Hyper- and hypometabolism are not related to nutritional status of patients on the waiting list for liver transplantation

Redefining Nutritional Requirements in End-Stage Liver Disease: Towards a Personalized Approach

Malnutrition is ubiquitous in cirrhotic patients presenting for liver transplant (LT). Providing an appropriate energy prescription is fundamental to effective nutrition therapy. We aimed to compare measured energy expenditure (mEE) with predicted energy expenditure (pEE) in patients awaiting LT and determine clinical factors associated with mEE. In this prospective observational study, energy expenditure was measured by indirect calorimetry in 110 adult patients referred for LT and predicted by commonly utilized equations (Harris-Benedict, Schofield, and EASL guidelines). Nutritional status, anthropometry, muscle function, biochemical and clinical data were also collected. The median model for end-stage liver disease (MELD) was 19 (IQR 13, 25), and the majority were Child-Pugh B (51%) or C (37%). Malnutrition was evident in 85%. Median mEE by calorimetry was 1756 (1531, 2104) kcal/d and significantly higher than pEE as per Harris-Benedict 1480 (1322, 1722) kcal/d and Schofield 1474 (1349, 1723) kcal/d (both p < 0.001), but lower than EASL guidelines (35 kcal/kg) when an activity factor was applied to mEE; 2283 (1990, 2735) kcal/d versus 2590 (2178, 3010) kcal/d (p < 0.001). Hypermetabolism (mEE:pEE > 1.2) was evident in 48% of the cohort. Multivariate analysis found MELD, Child-Pugh class, diuretic use, and severe malnutrition to be independent predictors of hypermetabolism. A new liver-specific predictive model has been developed, showing superior agreement with mEE than common predictive equations. In conclusion, there is a poor correlation between mEE and pEE in patients awaiting LTs, and hypermetabolism is common. Relying on historical predictive equations in this patient population may result in significant under or over-feeding. A tailored energy prescription based on indirect calorimetry or a liver-specific predictive model is recommended for LT candidates.

Predicted estimates of resting energy expenditure have limited clinical utility in patients with cirrhosis

BACKGROUND & AIMS

Malnutrition is associated with adverse clinical outcomes in patients with cirrhosis. Accurate assessment of energy requirements is needed to optimize dietary intake. Resting energy expenditure (REE), the major component of total energy expenditure, can be measured using indirect calorimetry (mREE) or estimated using prediction equations (pREE). This study assessed the usefulness of predicted estimates of REE in this patient population.

METHODS

Individual mREE data were available for 900 patients with cirrhosis (mean [±1 SD] age 55.7±11.6 years-old; 70% men; 52% south-east Asian) and 282 healthy controls (mean age 36.0±12.8 years-old; 52% men; 18% south-east Asian). Metabolic status was classified using thresholds based on the mean ± 1 SD of the mREE in the healthy controls. Comparisons were made between mREE and pREE estimates obtained using the Harris-Benedict, Mifflin, Schofield and Henry equations. Stepwise regression was used to build 3 new prediction models which included sex, ethnicity, body composition measures, and model for end-stage liver disease scores.

RESULTS

The mean mREE was significantly higher in patients than controls when referenced to dry body weight (22.4±3.8 cf. 20.8±2.6 kcal/kg/24 hr; p <0.001); there were no significant sex differences. The mean mREE was significantly higher in Caucasian than Asian patients (23.1±4.4 cf. 21.7±2.9 kcal/kg/24 hr; p <0.001). Overall, 37.1% of Caucasian and 25.3% of Asian patients were classified as hypermetabolic. The differences between mREE and pREE were both statistically and clinically relevant; in the total patient population, pREE estimates ranged from 501 kcal/24 hr less to 548 kcal/24 hr more than the mREE. Newly derived prediction equations provided better estimates of mREE but still had limited clinical utility.

CONCLUSIONS

Prediction equations do not provide useful estimates of REE in patients with cirrhosis. REE should be directly measured.

LAY SUMMARY

People with cirrhosis are often malnourished and this has a detrimental effect on outcome. Provision of an adequate diet is very important and is best achieved by measuring daily energy requirements and adjusting dietary intake accordingly. Prediction equations, which use information on age, sex, weight, and height can be used to estimate energy requirements; however, the results they provide are not accurate enough for clinical use, particularly as they vary according to sex and ethnicity.

Different combinations of the GLIM criteria for patients awaiting a liver transplant: Poor performance for malnutrition diagnosis but a potentially useful prognostic tool

BACKGROUND & AIMS

Studies using the Global Leadership Initiative on Malnutrition (GLIM) criteria for patients with liver cirrhosis are limited. This study aimed to assess the impact of malnutrition according to the GLIM criteria on the outcomes of patients awaiting a liver transplant (LTx) and compare these criteria with Subjective Global Assessment (SGA).

