Precision in Nutrition Therapy

A recent review discusses the challenges of evaluating nutrition strategies in critically ill patients through multicenter randomised controlled trials (RCTs). While smaller observational studies showed promise, many large-scale RCTs have failed to demonstrate effectiveness and have even indicated potential harm from some interventions. This discrepancy may stem from individual differences in patient responses, which are influenced by factors such as genetics, comorbidities, and metabolic status.

There is a need for personalised nutrition approaches, or precision nutrition, which seeks to identify patients most likely to benefit from specific interventions. Current obstacles include a limited understanding of biological mechanisms affecting individual responses and the complex interplay of nutrition timing, dose, and administration routes. Genetic variations, such as those in the FTO gene and epigenetic changes affecting mitochondrial function, can lead to metabolic differences among patients. Using appropriate biomarkers, including genetic information, may help predict responses to nutrition interventions, enabling the identification of patient groups more likely to achieve favourable outcomes.

Factors such as age, comorbidities, and organ dysfunction at ICU admission are important for predicting prognosis and favourable clinical outcomes following nutrition interventions in critically ill patients. 

Baseline scores like the Nutrition Risk in Critically ill (NUTRIC) score aim to predict the benefits of nutrition support by considering patients' inflammatory status and characteristics. However, analyses show that the NUTRIC score has poor discriminatory power, suggesting the need to incorporate dynamic factors occurring during critical illness for better prognostic accuracy.

Baseline nutritional status indicators, such as body mass index, frailty, and sarcopenia, are linked to adverse outcomes like increased mortality and healthcare costs. Precision nutrition approaches should acknowledge individual baseline diversity and incorporate factors reflecting the progression of critical illness, moving beyond generalised recommendations in current guidelines.

Metabolic changes occur during critical illness, characterised by increased energy expenditure, protein catabolism, and altered nutrient utilisation. Patients typically enter a catabolic state where the body breaks down tissues to meet heightened metabolic demands. Transitioning to an anabolic state, essential for recovery, can be influenced by various factors, including nutritional support, insulin therapy, hormonal support, exercise, and reduced inflammation.

Frequent assessments of metabolic tolerance can help guide nutrition support and determine the optimal timing for transitioning to full feeding. However, metabolic responses can vary over time and among patients. If metabolic demands are not met promptly, it can lead to muscle wasting, impaired immune function, and delayed wound healing.

There is a need to define each patient's metabolic trajectory and to monitor changes indicating their responsiveness to nutrition interventions. In the early acute phase, patients may struggle to utilise dietary nutrients effectively for anabolism. Studies have shown that patients with high C-reactive protein levels may experience harm from increased protein and caloric intake, and critically ill patients often have reduced protein synthesis compared to healthy individuals.

International nutrition guidelines recommend using biomarkers like nitrogen balance, inflammation levels, and insulin levels to identify a shift from catabolic to anabolic states. Serial measurements of these markers may provide signals for readiness to feed, allowing adjustments in macronutrient composition or dosage. Additionally, urea and the urea-to-creatinine ratio can offer insights into the patient's metabolic condition.

Estimating macronutrient needs using clinical tools (like the Penn State equation) often leads to significant variability compared to measuring energy expenditure through indirect calorimetry. This mismatch can result in inadequate matching between patients' needs and dietary nutrient dosing, contributing to variable clinical responses to nutrition interventions.

Overfeeding can exacerbate metabolic stress, leading to complications such as hyperglycaemia, hypertriglyceridaemia, impaired wound healing, increased infection rates, and liver injury. Conversely, underfeeding may worsen lean body mass loss, impair immune function, and delay recovery, affecting mid- to long-term patient outcomes. Studies, including the NUTRIREA-2 and -3 trials, have shown that full nutrition during the early acute phase may be harmful for mechanically ventilated patients on vasopressors, while the EFFORT Protein trial indicated negative effects of high-dose protein intake in patients with renal failure and severe illness.

Given the risk of underfeeding vulnerable populations (like frail or malnourished patients), further research is needed to develop markers that identify metabolic responders and determine appropriate nutrient dosing. Current care for critically ill patients should involve careful assessment of their status and monitoring of nutrient intake and metabolism using various clinical and laboratory tools. Feeding regimens should be adjusted to mitigate the risks of under- or overfeeding. 

While indirect calorimetry has shown positive associations with improved clinical outcomes in observational studies, studies have not consistently demonstrated its effectiveness in optimising caloric intake and enhancing clinical outcomes. This may be attributed to the limitations of older indirect calorimetry devices and their inability to accurately identify patients achieving anabolic responses during the initiation of nutrition.

There is an urgent need to better understand nutritional risks, metabolic heterogeneity, and responses to interventions, which could lead to more individualised treatment strategies. Identifying treatable traits based on various clinical, biochemical, and genotypic factors can help determine how patients will respond to critical illness and nutritional interventions. Furthermore, the development of surrogate biomarkers to monitor metabolic responsiveness and nutritional needs could guide the timing and modification of nutritional interventions. 

The review calls for innovative technologies for rapid and accurate measurement of inflammatory and metabolic statuses in clinical settings. By integrating biomarker monitoring into practice, healthcare providers can tailor nutritional support to meet individual patient needs, ultimately improving outcomes in critically ill patients.

Source: Critical Care Medicine

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