Introduction
Sarcopenia is a common complication of cirrhosis and has been associated with the progression of liver failure and an increased rate of complications, including mortality1. Despite its manifest clinical importance, the risk factors related to decreased muscle mass and strength in cirrhotic patients have been poorly evaluated.
In addition to the fact that no method is superior to the others, assessing this group of patients is still controversial1. Among the available tools, grip strength has emerged as a simple, low-cost, and effective method to detect malnutrition in cirrhotic patients, which adequately predicts the incidence of major complications, the need for transplantation, and mortality compared to some clinical indices2.
This study used different nutritional assessment methods, including grip strength, to determine the factors associated with muscle mass and strength in cirrhotic patients in our setting.
Materials and methods
A cross-sectional, descriptive, analytical study was carried out. Convenience sampling was defined. The population consisted of patients older than 18 who attended follow-up with outpatient hepatology in a medical center in Cartagena de Indias, Colombia, between January 2022 and March 2022. They had an unequivocal diagnosis of liver cirrhosis per clinical (signs of decompensation and laboratory findings or upper GI endoscopy [EGD] demonstrating esophageal varices), ultrasound (increased liver surface nodularity, increased liver echogenicity, right lobe atrophy, hypertrophy of the left or caudate lobes, decreased liver size, portosystemic shunts), elastographic (Baveno VI definition > 15 KPa regardless of etiology)3, or pathological (liver biopsy with evidence of severe fibrosis or cirrhosis) criteria.
We excluded patients in whom factors associated with malnutrition were presumed (patients diagnosed with human immunodeficiency virus [HIV] infection, hepatocarcinoma, stage V chronic kidney disease, on renal replacement therapy, with cognitive impairment that prevented an adequate caloric intake, or who had used oral steroids chronically in the month before the tests) or who, due to some physical limitation, could not undergo any of the required tests of the study.
All study subjects were in a follow-up protocol that included screening for hepatocellular carcinoma4 and esophageal varices with EGD, as proposed in Baveno VI3. The Calès5 classification was used to describe esophageal varices. The etiological diagnosis of cirrhosis was made following current international clinical practice guidelines6-12. Cryptogenic cirrhosis was determined in those cases where it was impossible to decide on any attributable etiology. Subsequently, all the subjects were scheduled for a day of nutritional assessment, including measurement of weight, height, body mass index (BMI), corrected body mass index, bioimpedanciometry, mid-arm circumference (MAC), triceps skin fold (TSF), mid-arm muscle circumference (MAMC), and grip strength, determination of ascites and peripheral edema, and application of the Royal Free Hospital-Nutritional Prioritizing Tool (RFH-NPT) screening scale.
The InBody 270® Segmental Multifrequency DSM-BIA body composition analyzer was used to determine weight. Dry weight was calculated following the European Association for the Study of the Liver (EASL) clinical practice guidelines for nutrition in patients with chronic liver disease1. The DETECTO® PHR portable stadiometer was used, with an accuracy of ± 0.005 m for each measurement. Dry BMI was calculated using the formula: dry weight/(height)2. The cut-off scores proposed by Campillo et al. regarding malnutrition13 were used for the corrected BMI.
An experienced physician measured the TSF (mm) and MAC (cm) on the non-dominant arm of each patient with a tape measure and caliper. Measurements were made at the midpoint between the acromion tip and the olecranon process, with the patient sitting in a relaxed position. The average of two consecutive measurements for each variable was recorded.
The MAMC (cm) was calculated according to the following formula: MAMC = MAC - (TSF * 0.314)14. The values were classified according to the TSF and MAMC tables standardized for age and sex proposed by Bishop et al. in 198115 (Appendix 1), and moderate and severe malnutrition were diagnosed according to Campillo et al.’s criteria16. According to the manufacturer’s recommendations, a trained physician performed bioimpedance analysis with the InBody 270® body composition analyzer.
Grip strength was measured in the non-dominant arm. The average (in kilograms) of two consecutive measurements was reported. The results were compared with the reference values put forward by Budziareck et al. in 200817, and malnutrition was defined as a value below the 5th percentile according to age group and sex. The Jamar hydraulic dynamometer was employed to guarantee the comparability of the measurements.
An expert doctor filled out the RFH-NPT nutritional screening scale, which consists of a questionnaire of basic questions that include the patient’s feeding route, the presence of acute hepatitis, the state of fluid overload, the dry BMI, the degree of unintentional weight loss, and any acute comorbidity that modifies dietary intake. Nutritional risk was calculated based on Borhofen et al.’s scores18.
