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Background: Body composition (BC) techniques, including bioelectrical impedance analysis (BIVA), nutritional ultrasound® (NU), and computed tomography (CT), can detect nutritional diagnoses such as sarcopenia (Sc). Sc in idiopathic pulmonary fibrosis (IPF) is associated with greater severity and lower survival. Our aim was to explore the correlation of BIVA, NU and functional parameters with BC at T12 level CT scans in patients with IPF but also its relationship with degree of Sc, malnutrition and mortality. Methods: This bicentric cross-sectional study included 60 IPF patients (85.2% male, 70.9 ± 7.8 years). Morphofunctional assessment (MFA) techniques included BIVA, NU, CT at T12 level (T12-CT), handgrip strength, and timed up and go. CT data were obtained using FocusedON®. Statistical analysis was conducted using JAMOVI version 2.3.22 to determine the cutoff points for Sc in T12-CT and to analyze correlations with other MFA techniques. Results: the cutoff for muscle area in T12-CT was ≤77.44 cm2 (area under the curve (AUC) = 0.734, sensitivity = 41.7%, specificity = 100%). The skeletal muscle index (SMI_T12CT) cutoff was ≤24.5 cm2/m2 (AUC = 0.689, sensitivity = 66.7%, specificity = 66.7%). Low SMI_T12CT exhibited significantly reduced median survival and higher risk of mortality compared to those with normal muscle mass (SMI cut off ≥ 28.8 cm/m2). SMI_T12CT was highly correlated with body cell mass from BIVA (r = 0.681) and rectus femoris cross-sectional area (RF-CSA) from NU (r = 0.599). Cronbach's α for muscle parameters across different MFA techniques and CT was 0.735, confirming their validity for evaluating muscle composition. Conclusions: T12-CT scan is a reliable technique for measuring low muscle mass in patients with IPF, specifically when the L3 vertebrae are not captured. An SMI value of <28.8 is a good predictor of low lean mass and 12-month mortality in IPF patients. [ABSTRACT FROM AUTHOR]

(1) Background: The assessment of muscle mass is crucial in the nutritional evaluation of patients with colorectal cancer (CRC), as decreased muscle mass is linked to increased complications and poorer prognosis. This study aims to evaluate the utility of AI-assisted L3 CT for assessing body composition and determining low muscle mass using both the Global Leadership Initiative on Malnutrition (GLIM) criteria for malnutrition and the European Working Group on Sarcopenia in Older People (EWGSOP2) criteria for sarcopenia in CRC patients prior to surgery. Additionally, we aim to establish cutoff points for muscle mass in men and women and propose their application in these diagnostic frameworks. (2) Methods: This retrospective observational study included CRC patients assessed by the Endocrinology and Nutrition services of the Regional University Hospitals of Malaga, Virgen de la Victoria of Malaga, and Vall d'Hebrón of Barcelona from October 2018 to July 2023. A morphofunctional assessment, including anthropometry, bioimpedance analysis (BIA), and handgrip strength, was conducted to apply the GLIM criteria for malnutrition and the EWGSOP2 criteria for sarcopenia. Body composition evaluation was performed through AI-assisted analysis of CT images at the L3 level. ROC analysis was used to determine the predictive capacity of variables derived from the CT analysis regarding the diagnosis of low muscle mass and to describe cutoff points. (3) Results: A total of 586 patients were enrolled, with a mean age of 68.4 ± 10.2 years. Using the GLIM criteria, 245 patients (41.8%) were diagnosed with malnutrition. Applying the EWGSOP2 criteria, 56 patients (9.6%) were diagnosed with sarcopenia. ROC curve analysis for the skeletal muscle index (SMI) showed a strong discriminative capacity of muscle area to detect low fat-free mass index (FFMI) (AUC = 0.82, 95% CI 0.77–0.87, p < 0.001). The identified SMI cutoff for diagnosing low FFMI was 32.75 cm2/m2 (Sn 77%, Sp 64.3%; AUC = 0.79, 95% CI 0.70–0.87, p < 0.001) in women, and 39.9 cm2/m2 (Sn 77%, Sp 72.7%; AUC = 0.85, 95% CI 0.80–0.90, p < 0.001) in men. Additionally, skeletal muscle area (SMA) showed good discriminative capacity for detecting low appendicular skeletal muscle mass (ASMM) (AUC = 0.71, 95% CI 0.65–0.76, p < 0.001). The identified SMA cutoff points for diagnosing low ASMM were 83.2 cm2 (Sn 76.7%, Sp 55.3%; AUC = 0.77, 95% CI 0.69–0.84, p < 0.001) in women and 112.6 cm2 (Sn 82.3%, Sp 58.6%; AUC = 0.79, 95% CI 0.74–0.85, p < 0.001) in men. (4) Conclusions: AI-assisted body composition assessment using CT is a valuable tool in the morphofunctional evaluation of patients with colorectal cancer prior to surgery. CT provides quantitative data on muscle mass for the application of the GLIM criteria for malnutrition and the EWGSOP2 criteria for sarcopenia, with specific cutoff points established for diagnostic use. [ABSTRACT FROM AUTHOR]

