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Background: Low back pain (LBP) is one of the most prevalent musculoskeletal disorders in adults worldwide. Alterations in postural and lumbopelvic control and functionality appear to be determining factors in its resolution. Methods: A cross-sectional study was performed. Patients with LBP were enrolled. Lumbar pain; postural control (PC), total area of the center of pressure (TACOP), and the velocity of the center of pressure (VCOP); lumbopelvic control (LPC); and functionality were evaluated. Statistical tests were implemented to determine differences between sex and age and correlation models among the variables. Results: Thirty adult patients with LBP were analyzed. A strong relationship was found between pain and functionality [r = 0.64; p < 0.001]. A moderate relationship was found between pain and TACOP [r = 0.395; p = 0.031]. A moderate relationship was observed between TACOP and functionality [0.413; p = 0.023] and between LPC and TACOP [r = 0.416; p = 0.001]. Conclusions: This study demonstrates the significant impact of LBP on postural control, lumbopelvic control, and functionality. These results highlight the importance of addressing postural and lumbopelvic control in LBP treatment. No significant differences based on gender and age were found, but all clinical variables differed significantly between the LBP and control groups, underscoring the unique impairments associated with LBP.
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Purpose: The integration of artificial intelligence (AI) in radiology has revolutionized diagnostics, optimizing precision and decision-making. Specifically in musculoskeletal imaging, AI tools can improve accuracy for upper extremity pathologies. This study aimed to assess the diagnostic performance of AI models in detecting musculoskeletal pathologies of the upper extremity using different imaging modalities. Methods: A meta-analysis was conducted, involving searches on MEDLINE/PubMed, SCOPUS, Cochrane Library, Lilacs, and SciELO. The quality of the studies was assessed using the QUADAS-2 tool. Diagnostic accuracy measures including sensitivity, specificity, diagnostic odds ratio (DOR), positive and negative likelihood ratios (PLR, NLR), area under the curve (AUC), and summary receiver operating characteristic were pooled using a random-effects model. Heterogeneity and subgroup analyses were also included. All statistical analyses and plots were performed using the R software package. Results: Thirteen models from ten articles were analyzed. The sensitivity and specificity of the AI models to detect musculoskeletal conditions in the upper extremity were 0.926 (95% CI: 0.900; 0.945) and 0.908 (95% CI: 0.810; 0.958). The PLR, NLR, lnDOR, and the AUC estimates were found to be 19.18 (95% CI: 8.90; 29.34), 0.11 (95% CI: 0.18; 0.46), 4.62 (95% CI: 4.02; 5.22) with a (P < 0.001), and 95%, respectively. Conclusion: The AI models exhibited strong univariate and bivariate performance in detecting both positive and negative cases within the analyzed dataset of musculoskeletal pathologies in the upper extremity.
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Understanding the nutritional content of protein supplements is crucial for optimal nutritional planning among athletes and other people. Distribution of macronutrients and aminograms in the main products available in the national Chilean market remains unknown. A descriptive cross-sectional study was conducted to identify the main protein supplements available in the Chilean market. Information on macronutrients and aminograms from the nutritional labels of each product was extracted. The analysis considered the content per portion and per 100 g. Cluster analysis models and graphical representations were explored. Eighty protein shakes were assessed in the Santiago de Chile market. The median protein dosage was 32 g (range from 25 to 52), and the median energy value stood at 390 kcal (range from 312 to 514). The median protein content per 100 g of product was found to be 75 g (range from 42.5 to 97.2). The combined median concentration of amino acids was 4749.75 mg. Among these, the essential amino acid L-Tryptophan exhibited the lowest concentration at 1591.50 mg, while the conditional amino acid L-Glutamine had the highest median concentration at 17,336 mg. There was a significant prevalence of animal-derived products, placing specific emphasis on protein supplements that feature elevated levels of the amino acids L-Glutamine and L-Leucine.