Abstract
Background
Muscle mass depletion caused by hypercatabolism and inappropriate nutritional support in patients with intestinal failure (IF) is associated with poor clinical outcomes and reduced quality of life. This retrospective study evaluated the correlation between nutritional support factors (type and composition) and muscle mass.
Methods
In this cohort study, two hundreds and twenty-three eligible patients with type I or II IF were included at a clinical nutrition center between September 2013 and September 2017. Muscle mass was measured via Bioelectrical Impedance Analysis. Statistical analyses included paired-samples T test, Pearson’s or Spearman’s rank correlation, univariate and multivariate regressions.
Results
The mean age was 46.1 ± 18.6 years, the mean nutritional risk screening -2002 score was 3.5 ± 0.8, and the median hospitalization duration was 19.5 days. Multivariate linear regression analysis revealed that Δsoft lean mass (ΔSLM) and Δskeletal muscle mass (ΔSMM) were significantly correlated with calories delivered via parenteral nutrition (PN) (β = 0.051, 95%CI [0.014, 0.008], p < 0.05 and β = 0.041, 95%CI [0.010, 0.072], p < 0.05). Among the PN composition variables, daily glucose intake via PN showed a significant correlation with ΔSLM (β = 0.350, 95%CI [0.091, 0.609], p < 0.01) and ΔSMM (β = 0.254, 95%CI [0.027, 0.481], p < 0.01). Subgroup analysis revealed that daily glucose intake via PN was associated with ΔSMM, especially at ≥1.2 g/kg/day of amino acid intake (r = 0.328, p < 0.01).
Conclusions
Adequate calories and amino acids supplementation delivered via parenteral nutrition play an important role in promoting muscle mass maintenance in patients with type I or II intestinal failure, who were under metabolically unstable or enteral nutrition intolerance condition.
Keywords: Intestinal failure, parenteral nutrition, muscle mass, nutritional support, adequate calories
Background
Intestinal failure (IF) is a rare form of organ failure that is defined as malabsorption and subsequent nutrient deficiency. The main causes are benign but severe gastrointestinal diseases, such as short bowel disease, mechanical obstruction, and intestinal fistula, although IF can also be caused by malignant diseases, such as end-stage intra-abdominal or pelvic cancers [1–4]. Unfortunately, patients with IF often require a prolonged recovery period and long-term nutritional support, as they develop hypercatabolism that is caused by disease stress, inflammation, and reduced nutrient intake [4,5].
According to the European Society for Clinical Nutrition and Metabolism (ESPEN) recommendations, intestinal failure had been defined as ‘the reduction of gut function below the minimum necessary for the absorption of macronutrients and/or water and electrolytes, such that intravenous supplementation (IVS) is required to maintain health and/or growth’ [2,3,6]. Patients with an acute, short-term and usually self-limiting condition, which often occurring perioperatively after abdominal surgery and/or in association with critical illnesses and requiring IVS for a few days or weeks, was defined as type I IF. Patients with type II IF were often in a prolonged acute condition with a metabolically unstable condition, who requiring complex multidisciplinary care and IVS for weeks or months. Type III IF were usually in a chronic metabolically stable condition, who requiring IVS for months or years [6,7].
Patients with IF also often develop muscle wasting or depletion because of hypercatabolism and/or inappropriate nutritional support [8,9]. However, muscle mass is needed to facilitate locomotion, maintain the entire body’s metabolic health, and promote recovery [10]. Moreover, studies have indicated that a low muscle mass and/or muscle wasting during critical illness are associated with poor clinical outcomes, reduce quality of life, and impaired rehabilitation [9,11]. Therefore, maintenance of muscle mass during hospitalization can promote recovery, preserve physical independence, and improve quality of life [10].
