Rita Commissari

Background: Critical illness is characterized by profound and rapidly evolving metabolic derangements driven by systemic inflammation, hypercatabolism, fluid shifts, and endocrine dysregulation. These dynamic changes markedly limit the accuracy of predictive equations, increasing the risk of both underfeeding and overfeeding. Indirect Calorimetry Energy represents the gold standard for measuring energy expenditure, while bioelectrical impedance vector analysis (BIVA) provides complementary insights into hydration status, cellular integrity, and body cell mass. In palliative care, AI-supported integration of indirect calorimetry and BIVA enables goal-concordant artificial nutrition by aligning energy delivery with real-time metabolic status while minimizing symptom burden. Artificial intelligence (AI) has emerged as a promising tool to integrate these heterogeneous data streams and support adaptive nutritional strategies. Methods: We conducted a structured narrative review of the literature published between 2000 and 2025 using PubMed, Scopus, Embase, and Web of Science. Artificial intelligence was not used to perform the literature search or study selection. Instead, AI was analyzed as a clinical and technological component within the included studies and explored as a future enabling strategy. Eligible publications involved adult critically ill patients and addressed indirect calorimetry, BIVA-derived parameters, or AI-based metabolic modeling applied to nutritional support. Given the heterogeneity of study designs and outcomes, findings were synthesized qualitatively. Results: Predictive equations showed substantial inaccuracy in unstable metabolic states, with errors frequently exceeding ±20–40%. Indirect calorimetry enabled individualized assessment of energy expenditure but remained limited by intermittent availability. Serial BIVA assessments consistently identified clinically relevant alterations in hydration status, body cell mass, and phase angle, the latter being strongly associated with adverse outcomes. Studies incorporating AI demonstrated improved integration of calorimetry, BIVA, and clinical variables, allowing identification of metabolic phenotypes, anticipation of metabolic shifts, and generation of adaptive nutritional recommendations. Conclusions: This narrative review highlights the complementary roles of Indirect Calorimetry and BIVA in characterizing metabolic needs in critical illness. Artificial intelligence does not replace these tools but enhances their clinical utility by integrating multidimensional data into dynamic, patient-specific nutritional strategies. The combined AI–IC–BIVA approach represents a promising framework for metabolic precision nutrition in the ICU, warranting prospective validation.

Background: There is limited knowledge about nutritional intake and energy needs during the post-intensive care unit (ICU) period and their relationship with clinical outcomes and physical recovery. Aims and Methods: Thus, this observational multicenter study (Azienda Ospedaliero-Universitaria “Santa Maria”, Terni and “Madonna del Soccorso” General hospital, San Benedetto del Tronto, Italy) aimed, firstly, to measure energy expenditure via indirect calorimetry (IC) (Q-NRG+^® Metabolic Monitor, Cosmed, Rome, Italy), derived respiratory quotient (R/Q1) and, malnutrition risk via Mini Nutritional Assessment (MNA) test and body composition through bioimpedance vector analysis (BIVA-Akern, Pontassieve, Italy); secondly, to assess their effect on energy needs, body composition and physical rehabilitation steps in critically ill adults after ICU discharge. The provision of nutrients (PIS test) was also recorded. Oral nutritional supplementation was used to reach the optimal nutritional intake. All patients followed a standardized rehabilitation program. Results: A total of 43 patients were enrolled from January 2024 until February 2025 at the beginning of their post-ICU period. The mean age was 65.7 ± 1.0 years, the mean BMI was 20.73 ± 0.8 kg/m² at the recovery ward, and 60.4% (n = 26) were male. The mean admission period was 19.5 ± 1.7 days. The resting energy expenditure (mREE) was 1591 ± 71.2 at the admission and 1.856 ± 62.7 kcal/kg/d at the discharge (p < 0.05). The median phase angle value was 4.33 ± 0.15 at the admission and 5.05 ± 0.17° at the discharge (p < 0.05); R/Q1 at the admission was 0.7 ± 0.1 and 1.086± 0.11 at the discharge (p < 0.05). Improved energy expenditure significantly correlated with R/Q1 and phase angle (r = 0.81 and r = 0.72, respectively). Interestingly, there was no significant correlation between improved metabolism and improved PIS test scores (r = 0.18). Improved metabolism and nutritional status showed a tendency to correlate with shorter post-ICU courses and earlier physical recovery, without reaching statistical significance. Conclusions: Measurement of energy expenditure and caloric intake, along with the assessment of body composition is feasible and provides an objective tool to guide and possibly enhance the functional recovery in patients during the post-ICU period.