METHODS

This retrospective observational study included adult patients awaiting LTx. Patient clinical data, nutritional status according to various tools including SGA, and resting energy expenditure were assessed. The distinct phenotypic and etiologic criteria provided 36 different GLIM combinations. The GLIM criteria and SGA were compared using the kappa coefficient. The variables associated with mortality before and after the LTx and with a longer length of stay (LOS) after LTx (≥18 days) were assessed by Cox regression and logistic regression analyses, respectively.

RESULTS

A total of 152 patients were included [median age 52.0 (interquartile range: 46.5-59.5) years; 66.4% men; 63.2% malnourished according to SGA]. The prevalence of malnutrition according to the GLIM criteria ranged from 0.7% to 30.9%. The majority of the GLIM combinations exhibited poor agreement with SGA. Independent predictors of mortality before and after LTx were presence of ascites or edema (p = 0.011; HR:2.58; CI95%:1.24-5.36), GLIM 32 (PA-phase angle + MELD) (p = 0.026; HR:2.08; CI95%:1.09-3.97), GLIM 33 (PA + MELD-Na≥12) (p = 0.018; HR:2.17; CI95%:1.14-4.13), and GLIM 34 (PA + Child-Pugh) (p = 0.043; HR:1.96; CI95%:1.02-3.77). Malnutrition according to GLIM 28 (handgrip strength + Child-Pugh) was independently associated with a longer LOS (p = 0.029; OR:7.21; CI95%:1.22-42.50).

CONCLUSION

The majority of GLIM combinations had poor agreement with SGA, and 4 of the 36 GLIM combinations were independently associated with adverse outcomes.

Bioelectrical impedance vector analysis in patients on the waiting list for liver transplant: Associated factors and prognostic effects

OBJECTIVES

The aim of this study was to assess patients on the waiting list for liver transplant (LTx) according to bioelectrical impedance vector analysis (BIVA), as well as to verify the association between the placement of the vectors on the graph with clinical outcomes and identify the predictors to vector placement in quadrant 4 (Q4; indicating more hydration and less cellularity).

METHODS

This was a retrospective observational study including 129 patients ≥20 y of age awaiting LTx. Patients' nutritional status was assessed by using different tools, including single-frequency bioelectrical impedance analysis and the Subjective Global Assessment (SGA). Clinical data were registered. The BIVA was evaluated by comparing the individual vectors plotted for all patients to the tolerance ellipses of 50%, 75%, and 95% of the reference healthy population. The quadrant of the vector for each patient was registered.

RESULTS

The majority of the vectors were placed in Q1 (n = 54; 41.9%) and Q4 (n = 39; 30.2%). The presence of ascites or edema (hazard ratio [HR], 2.43; 95% confidence interval [CI], 1.15-5.12; P = 0.019) and the BIVA vector placed in Q4 in any ellipse (HR, 2.10; 95% CI, 1.07-4.09; P = 0.029) were independent predictors for mortality on the waiting list or ≤1 y after LTx. BIVA was not associated with longer hospital length of stay. The predictors of vector placement in Q4 were higher age, malnutrition according to SGA, and presence of ascites or edema.

CONCLUSION

Patients on the waiting list for LTx with BIVA vectors placed in Q4, in the 50%, 75%, or 95% tolerance ellipses, presented a worse prognosis.

Early Hypermetabolism is Uncommon in Trauma Intensive Care Unit Patients

BACKGROUND

Classic experiments demonstrating hypermetabolism after major trauma were performed in a different era of critical care. We aim to describe the modern posttraumatic metabolic response in the trauma intensive care unit (TICU).

METHODS

This prospective observational study enrolled TICU mechanically ventilated adults (aged ≥18) from 3/2018-2/2019. Multiple, daily resting energy expenditure (REE) measurements were recorded. Basal energy expenditure (BEE) was calculated by the Harris-Benedict equation. Hypometabolism was defined as average daily REE < 0.85*BEE and hypermetabolism defined as average daily REE > 1.15*BEE. Demographics, interventions, and clinical outcomes were abstracted. Descriptive statistics and multivariable logistical regression models evaluating demographics with the outcome variable of hypermetabolism for the first 3 days ("sustained hypermetabolism") were performed, along with group-based trajectory modeling (GBTM).

