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All issues Volume 27 (2020) Parasite, 27 (2020) 74 Full HTML
Open Access
Issue
Parasite
Volume 27, 2020
Article Number 74
Number of page(s) 9
DOI https://doi.org/10.1051/parasite/2020071
Published online 23 December 2020

© Z. Wang et al., published by EDP Sciences, 2020

Licence Creative CommonsThis is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Introduction

Echinococcosis is a zoonotic parasitic disease. Because of its insidious and asymptomatic early stages, the diagnosis and treatment of echinococcosis is complex, and the disease has a high mortality rate in its late stages. Echinococcosis poses a serious threat to human health as well as social and economic development in susceptible areas [8]. Echinococcosis is prevalent across the world except in Antarctica [25]. There are two kinds of echinococcosis: cystic echinococcosis (CE), which is caused by Echinococcus granulosus sensu lato, and alveolar echinococcosis (AE), caused by Echinococcus multilocularis [9, 22]. Echinococcus is harmful to the human body in many ways, mainly by mechanical damage. Because of the continuous growth of Echinococcus, it compresses the surrounding tissues and organs, causing tissue cell atrophy and necrosis, affecting organ function. Patients often have low fever, fatigue, emaciation, loss of appetite and other manifestations [4]. We often find echinococcosis patients with malnutrition in the clinical diagnosis and treatment process. Echinococcosis patients often require prolonged hospitalization and increased costs due to malnutrition. Studies on malnutrition associated with other liver diseases have shown that patients with malnutrition experience higher rates of infection, morbidity and mortality compared to patients without malnutrition [16]. Therefore, studying malnutrition related to hepatic echinococcosis is particularly important. No previous studies have analyzed and evaluated the nutritional status of patients with echinococcosis (as of the start date of this study). In this study, NRS2002 [11], MUST [15], MNA-SF [14] and NRI [5, 7] were used to investigate the nutritional status of hospitalized patients with echinococcosis. Through a comprehensive comparative analysis of the four methods, a suitable nutritional evaluation program was selected for patients with echinococcosis to provide a reference for clinical practice.

Methods

Patients

Patients at the Affiliated Hospital of Qinghai University from May 2016 to May 2018 were enrolled as study subjects. All cases were diagnosed as echinococcosis based on the criteria presented in “Expert consensus for the diagnosis and treatment of cystic and alveolar echinococcosis in humans” (2010 edition) [3]. Inclusion criteria for patients were: (i) age over 14 years, (ii) patient is conscious and able to stand, and (iii) patient is willing to participate in the study, and able to answer questions and complete relevant measurements. Exclusion criteria for patients were: (i) hepatic encephalopathy, (ii) difficulty of access to severely ill patients, and (iii) refusal or lack of cooperation with the questionnaire.

Data collection

General data and anthropometric data of patients were collected from medical records. General data parameters were diagnosis, gender, age, morbidity, appetite change, physical exercise, past medical history, and current combined diseases. Anthropometric parameters included current weight, past weight, height, unexpected weight loss, and body mass index (BMI). The laboratory parameters evaluated were serum albumin.

Nutritional risk assessment

The following nutritional risk screening tools were used to assess nutritional risk status in patients with echinococcosis: NRS 2002, MNA-SF, MUST and NRI.

NRS-2002 [11] parameters include a disease severity score, nutrition score and age score. The disease severity score is ranked from least to most severe (1–3 points).

Severity of disease score: cirrhosis, hip fracture, long-term hemodialysis, diabetes or chronic disease with acute complications = 1; stroke, major abdominal surgery, hematologic malignancies, or severe pneumonia = 2; head injury, bone marrow transplantation or patients in the intensive care unit with APACHE > 10 (Acute Physiology and Chronic Health Evaluation) = 3. Nutritional score: weight loss of more than 5% in 3 months or food intake is 50–75% of normal expected intake = 1; weight loss of more than 5% in 2 months, BMI of 18.5–20.5 kg/m2, or food intake is 25–60% of the normal expected intake = 2; weight loss is more than 5% in 1 month, BMI is <18.5 kg/m2, or food intake is < 25% of the expected intake = 3. Age score: age ≥ 70 years = 1; age < 70 years = 0. Nutritional risk was assessed by combining disease severity scores, nutritional scores and age scores. A total score < 3 indicates there is no or low risk of malnutrition, and a total score ≥ 3 indicates a high risk for malnutrition [7, 26].