Both resistance training and sufficient nutrient supplementation play an important roles in maintaining muscle mass [12,13]. However, the ESPEN guidelines recommend that nutritional support regimens be personalized for each patient and adjusted over time based on formal nutritional assessments [2,3]. Nevertheless, most guidelines only provide recommendations regarding total energy and protein requirements, based on the basal metabolic rate and nitrogen balance rather than the muscle mass [3,14,15]. Previously, most studies focused on different dose, regimens and timing of nutrition support on clinical outcomes, few regarding on muscle mass [16–18]. Thus, the relationships between different nutritional support regimens and muscle mass remain unclear. This study aimed to investigate the relationships between nutritional support factors and muscle mass among patients with type I or II IF, in order to identify nutrients and regimens that can help preserve muscle mass.
Methods and materials
Patient selection
This retrospective study evaluated data from 325 consecutive patients with type I or II IF who underwent treatment at a clinical nutrition center between September 2013 and September 2017. The study aimed to identify nutritional support factors that influenced muscle mass during these patients’ hospitalization. Adult patients with type I or II IF were considered eligible if they received parenteral nutrition (PN) for >7 days. The exclusion criteria were (1) patients with hepatic insufficiency based on an alanine transaminase/aspartate transaminase ratio that was >2× the upper limit of normal or a bilirubin level of >3 mg/dL; (2) patients with renal dysfunction based on a serum creatinine level of >1.5 mg/dL; (3) patients with serious illness, such as shock, collapse, stroke, coma of unknown etiology, or recent cardiac infarction; and (4) pregnant or lactating women. The study was conducted in accordance with the Declaration of Helsinki and has been approved by the Ethics Committee of the Jinling hospital, Medical School of Nanjing University (2021NZKY-069). Written informed consent participating in this study was obtained from all of the patients.
Definitions
The definition of muscle mass included soft lean mass (SLM), skeletal muscle mass (SMM), and fat-free mass (FFM), which were measured and recorded using a body composition analyzer (InBody S10, Biospace, Seoul, Korea) at the patients’ admission and discharge. FFM is defined as total body weight minus body fat mass. SLM is calculated by subtracting the content of extra bone inorganic salts from FFM. SMM represents the portion of skeletal muscle tissue within the SLM. Changes in muscle mass were calculated by comparing the discharge and admission values, and were reported as ΔSLM, ΔSMM and ΔFFM. SLM and SMM, as commonly utilized indicators of muscle mass, were assessed via bioelectrical impedance analysis (BIA) in the context of sarcopenia diagnosis and the Global Leadership Initiative on Malnutrition (GLIM) criteria for malnutrition [19]. The dynamic changes in SLM (ΔSLM) and SMM (ΔSMM) serve as clinically validated parameters for monitoring the efficacy of in-hospital nutritional support interventions. Data were also collected regarding the patients’ basic characteristics and nutritional support parameters, such as age, sex, body mass index, NRS-2002 score, SGA grade, etiology of malnutrition, and daily energy and protein values from enteral nutrition (EN) and PN. Resting energy expenditure was used to guide energy delivery, and was evaluated weekly using indirect calorimetry (Quark PFT ERGO, COSMED Srl, Italy). A protein intake target of 1.2 g/kg/day was selected based on the patients’ daily serum albumin results. The dosage of protein provision was according to the American Society for Parenteral and Enteral Nutrition (ASPEN) and ESPEN guidelines. According to the ASPEN guidelines, the target dosage of protein intake was 1.2–2.0 g/kg/day and adjusted according to the nitrogen balance and other nutrition biomarkers [14]. ESPEN guidelines recommended that the dosage of protein intake was 0.8–1.4 g/kg/day based on individual patient characteristics (e.g. intestinal absorptive capacity as estimated by gastrointestinal anatomy and/or underlying disease) and specific needs (e.g. acute illness, protein malnutrition), and that the adequacy of the regimen is regularly evaluated through clinical, anthropometric, and biochemical parameters [2,3]. All patients received strict fluid intake management. The nutritional support regimens were recorded daily.
