Assessing the risk factors associated with nutritional status in patients with liver cirrhosis: A case-control study

Abstract

BACKGROUND:

Cirrhosis is one of the most common clinical diseases in the world. The patient with cirrhosis has many complications, such as spontaneous peritonitis, hepatic encephalopathy. Malnutrition is one of the most common complications in patients with cirrhosis, and it is also a key factor affecting the prognosis of patients. However, the research on cirrhosis malnutrition is relatively scarce.

OBJECTIVE:

This study aimed to explore the new factors of the liver cirrhosis with the nutritional status.

METHODS:

A total of 370 patients with liver cirrhosis were admitted to the Fourth Affiliated Hospital of Harbin Medical University from January 2019 to January 2023 were selected. Patients were assigned to the malnourished group and normal group. The weight, height, mid arm circumference (MAC) and triceps skinfold thickness (TSF) of the two groups were measured. Body mass index (BMI) and mid-arm muscle circumference (MAMC) were calculated. Furthermore, the Health Literacy Management Scale (HeLMS), biochemical indexes, incidence of complications, disease grade were also counted and the Royal Free Hospital-Nutrition Prioritization Tool were used to evaluate the nutritional status of the patient.

RESULTS:

A total of 370 patients was included in this study, including 177 malnutrition patients, accounting for 45.29%, and the scores and total scores of the patients in the malnutrition group were lower than those in the normal group. The measured values of Na $+$ , Alb, PA, T-Bil, TC, TLC, Hb, and RBC were all lower than those of the normal group, and the difference was statistically significant. The overall complication rate of the patients in the malnourished group was 89.61%, and that of the normal group was 39.78%. Multifactorial logistic regression analysis was performed with nutritional level as the dependent variable (normal $=$ 0, malnutrition $=$ 1), and the above indicators of variability (Na $+$ , Alb, PA, T-Bil, TC, PT, Hb, RBC, HG, and HeLMS scores) as the independent variables. The results showed that Na $+$ , Hb were the influencing factors of nutritional level ( $P<$ 0.05).

CONCLUSION:

The incidence of malnutrition in cirrhotic patients included in this study was at a moderate level, and the nutritional literacy of these patients was low. In addition, the level of serum sodium, Hemoglobin can affect the nutritional level of patients with cirrhosis.

Keywords

Cirrhosis malnutrition correlation factor

1. Introduction

Cirrhosis is one of the most common clinical diseases in the world. The disease is characterized by diffuse proliferation of fibrous tissue in the liver, resulting in extensive necrosis and the formation of nodules and pseudolobules, which impairs the liver’s ability to perform normal physiological functions [1, 2]. According to a systematic report of disease research covering 195 countries [3], the number of cirrhosis patients worldwide has exceeded 160 million in 2017, and the number of cirrhosis deaths accounted for 2.4% of the total global deaths. Although with the development of medical technology in recent years, the mortality rate of this disease has been reduced, however, how to reduce the mortality rate and improve the quality of life of patients is still the primary area of investigation for scholars. Malnutrition is one of the most common complications in patients with cirrhosis, and it is also a key factor affecting the prognosis of patients [4]. In a prospective cross-sectional study of out-patients with cirrhosis in Australia [5], 40% of out-patients with cirrhosis had malnutrition complications. The single-center cross-sectional study conducted by Sharma P et al. [6] showed that 65% of patients with cirrhosis had malnutrition. Meanwhile, the study found that even patients with cirrhosis with normal nutritional status had significantly lower total calorie and protein intake than the recommended value, and malnutrition was a predictor of the morbidity and mortality of patients with cirrhosis. Currently, there are many methods of nutritional screening and nutritional assessment for the diagnosis of malnutrition in cirrhosis [7], such as anthropometric methods, relevant indicators such as Body mass index (BMI), Arm circumference (AC), Triceps Skinfold Thickness (TSF), Arm muscle circumference (AMC). However, there are many malnutrition factors that cause cirrhosis. Meanwhile, because of the differences in population characteristics, regions, diagnostic criteria and diagnostic tools, the influencing factors in various studies varies greatly [5, 6]. Therefore, the objective of this study is to investigate the factors that influence nutritional status in patients with liver cirrhosis, aiming to identify high-risk groups and develop early preventive interventions for malnutrition in cirrhotic patients.

