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Malnutrition and inflammation are closely linked to vascular calcification (VC), the severity of which correlate with adverse outcome. However, there were few studies on the interplay between malnutrition, inflammation and VC progression, rather than VC presence per se. We aimed to determine the relationship of malnutrition, inflammation, abdominal aortic calcification (AAC) progression with survival in hemodialysis (HD) patients. Malnutrition and inflammation were defined as low serum albumin (< 40 g/L) and high hs-CRP (≥ 28.57 nmol/L), respectively. We defined AAC progression as an increase in AAC score using lateral lumbar radiography at both baseline and one year later. Patients were followed up to investigate the impact of AAC progression on all-cause and cardiovascular mortality. AAC progressed in 54.6% of 97 patients (mean age 58.2±11.7 years, 41.2% men) at 1-year follow-up. Hypoalbuminemia (Odds ratio 3.296; 95% confidence interval 1.178-9.222), hs-CRP (1.561; 1.038-2.348), low LDL-cholesterol (0.976; 0.955-0.996), and the presence of baseline AAC (10.136; 3.173-32.386) were significant risk factors for AAC progression. During the mean follow-up period of 5.9 years, 38(39.2%) patients died and 27(71.0%) of them died of cardiovascular disease. Multivariate Cox regression analysis adjusted for old age, diabetes, cardiovascular history, and hypoalbuminemia determined that AAC progression was an independent predictor of all-cause mortality (2.294; 1.054-4.994). Malnutrition and inflammation were significantly associated with AAC progression. AAC progression is more informative than AAC presence at a given time-point as a predictor of all-cause mortality in patients on maintenance HD.

Background Although malnutrition and sarcopenia are prevalent in cirrhosis, their impact on outcomes following liver transplantation is not well documented. Methods The associations of nutritional status and sarcopenia with post‐transplant infections, requirement for mechanical ventilation, intensive care (ICU) and hospital stay, and 1 year mortality were assessed in 232 consecutive transplant recipients. Nutritional status and sarcopenia were assessed using the Royal Free Hospital‐Global Assessment (RFH‐GA) tool and the L3‐psoas muscle index (L3‐PMI) on CT, respectively. Results A wide range of RFH‐SGA and L3‐PMI were observed within similar Model for End‐stage Liver Disease (MELD) sub‐categories. Malnutrition and sarcopenia were independent predictors of all outcomes. Post‐transplant infections were associated with MELD (OR = 1.055, 95%CI = 1.002–1.11) and severe malnutrition (OR = 6.55, 95%CI = 1.99–21.5); ventilation > 24 h with MELD (OR = 1.1, 95%CI = 1.036–1.168), severe malnutrition (OR = 8.5, 95%CI = 1.48–48.87) and suboptimal donor liver (OR = 2.326, 95%CI = 1.056–5.12); ICU stay > 5 days, with age (OR = 1.054, 95%CI = 1.004–1.106), MELD (OR = 1.137, 95%CI = 1.057–1.223) and severe malnutrition (OR = 7.46, 95%CI = 1.57–35.43); hospital stay > 20 days with male sex (OR = 2.107, 95%CI = 1.004–4.419) and L3‐PMI (OR = 0.996, 95%CI = 0.994–0.999); 1 year mortality with L3‐PMI (OR = 0.996, 95%CI = 0.992–0.999). Patients at the lowest L3‐PMI receiving suboptimal grafts had longer ICU/hospital stay and higher incidence of infections. Conclusions Malnutrition and sarcopenia are associated with early post‐liver transplant morbidity/mortality. Allocation indices do not include nutritional status and may jeopardize outcomes in nutritionally compromised individuals.

