Metabolism of Proteins and Amino Acids in Critical Illness: From Physiological Alterations to Relevant Clinical Practice

Physical and respiratory therapy in the critically ill patient with obesity: a narrative review

Obesity has become increasingly prevalent in the intensive care unit, presenting a significant challenge for healthcare systems and professionals, including rehabilitation teams. Caring for critically ill patients with obesity involves addressing complex issues. Despite the well-established and safe practice of early mobilization during critical illness, in rehabilitation matters, the diverse clinical disturbances and scenarios within the obese patient population necessitate a comprehensive understanding. This includes recognizing the importance of metabolic support, both non-invasive and invasive ventilatory support, and their weaning processes as essential prerequisites. Physiotherapists, working collaboratively with a multidisciplinary team, play a crucial role in ensuring proper assessment and functional rehabilitation in the critical care setting. This review aims to provide critical insights into the key management and rehabilitation principles for obese patients in the intensive care unit.

Amino acid kinetics in the critically ill

PURPOSE OF REVIEW

Stable isotope methods have been used for many years to assess whole body protein and amino acid kinetics in critically ill patients. In recent years, new isotope approaches and tracer insights have been developed. The tracer pulse approach has some advantages above the established primed-continuous tracer infusion approach because of the high amount of metabolic information obtained, easy applicability, and low tracer costs. Effects of disease severity and sex on amino acid kinetics in ICU patients will also be addressed.

RECENT FINDINGS

Current knowledge was synthesized on specific perturbations in amino acid metabolism in critically ill patients, employing novel methodologies such as the pulse tracer approach and computational modeling. Variations were evaluated in amino acid production and linked to severity of critical illness, as measured by SOFA score, and sex. Production of the branched-chain amino acids (BCAAs), glutamine, tau-methylhistidine and hydroxyproline were elevated in critical illness, likely related to increased transamination of the individual BCAAs or increased breakdown of proteins. Citrulline production was reduced, indicative of impaired gut mucosa function. Sex and disease severity independently influenced amino acid kinetics in ICU patients.

SUMMARY

Novel tracer and computational approaches have been developed to simultaneously measure postabsorptive kinetics of multiple amino acids that can be used in critical illness. The collective findings lay the groundwork for targeted individualized nutritional strategies in ICU settings aimed at enhancing patient outcomes taking into account disease severity and sex.

Development and validation of a nomogram for predicting in-hospital mortality in patients with nonhip femoral fractures

BACKGROUND

The incidence of nonhip femoral fractures is gradually increasing, but few studies have explored the risk factors for in-hospital death in patients with nonhip femoral fractures in the ICU or developed mortality prediction models. Therefore, we chose to study this specific patient group, hoping to help clinicians improve the prognosis of patients.

METHODS

This is a retrospective study based on the data from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. Least absolute shrinkage and selection operator (LASSO) regression was used to screen risk factors. The receiver operating characteristic (ROC) curve was drawn, and the areas under the curve (AUC), net reclassification index (NRI) and integrated discrimination improvement (IDI) were calculated to evaluate the discrimination of the model. The consistency between the actual probability and the predicted probability was assessed by the calibration curve and Hosmer-Lemeshow goodness of fit test (HL test). Decision curve analysis (DCA) was performed, and the nomogram was compared with the scoring system commonly used in clinical practice to evaluate the clinical net benefit.

RESULTS

The LASSO regression analysis showed that heart rate, temperature, red blood cell distribution width, blood urea nitrogen, Glasgow Coma Scale (GCS), Simplified Acute Physiology Score II (SAPSII), Charlson comorbidity index and cerebrovascular disease were independent risk factors for in-hospital death in patients with nonhip femoral fractures. The AUC, IDI and NRI of our model in the training set and validation set were better than those of the GCS and SAPSII scoring systems. The calibration curve and HL test results showed that our model prediction results were in good agreement with the actual results (P = 0.833 for the HL test of the training set and P = 0.767 for the HL test of the validation set). DCA showed that our model had a better clinical net benefit than the GCS and SAPSII scoring systems.

CONCLUSION

In this study, the independent risk factors for in-hospital death in patients with nonhip femoral fractures were determined, and a prediction model was constructed. The results of this study may help to improve the clinical prognosis of patients with nonhip femoral fractures.

[Immunomodulation by nutritional intervention in critically ill patients]

Critically ill patients often suffer from a complex and severe immunological dysfunction. The differentiation and function of human immune cells are fundamentally controlled through metabolic processes. New concepts of immunonutrition therefore try to use enteral and parenteral nutrition to positively impact on the immune function of intensive care unit patients. This review article concisely presents the currently available evidence on the commonly used isolated supplements (anti-oxidative substances, amino acids, essential fatty acids) and difficulties related to their clinical use. The second part presents new and more comprehensive concepts of immunonutrition to influence the intestinal microbiome and to modulate the macronutrient composition. Immunonutrition of critically ill patients bears enormous potential and could become a valuable clinical tool for modulation of the immunometabolism of intensive care unit patients.