Background: The SARS-COV 2 pandemic has hit on our lives since early 2020. During different contagion waves, both malnutrition and overweight significantly correlated with patient mortality. Immune-nutrition (IN) has shown promising results in the clinical course of pediatric inflammatory bowel disease (IBD) and in both the rate of extubation and mortality of patients admitted to an intensive care unit (ICU). Thus, we wanted to assess the effects of IN on a clinical course of patients admitted to a semi-intensive COVID-19 Unit during the fourth wave of contagion that occurred at the end of 2021. Methods: we prospectively enrolled patients admitted to the semi-intensive COVID-19 Unit of San Benedetto General hospital. All patients had a biochemical, anthropometric, high-resolution tomography chest scan (HRCT) and complete nutritional assessments at the time of admission, after oral administration of immune-nutrition (IN) formula, and at 15 days interval follow-up. Results: we enrolled 34 consecutive patients (age 70.3 ± 5.4 years, 6 F, BMI 27.0 ± 0.5 kg/m²). Main comorbidities were diabetes (20%, type 2 90 %), hyperuricemia (15%), hypertension (38%), chronic ischemic heart disease (8 %), COPD (8%), anxiety syndrome (5%), and depression (5%). 58% of patients were affected as moderately-to-severely overweight; mini nutritional assessment (MNA) score (4.8 ± 0.7) and phase angle (PA) values (3.8 ± 0.5) suggestive of malnutrition were present in 15% of patients, mainly with a history of cancer. After 15 days upon admission, we recorded 3 deaths (mean age 75.7 ± 5.1 years, BMI 26.3 ± 0.7 kg/m²) and 4 patients were admitted to the ICU. Following IN formula administration, inflammatory markers significantly decreased (p < 0.05) while BMI and PA did not worsen. These latter findings were not observed in a historical control group that did not receive IN. Only one patient needed protein-rich formula administration. Conclusions: in this overweight COVID-19 population immune-nutrition prevented malnutrition development with a significant decrease of inflammatory markers.

The novel SARS-CoV-2 virus has led to a severe pandemic, starting from early 2020. Intensive care (ICU) management of the COVID-19 disease is difficult with high morbidity and mortality. Early nutritional support, especially with whey protein, seems to be crucial in this medical case. Thus, we aimed to assess the effects of an adequate nutritional protocol rich in whey protein on nutritional and inflammatory status, extubating time, and mortality of critically ill COVID-19 patients (CICP). Methods: A prospective single-center exploratory observational study was undertaken on 32 consecutive CICP admitted to the ICU of Santa Maria Hospital, Terni, Italy, and treated with whey protein-enriched formula. Patients’ demographics, nutritional status, indexes of inflammation, daily pre-albumin serum levels, duration of mechanical ventilation, and mortality were recorded. Results: Thirty-two patients were enrolled. Ninety-five percent of them showed a gradual reduction in C-reactive protein (CRP) values and increase in pre-albumin levels after the whey protein-enriched formula. Prealbumin levels were not correlated with a better nutritional status but with a shorter extubating time and better survival. Conclusions: An adequate administration of whey protein during COVID-19 patients’ ICU stays can provide fast achievement of protein targets, reducing the duration of mechanical ventilation, and improving inflammatory status and ICU survival. Further prospective and large-scale, controlled studies are needed to confirm these results.