The results of each patient’s laboratory examinations were recorded three months before the nutritional assessment date to calculate the disease’s prognostic indices.
Statistical analysis
Quantitative and categorical variables were described using mean (standard deviation [SD]) and percentages, respectively. A logistic regression or linear regression analysis was used, as appropriate, to identify the factors associated with muscle mass and grip strength. Results were expressed as odds ratio (OR) or regression coefficients (B). A p less than or equal to 0.05 was considered statistically significant.
Ethical aspects
We complied with all the ethical regulations for research in humans under Colombian Resolution 8430 dated October 4, 1993, which qualifies the present investigation as of minimal risk since no intervention made was invasive. The institution’s ethics committee designed, disseminated, and approved a written informed consent form. All patients freely and independently agreed to participate in the study.
Results
Sample description
Forty patients with a previous diagnosis of liver cirrhosis were included. No diagnosis was made de novo since all the patients were referred from other institutions. The majority were women (65%), and the mean age was 66. The diagnosis was confirmed mainly by elastographic (72.5%) and ultrasound (17.5%) methods, and only four patients (10%) had the definitive anatomopathological study. The most common causes of advanced chronic liver disease were nonalcoholic steatohepatitis (NASH) cirrhosis in 42.5% (17 patients) and cryptogenic cirrhosis in 25% (ten patients) (Table 1).
Total sample n = 40 | |
---|---|
Age (years) | 66 (4.58) |
Average (SD) | |
Identification | |
- Women, n (%) | 26 (65) |
- Urban, n (%) | 39 (97.5) |
Personal history | |
- High blood pressure, n (%) | 18 (45) |
- Type 2 diabetes mellitus, n (%) | 15 (37.5) |
- Chronic kidney disease, n (%) | 6 (15) |
- Smoking, n (%) | 5 (12.5) |
- Osteoporosis, n (%) | 2 (5) |
- Menopause*, n (%) | 22 (84) |
- History of ascites, n (%) | 14 (35) |
- History of hepatic encephalopathy, n (%) | 10 (25) |
- History of variceal bleeding, n (%) | 4 (10) |
Diagnostic information | |
Etiology | |
- NASH, n (%) | 17 (42.5) |
- Cryptogenic, n (%) | 10 (25) |
- AIH/PBC overlap, n (%) | 4 (10) |
- HCV infection, n (%) | 3 (7.5) |
- AIH, n (%) | 3 (7.5) |
- Alcoholic, n (%) | 2 (5) |
- SBC, n (%) | 1 (2.5) |
Varicose veins | |
- Yes, n (%) | 20 (50) |
Varicose vein size | |
- Small, n (%) | 5 (25) |
- Medium, n (%) | 6 (30) |
- Large, n (%) | 9 (45) |
Child-Pugh score | |
- A, n (%) | 31 (77.5) |
- B, n (%) | 9 (22.5) |
- C, n (%) | 0 |
- Modified MELD, n (%) | 13.37 (1.16) |
PBC: primary biliary cholangitis; SBC: secondary biliary cholangitis; AIH: autoimmune hepatitis; MELD: Model for End-stage Liver Disease; NASH: nonalcoholic steatohepatitis; HCV: chronic infection with the hepatitis C virus. Source: The authors.
So, 77.5% were classified as category A (31 patients) on the Child-Pugh prognostic scale, and 22.5% as category B (nine patients). None were category C. Also, 42.5% (17 patients) had a history of decompensation, and the leading causes were ascites in 35% (14 episodes) and hepatic encephalopathy in 25% (ten episodes); 50% (20 patients) had esophageal varices, of which 45% (nine patients) were large. The mean modified MELD score was 13.37 points (Table 1).
Regarding the anthropometric variables, the average BMI of the population was 27.36 kg/m2, the skeletal muscle mass was 25.18 kg, and the average grip strength was 15.62 kg (Table 2).