RESULTS

Fifty-five patients were analyzed: median age was 38 (28-56) years; 38 (69%) were male; body mass index (kg/m² ) was 28 (26-32); and Injury Severity Score was 27 (19-34), with (38 [71%] blunt, 8 [15%] penetrating, 7 [13%] burn) injury mechanism. Overall, 19 (35%) had hypermetabolism on day 1 ("immediate hypermetabolism"), and 11 (21%) had sustained hypermetabolism for the first 3 days. Logistic regression analysis identified penetrating mechanism (adjusted odds ratio [AOR], 16.4; 95% CI, 1.9-199.6; p = .015), burn mechanism (AOR, 11.1; 95% CI, 1.3-116.8; p =.029), and maximum temperature (AOR, 4.2; 95% CI, 1.3-20.3; p= .041) as independent predictors of sustained hypermetabolism. GBTM identified 4 nutrition phenotypes, with 2 hyperconsumptive phenotypes associated with increased risk of malnutrition at discharge.

CONCLUSION

Only a minority of injured patients is hypermetabolic in the first week after injury. Elevated temperature, penetrating mechanism, and burn mechanism are independently associated with sustained hypermetabolism. Hyperconsumptive phenotype patients are more likely to develop malnutrition during hospitalization.

The Analysis of Food Intake in Patients with Cirrhosis Waiting for Liver Transplantation: A Neglected Step in the Nutritional Assessment

Patients with cirrhosis waiting for liver transplantation (LT) frequently present a nutritional disorder, which represents an independent predictor of morbidity and mortality before and after transplantation. Thus, a proper assessment of the food intake by using different methods, such as food records, food frequency questionnaires, and 24 h recall, should be deemed an important step of the nutritional management of these patients. The available published studies indicate that the daily food intake is inadequate in the majority of waitlisted patients. These findings were confirmed by our experience, showing that the daily intake of total calories, proteins and carbohydrates was inadequate in approximately 85–95% of patients, while that of lipids and simple carbohydrates was inadequate in almost 50% of them. These data highlight the need to implement an effective educational program provided by certified nutritionists or dieticians, who should work in close collaboration with the hepatologist to provide a nutritional intervention tailored to the individual patient requirements.

Are Predictive Energy Expenditure Equations Accurate in Cirrhosis?

Malnutrition is associated with significant morbidity and mortality in cirrhosis. An accurate nutrition prescription is an essential component of care, often estimated using time-efficient predictive equations. Our aim was to compare resting energy expenditure (REE) estimated using predictive equations (predicted REE, pREE) versus REE measured using gold-standard, indirect calorimetry (IC) (measured REE, mREE). We included full-text English language studies in adults with cirrhosis comparing pREE versus mREE. The mean differences across studies were pooled with RevMan 5.3 software. A total of 17 studies (1883 patients) were analyzed. The pooled cohort was comprised of 65% men with a mean age of 53 ± 7 years. Only 45% of predictive equations estimated energy requirements to within 90⁻110% of mREE using IC. Eighty-three percent of predictive equations underestimated and 28% overestimated energy needs by ±10%. When pooled, the mean difference between the mREE and pREE was lowest for the Harris⁻Benedict equation, with an underestimation of 54 (95% CI: 30⁻137) kcal/d. The pooled analysis was associated with significant heterogeneity (I² = 94%). In conclusion, predictive equations calculating REE have limited accuracy in patients with cirrhosis, most commonly underestimating energy requirements and are associated with wide variations in individual comparative data.

Persistently Increased Resting Energy Expenditure Predicts Short-Term Mortality in Patients with Acute-on-Chronic Liver Failure

OBJECTIVE

Hypermetabolism based on measurements of resting energy expenditure (REE) is suggested to be a potential biomarker for predicting the clinical outcomes of some diseases. We aimed to evaluate the potential value of hypermetabolism for predicting the short-term (28-day) mortality of patients with hepatitis B virus-related acute-on-chronic liver failure (HBV-ACLF).

METHODS

A total of 105 HBV-ACLF patients, 30 chronic hepatitis B (CHB) patients and 30 healthy controls (HCs) were included in this study. The REE was measured using indirect calorimetry in the morning after 8-10 h of fasting. The predicted REE (REEHB) was determined using Harris-Benedict equation. Persistent hypermetabolism was defined as the REE:REEHB ratio > 1.20 at day 1 and day 7 after admission. The severity of liver disease was estimated using the Model for End-Stage Liver Disease (MELD). Clinical and biochemical variables were determined using blood samples ordered upon admission. These variables were compared between nonsurviving and surviving patients who were classified according to the 28-day mortality.

RESULTS

The frequency of hypermetabolism at baseline was significantly higher in ACLF patients than that in HCs and CHB patients. Forty-six (43.8%) ACLF patients died within follow-up of 28 days. Persistent hypermetabolism (OR 2.10; 95% CI 1.15-3.69; p = 0.002) and MELD score (OR 1.93; 95% CI 1.47-3.51; p = 0.012) were independent predictive indicators of 28-day mortality. Furthermore, the performance of the 2 variables (persistent hypermetabolism and MELD) together with the area under the receiver operating curve (AUROC: 0.819) was significantly better than that of MELD alone -(AUROC: 0.694) for prediction of short-term mortality (p = 0.014).

