(1) Background: Health-related quality of life (HRQoL) gains importance as novel treatment options for individuals with esophagogastric tumors to improve long-term survival. Impaired HRQoL has been shown to be a predictor of overall survival. Sarcopenia is a known prognostic factor for postoperative complications. As the regular control of sarcopenia through CT scans might not always be possible and HRQoL and nutritional scores are easier to obtain, this study aimed to assess the relationship between nutritional scores, HRQoL and skeletal muscle mass in patients undergoing chemotherapy for cancers of the upper gastrointestinal tract. (2) Methods: Eighty patients presenting with tumors of the upper GI tract were included and asked to fill out the standardized HRQoL questionnaire, EORTC's QLQ-C30. Nutritional status was assessed using the MNA, MUST and NRS 2002 scores. Sarcopenia was determined semi-automatically based on the skeletal muscle index at the L3 vertebrae level in staging CT scans. (3) Results: In chemo-naïve patients, HRQoL summary scores correlated significantly with nutritional scores and SMI. SMI and HRQoL prior to neoadjuvant therapy correlated significantly with SMI after treatment. (4) Conclusions: HRQoL is a helpful tool for assessing patients' overall constitution. The correlation of HRQoL summary scores and SMI might allow for a rough assessment of skeletal muscle status through HRQoL assessment in chemo-naïve patients.
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http://dx.doi.org/10.3390/cancers16061232 | DOI Listing |
Front Public Health
January 2025
Department of Statistics, College of Science, Bahir Dar University, Bahir Dar, Ethiopia.
Introduction: Reducing poverty through crop commercialization is one of the antipoverty efforts that helps promote health. This study explored the prevalence and the causal relationship between crop commercialization and rural Ethiopian households' multidimensional poverty using multilevel data.
Methods: The study uses data from the most recent nationally representative Ethiopian socioeconomic survey 2018/19 to calculate the rural multidimensional poverty index using the Alkire and Foster technique.
Front Neurosci
January 2025
Department of Neurology, Jiangxi Provincial People's Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, China.
Background And Purpose: To evaluate the association between sleep-related factors, including sleep duration, self-reported sleep disturbances, and diagnosed sleep disorders, and the risk of cardiovascular disease (CVD) in US participants.
Methods: The data of this study from the National Health and Nutrition Examination Survey (NHANES) conducted between 2007 and 2014. Sleep factors were assessed using a standardized questionnaire, and overall sleep scores were calculated on a scale of 0 to 3.
Biochem Res Int
January 2025
Department of Animal Nutrition, Veterinary College and Research Institute, Tamil Nadu Veterinary and Animal Sciences University, Chennai, Tamil Nadu, India.
Members of the genus are the conventional medicinal plants used in the therapeutic management of numerous ailments, especially for their antioxidant and pharmacological activities. The crude extract of was profiled using high-resolution GC-MS and LC-MS/MS techniques to determine possible bioactive compounds that are vital to the antioxidant activity. A total of 52 and 63 bioactive compounds have been detected in GC-MS chromatograms using different solvents (methanol and ethanol) in leaf extracts, representing the presence of certain bioactive compounds.
View Article and Find Full Text PDFFront Oral Health
January 2025
Department of Cardiovascular Pathology and Diet Therapy, Federal Research Centre for Nutrition, Biotechnology and Food Safety, Moscow, Russia.
Background: Cardiovascular diseases (CVDs) are the leading cause of mortality and morbidity among noncommunicable diseases. Over the past decade, there has been a notable increase in the prevalence of CVDs among young individuals. Obesity, a well-known risk factor for CVDs, is also associated with various comorbidities that may contribute to cardiovascular risk.
View Article and Find Full Text PDFFront Cardiovasc Med
January 2025
Shengli Clinical Medical College of Fujian Medical University, Fujian Medical University, Fuzhou, Fujian, China.
Background: Depression is being increasingly acknowledged as an important risk factor contributing to coronary heart disease (CHD). Currently, there is no predictive model specifically designed to evaluate the risk of coronary heart disease among individuals with depression. We aim to develop a machine learning (ML) model that will analyze risk factors and forecast the probability of coronary heart disease in individuals suffering from depression.
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