Statistical analysis
Statistical analyses were performed using IBM SPSS software (version 20.0; IBM Corp., Armonk, NY). Two-tailed p-values of <0.05 were considered statistically significant, and p-values of <0.1 were considered indicative of a statistical tendency. Normally distributed continuous variables were reported as mean ± standard deviation, and non-normally distributed continuous variables were reported as median (interquartile range). The admission and discharge values for SLM, SMM, and FFM were compared using the paired-samples T test. Correlations between the patients’ characteristics and the ΔSLM, ΔSMM, and ΔFFM values were evaluated using Pearson’s correlation coefficient or Spearman’s rank correlation value (categorical variables). The univariate analysis of ΔSLM, ΔSMM and ΔFFM were performed using bivariate linear correlation, and all parameters with a p-value of <0.1 were entered into the multivariate analysis. Multivariate linear regression models (backward regression) were used to identify factors that independently influenced ΔSLM, ΔSMM, and ΔFFM.
Results
Among the 325 potentially eligible patients, we excluded 57 patients who only received enteral nutrition (EN). Among the 268 patients with type I or II IF who received PN, we also excluded patients based on an age of <18 years (22 cases), hepatic insufficiency (13 cases), renal insufficiency (5 cases), acute or life-threatening conditions (4 cases), and pregnancy (1 case). Thus, data from 223 patients with type I or II IF were included in the final analysis (Figure 1).
Figure 1.
Study flow chart.
The patients’ demographic and clinical characteristics
Table 1 shows the patients’ clinical and demographic characteristics. The cohort included 119 women. The mean age was 46.08 ± 18.57 years and the mean body mass index was 16.80 ± 3.44 kg/m2. A nutritional risk screening 2002 score of >3 was detected for 94.8% of the patients, and only 6.8% of the patients were considered well-nourished based on their subjective comprehensive assessment score. The median hospitalization duration was 19.5 days, and ileus was the main cause of malnutrition. The values for daily calories and protein intake are also shown in Table 1.
Table 1.
Demographic and clinical information for included patients.
| Characteristics | Value |
|---|---|
| n | 223 |
| Age (years) | 46.08 ± 18.57 |
| Body weight (kg) | 44.57 ± 11.24 |
| BMI (kg/m2) | 16.80 ± 3.44 |
| Sex | |
| Male | 104 (46.6%) |
| Female | 119 (53.4%) |
| NRS2002 | 3.54 ± 0.82 |
| ≥3 | 182 (94.8%) |
| <3 | 10 (5.2%) |
| SGA class | |
| A | 13 (6.8%) |
| B | 74 (38.9%) |
| C | 103 (54.2%) |
| Etiology of malnutrition | |
| SBS | 35 |
| Ileus | 84 |
| Gastrointestinal mucosa diseases | 26 |
| Severe stress or wasting conditions | 40 |
| Gastrointestinal dysfunction | 37 |
| Others | 1 |
| Mean LOS (days) | 23.55 ± 16.40 |
| Median LOS (days) | 19.50 (13.25, 29.00) |
| Basal metabolic rate (kcal/kg) | 28.51 ± 4.62 |
| Daily energy (kcal/kg) | 29.11 ± 10.90 |
| Daily protein (g/kg) | 1.29 ± 0.53 |
| Daily energy via EN (kcal/kg) | 13.46 ± 10.49 |
| Daily energy via PN (kcal/kg) | 15.87 ± 9.77 |
Abbreviations: BMI, body mass index; NRS2002, nutritional risk screening 2002; SGA, subjective global assessment; SBS, short bowel syndrome; LOS, length of hospital stay; EN, enteral nutrition; PN, parenteral nutrition.
Correlations between nutritional support, clinical factors, and changes in muscle mass
SLM and SMM were significantly increased at discharge after nutritional support in hospitalization (Table S1). Table 2 shows the correlations between the changes in muscle mass and the daily energy and protein intakes. The results indicate that ΔSLM was significantly correlated with calories delivered via PN (r = 0.230, p < 0.01) and protein delivered via PN (r = 0.202, p < 0.05). In addition, ΔSMM was significantly correlated with total calories (r = 0.270, p < 0.01), calories delivered via PN (r = 0.296, p < 0.01), total protein (r = 0.223, p < 0.01), and protein delivered via PN (r = 0.224, p < 0.01). However, ΔFFM was not significantly correlated with any of the nutritional regimen variables. Table S2 shows the correlations between the other clinical and nutritional parameters. The results indicate that ΔSLM was also significantly correlated with gender (r= −0.195, p < 0.05), while ΔSMM was significantly correlated with gender (r = −0.177, p < 0.05) and body weight (r= −0.224, p < 0.01).