The significance of imaging-based assessment of muscles and malnutrition in patients with primary hepatocellular carcinoma (HCC) remains unclear. This study aimed to elucidate the prognostic role of the combination of Low Muscle Volume and Value (LMVV) and malnutrition. A total of 714 Child-Pugh grade A/ B patients with first-diagnosed HCC were enrolled, and analyzed factors associated with overall survival. LMVV was defined using psoas muscle mass index and computed tomography values of multifidus muscle at the level of the third lumbar vertebra. We used hypoalbuminemia, Child-Pugh grade B, Subjective Global Assessment (SGA) grade B/C, and Royal Free Hospital Nutrition Prioritizing Tool (RFH-NPT) score > 2 as malnutrition factors in this study. At baseline, 29% showed LMVV, and 59% met one or more of the malnutrition criteria. No items meeting the criteria of LMVV and malnutrition was observed in 41%, 1 of them was found in 29%, and both were found in 29%. The number of items meeting criteria was an independent factor for a shorter survival. The frequency of liver-related deaths did not differ by presence of LMVV alone, while it was associated with malnutrition. In contrast, the incidence of other types of deaths was influenced by LMVV and malnutrition. The combination of LMVV and malnutrition is a prognostic factor in patients with primary HCC.

Our objective was to obtain information about diaphragm muscle mass, strength, and quality using conventional US and US-based imaging method shear wave elastography (SWE) in pediatric patients with primary malnutrition. We also sought to evaluate the usability of SWE in the diagnosis and follow-up of sarcopenia. We evaluated the diaphragm thickness and stiffness of patients diagnosed with primary malnutrition in the pediatrics and pediatric gastroenterology outpatient clinic using US and US-based SWE. The data were compared with those of an age- and gender-matched healthy control group. The study included 115 volunteers. Of the cases included, 53 were healthy controls and 62 (54%) were patients with primary malnutrition. There was no significant difference between the groups in terms of age and gender ( p  = 0.891 and p  = 0.923, respectively). The malnourished patient group had significantly lower diaphragm thickness and stiffness. There is a significant positive correlation between anthropometric measurement Z scores and diaphragm thickness and stiffness. Conclusion : Our study indicated that there was a reduction in the thickness of the diaphragm and a decline in its stiffness, which could be an indirect indicator of the quality and strength of the diaphragm muscle. These findings suggest that US and SWE evaluation of the diaphragm muscle may have the potential for use in the diagnosis and follow-up of sarcopenia. However, further comprehensive randomized controlled studies are needed to confirm this. What is Known: • Magnetic resonance imaging, computed tomography, and dual-energy x-ray absorptiometry are commonly used in the evaluation of sarcopenia. • The psoas and paraspinal muscles are commonly used in the evaluation of sarcopenia. What is New: • Ultrasound and shear wave elastography can be used in the evaluation of pediatric sarcopenia. • Diaphragm muscle can be used in the evaluation of pediatric sarcopenia.

Background: Computed Tomography (CT) is considered a highly accurate tool for assessing body composition. The aim of this study is to assess the usefulness of chest CT for malnutrition diagnosis in people with cystic fibrosis (PwCF), compared with other body composition techniques, as well as to assess possible associations with nutritional and respiratory status. Methods: A cross-sectional study was carried out in clinically stable adult PwCF. Subjects who had undergone a CT including the twelfth thoracic vertebra (T12) during the 6 months prior to or after our assessment were included and body composition was assessed using FocusedON-BC. The results were compared with anthropometry, bioelectrical impedance analysis (BIA), muscle ultrasonography, and handgrip strength (HGS). Respiratory parameters were collected, and nutritional status was assessed using Global Leadership Initiative on Malnutrition (GLIM) criteria. Results: A total of 55 PwCF were included. Muscle area assessed by CT correlated significantly with fat-free mass determined by BIA (r = 0.725) and anthropometry (r = 0.645), muscle mass evaluated by ultrasonography (r = 0.657), HGS (r = 0.593), Bhalla score (r = 0.403), and FEV1 (r = 0.488). Differences were observed when comparing muscle area in CT based on the Bhalla score (94.6 ± 21.1 cm2 in normal/mild involvement vs. 79.3 ± 20.9 cm2 in moderate/severe involvement; p = 0.009) and on nutritional status (96.3 ± 17.9 cm2 in normo-nourished vs. 75.9 ± 22.1 cm2 in malnourished; p < 0.001). Conclusions: In adult PwCF, measurements obtained from CT image analysis correlate adequately with anthropometry, BIA, muscle ultrasound, and HGS. Muscle area in CT is related to nutritional and respiratory status.