2. Study subjects and methods

2.1 Study subjects

Cirrhotic patients admitted to The Fourth Affiliated Hospital of Harbin Medical University from January 2019 to January 2023 were selected.

Studies have shown that the higher disease grade of cirrhosis, the higher incidence of malnutrition, and its incidence ranges from 25.1% to 65.5% [6, 7, 8, 9]. The incidence rate of 25.1% was employed in this study to estimate the sample size, aiming to comprehensively evaluate the nutritional status of patients with cirrhosis. The sample size was determined to be 154 cases using PASS software. Considering potential trial loss, the sample size was increased by 10%. Consequently, a minimum of 170 patients were proposed for inclusion in the study.

2.2 Inclusion criteria

1) Patients with age from 18 to 85 years. 2) Patients with decompensated cirrhosis with Child-Turcotte-Pugh (CTP) of at least 6 and 13 or less. Decompensation was defined as the occurrence of any of the following events: ascites, encephalopathy, variceal bleeding, jaundice, or hepatorenal syndrome (HRS). 3) Patients who agreed to participate in the study and signed informed consent.

2.3 Exclusion criteria

1) Patients with acute liver disease except cirrhosis. 2) Patients with serious underlying diseases other than cirrhosis or potential malnutrition potentially interfering with the study results. 3) Patients with incomplete medical records.

On overall subjects the following measures were performed:

2.4 Anthropometric measures

According to the measurements conducted by a dietitian, weight, height, mid-arm circumference (MAC), and triceps skinfold thickness (TSF) were assessed. Body mass index (BMI) and mid-arm muscle circumference (MAMC) were calculated. The average value of each variable was obtained through three repetitions.

According to the Royal Free Hospital-Nutrition Prioritization Tool (RFH-NPT) Nutritional screening: Specific screening contents include: assessment of acute alcoholic hepatitis or nasal feeding nutrition, fluid retention, BMI, unplanned weight loss, and insufficient food intake. The evaluation results were divided into 3 levels, 0 as low nutritional risk, 1 as medium nutritional risk, and 2 to 7 as high nutritional risk, the patients were assigned to the malnutrition group who RFH-NPT evaluation results were 1 to 7, and the rest were assigned to the normal group.

2.5 Patient clinical data

Clinical information about the patient was collected, such as gender, age, marital status, and education level.

2.6 Health literacy management scale

The Health Literacy Management Scale (HeLMS) was developed by Simonds in 1976 to assess the ability of chronic disease patients to perceive health information and risks. The translated and modified version of 2011 by Sun Haolin was used in this study. The scale consists of 24 items, which comprehensively assess patients’ health literacy across four dimensions in the following domains: information acquisition proficiency, communication and interaction aptitude, willingness to improve health outcomes, and readiness to contribute financially. The questionnaire consisted of five options, ranging from “very difficult” to “very not difficult,” with corresponding scores from 1 to 5. The scale scores ranged from 24 to 120, where higher scores indicated greater levels of health literacy in patients. The Cronbach’ $\alpha$ coefficients for each dimension of the scale ranged from 0.885 to 0.925, the retest reliability Pearson correlation coefficient was 0.683.

2.7 Biochemical indexes

In order to ensure the integrity of the collected data, we included routine admission examination indicators. The biochemical indexes of the two groups were counted separately, which included blood sodium (Na $+$ ), blood ammonia, total cholesterol (TC), Alb, PA, total bilirubin (T-Bil), prothrombintime (PT), total lymphocyte count (TLC), hemoglobin (Hb), red blood cell (RBC).

2.7.1 The incidence of complications

According to the medical records, the cases of hypersplenism, ascites, peritonitis, and esophageal and gastric fundus varices in the two groups were counted.

2.7.2 Nutritional status assessment

The nutrition status was measured using the Royal Free Hospital-Nutritional Prioritizing Tool (RFH-NPT), which considers factors such as body fluid retention status, unplanned body mass loss, and alcoholic cirrhosis. The obtained scores were utilized for the classification of nutritional risk levels, with a score of 0 indicating a low risk of malnutrition, a score of 1 representing moderate risk, and scores ranging from 2 to 7 indicating high risk. The tool categorizes a patient’s nutritional risk as low, medium or high. At present, this tool was widely used to assessing the nutritional risk of patients.