Table 2.
The bivariate linear correlations between muscle mass and nutritional regimen variables.
| ΔSLM | ΔSMM | ΔFFM | |||
|---|---|---|---|---|---|
| Calories | Total (kcal/kg) | r | 0.139₤ | 0.270** | –0.026 |
| PN (kcal/kg) | r | 0.230** | 0.296** | 0.082 | |
| EN (kcal/kg) | r | –0.082 | –0.018 | –0.102 | |
| Protein | Total (kcal/kg) | r | 0.144₤ | 0.223** | 0.007 |
| PN (kcal/kg) | r | 0.202* | 0.224** | 0.090 | |
| EN (kcal/kg) | r | –0.108 | –0.041 | –0.120 |
Note: Correlations between caloric intake and the changes in skeletal muscle mass (ΔSMM), lean soft tissue mass (ΔSLM), and fat-free mass (ΔFFM) values were evaluated using Pearson’s correlation coefficient analysis. *p < 0.05; **p < 0.01; ₤p = 0.05–0.1. Δ, change in parameter; SLM, soft lean mass; SMM, skeletal muscle mass; FFM, fat-free mass; EN, enteral nutrition; PN, parenteral nutrition. ΔSLM = SLM at discharge – SLM at admission. ΔSMM = SMM at discharge – SMM at admission. ΔFFM = FFM at discharge – FFM at admission.
Calories delivered via PN were independently associated with ΔSLM and ΔSMM
All parameters with p-values of <0.1 in the univariate analyses were included in the multivariate analyses, and the adjusted results are shown in Table 3. Female gender was an independent risk factor for negative ΔSLM among patients with IF (β = –0.992, 95%CI [−1.719, −0.265], p = 0.008). Body weight was independently and negatively associated with ΔSMM (β = –0.036, 95%CI [−0.069, −0.003], p = 0.043). Calories delivered via PN were positively correlated with both ΔSLM (β = 0.051, 95%CI [0.014, 0.008], p = 0.009) and ΔSMM (β = 0.041, 95%CI [0.010, 0.072], p = 0.014).
Table 3.
Multivariate linear regression analysis for predictors of ΔSLM and ΔSMM.
| Parameters | Unstandardized coefficients |
t | p | |||
|---|---|---|---|---|---|---|
| β | 95%CI | SE | ||||
| ΔSLM | (Constant) | 1.205 | [−0.191, 2.601] | 0.712 | 1.693 | 0.093 |
| Female sex | –0.992 | [−1.719, −0.265] | 0.371 | –2.676 | <0.01 | |
| Calories (PN) | 0.051 | [0.014, 0.008] | 0.019 | 2.629 | <0.01 | |
| ΔSMM | (Constant) | 2.049 | [−0.136, 4.234] | 1.115 | 1.838 | 0.068 |
| Female sex | –0.512 | [−1.090, 0.066] | 0.295 | –1.734 | 0.085 | |
| Body weight (kg) | –0.036 | [−0.069, −0.003] | 0.017 | –2.048 | <0.05 | |
| Calories (PN) | 0.041 | [0.010, 0.072] | 0.016 | 2.499 | <0.05 | |
Abbreviations: SLM, soft lean mass; SMM, skeletal muscle mass; PN, parenteral nutrition.
Note: ΔSLM = SLM at discharge – SLM at admission. ΔSMM = SMM at discharge – SMM at admission.
Daily glucose intake via PN affects both ΔSLM and ΔSMM
As calories delivered via PN were independently associated with both ΔSLM and ΔSMM, we evaluated which nutritional components affected this relationship. The univariate analyses revealed that ΔSLM was significantly correlated with daily glucose intake (r = 0.215, p < 0.01) and daily amino acid intake (r = 0.207, p < 0.05), while ΔSMM was significantly correlated with daily glucose intake (r = 0.313, p < 0.01), daily amino acid intake (r = 0.229, p < 0.01), daily soybean oil intake (r = 0.269, p < 0.01), and daily fish oil intake (r = 0.293, p < 0.01) (Table 4). The variables with a p-value of <0.1 in the univariate analyses were entered into the multivariate analyses, and the results are shown in Table 5. We found that only daily glucose intake via PN independently affected ΔSLM (β = 0.35, 95%CI [−0.069, −0.003], p = 0.009) and ΔSMM (β = 0.254, 95%CI [0.027, 0.481], p = 0.030).