Emerging evidence suggests that diminished skeletal muscle mass is associated with lower health-related quality of life (HRQOL) in individuals with cancer. There are no studies that we know of in the literature that use ultrasound system to evaluate muscle mass and its relationship with HRQOL. The aim of our study was to evaluate the relationship between HRQOL determined by the EuroQol-5D tool and muscle mass determined by an artificial intelligence–based ultrasound system at the rectus femoris (RF) level in outpatients with cancer. Anthropometric data by bioimpedance (BIA), muscle mass by ultrasound by an artificial intelligence–based at the RF level, biochemistry determination, dynamometry and HRQOL were measured. A total of 158 patients with cancer were included with a mean age of 70.6 ±9.8 years. The mean body mass index was 24.4 ± 4.1 kg/m2 with a mean body weight of 63.9 ± 11.7 kg (38% females and 62% males). A total of 57 patients had a severe degree of malnutrition (36.1%). The distribution of the location of the tumors was 66 colon-rectum cancer (41.7%), 56 esophageal-stomach cancer (35.4%), 16 pancreatic cancer (10.1%), and 20.2% other locations. A positive correlation cross-sectional area (CSA), muscle thickness (MT), pennation angle, (BIA) parameters, and muscle strength was detected. Patients in the groups below the median for the visual scale and the EuroQol-5D index had lower CSA and MT, BIA, and muscle strength values. CSA (beta 4.25, 95% CI 2.03–6.47) remained in the multivariate model as dependent variable (visual scale) and muscle strength (beta 0.008, 95% CI 0.003–0.14) with EuroQol-5D index. Muscle strength and pennation angle by US were associated with better score in dimensions of mobility, self-care, and daily activities. CSA, MT, and pennation angle of RF determined by an artificial intelligence–based muscle ultrasound system in outpatients with cancer were related to HRQOL determined by EuroQol-5D. •A positive correlation cross-sectional area (CSA), muscle thickness (MT), pennation angle determined by an artificial intelligence-based muscle ultrasound system in outpatients with cancer with (BIA) parameters and muscle strength was detected.•Patients in the groups below the median for the visual scale and the EuroQol-5D index had lower CSA and MT, BIA, and muscle strength values.•CSA remained in the multivariate model as dependent variable (visual scale) and muscle strength with EuroQol-5D index.•Muscle strength and pennation angle by an artificial intelligence-based muscle ultrasound system were associated with better score in dimensions of mobility, self-care, and daily activities.

To assess differences in cognition functions and gross brain structure in children seven years after an episode of severe acute malnutrition (SAM), compared with other Malawian children. Prospective longitudinal cohort assessing school grade achieved and results of five computer-based (CANTAB) tests, covering three cognitive domains. A subset underwent brain MRI scans which were reviewed using a standardized checklist of gross abnormalities and compared with a reference population of Malawian children. Blantyre, Malawi.ParticipantsChildren discharged from SAM treatment in 2006 and 2007 (n 320; median age 9·3 years) were compared with controls: siblings closest in age to the SAM survivors and age/sex-matched community children. SAM survivors were significantly more likely to be in a lower grade at school than controls (adjusted OR = 0·4; 95 % CI 0·3, 0·6; P < 0·0001) and had consistently poorer scores in all CANTAB cognitive tests. Adjusting for HIV and socio-economic status diminished statistically significant differences. There were no significant differences in odds of brain abnormalities and sinusitis between SAM survivors (n 49) and reference children (OR = 1·11; 95 % CI 0·61, 2·03; P = 0·73). Despite apparent preservation in gross brain structure, persistent impaired school achievement is likely to be detrimental to individual attainment and economic well-being. Understanding the multifactorial causes of lower school achievement is therefore needed to design interventions for SAM survivors to thrive in adulthood. The cognitive and potential economic implications of SAM need further emphasis to better advocate for SAM prevention and early treatment.