MNA-SF [14] is an assessment tool designed for elderly subjects based on MNA. It has six parameters related to body mass index, recent weight loss, appetite change, activity ability, psychological stress and neuropsychological problems. Questions cover topics including BMI, recent weight loss, recent acute disease or stress, activity ability, neuropsychiatric disease, recent loss of appetite, dyspepsia, and eating difficulties. The score of each question was 0–2 or 0–3, and 14 was the total score possible. Patients with a score >12 were within a normal nutritional status. Patients with a score ≤11 were at risk of malnutrition [7, 26].

The MUST [1, 15] assessment tool has three clinical parameters: weight, unexpected weight loss, and the presence of acute disease. BMI values > 20, 18.5–20.0 and < 18.5 were assigned scores of 0, 1 and 2, respectively. Presence of acute disease and no acute disease were assigned scores of 0 and 2, respectively. The total risk of malnutrition was determined as follows: 0 score, low risk; 1 score, medium risk; and 2 score, high risk.

NRI [5, 7] is a nutritional risk assessment criterion based on serum albumin concentration and weight loss percentage, as follows: NRI = (1.519 × serum albumin) + (41.7 × current weight/normal weight). NRI score > 100 indicates no risk, 97.5–100 is low risk, 83.5–97.5 is medium risk, and ≤83.5 is high risk.

New ESPEN malnutrition diagnosis standard

The European Society for clinical nutrition and metabolism (ESPEN) recently proposed a new standard for the diagnosis of malnutrition, which provides a reference standard for the evaluation and comparison of nutrition screening tools. The new ESPEN diagnostic standard includes two options. One is BMI ≤ 18.5 kg/m2. The other is weight loss > 5% (in 3 months) or 10% (indefinite amount of time) and reduced BMI (BMI < 20 kg/m2 in patients under 70 years old, BMI < 22 kg/m2 in patients over 70 years old) [7, 13, 26]. Malnutrition can be diagnosed when the patient meets one of the two options.

Statistical analysis

Statistical analysis was performed using SPSS 24.0 (IBM, USA). Continuous variables are expressed as mean and standard deviation (SD), and values for each categorized variable were expressed by frequencies. An independent sample t-test, Pearson’s χ 2 test and Mann–Whitney U nonparametric test were used to analyze the differences in variance. In order to analyze the consistency among the four assessment tools, and the consistency between each of the four assessment tools and the new ESPEN malnutrition diagnosis standard [6], kappa (κ) statistics were used. The positive and negative likelihood ratios of all four tools were calculated to evaluate their sensitivity and specificity based on the ESPEN criteria for malnutrition diagnosis. Receiver operating characteristic (ROC) curves for the four screening tools were also used to assess the ability to accurately distinguish malnutrition patients.

Results

The study included 396 patients (164 with AE and 232 with CE). Specific characteristics of the study patients are presented in Table 1. In the CE cohort, 67 patients were malnourished. There were significant differences between the CE patients with and without malnutrition for parameters of age, weight, BMI, ALB and lesion size (p < 0.05). No significant differences were observed between the CE patients with and without malnutrition for gender, height, HGB, LYMPH, stage, and number of comorbidities (p > 0.05). In the AE cohort, 52 patients were malnourished. There were significant differences between AE patients with and without malnutrition for weight, BMI, ALB, HGB, lesion size and stage (p < 0.05). There were no significant differences between the AE patients with and without malnutrition for age, gender, height, LYMPH, and number of comorbidities (p > 0.05). There were significant differences between the CE and AE cohorts (p < 0.05) related to prevalence of hepatitis B, gallbladder diseases, echinococcosis disseminated.

Table 1

Characteristics of patients.

