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AbstractPurpose Approximately 700,000 people in the USA have chronic kidney disease requiring dialysis. Protein-energy wasting (PEW), a condition of advanced catabolism, contributes to three-year survival rates of 50%. PEW occurs at all levels of Body Mass Index (BMI) but is devastating for those people at the extremes. Treatment for PEW depends on an accurate understanding of energy expenditure. Previous research established that current methods of identifying PEW and assessing adequate treatments are imprecise. This includes disease-specific equations for estimated resting energy expenditure (eREE). In this study, we applied machine learning (ML) modelling techniques to a clinical database of dialysis patients. We assessed the precision of the ML algorithms relative to the best-performing traditional equation, the MHDE.Methods This was a secondary analysis of the Rutgers Nutrition and Kidney Database. To build the ML models we divided the population into test and validation sets. Eleven ML models were run and optimized, with the best three selected by the lowest root mean squared error (RMSE) from measured REE. Values for eREE were generated for each ML model and for the MHDE. We compared precision using Bland-Altman plots.Results Individuals were 41.4% female and 82.0% African American. The mean age was 56.4 ± 11.1 years, and the median BMI was 28.8 (IQR = 24.8 − 34.0) kg/m2. The best ML models were SVR, Linear Regression and Elastic net with RMSE of 103.6 kcal, 119.0 kcal and 121.1 kcal respectively. The SVR demonstrated the greatest precision, with 91.2% of values falling within acceptable limits. This compared to 47.1% for the MHDE. The models using non-linear techniques were precise across extremes of BMI.Conclusion ML improves precision in calculating eREE for dialysis patients, including those most vulnerable for PEW. Further development for clinical use is a priority.

Purpose For individuals receiving maintenance dialysis, estimating accurate resting energy expenditure (REE) is essential for achieving energy balance, and preventing protein-energy wasting. Dialysis-specific, predictive energy equations (PEEs) offer a practical way to calculate REE. Three PEEs have been formulated via similar methods in different demographic samples; the Maintenance Haemodialysis Equation (MHDE REE), Vilar et al. Equation (Vilar REE) and the Fernandes et al. Equation (Cuppari REE). We compared them in a US cohort and assessed precision relative to measured REE (mREE) from indirect calorimetry. Because of expected imprecision at the extremes of the weight distribution, we also assessed the PEEs stratified by body mass index (BMI) subgroups.Methods This analysis comprised of 113 individuals from the Rutgers Nutrition and Kidney Database. Estimated REE (eREE) was calculated for each PEE, and agreement with mREE was set at > 50% of values within the limits of ±10%. Reliability and accuracy were determined using intraclass correlation (ICC) and a Bland Altman plot, which analysed the percentage difference of eREE form mREE.Results Participants were 58.4% male and 81.4% African American. Mean age was 55.8 ± 12.2 years, and the median BMI was 28.9 (IQR = 25.3 − 34.4) kg/m2. The MHDE REE achieved 58.4% of values within ±10% from mREE; Cuppari REE achieved 47.8% and Vilar REE achieved 46.0% agreement. Reliability was good for the MHDE REE (ICC = 0.826) and Cuppari REE (ICC = 0.801), and moderate for the Vilar REE (ICC = 0.642) (p

Research suggests that adiponectin, leptin, and genetic polymorphisms such as catechol-O-methyltransferase (COMT) genotype may play an integral role in blood pressure status and thereby cardiovascular health. This is an area especially important for women who are post-menopause; however, the current literature investigating these associations is limited. This study was a cross-sectional secondary analysis of baseline data (N 237) from the Minnesota Green Tea Trial (MGTT). The current study explored the relationships between plasma adiponectin, leptin, and COMT genotype on blood pressure measures. Plasma adiponectin and leptin were obtained after an overnight fast of at least 10 h and were measured by the radioimmunoassay method. The relationships were analysed using multiple linear regression after adjusting for potential confounders. Effect modifications by age, body mass index (BMI) category, blood pressure category, antihypertensive medication use, and COMT genotype were also investigated. The majority of participants were non-Hispanic (97⋅9 %) and Caucasian (94⋅9 %). Mean (sd) age and BMI were 60⋅7 (5⋅0) years and 28⋅2 (2⋅9) kg/m2, respectively. After adjustment for confounding variables, neither plasma adiponectin, plasma leptin nor COMT genotype was associated with systolic or diastolic blood pressure measures. The results of stratified analyses also did not reveal any significant interactions or associations. Based on the findings of this study, which utilised more rigorous statistical methods than previous research, neither adiponectin, leptin nor COMT genotype play a role in blood pressure measures in women who are post-menopause.

Rationale & Objective: People receiving maintenance hemodialysis (HD) experience significant activity barriers but desire the ability to do more and remain independent. To learn about how to help people who require dialysis stay active, a mixed methods study was designed to assess functional status and explore participants’ lived activity experiences. Study Design: A concurrent mixed methods design was chosen to increase understanding of the real-life activity experiences of people who require dialysis through in-depth interviews paired with functional status measures. The qualitative findings were fully integrated with the quantitative results to link characteristics associated with different physical activity levels. Setting & Participants: A purposive sample of 15 adult patients receiving maintenance HD for at least 3 months was recruited from 7 dialysis centers in Newark, New Jersey. Analytical Approach: Thematic analysis using principles of interpretive phenomenology. Fully integrated quantitative and qualitative data with joint displays and conversion mixed methods. Results: Participants had a median age of 58 years and were predominantly African American (83%) and men (67%). Three descriptive categories were generated about the participants. They described physical activity as a routine daily activity rather than structured exercise. All participants experienced substantial hardship in addition to chronic kidney disease and expressed that family, friends, and faith were essential to their ability to be active. An overarching theme was generated for participants’ mindsets about physical activity. Within the mindset theme, we discerned 3 subthemes comprising characteristics of participants’ mindsets by levels of engagement in physical activity. Limitations: While code saturation and trends in functional status measures were achieved with 15 participants, a larger sample size would allow for deeper meaning saturation and statistical inference. Conclusions: Patients receiving maintenance HD with an engaged mindset exhibited more adaptive coping skills, moved more, wanted to help others, and had a normal body weight habitus. These participants employed adaptive coping skills to carry out daily life activities of importance, highlighting the value of adaptive coping to help overcome the challenges of being physically active.

Food-related quality of life is defined as achieving adequate nutrition, deriving pleasure, and maintaining social activities through eating and drinking. The objective of this qualitative study was to characterize the parental perspective about eating experiences and family functioning after diagnosis of inflammatory bowel disease in their child in order to describe how these experiences may impact food-related quality of life. Semistructured interviews were completed with 10 parents of a child with inflammatory bowel disease. Conventional content analysis was conducted with steps to ensure trustworthiness. Family Systems Theory was the interpretive framework. Ambiguous nutrition information emerged as the main theme. Families experienced various and conflicting viewpoints regarding the role of diet, which presented a challenge after diagnosis. Parents reported frustration regarding the lack of uniform and personalized nutrition guidance. Our results support that families desire shared decision-making in regard to medication and diet, which is an important clinical practice implication for the entire gastroenterology medical team. Understanding the challenges faced by families after a major medical diagnosis in a child provides insight into designing medical interventions that maintain optimal quality of life in families., Competing Interests: The authors declare no conflicts of interest or sources of funding., (Copyright © 2021 Society of Gastroenterology Nurses and Associates.)