Background: Malnutrition, influenced by inflammation, is associated with muscle depletion and body composition changes. This study aimed to evaluate muscle mass and quality using Artificial Intelligence (AI)-enhanced ultrasonography in patients with inflammation. Methods: This observational, cross-sectional study included 502 malnourished patients, assessed through anthropometry, electrical bioimpedanciometry, and ultrasonography of the quadriceps rectus femoris (QRF). AI-assisted ultrasonography was used to segment regions of interest (ROI) from transversal QRF images to measure muscle thickness (RFMT) and area (RFMA), while a Multi-Otsu algorithm was used to extract biomarkers for muscle mass (MiT) and fat mass (FatiT). Inflammation was defined as C-reactive protein (CRP) levels above 3 mg/L. Results: The results showed a mean patient age of 63.72 (15.95) years, with malnutrition present in 82.3% and inflammation in 44.8%. Oncological diseases were prevalent (46.8%). The 44.8% of patients with inflammation (CRP > 3) exhibited reduced RFMA (2.91 (1.11) vs. 3.20 (1.19) cm2, p < 0.01) and RFMT (0.94 (0.28) vs. 1.01 (0.30) cm, p < 0.01). Muscle quality was reduced, with lower MiT (45.32 (9.98%) vs. 49.10 (1.22%), p < 0.01) and higher FatiT (40.03 (6.72%) vs. 37.58 (5.63%), p < 0.01). Adjusted for age and sex, inflammation increased the risks of low muscle area (OR = 1.59, CI: 1.10–2.31), low MiT (OR = 1.49, CI: 1.04–2.15), and high FatiT (OR = 1.44, CI: 1.00–2.06). Conclusions: AI-assisted ultrasonography revealed that malnourished patients with inflammation had reduced muscle area, thickness, and quality (higher fat content and lower muscle percentage). Elevated inflammation levels were associated with increased risks of poor muscle metrics. Future research should focus on exploring the impact of inflammation on muscles across various patient groups and developing AI-driven biomarkers to enhance the diagnosis, monitoring, and treatment of malnutrition and sarcopenia.

(1) Background: The aim was to validate an AI-based system compared to the classic method of reading ultrasound images of the rectus femur (RF) muscle in a real cohort of patients with disease-related malnutrition. (2) Methods: One hundred adult patients with DRM aged 18 to 85 years were enrolled. The risk of DRM was assessed by the Global Leadership Initiative on Malnutrition (GLIM). The variation, reproducibility, and reliability of measurements for the RF subcutaneous fat thickness (SFT), muscle thickness (MT), and cross-sectional area (CSA), were measured conventionally with the incorporated tools of a portable ultrasound imaging device (method A) and compared with the automated quantification of the ultrasound imaging system (method B). (3) Results: Measurements obtained using method A (i.e., conventionally) and method B (i.e., raw images analyzed by AI), showed similar values with no significant differences in absolute values and coefficients of variation, 58.39–57.68% for SFT, 30.50–28.36% for MT, and 36.50–36.91% for CSA, respectively. The Intraclass Correlation Coefficient (ICC) for reliability and consistency analysis between methods A and B showed correlations of 0.912 and 95% CI [0.872–0.940] for SFT, 0.960 and 95% CI [0.941–0.973] for MT, and 0.995 and 95% CI [0.993–0.997] for CSA; the Bland–Altman Analysis shows that the spread of points is quite uniform around the bias lines with no evidence of strong bias for any variable. (4) Conclusions: The study demonstrated the consistency and reliability of this new automatic system based on machine learning and AI for the quantification of ultrasound imaging of the muscle architecture parameters of the rectus femoris muscle compared with the conventional method of measurement.

(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.