Table 2 presents the characteristics and anthropometric data of patients with cystic echinococcosis summarized and stratified by nutritional status. There were no statistical differences (p > 0.05) in age, height and ALB between the malnutrition and non-malnutrition groups when NRS2002 was used. However, there were significant differences (p < 0.05) in gender, weight and BMI between the two groups. There was no statistical difference (p > 0.05) in age, gender and height between the two groups when MUST, MNA-SF and NRI were used, but there were statistical differences in weight, BMI and ALB between the two groups. Using the ESPEN criteria, there were no statistical differences (p < 0.05) in age, gender, height and ALB between the two groups, and there were statistical differences in weight and BMI between the two groups.

Table 2

Characteristics and anthropometric data of cystic echinococcosis by nutritional status.

Table 3 presents the characteristics and anthropometric data of patients with alveolar echinococcosis summarized and stratified by nutritional status. There was no statistical difference in age, gender and height between the two groups when NRS2002 and ESPEN criteria were used, and there were statistical differences in BMI and HGB between the two groups. There were no statistical differences in age, gender and height between the two groups when MUST and MNA-SF were used, and there were statistical differences in weight, BMI and ALB between the two groups. There were no statistical differences in age, gender, height and weight between the two groups in NRI results, and there were statistical differences in ALB and BMI between the two groups. Table 4 lists the consistency analysis results of the three tools with the malnutrition standard. Consistency of κ ≥ 0.75 is good; consistency of 0.4 ≤ κ ≤ 0.75 is moderate; consistency of κ ≤ 0.4 is poor.

Table 3

Characteristics and anthropometric data of alveolar echinococcosis by nutritional status.

Table 4

Consistency test of three nutritional screening and ESPEN standard.

According to the new ESPEN diagnostic standard, the sensitivity and specificity of the four assessed nutritional screening tools are inconsistent. In cystic echinococcosis patients, MUST was the most sensitive (91.1%) tool and NRI was the least sensitive (66.1%) compared with ESPEN. NRS2002 had the highest specificity (75.8%), while NRI had the lowest specificity (55.1%). MUST had the highest negative predictive value (94.3%), while NRI had the lowest negative predictive value (79.8%). Finally, the area-under-the-curve (AUC) calculated by ROC showed that NRS 2002, MUST and MNA-SF had a moderate diagnostic value (AUC values for MUST, NRS 2002 and MNA-SF were 0.776, 0.780 and 0.803, respectively), while NRI had poor diagnostic value (AUC was 0.607). The results are detailed in Table 5.

Table 5

Comparison of four screening tools for malnutrition with ESPEN diagnostic criteria in cystic echinococcosis patients.

In alveolar echinococcosis patients, MNA-SF had the highest sensitivity (86.2%) compared with ESPEN, while NRS2002 had the lowest sensitivity (68.6%). NRS2002 had the highest specificity (86.6%), while NRI had the lowest sensitivity (40.2%). MUST and MNA-SF had the highest negative predictive value (91.2%), while NRI had the lowest negative predictive value (84.9%). Finally, the area-under-the-curve (AUC) calculated using ROC showed that NRS 2002, MUST and MNA-SF had moderate diagnostic value (AUC values of NRS 2002, MUST and MNA-SF are 0.776, 0.757 and 0.792, respectively), while NRI had poor diagnostic value (AUC is 0.622). The results are detailed in Table 6.

Table 6

Comparison of four screening tools for malnutrition with ESPEN diagnostic criteria in alveolar echinococcosis patients.

Discussion

Echinococcosis, a type of chronic consumptive disease, can damage the liver continuously and oppress normal liver tissue, and surrounding tissues and organs. It can lead to malnutrition and emaciation [22]. Echinococcosis is usually found in the liver, but can also be transferred to the abdominal cavity, lungs, brain and other organs [19, 20, 24]. It has the characteristics of slow onset and occult onset. At present, there are few reports on the nutritional status of patients with echinococcosis. In this study, the nutritional status of patients with alveolar echinococcosis or cystic echinococcosis (hydatid cysts and hydatid vesicles) was analyzed comprehensively for the first time. Four common nutritional screening tools were used to evaluate echinococcosis, and the results were compared with the results of the new European Society for clinical nutrition and metabolism (ESPEN) diagnostic standard [13, 26] to assess their suitability for diagnosing malnutrition in patients with echinococcosis disease. According to the ESPEN diagnostic criteria, 29.2% of the patients with cystic echinococcosis and 31.1% of the patients with alveolar echinococcosis were malnourished.