Head and neck cancer (HNC) is a prevalent and aggressive form of cancer with high mortality rates and significant implications for nutritional status. Accurate assessment of malnutrition in patients with HNC is crucial for optimizing treatment outcomes and improving survival rates. This study aimed to evaluate the use of ultrasound techniques for predicting nutritional status, malnutrition, and cancer outcomes in patients with HNC. A total of 494 patients with HNC were included in this cross-sectional observational study. Various tools and body composition measurements, including muscle mass and adipose tissue ultrasound evaluations, were implemented. Using regression models, we mainly found that high levels of RF-CSA (rectus femoris cross-sectional area) were associated with a decreased risk of malnutrition (as defined with GLIM criteria (OR = 0.81, 95% CI: 0.68–0.98); as defined with PG-SGA (OR = 0.78, 95% CI: 0.62–0.98)) and sarcopenia (OR = 0.64, 95% CI: 0.49–0.82) after being adjusted for age, sex, and BMI. To predict the importance of muscle mass ultrasound variables on the risk of mortality, a nomogram, a random forest, and decision tree models were conducted. RF-CSA was the most important variable under the random forest model. The obtained C-index for the nomogram was 0.704, and the Brier score was 16.8. With an RF-CSA < 2.7 (AUC of 0.653 (0.59–0.77)) as a split, the decision tree model classified up to 68% of patients as possessing a high probability of survival. According to the cut-off value of 2.7 cm2, patients with a low RF-CSA value lower than 2.7 cm2 had worse survival rates (p < 0.001). The findings of this study highlight the importance of implementing ultrasound tools, for accurate diagnoses and monitoring of malnutrition in patients with HNC. Adipose tissue ultrasound measurements were only weakly associated with malnutrition and not with sarcopenia, indicating that muscle mass is a more important indicator of overall health and nutritional status. These results have the potential to improve survival rates and quality of life by enabling early intervention and personalized nutritional management. [ABSTRACT FROM AUTHOR]

Introduction: malnutrition is a very frequent problem in oncology patients and may have serious repercussions. Adequate nutritional management is cost-effective in terms of health and survival in this population, but it requires multidisciplinary coordination, specific training, and continuous follow-up. Objective: to validate the applicability and efficacy of a multidisciplinary nutritional support protocol in oncology patients. Methods: a multidisciplinary nutritional protocol was developed for oncology patients, with guidelines for screening and assessment of malnutrition, treatment, re-evaluation, and management of side effects, as well as guidance on supplementation and eating patterns. The protocol would be implemented in various clinical centers, collecting data through a structured questionnaire, registering variables before and after implementation. Results: the protocol and its impact were implemented and evaluated in 39 centers. An improvement in nutritional care was observed, evidenced by an earlier initiation of nutritional assessment and an increase in the number of patients receiving adequate care following the protocol implementation. Problems related to inadequate malnutrition coding in the centers, limited resources, and the need for greater interdepartmental collaboration were identified. Conclusions: the conduct of this study provides insights into how the implementation of a multidisciplinary nutritional support protocol can improve the nutritional care received by patients and informs about the main obstacles to adequate implementation. [ABSTRACT FROM AUTHOR]

Introduction: Introduction: malnutrition is a very frequent problem in oncology patients and may have serious repercussions. Adequate nutritional management is cost-effective in terms of health and survival in this population, but it requires multidisciplinary coordination, specific training, and continuous follow-up. Objective: to validate the applicability and efficacy of a multidisciplinary nutritional support protocol in oncology patients. Methods: a multidisciplinary nutritional protocol was developed for oncology patients, with guidelines for screening and assessment of malnutrition, treatment, re-evaluation, and management of side effects, as well as guidance on supplementation and eating patterns. The protocol would be implemented in various clinical centers, collecting data through a structured questionnaire, registering variables before and after implementation. Results: the protocol and its impact were implemented and evaluated in 39 centers. An improvement in nutritional care was observed, evidenced by an earlier initiation of nutritional assessment and an increase in the number of patients receiving adequate care following the protocol implementation. Problems related to inadequate malnutrition coding in the centers, limited resources, and the need for greater interdepartmental collaboration were identified. Conclusions: the conduct of this study provides insights into how the implementation of a multidisciplinary nutritional support protocol can improve the nutritional care received by patients and informs about the main obstacles to adequate implementation.