Table 4.
The bivariate linear correlation between muscle mass and parenteral nutrition components.
| Parameters | Glucose | Amino acids | Soybean oil | Fish oil | |
|---|---|---|---|---|---|
| (g/kg) | (g/kg) | (g/kg) | (g/kg) | ||
| ΔSLM | r | 0.215** | 0.207* | 0.157₤ | 0.158₤ |
| ΔSMM | r | 0.313** | 0.229** | 0.269** | 0.293** |
Note: Correlations between caloric intake and the changes in skeletal muscle mass (ΔSMM) and lean soft tissue mass (ΔSLM) values were evaluated using Pearson’s correlation coefficient analysis. *p < 0.05; **p < 0.01; ₤p = 0.05–0.1. SLM, soft lean mass; SMM, skeletal muscle mass. ΔSLM = SLM at discharge – SLM at admission. ΔSMM = SMM at discharge – SMM at admission.
Table 5.
Multivariate linear regression analysis for predictors of ΔSLM and ΔSMM (parenteral nutrition components).
| Parameters | Unstandardized Coefficients |
t | p | |||
|---|---|---|---|---|---|---|
| β | 95%CI | SE | ||||
| ΔSLM | (Constant) | 1.084 | [−0.315, 2.483] | 0.714 | 1.517 | 0.131 |
| Glucose (g/kg) | 0.35 | [0.091, 0.609] | 0.132 | 2.651 | <0.01 | |
| ΔSMM | (Constant) | −0.557 | [−1.149, 0.035] | 0.302 | −1.845 | 0.067 |
| Glucose (g/kg) | 0.254 | [0.027, 0.481] | 0.116 | 2.196 | <0.05 | |
| Fish oil (g/kg) | 2.495 | [−0.420, 5.410] | 1.487 | 1.677 | 0.096 | |
Abbreviations: SLM, soft lean mass; SMM, skeletal muscle mass.
Note: ΔSLM = SLM at discharge – SLM at admission. ΔSMM = SMM at discharge – SMM at admission.
Relationships between PN variables and ΔSLM and ΔSMM according to daily protein intake
We then performed a subgroup analysis and divided patients into a low-protein group (<1.2 g/kg/day) and a high-protein group (≥1.2 g/kg/day), based on their average daily total protein intake during hospitalization. When the protein intake was <1.2 g/kg/day, amino acids delivered via PN were significantly associated with both ΔSLM (r = 0.257, p = 0.044) and ΔSMM (r = 0.263, p = 0.039), while glucose delivered via PN only trended towards being a significant factor. When the protein intake was ≥1.2 g/kg/day, glucose delivered via PN was significantly associated with ΔSMM (r = 0.328, p = 0.002), while amino acids delivered via PN showed no significant difference. The detailed results are shown in Figure 2.
Figure 2.
Correlations between PN variables (glucose via PN and amino acids via PN) and ΔSLM and ΔSMM according to daily protein intake.
Pearson’s correlation coefficients analysis were calculated to assess the relationships between parenteral nutrition (PN) variables (glucose and amino acid delivery via PN) and changes in skeletal lean mass (ΔSLM) and skeletal muscle mass (ΔSMM), stratified by daily protein intake. ΔSLM = SLM at discharge – SLM at admission; ΔSMM = SMM at discharge – SMM at admission.