2.7.3 Disease grade

The Child-Pugh liver function grading standard was employed in this study to evaluate the hepatic function of the patients, which currently serves as a widely adopted assessment criterion for liver function. This grading system primarily encompasses five parameters, namely serum albumin, total bilirubin, prolonged prothrombin time, ascites, and hepatic encephalopathy. When the score is 5–6, it is class A, when the score is 7–9, it is class B,and if the score is 10 or more, it is class C. A higher score proves that the patient’s liver function is poorer. In this study, patients classified as A were assigned to the normal group, while patients classified as B and C were assigned to the malnourished group

2.8 Statistical analysis

The collected data underwent statistical analysis using the SPSS 21.0 software. Mean and standard deviation (mean and SD) were employed to quantify the data, while median and quartiles [M (P25, P75)] were utilized for assessing skewed distribution of the measurement data. The $t$ test or Mann-Whitney $U$ test was used to compare differences between groups for measurement data. The $\chi^{2}$ test was used to compare differences between groups for count data. Logistic regression was used to analyze the factors influencing nutritional risk.

3. Results

3.1 General information

A total of 370 patients was included in this study, including 177 malnutrition patients, accounting for 45.29%. There were 109 males and 68 females, aged 36–68 years, with a mean of (56.76 $\pm$ 5.28) years. The disease was classified as Child-Pugh A in 80 cases, Child-Pugh B in 64 cases, and Child-Pugh C in 33 cases. In the healthy group, there were 55 males and 38 females aged between 41 and 74 years, with a mean age of 57.83 $\pm$ 5.76 years. The disease classification included Child-Pugh A in 83 cases, Child-Pugh B in 74 cases, and Child-Pugh C in 36 cases (Table 1).

Table 1
General information

Items		Malnutrition group ( $n=$ 177)	Normal group ( $n=$ 193)	$t/X^{2}$	$P$
Gender	Male	109	121	0.049	0.826
	Female	68	72
Age		56.76 $\pm$ 5.28	57.83 $\pm$ 5.75	1.862	0.063
Marital status	Married	156	169	1.859	0.395
	Divorced	8	14
	Widowhood	13	10
Professional status	Employed	125	132	3.472	0.180
	Retired	31	46
	Unemployed	21	15
Degree of education	Primary school or below	73	84	3.228	0.358
	Junior school	64	62
	Senior school	28	25
	College or above	12	22
Disease graded	Child-Pugh A	80	83	0.219	0.896
	Child-Pugh B	64	74
	Child-Pugh C	33	36
Disease triggers	Alcoholic	97	115	2.935	0.402
	Viral	46	36
	Metabolic	22	28
	Others	12	14
BMI (kg/m²)		19.15 $\pm$ 2.03	22.46 $\pm$ 3.51	11.222	0.00
MAMC (mm)		19.64 $\pm$ 2.18	21.48 $\pm$ 5.34	4.381	0.00
MAC (mm)		22.51 $\pm$ 3.36	24.72 $\pm$ 6.02	4.308407	0.00
TSF (mm)		8.36 $\pm$ 1.05	11.12 $\pm$ 5.78	6.522	0.00

3.2 Comparison of the HeLMS

The scores and total scores of the patients in the malnutrition group were lower than those in the normal group (Fig. 1).

Figure 1.

Comparison of the HeLMS.

3.3 Comparison of biochemical indexes

The measured values of Na $+$ , Alb, PA, T-Bil, TC, TLC, Hb, and RBC were all lower than those of the normal group, and the difference was statistically significant (Fig. 2).

3.4 Comparison of complication rates

The overall complication rate among patients in the malnourished group was 89.61%, whereas it was 39.78% among those in the normal group. The incidence of complications in the normal group was significantly lower compared to that in the malnourished group (Table 2).

Table 2
Comparison of complication rates [ $n$ (%)]

Items	Malnutrition group	Normal group	$X^{2}$	$P$
Hypersplenism	11 (6.21)	15 (7.77)
Ascites	29 (16.38)	23 (11.91)
Peritonitis	17 (9.60)	15 (7.77)
Esophageal and gastric fundus varices	13 (24.29)	6 (3.11)
Incidence	70 (39.54)	59 (30.57)	6.357	0.174

Figure 2.