Malnutrition in patients with CE may be caused by the cystic hydatid cyst, which continuously increases in volume, putting pressure on the liver parenchyma and the bile duct. Bile duct necrosis occurs under a long-term high-pressure external force, resulting in the occurrence of cysts, obstructive jaundice, cholangitis, secondary infection of cyst, abnormal liver function, and the imbalance of nutrient metabolism [3]. Through asexual proliferation and strong granuloma reaction, AE infiltrates and grows to surrounding tissues, which is similar to a tumor to a certain extent, thus causing serious pathological damage to normal cells and tissues of the liver, compressing and eroding the bile duct, leading to extensive fibrosis, infiltration and necrosis of various inflammatory cells [2, 23]. Our study found that in-patients with echinococcosis often have other diseases as well. In this study, 46.2% of patients with echinococcosis also had hepatitis B, and 37.9% had gallbladder diseases. Echinococcosis is most prevalent in the Tibet Autonomous Region of China. There is also a high incidence rate of hepatitis B (HBV) among these populations, which may be related to poor living environments in some cases. Some studies have shown that the incidence rate of HBV in Tibetan populations is related to poor hygiene conditions, such as diet and drinking water, and lack of awareness of disease prevention methods and local epidemics [12]. Hepatitis B can lead to anorexia and daily calorie intake declines in patients with chronic liver disease, resulting in malnutrition [17]. In the same way, patients with cholecystitis may suffer from malnutrition due to the reduction of food intake and dyspepsia [16]. These may be additional reasons for the high incidence of malnutrition in hospitalized echinococcosis patients. In this study, malnutrition in both the AE and CE patients was associated with larger lesion sizes (statistically significant difference). This indicates that lesion size may be a risk factor for malnutrition in patients with echinococcosis. For patients with AE, the classification level may also be a risk factor. Nonparametric analysis results showed that patients with higher echinococcosis classification were more likely to suffer from malnutrition.

In this study, according to NRS2002 and MUST results, 40.3% and 51.5% of patients with CE were found to be at moderate or high risk of malnutrition. Using MNA-SF and NRI, results showed that 46.8% and 51.1% of patients, respectively, were found to be at risk of malnutrition. There were statistically significant differences in how the four nutritional screening tools classified patients with cystic echinococcosis by nutritional risk. This may be attributed to the differences in the nutritional screening tools. Among these tools, the reason for the poor consistency between NRI and the other three tools may be that many in-patients with cystic echinococcosis also have other diseases such as hepatitis, infections, etc., which lead to decreases in albumin and affect the NRI score. In a study by Poulia et al. [13], a comparison of NRS2002 and MUST tools was performed for hospitalized patients, using ESPEN diagnostic criteria as the gold standard of malnutrition. In this study, the new diagnostic criteria for malnutrition of MUST and ESPEN were better correlated (k = 0.843). However, in our study of patients with hydatid cysts, the correlation analysis comparing the four screening tools to the ESPEN diagnostic criteria showed that the correlation for MUST, NRS2002 and MNA-SF was moderate (k = 0.457, 0.496 and 0.515, respectively), and the correlation between ESPEN and NRI was poor (k = 0.175).

In this study, according to NRS2002 and MUST, 30.7% and 50.9% of the patients, respectively, with AE were found to be at moderate or high risk of malnutrition. Using MNA-SF and NRI, 44.1% and 67.4% of patients, respectively, were found to be at risk of malnutrition. There were statistically significant differences in how the four nutritional screening tools classified patients with alveolar echinococcosis by nutritional risk. Ye et al. [26] reported a comparison of NRS2002, MUST and MNA-SF tools in elderly patients with gastrointestinal cancer, using ESPEN diagnostic criteria as the gold standard of malnutrition. Their results showed that compared with NRS 2002 and MNA-SF, the correlation between MUST and ESPEN diagnostic criteria was the best (К = 0.530). In the current study of patients with AE, the correlation analysis between the four screening tools and ESPEN diagnostic criteria showed that the correlations between ESPEN and MUST, and NRS2002 and MNA-SF, respectively, were moderate (k = 0.525, 0.555, 0.439), and the correlation between ESPEN and NRI was poor (k = 0.186).