Discussion
Nutritional support provides benefits to patients with critical illness, patients who have undergone surgery, and patients with IF [2,3, 14,20]. Previous studies mostly focused on nutritional support on patients’ morbidity and mortality in critical illness or postoperative conditions, few studies demonstrated the effect of nutritional support on muscle mass changes. Thus, we investigated the correlations between nutritional support variables and muscle mass among patients with type I or II IF. The results revealed that nutritional support significantly increased these patients’ muscle mass. Unexpectedly, we found that calories delivered via PN, but not via EN, were independently associated with increased SLM and SMM values, even after adjustment for sex, age, body weight, nutrition status, and disease status. Furthermore, we found that the amount of glucose delivered via PN, in patients with sufficient amino acid intake, was significantly associated with muscle mass preservation. However, the effect of glucose intake via PN on muscle mass was nullified by inadequate amino acid supplementation.
The patients in the present study received nutritional support that contained average values of 1.29 g/kg/day for protein and 29.11 kcal/kg/day for energy, with glucose accounting for 8.97 kcal/kg/day and fatty acids accounting for 5.68 kcal/kg/day. These nutritional support regimens are consistent with the several clinical nutrition guidelines for critically ill patients’ recommendations [3,14,15]. Furthermore, as the patients’ regimens were based on their nutritional assessments and biochemical parameters, we were able to analyze the relationships between the nutritional support variables and changes in SLM and SMM.
In present study, the multivariate linear regression analysis revealed that calories and protein delivered via PN, but not via EN, played important roles in increasing the SLM and SMM values. As well known, the recent guidelines and related meta-analysis suggest that EN, and especially early EN, provides a greater benefit than PN for various critically ill patients [14,17, 18,21]. This may partially explained by the difference in tolerating enteral nutrition in different study population. In our study, patients with type I or II IF had a severe gastrointestinal condition with most patients suffered from ileus, severe stress or wasting conditions, gastrointestinal dysfunction and short bowel syndrome. As enteral nutrition was poorly tolerated in these patients, the supplemented enteral nutrition was not efficiently absorbed into the circulation and even aggravate the loss of water, electrolytes and nutrients. However, lots of critically ill patients, such as patients with neurological or respiratory disorders, typically have better gastrointestinal function than patients with type I or IF, and are more likely to achieve their targeted full caloric intake via EN during a short time [21]. In addition, patients admitted into our study were in metabolically unstable states with muscle protein catabolism greater than muscle protein synthesis. Long-term total parenteral nutrition or supplemental parenteral nutrition, rather than enteral nutrition, was the main nutrition support regime to meet patients’ energy requirement, which reduced the positive effect of enteral nutrition support.
Although long term PN provision was associated with a range of complications, notably catheter-related bloodstream infections and intestinal failure associated intestinal failure, PN was considered safe, effective and the mainstay in the treatment of patients with IF [22]. In the study population, there was no obviously severe PN related complications that lead to PN cessation. In our center, the caloric requirements were evaluated weekly based on the value of resting energy expenditure measured using indirect calorimetry, to ensure adequate calories were provided and avoid excessive or insufficient nutritional supplements, which can also cause muscle mass depletion. Previous studies reported that early PN, especially nutrient solutions rich in amino acids and fat emulsions during PN, can lead to inhibition of autophagy, inducing accumulation of damaged proteins and mitochondria, and thus contributing to skeletal muscle depletion in critically ill patients [16]. However, results among critically ill patients were not applicable for patients with IF, who had less severe disease and required long-term PN. Patients with type I or II IF typically have both calories and protein deficiency, it is unrealistic to limit their energy and protein supplementation.