Role of Fat-Free Mass Index on Amino Acid Loss during CRRT in Critically Ill Patients

Background and objectives: Amino acid (AA) loss is a prevalent unwanted effect of continuous renal replacement therapy (CRRT) in critical care patients, determined both by the machine set-up and individual characteristics. The aim of this study was to evaluate the bioelectrical impedance analysis-derived fat-free mass index (FFMI) effect on amino acid loss. Materials and methods: This was a prospective, observational, single sample study of critical care patients upon initiation of CRRT. AA loss during a 24 h period was estimated. Conventional determinants of AA loss (type and dose of CRRT, concentration of AA) and FFMI were entered into the multivariate regression analysis to determine the individual predictive value. Results: Fifty-two patients were included in the study. The average age was 66.06 ± 13.60 years; most patients had a high mortality risk with APAHCE II values of 22.92 ± 8.15 and SOFA values of 12.11 ± 3.60. Mean AA loss in 24 h was 14.73 ± 9.83 g. There was a significant correlation between the lost AA and FFMI (R = 0.445, B = 0.445 CI95%: 0.541-1.793 p = 0.02). Multivariate regression analysis revealed the independent predictors of lost AA to be the systemic concentration of AA (B = 6.99 95% CI:4.96-9.04 p = 0.001), dose of CRRT (B = 0.48 95% CI:0.27-0.70 p < 0.001) and FFMI (B = 0.91 95% CI:0.42-1.41 p < 0.001). The type of CRRT was eliminated in the final model due to co-linearity with the dose of CRRT. Conclusions: A substantial amount of AA is lost during CRRT. The amount lost is increased by the conventional factors as well as by higher FFMI. Insights from our study highlight the FFMI as a novel research object during CRRT, both when prescribing the dosage and evaluating the nutritional support needed.

Factors Associated with Interruptions of Enteral Nutrition and the Impact on Macro- and Micronutrient Deficits in ICU Patients

BACKGROUND AND AIM

Feeding interruptions in critical care patients are often unjustified. We aimed to determine the causes, duration, and frequency of enteral nutrition interruptions (ENIs) and to assess macronutrients and antioxidant deficits according to European Society of Parenteral Enteral Nutrition (ESPEN) guidelines.

METHODS

We prospectively enrolled Intensive Care Unit (ICU) patients admitted for more than 48 h with an inability to orally eat from April to December 2019. The type of enteral nutrition, the number of calories administered, the time of feeding initiation, the reasons for delaying feeding, and the causes for ENI were recorded.

RESULTS

81 patients were enrolled, with a median duration of ENIs of 5.2 (3.4-7.4) hours/day. Gastric residual volume (GRV) monitoring-a highly controversial practice-was the most common cause of ENI (median duration 3 (2.3-3) hours/day). The mean energy intake was 1037 ± 281 kcal/day, while 60.5% of patients covered less than 65% of the total energy needs (1751 ± 295 kcal/day, according to mean Body Mass Index (BMI)). The median daily protein intake did not exceed 0.43 ± 0.3 gr/kg/day of the actual body weight (BW), whereas ESPEN recommends 1.3 gr/kg/day for adjusted BW (p < 0.001). The average administration of micronutrients and antioxidants (arginine, selenium, zinc, vitamins) was significantly less than the dietary reference intake (p < 0.01).

CONCLUSION

ENIs lead to substantial caloric, protein, and antioxidant deficits.

The emerging roles of next-generation metabolomics in critical care nutrition

Critical illness leads to millions of deaths worldwide each year, with a significant surge due to the COVID-19 pandemic. Patients with critical illness are frequently associated with systemic metabolic disorders and malnutrition. The idea of intervention for critically ill patients through enteral and parenteral nutrition has been paid more and more attention gradually. However, current nutritional therapies focus on evidence-based practice, and there have been lacking holistic approaches for nutritional support assessment. Metabolomics is a well-established omics technique in system biology that enables comprehensive profiling of metabolites in a biological system and thus provides the underlying information expressed and modulated by all other omics layers. In recent years, with the development of high-resolution and accurate mass spectrometry, metabolomics entered a new "generation", promoting its broader applications in critical care nutrition. In this review, we first described the technological development and milestones of next-generation metabolomics in the past 20 years. We then discussed the emerging roles of next-generation metabolomics in advancing our understanding of critical care nutrition, such as nutritional deficiency risk evaluation, metabolic mechanisms of nutritional therapies, and novel nutrition target identification.

Energy requirements for critically ill patients with COVID-19

Early reports suggested that predictive equations significantly underestimate the energy requirements of critically ill patients with coronavirus disease 2019 (COVID-19) based on the results of indirect calorimetry (IC) measurements. IC is the gold standard for measuring energy expenditure in critically ill patients. However, IC is not available in many institutions. If predictive equations significantly underestimate energy requirements in severe COVID-19, this increases the risk of underfeeding and malnutrition, which is associated with poorer clinical outcomes. As such, the purpose of this narrative review is to summarize and synthesize evidence comparing measured resting energy expenditure via IC with predicted resting energy expenditure determined via commonly used predictive equations in adult critically ill patients with COVID-19. Five articles met the inclusion criteria for this review. Their results suggest that many critically ill patients with COVID-19 are in a hypermetabolic state, which is underestimated by commonly used predictive equations in the intensive care unit (ICU) setting. In nonobese patients, energy expenditure appears to progressively increase over the course of ICU admission, peaking at week 3. The metabolic response pattern in patients with obesity is unclear because of conflicting findings. Based on limited evidence published thus far, the most accurate predictive equations appear to be the Penn State equations; however, they still had poor individual accuracy overall, which increases the risk of underfeeding or overfeeding and, as such, renders the equations an unsuitable alternative to IC.