CONCLUSION

These findings indicate that persistent hypermetabolism is predictive of short-term mortality in this small population.

A mechanism based approach to management of children with end-stage liver disease

Due to parallel advances in surgical and acute care disciplines, liver transplantation (LT) has revolutionized the outlook for children with end-stage liver disease (ESLD). Contrary to advances in technical aspects of LT and the peri-operative care, pre-transplant management of ESLD remains quite a formidable challenge. Areas covered: This review provides mechanisms based management strategies to address common complications of ESLD including malnutrition, amended metabolic pathways, gastrointestinal dysfunction, and development of ascites. Clinically relevant discussion of each paradigm is followed by an account of high impact therapeutic interventions which can be used as guides for formulating management plans. A tabulated summary of the suggested interventions is also provided. Indeed, execution of a dynamic plan tailored to the evolution of pathophysiologic derangements can further enhance outcomes of pediatric LT. Expert commentary: LT has evolved as a dependable therapeutic option for a variety of fatal pediatric liver diseases. However, relative organ shortage remains a formidable challenge. Similarly, consumer expectations continue to grow for sustained improvement of graft and patient survival after LT. In this environment, the level of sophistication applied to the management ESLD before LT stands out as a major opportunity with lasting impact on the future of pediatric LT.

ESTIMATING BASAL ENERGY EXPENDITURE IN LIVER TRANSPLANT RECIPIENTS: THE VALUE OF THE HARRIS-BENEDICT EQUATION

Background:

Reliable measurement of basal energy expenditure (BEE) in liver transplant (LT) recipients is necessary for adapting energy requirements, improving nutritional status and preventing weight gain. Indirect calorimetry (IC) is the gold standard for measuring BEE. However, BEE may be estimated through alternative methods, including electrical bioimpedance (BI), Harris-Benedict Equation (HBE), and Mifflin-St. Jeor Equation (MSJ) that carry easier applicability and lower cost.

Aim:

To determine which of the three alternative methods for BEE estimation (HBE, BI and MSJ) would provide most reliable BEE estimation in LT recipients.

Methods:

Prospective cross-sectional study including dyslipidemic LT recipients in follow-up at a 735-bed tertiary referral university hospital. Comparisons of BEE measured through IC to BEE estimated through each of the three alternative methods (HBE, BI and MSJ) were performed using Bland-Altman method and Wilcoxon Rank Sum test.

Results:

Forty-five patients were included, aged 58±10 years. BEE measured using IC was 1664±319 kcal for males, and 1409±221 kcal for females. Average difference between BEE measured by IC (1534±300 kcal) and BI (1584±377 kcal) was +50 kcal (p=0.0384). Average difference between the BEE measured using IC (1534±300 kcal) and MSJ (1479.6±375 kcal) was -55 kcal (p=0.16). Average difference between BEE values measured by IC (1534±300 kcal) and HBE (1521±283 kcal) was -13 kcal (p=0.326). Difference between BEE estimated through IC and HBE was less than 100 kcal for 39 of all 43patients.

Conclusions:

Among the three alternative methods, HBE was the most reliable for estimating BEE in LT recipients.

Nutrition therapy: Integral part of liver transplant care

Managing malnutrition before liver transplantation (LTx) while on the waiting list and, excessive weight gain/metabolic disturbances in post-surgery are still a challenge in LTx care. The aim of this review is to support an interdisciplinary nutrition approach of these patients. Cirrhotic patients are frequently malnourished before LTx and this is associated with a poor prognosis. Although the relation between nutritional status versus survival, successful operation and recovery after LTx is well established, prevalence of malnutrition before the operation is still very high. Emerging research has also demonstrated that sarcopenia pre and post-transplant is highly prevalent, despite the weight gain in the postoperative period. The diagnosis of the nutritional status is the first step to address the adequate nutritional therapy. Nutritional recommendations and therapy to manage the nutritional status of LTx patients are discussed in this review, regarding counseling on adequate diets and findings of the latest research on using certain immunonutrients in these patients (branched chain amino-acids, pre and probiotics). Nutrition associated complications observed after transplantation is also described. They are commonly related to the adverse effects of immunosuppressive drugs, leading to hyperkalemia, hyperglycemia and weight gain. Excessive weight gain and post-transplant metabolic disorders have long been described in post-LTx and should be addressed in order to reduce associated morbidity and mortality.