Comparison of serological indexes.

3.5 Logistic regression analysis of factors affecting nutrition level

Multifactorial logistic regression analysis was performed with nutritional level as the dependent variable (normal $=$ 0, malnutrition $=$ 1), and the above indicators of variability (Na $+$ , Alb, PA, T-Bil, TC, PT, Hb, RBC, HG, and HeLMS scores) as the independent variables. The results showed that Na $+$ , Hb were the influencing factors of nutritional level ( $P<$ 0.05) (Table 3).

Table 3
Logistic regression analysis of factors affecting nutrition level

Influence factor	Regression coefficient	Standard error	Wald $\chi^{2}$	$P$	OR
Na	$-$ 0.240	0.114	4.438	0.035	0.787
TC	0.347	0.639	0.295	0.587	1.414
Alb	0.014	0.183	0.006	0.940	1.014
PA	$-$ 0.080	0.058	1.896	0.169	0.923
TBIL	$-$ 0.176	0.212	0.693	0.405	0.839
PT	$-$ 0.511	0.385	1.764	0.184	0.600
Hb	$-$ 2.288	0.892	6.585	0.010	0.101
RBC	$-$ 0.160	0.795	0.041	0.840	0.852
HeLMS scores	$-$ 0.050	0.070	0.517	0.472	0.951

4. Discussion

The statistical findings of different scholars regarding the prevalence of malnutrition in individuals with liver cirrhosis exhibit significant variations. JUAKIEM et al. [10] showed that the incidence of malnutrition is only about 5%, while Boulhosa et al. [11] showed the incidence of malnutrition can reach 57.2%. A total of 370 patients with cirrhosis were included in this study, and among them, 177 or 45.29% were identified as malnourished individuals. A study has shown that patients with different degrees of cirrhosis have different risks of malnutrition [10]. In the early stage of cirrhosis, patients often do not show obvious malnutrition because of the high compensatory capacity of liver. The progressive nature of the disease leads to a loss in hepatic compensatory capacity, resulting in an increasing prominence of malnutrition. The study conducted by CEDERHOLM [12] revealed that patients with cirrhosis in Child-Pugh B category had a significantly higher incidence of malnutrition, approximately five times greater than those in the Child-Pugh A category. In addition, comparing the nutritional literacy scores of the two groups, the results showed that the overall HeLMS of cirrhotic patients in the malnourished group was lower than that of the normal group, suggesting that malnourished cirrhotic patients have a lower degree of cognition and attention to their own nutritional status.