According to ESPEN diagnostic criteria and the four nutrition screening tools, AE and CE patients vary in incidence of malnutrition, with AE patients exhibiting a slightly higher rate of malnutrition than CE patients. Some patients with both of these types of echinococcosis had disseminated echinococcosis. In this study, 17.1% of AE patients and 9.9% of CE patients had disseminated, which may be one of the reasons the AE patients had a slightly higher incidence of malnutrition. In CE patients, the consistency between MNA-SF and ESPEN results was the best, while in AE, the consistency between NRS2002 and ESPEN results was the best. The purpose of nutrition screening is to accurately identify patients who are malnourished or at risk of malnutrition, and who can benefit from nutrition therapy. Good nutritional screening should be highly sensitive and specific. In this study of CE, according to the ESPEN diagnostic criteria, although the AUC value (0.780) of MUST was slightly higher than that of NRS2002 (0.776), the positive likelihood ratio of NRS2002 was significantly higher than that of MUST. In this study of AE, although the AUC value of MNA-SF was higher (0.792) than that of NRS2002 (0.776), the positive likelihood ratio and recessive likelihood ratio of NRS2002 were significantly higher than the corresponding values for MNA-SF. Based on these results, we conclude that MNA-SF and NRS2002 can be used in patients with CE and AE, but further research is needed to confirm this.

This study had some limitations. First, the scope of this study was hospitalized patients with hydatidosis, with many complications, which may not accurately represent all patients with echinococcosis, and the risk factors of malnutrition in patients with echinococcosis may not be comprehensive. Second, the sample size was relatively small, and focused on a single center. Third, this study lacks the reduction of fat free mass index (FFMI) to diagnose malnutrition. The ESPEN malnutrition diagnosis standard can also allow diagnosis by unintended weight loss and fat free mass index (FFMI) reduction. The hospital where our study was focused lacked the specialized equipment needed for FFMI measurement. Therefore, further research is needed to verify our findings.

Conclusions

This is the first time common nutritional screening tools have been used to screen the nutritional risk of echinococcosis patients and the first comparison of four malnutrition screening tools (NRS 2002, MUST, MNA-SF and NRI) against the ESPEN malnutrition diagnosis standard. In this study, according to the ESPEN diagnostic criteria for malnutrition in patients with CE and AE, the malnutrition rates were 29.2% and 31.1%, respectively. NRS2002 and MNA-SF may be better screening tools for hospitalized patients with hepatic echinococcosis.

Conflicts of interest

The authors have no potential conflict of interest.

Funding

Funding were provided by Innovation platform construction project in the Qinghai Department of Science and Technology (2020-ZJ-Y01) and the Key Projects of Precision Medicine Research in National Key R&D Programmes (2017YFC0909900).

Acknowledgments

We gratefully acknowledge the valuable cooperation of Professor HaiNing Fan and the members of hepatobiliary and pancreatic surgery department of the Affiliated Hospital of Qinghai University in data collection.

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Cite this article as: Wang Z, Xu J, Song G, Pang M, Guo B, Xu X, Wang H, Zhou Y, Ren L, Zhou H, Ma J & Fan H. 2020. Nutritional status and screening tools to detect nutritional risk in hospitalized patients with hepatic echinococcosis. Parasite 27, 74.

All Tables

Table 1

Characteristics of patients.

In the text
Table 2

Characteristics and anthropometric data of cystic echinococcosis by nutritional status.

In the text
Table 3

Characteristics and anthropometric data of alveolar echinococcosis by nutritional status.

In the text
Table 4

Consistency test of three nutritional screening and ESPEN standard.

In the text
Table 5

Comparison of four screening tools for malnutrition with ESPEN diagnostic criteria in cystic echinococcosis patients.

In the text
Table 6

Comparison of four screening tools for malnutrition with ESPEN diagnostic criteria in alveolar echinococcosis patients.

In the text

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