The PN compositions were also evaluated for associations with changes in muscle mass during the patients’ hospitalization. In the present study, SMM, FFM, and SLM all demonstrated significant increases at discharge following in-hospital nutritional support. However, the increase in FFM did not reach statistical significance. Similarly, bivariate linear correlation analyses between muscle mass parameters and nutritional regimen variables revealed no significant associations with FFM. This observation may be primarily attributed to the relatively short assessment interval (hospital stay duration approximately 2–4 weeks). Furthermore, when compared to FFM, which encompasses SLM as well as inorganic salts within bone tissue, both SLM and SMM demonstrate superior sensitivity in reflecting changes in muscle mass. The univariate analyses revealed that daily glucose and amino acid intakes were positively correlated with the changes in SLM and SMM. In addition, fatty acids from soybean oil and fish oil were also significantly related to the changes in SMM. Furthermore, glucose intake was independently and positively correlated with changes in SLM and SMM after adjusting for sex, body weight, and disease status. However, previous studies have indicated that essential amino acids and branched chain amino acids, but not glucose, contribute to almost all muscle protein synthesis [10]. In particularly, leucine is the most effective essential amino acid for promoting muscle protein synthesis [12,23]. Nevertheless, the maintenance of muscle mass depends on the balance between muscle protein synthesis and catabolism [10], and most of patients with type I or II IF are in a state of hypercatabolism. Thus, to maintain their muscle mass, protein catabolism suppression may be more important than promoting protein synthesis. In this context, it is clear that amino acids alone cannot suppress muscle protein catabolism [24], which must be achieved using elevated insulin levels and nutritional supplements [25]. Glucose serves as the primary direct energy substrate for the human body. Adequate glucose supplementation can effectively suppress muscle protein catabolism, particularly in patients with type I or II IF who exhibit a hyper-catabolic state. Therefore, the increases in SLM and SMM that were detected in the present study could be related to glucose supplementation and the accompanying increased insulin levels. Interestingly, although glucose intake was associated with muscle mass, the results of the subgroup analysis revealed that amino acid supplementation also played a key role in maintaining muscle mass. This is because lower amino acid intake (<1.2 g/kg/day) nullified the effects of increased glucose intake, and these effects were only apparent for patients with adequate amino acid intake supplementation.
The present study also revealed that fish oil intake trended towards a correlation with the change in SMM after adjustment for sex and body weight. Previous studies have indicated that n-3 polyunsaturated fatty acids reduce the levels of tumor necrosis factor-α and interleukin-6, which may explain the beneficial effects of fish oil on muscles [26]. Furthermore, other clinical studies have indicated fish oil supplementation can help increase muscle mass and preserve musculoskeletal health [27]. Moreover, animal studies have indicated that eicosapentaenoic acid- and docosahexaenoic acid-enriched fish oils reduced non-inflammatory skeletal muscle disuse atrophy and energy restriction-related muscle mass loss, by activating protein synthesis and insulin signaling pathways [28].
The present study had several limitations. (i) It was a retrospective single-institution study performed at a tertiary-care referral center. (ii) Patients with IF have complex etiologies, and their baseline data—such as small bowel length and the nature of intestinal lesions—are heterogeneous, which may introduce potential biases and confounding factors. (iii) The sample size was might be relatively small, which limited the persuasiveness of the conclusion. Therefore, large-scale randomized controlled trials are needed to determine the correlation between various nutritional support regimes and components on muscle mass preservation, and to optimize the cost-effectiveness and clinical efficacy of nutritional support.
Conclusions
In conclusion, the present study revealed that adequate calories and amino acids delivered via PN play an important role in maintaining muscle mass, especially SMM, for patients with type I or II IF in a metabolically unstable or enteral nutrition intolerance condition. In clinical practice, when given patients sufficient isocaloric nutritional support, we should fully emphasize the importance of giving adequate amino acids or protein supplements. The effect of glucose intake on muscle mass can be offset by inadequate amino acid or protein supplementation.
Supplementary Material
Acknowledgments
The authors thank the patients for their clinical data. JY, QW, FT and XW had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis; JY and FT contributed to the concept and design, data analysis, data interpretation, and drafting the manuscript; JY, QW, FT and XW contributed to the critical revision of the manuscript for important intellectual content; All authors revised the manuscript critically for important intellectual content and approved the final version of the manuscript.
Funding Statement
This research was funded by the National Natural Science Foundation of China under Grant [81900524, 82000492, 82170575], the Natural Science Foundation of Shandong Province under Grants [ZR2020MH252, ZR2020MH205, and ZR2022MH085], the China Postdoctoral Science Foundation under Grant [2020M672102], and the Science and Technology Development Program of Jinan under Grant [202134027]
Disclosure statement
No potential conflict of interest was reported by the authors.
Data availability statement
The data that support the findings of this study are available from the corresponding author upon reasonable request (XW).
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request (XW).