Anthropometry | |
---|---|
Triceps fold (mm) Average (SD) | 20.18 (3.88) |
Mid-arm circumference (cm) Average (SD) | 27.37 (1.46) |
Mid-arm muscle circumference (cm) Average (SD) | 21.03 (0.78) |
Grip strength (kg) Average (SD) | 15.62 (2.23) |
Bioimpedancemetry | |
Weight (kg) Average (SD) | 74.21 (5.23) |
Size (m) Average (SD) | 1.65 (0.02) |
BMI (m/kg2) Average (SD) | 27.36 (2.16) |
Total body water (kg) Average (SD) | 39.06 (3.24) |
Bone mineral content (kg) Promedio (DE) | 3.78 (0.36) |
Body fat mass (kg) Average (SD) | 19.37 (4.97) |
Fat mass percentage (%) Average (SD) | 25.18 (5.78) |
Skeletal muscle mass (kg) Average (SD) | 27.36 (2.80) |
Fat-free mass (kg) Average (SD) | 54.83 (4.80) |
Total body protein (kg) Average (SD) | 9.73 (0.91) |
Muscular strength | |
Normal, n (%) | 33 (82.5) |
Decreased, n (%) | 7 (17.5) |
Source: The authors.
Factors associated with skeletal muscle mass
Univariate linear regression found an association between skeletal muscle mass, male sex, and total body protein value. Grip strength also had a statistically significant relationship (b = 0.55; 95% confidence interval [CI]: 0.36-3.04; p = 0.0001) (Table 3).
Relationship of variables with skeletal muscle mass | |||
---|---|---|---|
Univariable linear regression | |||
Variable | B | CI | p |
Male sex | 10.56 | 7.98 a 13.14 | 0.0001 |
Age | -0.205 | -0.36 a -0.04 | 0.01 |
High blood pressure | 2.49 | -2.44 a 7.43 | 0.3 |
Type 2 diabetes mellitus | -1.23 | -5.67 a 3.21 | 0.56 |
Chronic kidney disease | 1.49 | -4.70 a 7.68 | 0.61 |
Smoking | -1.07 | -9.45 a 7.29 | 0.78 |
Osteoporosis | -4.4 | -11.68 a 2.87 | 0.21 |
Menopause | -0.75 | -6.69 a 5.18 | 0.79 |
History of ascites | 0.57 | -6.78 a 7.94 | 0.87 |
History of hepatic encephalopathy | -2.4 | -10.79 a 5.98 | 0.55 |
History of variceal bleeding | 1.57 | -6.43 a 9.58 | 0.68 |
KDIGO classification of chronic kidney disease | -0.04 | -0.11 a 0.02 | 0.22 |
Child-Pugh score | -0.02 | -0.15 a 0.10 | 0.71 |
BMI | -0.03 | -0.06 a -0.006 | 0.01 |
Bioimpedancemetry | |||
- Total body water | 0.39 | 0.17 a 0.60 | 0.001 |
- Mineral | 0.17 | -0.04 a 0.39 | 0.11 |
- Body fat mass | -0.02 | -0.06 a 0.009 | 0.13 |
- Body fat percentage | 0.061 | 0.01 a 0.11 | 0.017 |
- Fat-free mass | -0.16 | -0.24 a -0.07 | 0.0001 |
- Total body protein | 2.43 | 2.07 a 2.8 | 0.0001 |
Anthropometry | |||
- TSF | -0.002 | -0.009 a 0.005 | 0.57 |
- MAMC | 0.024 | -0.003 a 0.05 | 0.08 |
- Grip strength | 0.55 | 0.36 a 0.74 | 0.0001 |
- RFH-NPT | -1.38 | -5.82 a 3.047 | 0.52 |
MAMC: mid-arm muscle circumference; RFH-NPT: Royal Free Hospital-Nutritional Prioritizing Tool; TSF: triceps fold. Source: The authors.
Multivariate linear regression was performed with the variables that had a significant association with muscle mass in the univariate linear regression. Association was found with age, total body protein value, BMI, total body water, fat mass percentage, and fat-free mass. This analysis found no significant association between muscle strength and the male sex (Table 4).
Relationship of variables with skeletal muscle mass | |||
---|---|---|---|
Variable | B | CI | p |
Male sex | 0.13 | -0.01 a 0.27 | 0.07 |
Age | -0.005 | -0.009 a -0.001 | 0.01 |
BMI | -0.048 | -0.07 a -0.02 | 0.001 |
Total body water | 0.52 | 0.33 a 0.70 | 0.0001 |
Total body protein | 2.22 | 1.89 a 2.54 | 0.0001 |
Body fat mass percentage | 0.28 | 0.01 a 0.04 | 0.0001 |
Fat-free mass | -0.21 | -0.29 a -0.14 | 0.0001 |
Source: The authors.
