Background: This study aimed to evaluate the clinical impact of an artificial intelligence (Al)-based decision support system (DSS), Koios DS, on the analysis of ultrasound imaging and suspicious characteristics for thyroid nodule risk stratification Methods: A retrospective ultrasound study was conducted on all thyroid nodules with histological findings from June 2021 to December 2022 in a thyroid nodule clinic. The diagnostic performance of ultrasound imaging was evaluated by six readers on American College of Radiology Thyroid Imaging Reporting and Data System (ACR TI-RADS) before and after the use of the AI-based DSS, and by the AI itself. Results: A total of 172 patients (83.1% women) with a mean age of 52.3±15.3 years were evaluated. The mean maximum nodular diameter was 2.9±1.2 cm, with 11.0% being differentiated thyroid carcinomas. Among the nodules initially classified as ACR TI-RADS 3 and 4, Al reclassified 81.4% and 24.5% into lower risk categories, respectively.Receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic performance of the readers and the AI-based DSS versus histological diagnosis. There was an increase in the area under the receiver operating characteristic curve (AUROC) after the use of Al (0.776 vs. 0.817, p<0.001). The AI-based DSS improved the mean sensitivity (82.3% vs. 86.5%) and specificity (38.3% vs. 54.8%), produced a high negative predictive value (94.5% vs. 96.4%), and increased the positive predictive value (14.0% vs. 16.1%) and diagnostic precision (43.0% vs. 49.3%). Based on the ACR TI-RADS score, there was a significant improvement in interobserver agreement after the use of Al (r=0.741 for ultrasound imaging alone vs. 0.981 for ultrasound imaging and the AI-based DSS, p<0.001). Conclusion: The use of an AI-based DSS was associated with an overall improvement in the diagnostic efficacy of ultrasound imaging, based on the AUROC, as well as an increase in sensitivity, specificity, the negative and positive predictive value, and diagnostic accuracy. There was also a reduction in interobserver variability and an increase in the degree of concordance with the use of Al. Al reclassified more than half of the nodules with intermediate ACR TI-RADS into lower risk categories.

Nutritional ultrasonography is an emerging technique for measuring muscle mass and quality. The study aimed to evaluate the relationship between the parameters of body mass and quality of ultrasonography with other parameters of morphofunctional assessment in patients with disease-related malnutrition (DRM). Methods: A cross-sectional study was developed on 144 patients diagnosed with DRM according to the Global Leadership Initiative on Malnutrition (GLIM) criteria. Morphofunctional evaluation was assessed with anthropometric variables, handgrip strength and bioelectrical impedanciometry (BIA). Nutritional ultrasonography of quadriceps rectus femoris (QRF) was made (muscle mass (Muscle Area of Rectus Femoris index (MARFI)), Y axis and muscle quality (X-Y index and echogenicity). Results: The mean age of patients was 61.4 (17.34) years. The prevalence of sarcopenia in the sample was 33.3%. Patients with sarcopenia (S) had lower values of MARFI [(S: 1.09 (0.39) cm²/m²; NoS: 1.27 (0.45); p = 0.02), Y axis (S: 0.88 (0.27); NoS: 1.19 (0.60); p < 0.01) and X-Y index (S: 1.52 (0.61); NoS: 1.30 (0.53); p < 0.01)]. There was a correlation between BIA parameters (phase angle) and muscle mass ultrasonographic variables (MARFI) (r = 0.35; p < 0.01); there was an inverse correlation between muscle quality ultrasonographic variables (echogenicity) and handgrip strength (r = −0.36; p < 0.01). In the multivariate analysis adjusted by age, the highest quartile of the X-Y index had more risk of death OR: 4.54 CI95% (1.11–18.47). Conclusions: In patients with DRM and sarcopenia, standardized muscle mass and muscle quality parameters determined by ultrasonography of QRF are worse than in patients without sarcopenia. Muscle quality parameters had an inverse correlation with electric parameters from BIA and muscle strength. The highest quartile of the X-Y index determined by ultrasonography was associated with increased mortality risk.

Objectives: To evaluate in patients admitted for stroke: (1) The frequency of hyperglycaemia associated with enteral nutrition (EN). (2) The risk of morbidity and mortality associated with the development of this type of hyperglycaemia. Methods: A longitudinal observational study was conducted in 115 non-diabetic patients admitted for stroke with EN. Age, functional capacity (Rankin scale), and blood plasma glucose (BPG) were recorded. Hyperglycaemia was considered as: a value higher than 126 mg/dL before the EN and/or a value higher than 150 mg/dL after a week of enteral nutrition. According to this, three groups were differentiated: HyperES: Those who had hyperglycemia before the beginning of the EN (33% patients); NoHyper: those who did not have hyperglycemia before or after (47.8% patients); and HyperEN: Those who did not have hyperglycemia before but suffered it after the beginning of the EN (19.1% patients). Results: The age was 72.72 (15.32) years. A higher rate of mortality was observed in the HyperEN group 45.50%, than HyperES 15.80% or NoHyper: 10.90%). A lower recovery of the oral feeding was observed in those patients of the HyperEN group 27.30%, than HyperES: 42.10% or NoHyper: 61.80%). In the multivariate analysis adjusting for age, sex, and Rankin scale the development of hyperglycemia in those who did not have it at the beginning (HyperEN) was an independent risk factor for non-recovery of the oral feeding (OR: 4.21 (1.20–14.79), p = 0.02); and mortality adjusted for age, sex and Rankin scale (OR: 6.83 (1.76–26.47), p < 0.01). Conclusions: In non-diabetic patients admitted for stroke with EN, the development of hyperglycaemia in relation to enteral nutrition supposes an independent risk factor for mortality and for the non-recovery of the oral feeding.

Background/Objectives: Assessing oral intake in patients with disease-related malnutrition (DRM) and sarcopenia remains a clinical challenge. This study aimed to evaluate the relationship between oral intake adjusted to nutritional requirements and the presence of sarcopenia in patients with DRM. Methods: This was a prospective observational study involving 118 outpatients with DRM, diagnosed according to Global Leadership Initiative on Malnutrition criteria. Sarcopenia was assessed using the European Working Group on Sarcopenia in Older People criteria. A 3-day dietary intake record was collected at the beginning of nutritional follow-up. Caloric (kcal/day) and protein (g/day) intakes were calculated. Energy needs were estimated using the Harris-Benedict equation with stress factors, and protein needs were set at 1.5 g/kg/day. Intake was categorized based on whether energy and protein intake exceeded or fell below 70% of requirements. Results: The mean age was 62.2 years, and 58.8% were female. Sarcopenia was present in 42% of patients. No significant difference was found in body mass index between patients with and without sarcopenia. Mean caloric intake was 29.6 kcal/kg/day and protein intake was 1.3 g/kg/day. Average fulfilment was 78.3% for energy and 86.8% for protein. Patients with sarcopenia had significantly lower intake of calories and macronutrients. Sarcopenia was more prevalent in those with <70% fulfilment of caloric and protein requirements. Multivariate analysis showed increased risk of sarcopenia (Odds ratio (OR): 4.27; 95% Confidence Interval (CI): 1.30–14.03; p = 0.017) and severe malnutrition (OR: 5.17; 95% CI: 1.63–16.42; p < 0.01) in patients with low protein intake. Conclusions: In patients with DRM, insufficient intake of calories and protein was associated with a higher prevalence of sarcopenia. There was an increased risk of sarcopenia and severe malnutrition in patients with lower protein intake.