Authors:  Justina Sam; Geoffrey C Nguyen
Journal:  Liver Int       Date:  2009-07-07       Impact factor: 5.828

9.  Free fatty acid as a marker of energy malnutrition in liver cirrhosis.

Authors:  Tatsunori Hanai; Makoto Shiraki; Kayoko Nishimura; Kenji Imai; Atsushi Suetsugu; Koji Takai; Masahito Shimizu; Takafumi Naiki; Hisataka Moriwaki
Journal:  Hepatol Res       Date:  2013-04-18       Impact factor: 4.288

10.  Preferential use of branched-chain amino acids as an energy substrate in patients with liver cirrhosis.

Authors:  M Kato; Y Miwa; M Tajika; T Hiraoka; Y Muto; H Moriwaki
Journal:  Intern Med       Date:  1998-05       Impact factor: 1.271

View more
  7 in total

1.  Erratum: Medicine, Volume 95, Issue 24: Erratum.

Authors: 
Journal:  Medicine (Baltimore)       Date:  2016-08-07       Impact factor: 1.889

2.  Effect of physical exercise on sarcopaenia in patients with overt hepatic encephalopathy: a study protocol for a randomised controlled trial.

Authors:  Kazunori Yoh; Hiroki Nishikawa; Hirayuki Enomoto; Yoshinori Iwata; Akio Ishii; Yukihisa Yuri; Noriko Ishii; Yuho Miyamoto; Kunihiro Hasegawa; Chikage Nakano; Ryo Takata; Takashi Nishimura; Nobuhiro Aizawa; Yoshiyuki Sakai; Naoto Ikeda; Tomoyuki Takashima; Hiroko Iijima; Shuhei Nishiguchi
Journal:  BMJ Open Gastroenterol       Date:  2017-12-10

3.  The Relationship between Controlling Nutritional (CONUT) Score and Clinical Markers among Adults with Hepatitis C Virus Related Liver Cirrhosis.

Authors:  Hiroki Nishikawa; Kazunori Yoh; Hirayuki Enomoto; Noriko Ishii; Yoshinori Iwata; Ryo Takata; Takashi Nishimura; Nobuhiro Aizawa; Yoshiyuki Sakai; Naoto Ikeda; Kunihiro Hasegawa; Tomoyuki Takashima; Hiroko Iijima; Shuhei Nishiguchi
Journal:  Nutrients       Date:  2018-08-29       Impact factor: 5.717

Review 4.  Comorbidity-associated glutamine deficiency is a predisposition to severe COVID-19.

Authors:  Toshifumi Matsuyama; Steven K Yoshinaga; Kimitaka Shibue; Tak W Mak
Journal:  Cell Death Differ       Date:  2021-10-18       Impact factor: 15.828

5.  Impact of Wisteria floribunda Agglutinin-Positive Mac-2-Binding Protein in Patients with Hepatitis C Virus-Related Compensated Liver Cirrhosis.

Authors:  Kunihiro Hasegawa; Ryo Takata; Hiroki Nishikawa; Hirayuki Enomoto; Akio Ishii; Yoshinori Iwata; Yuho Miyamoto; Noriko Ishii; Yukihisa Yuri; Chikage Nakano; Takashi Nishimura; Kazunori Yoh; Nobuhiro Aizawa; Yoshiyuki Sakai; Naoto Ikeda; Tomoyuki Takashima; Hiroko Iijima; Shuhei Nishiguchi
Journal:  Int J Mol Sci       Date:  2016-09-12       Impact factor: 5.923

6.  Association between Albumin-Bilirubin Grade and Non-Protein Respiratory Quotient in Patients with Chronic Liver Diseases.

Authors:  Ryo Takata; Hiroki Nishikawa; Hirayuki Enomoto; Kazunori Yoh; Yoshinori Iwata; Yoshiyuki Sakai; Kyohei Kishino; Naoto Ikeda; Tomoyuki Takashima; Nobuhiro Aizawa; Kunihiro Hasegawa; Noriko Ishii; Yukihisa Yuri; Takashi Nishimura; Hiroko Iijima; Shuhei Nishiguchi
Journal:  J Clin Med       Date:  2019-09-18       Impact factor: 4.241

7.  Serum Zinc Level and non-Protein Respiratory Quotient in Patients with Chronic Liver Diseases.

Authors:  Hiroki Nishikawa; Ryo Takata; Hirayuki Enomoto; Kazunori Yoh; Yoshinori Iwata; Yoshiyuki Sakai; Kyohei Kishino; Yoshihiro Shimono; Naoto Ikeda; Tomoyuki Takashima; Nobuhiro Aizawa; Kunihiro Hasegawa; Noriko Ishii; Yukihisa Yuri; Takashi Nishimura; Hiroko Iijima; Shuhei Nishiguchi
Journal:  J Clin Med       Date:  2020-01-17       Impact factor: 4.241

  7 in total

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