Factors associated with muscle strength
Univariable linear regression was performed, noting that the main factors associated with muscle strength were male sex (b = 11.94; 95% CI: 8.5 to 15.3; p = 0.0001), age (b = -0.28; 95% CI -0.46 to -0.096; p = 0.004), chronic kidney disease (b = -6.11; 95% CI -10.92 to -1.31; p = 0.016), and fat-free mass (b = 4.01; 95% CI: 0.095 to 7.93; p = 0.045). Multivariate linear regression was performed with variables that had a significant association with muscle strength in univariate linear regression. In this analysis, male gender was the only independent predictor of muscle strength (b = 10.79; 95% CI 7.17 to 14.42; p = 0.0001).
Accordingly, the data on gender and age were analyzed based on Budziareck et al.’s tables17. The variables related to the decrease in muscle strength were the Child-Pugh score, history of ascites and hepatic encephalopathy, use of ammonium-lowering therapies, RFH-NPT score, and fat-free mass (Table 5).
Regresión lineal univariable | |||
---|---|---|---|
Variable | OR | CI | p |
Male sex | 3.06 | 0.57 a 16.30 | 0.189 |
Age | 1.01 | 0.94 a 1.08 | 0.686 |
High blood pressure | 1.81 | 0.34 a 9.40 | 0.48 |
Type 2 diabetes mellitus | 1.31 | 0.25 a 6.87 | 0.74 |
Chronic kidney disease | 2.9 | 0.41 a 20.27 | 0.283 |
Smoking | 1.2 | 0.11 a 12.81 | 0.87 |
History of ascites | 6.66 | 1.09 a 40.7 | 0.04 |
History of hepatic encephalopathy | 6 | 1.05 a 34.14 | 0.04 |
Presence of varicose veins | 8.1 | 0.87 a 75.47 | 0.06 |
KDIGO classification of chronic kidney disease | 2.49 | 0.83 a 7.39 | 0.1 |
Ammonium-lowering therapy | 6 | 1.05 a 34.14 | 0.04 |
Serum albumin | 0.85 | 0.2 a 3.6 | 0.82 |
Child-Pugh score | 7.46 | 1.26 a 44 | 0.02 |
BMI | 1.2 | 0.98 a 1.5 | 0.07 |
Corrected BMI | 0.93 | 0.09:9.50 | 0.95 |
Bioimpedancemetry | |||
- Skeletal muscle mass | 1.06 | 0.93 a 1.20 | 0.35 |
- Body fat mass | 1 | 0.92 a 1.08 | 0.97 |
- Body fat percentage | 0.97 | 0.90 a 1.04 | 0.42 |
- Fat-free mass | 1.08 | 1 a 1.18 | 0.05 |
- Total body protein | 1.21 | 0.82 a 1.79 | 0.32 |
Anthropometry | |||
- TSF | 1 | 0.91 a 1.09 | 0.98 |
- MAC | 1.03 | 0.84 a 1.27 | 0.752 |
- MAMC | 1.07 | 0.79 a 1.45 | 0.65 |
Scales | |||
- Nutritional status according to the MAMC | 0.49 | 0.49 a 2.43 | 0.813 |
- RFH-NPT | 5.69 | 1.09 a 29.71 | 0.039 |
Source: The authors.
Malnutrition prevalence
Taking into account the scores obtained in the RFH-NPT, 40% (16 patients) had a moderate and high risk of malnutrition. Regarding the standardized MAMC tables proposed by Bishop et al.15, 37.5% (15 patients) had some degree of malnutrition. Based on the age and sex tables by Budziareck et al.17, 17.5% (seven patients) presented with decreased muscle strength. According to the IMCC, 15% (six patients) had malnutrition.
Discussion
The present study identified that the main determinants of skeletal muscle mass in cirrhotic patients were male sex, age, BMI, total body water, fat mass percentage, fat-free mass, total body protein, and grip strength.
Few works have tried to answer this question. In 2019, a study conducted by Sung et al.19 demonstrated that grip strength (<18 kg for women; <26 kg for men), age (>60 years), history of hepatic encephalopathy, and elevated levels of Wisteria floribunda agglutinin-positive mac-2-binding protein (WFA+-M2BP > 1.86 COI; a recent marker of liver fibrosis)20 were the main predictors of loss of skeletal muscle mass in a population of cirrhotic patients.
Another study by Hiraoka et al. concluded that increased Child-Pugh score and decreased serum albumin levels were the most critical risk factors associated with decreased muscle mass and strength in patients with chronic liver disease21. Our study found no significant relationship between serum albumin levels and muscle mass or strength.