In our study, we found that Sodium, anemia, complications, grade of disease were risks factor of cirrhosis. Sodium, as an essential substance in the human body, is crucial for the regulation of blood volume, blood pressure, osmotic balance, and blood PH stabilization [13]. At the same time, the deficiency of Na $+$ can also result in the occurrence of malnutrition in the organism. In patients with cirrhosis, physicians frequently opt to deliberately restrict sodium intake in the formulation of the patient’s daily diet due to considerations regarding ascites and fluid retention. The restriction of Na $+$ intake, however, may potentially have a detrimental impact on their nutritional status due to the unpalatability of low-sodium foods, resulting in decreased protein and calorie consumption. Consequently, some people question the necessity of current sodium restrictions [14]. As observed by Reynolds et al. [15], a low-sodium diet does not significantly reduce the risk of ascites; conversely, a normal sodium diet enhances patients’ appetite and improves their nutritional status. Also, Gauthier et al. [16] concluded that a normal sodium diet increases the appetite of cirrhotic patients, which in turn improves their nutritional status and improves their 90-day survival rate. The results of this study showed that sodium level is a protective factor of nutritional state in patients with cirrhosis. However, it should be noted that excessive sodium intake does not necessarily impede the progression of cirrhosis in patients. In clinical practice, it is essential to consider both the patient’s condition and the severity of their liver disease before determining an optimal daily sodium intake through careful assessment. A report by the American Association for the Study of Liver Diseases (AASLD) showed that the dietary sodium intake should be limited to less than or equal to 2000 mg per day, as it has a positive impact on ascites. Additionally, patients with chronic hypertension should aim for an intake of approximately 1500 mg of sodium per day [17]. The presence of anemia is frequently observed in cirrhotic patients, and research has demonstrated a direct correlation between the severity of anemia and the prognosis of these individuals. Moreover, higher degrees of anemia are associated with increased mortality risk [18, 19]. The pathogenesis of anemia in cirrhotic patients has been essentially elucidated, primarily attributed to deficiencies in nutrients such as folic acid and vitamin B12, consequently resulting in microcytic hypochromic anemia [20]. The level of HB has been previously utilized as an independent prognostic risk factor in determining the prognosis of patients with cirrhosis. In this current study, logistic statistics revealed that the level of HB serves as a protective factor for the nutritional status of patients with cirrhosis, aligning with previous literature findings. The complications as a risk factor for malnutrition in patients with liver cirrhosis has been reported in other scholars’ studies [21]. The factor was not incorporated into the model calculations in this study, as complications did not demonstrate statistical significance among the included patients. Cirrhotic patients are highly susceptible to the development of ascites due to their own protein deficiencies, which can lead to severe gastrointestinal symptoms and reduce the patient’s appetite. This reduction in appetite may further compromise their nutritional status and exacerbate disease progression. This is evident in the ESPEN guidelines, which indicate that there is a direct correlation between the severity of malnutrition and the incidence of complications related to liver disease, such as hepatic encephalopathy, ascites, hepatorenal syndrome, and overall mortality [22]. There is a significant negative correlation observed between the severity of cirrhosis and the nutritional status of the patient. As cirrhosis worsens, hepatic metabolism declines leading to decreased synthesis of liver proteins, ultimately resulting in a lower nutritional level for the patient. The nutritional status of patients with cirrhosis has been reported to decrease in previous studies as the disease progresses. However, this association was not found to be statistically significant in the included patient population; therefore, it was not considered in the calculations for this study. Carvalho L et al. [23] showed that the incidence of malnutrition in Child-Pugh C patients was about twice as high as in Child-Pugh A patients. And in an Italian study of 1053 cirrhotic patients, it was similarly shown that the incidence of malnutrition with Child-Pugh C class was 57%, which was much higher than the 23% in Child-Pugh A class patients [24]. Moreover, this study analyzed the nutritional level of cirrhotic patients admitted to our hospital and analyzed the related factors, which is intended to provide theoretical references for grasping the overall nutritional level of cirrhotic patients in China and formulating related interventions based on these factors may help improve the nutritional level of such patients in the future.

5. Conclusion

In conclusion, the incidence of malnutrition in cirrhotic patients included in this study was at an intermediate level and the nutritional literacy was low. In addition, the level of serum sodium, Hemoglobin can affect the nutritional level of patients with cirrhosis.

Funding

The authors report no funding.

Data availability

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Ethical approval

The study was approved by the Ethics Committee of the Fourth Affiliated Hospital of Harbin Medical University, China.

Footnotes

Acknowledgments

The authors have no acknowledgments.

Conflict of interest

The authors declare that they have no conflict of interest.

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Assessing the risk factors associated with nutritional status in patients with liver cirrhosis: A case-control study

Abstract

BACKGROUND:

OBJECTIVE:

METHODS:

RESULTS:

CONCLUSION:

Keywords

1. Introduction

2. Study subjects and methods

2.1 Study subjects

2.2 Inclusion criteria

2.3 Exclusion criteria

2.4 Anthropometric measures

2.5 Patient clinical data

2.6 Health literacy management scale

2.7 Biochemical indexes

2.7.1 The incidence of complications

2.7.2 Nutritional status assessment

2.7.3 Disease grade

2.8 Statistical analysis

3. Results

3.1 General information

Table 1 General information

3.4 Comparison of complication rates

Table 2 Comparison of complication rates [ n (%)]

Table 3 Logistic regression analysis of factors affecting nutrition level

5. Conclusion

Funding

Data availability

Ethical approval

Footnotes

Acknowledgments

Conflict of interest

References

Table 1
General information

Table 2
Comparison of complication rates [ $n$ (%)]

Table 3
Logistic regression analysis of factors affecting nutrition level