Regarding the other results, the relationship found between muscle mass and total body water could be explained by the fact that the water content of skeletal muscle mass is approximately between 70% and 75%, causing the total body water volume to increase at the expense of intracellular water in skeletal muscle fibers22.
It is striking that, in our results, a negative association was found between skeletal muscle mass and fat-free mass. It could be speculated that the greater free mass in these patients is determined by increased extracellular water due to the pathophysiological processes typical of advanced chronic liver disease23.
We also could demonstrate a significant relationship between muscle mass and strength, whose indirect measurement through grip strength has been emerging in recent years as a cost-effective, non-invasive tool in the early identification of malnutrition in cirrhotic patients24 and even as a predictor of mortality25.
Our analysis revealed similar results for muscle strength to those reported in previous studies. Significant relationships were found with male sex, age, presence and severity of chronic kidney disease, and fat-free mass. Sex was the only independent predictor in multivariate linear regression.
A study conducted by Nishikawa et al. in 2021 observed that in men, the main determinants of muscle strength loss were age, diagnosis of cirrhosis, glomerular filtration rate, and the ratio of extracellular water to total body water. Meanwhile, in women, they were the diagnosis of cirrhosis, serum albumin concentrations, the albumin:bilirubin ratio, prothrombin time, platelet count, and the ratio of extracellular water to total body water26.
Consequently, considering the apparent differences between the sexes concerning muscle strength under Budziareck et al.’s tables17, the population was discriminated by sex and age. It was shown that the variables most closely related to muscle strength were the Child-Pugh score, history of ascites, history of hepatic encephalopathy, use of ammonium-lowering therapies, RFH-NPT score, and fat-free mass. Some of these factors, such as the Child-Pugh score and history of encephalopathy, were also reported in Sung et al.’19 and Hiraoka et al.’21 works.
The use of ammonium therapies was related to decreased muscle strength. This finding is not surprising and can be explained by the fact that currently, the indication for these therapies is limited to the management of overt encephalopathy and secondary prophylaxis to prevent recurrences27, which implies more advanced stages of chronic liver disease.
The RFH-NPT scale has been correlated with clinical deterioration, the severity of the disease (according to the Child-Pugh and MELD scores), and the appearance of different clinical complications such as ascites, hepatorenal syndrome, and hepatic encephalopathy. In addition, its application is an independent predictor of clinical deterioration and transplant-free survival, and improvements in this scale are associated with improved survival18. The most recent EASL guidelines support its use1. Our study revealed that it is the only screening scale significantly associated with muscle strength, so it is a good tool for identifying cirrhotic patients at risk of malnutrition.
In the present study, the prevalence of malnutrition ranged between 15% and 40% depending on the method used. This reflected the need for more uniformity among the available instruments and expressed the need for precise tools that can be used in daily practice. All this, added to the heterogeneous groups included in the studies, the severity of the disease, the etiology of cirrhosis, and the comorbidities presented, makes the prevalence of malnutrition in the literature vary greatly: 10% to 100%28.
Taking into account that in our study, grip strength was the only nutritional assessment tool significantly associated with muscle mass, it could be determined that the most accurate prevalence of malnutrition was 17.5%. The high prevalence evidenced by the RFH-NPT score (40%) does not diminish its validity but, on the contrary, positions it as a good screening tool with excellent sensitivity.
The other measurements used in the nutritional assessment of cirrhotic patients did not have a significant association with each other or with the RFH-NPT. Thus, our results do not support using any of them (IMCC, MAMC, TSF, MAC) in daily practice.
The main limitation of our study was the sample size, considering that the collection of patients was restricted by the coronavirus disease 2019 (COVID-19) pandemic. Besides, there are no standardized national tables for anthropometric measurements (MAC, TSF, MAMC) or the grip strength values used in this study. To adequately interpret the results, local tables should be designed that account for our population’s characteristics.
The main strength is that it is the first study that comprehensively evaluates the nutritional status of cirrhotic patients in Latin America.
Conclusions
The skeletal muscle mass of the cirrhotic patient was mainly associated with age, changes in body composition, and grip strength.
The main determinants of muscle strength were the stage of the disease, the use of ammonium-lowering therapies, and the score on the RFH-NPT scale. The latter seems to be a helpful tool for screening the nutritional status of cirrhotic patients in daily practice.