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Background/Objectives: Obesity and metabolic conditions increase the risk of metabolic-associated steatotic liver disease (MASLD). This study examined the risk of MASLD in 137 renal transplant recipients (RTRs) from a single-center hospital on the basis of their obesity and metabolic health status. Methods: Participants were categorized into four groups: metabolically healthy nonobese (MHNO), metabolically healthy obese (MHO), metabolically abnormal nonobese (MANO), and metabolically abnormal obese (MAO). MASLD was assessed using the hepatic steatosis index (HSI), calculated as 8 × (aspartate aminotransferase/alanine aminotransferase ratio) + body mass index + 2 (if diabetic) + 2 (if woman). The HSI scores were 29.50 ± 4.55, 38.08 ± 5.44, 33.61 ± 5.23, and 39.86 ± 4.13 in the MHNO, MHO, MANO, and MAO groups, respectively (p < 0.05). Results: Overall, 25.55% of the participants (57.14% men) were classified as having MASLD (HSI > 36). A multivariate-adjusted regression analysis revealed significantly higher HSI scores in the MAO group than in the MHNO group. Both MHO and MANO groups also had significantly higher HSI scores. The odds ratios for more severe MASLD were 2.74 (95% CI: 0.88–8.52) for the MANO group and 74.59 (95% CI: 13.29–418.68) for the MAO group compared with the MHNO group. Conclusions: These findings suggest that RTRs with obesity have a higher risk of MASLD, but even those with a normal weight and metabolic abnormalities are at increased risk. [ABSTRACT FROM AUTHOR]

The scarcity of dietary guidance for renal transplant recipients (RTRs) raises concerns regarding obesity and associated comorbidities, including impaired renal function. This two-stage cross-sectional study examined longitudinal changes in dietary nutrient intake in the same individuals over a 5-year interval. This study involved two stages: T1 (September 2016 to June 2018) and T2 (July 2022 to August 2023). The average duration between the two data collection stages was 6.17 ± 0.42 (range 5.20–6.87) years. The study included 227 RTRs with an average age and time since transplant of 49.97 ± 12.39 and 9.22 ± 7.91 years, respectively. Of the 35 patients who participated in both phases, fewer than half met the recommended intakes for energy, dietary fiber, and most vitamins and minerals, as set in the Dietary Reference Intakes (DRIs) or by the Dietitian Association Australia (DAA). Over half exceeded the DRI recommended intake for total protein, and more than 80% of the protein consumed per kilogram of body weight exceeded the DAA's recommendations. In the T2 stage, the RTRs had a significantly higher blood urea nitrogen level, lower albumin level, and estimated glomerular filtration rate. These findings indicate that deteriorating dietary intake in RTRs can adversely affect their nutritional status and transplanted kidney function over a 5-year period. [ABSTRACT FROM AUTHOR]

The scarcity of dietary guidance for renal transplant recipients (RTRs) raises concerns regarding obesity and associated comorbidities, including impaired renal function. This two-stage cross-sectional study examined longitudinal changes in dietary nutrient intake in the same individuals over a 5-year interval. This study involved two stages: T1 (September 2016 to June 2018) and T2 (July 2022 to August 2023). The average duration between the two data collection stages was 6.17 ± 0.42 (range 5.20-6.87) years. The study included 227 RTRs with an average age and time since transplant of 49.97 ± 12.39 and 9.22 ± 7.91 years, respectively. Of the 35 patients who participated in both phases, fewer than half met the recommended intakes for energy, dietary fiber, and most vitamins and minerals, as set in the Dietary Reference Intakes (DRIs) or by the Dietitian Association Australia (DAA). Over half exceeded the DRI recommended intake for total protein, and more than 80% of the protein consumed per kilogram of body weight exceeded the DAA's recommendations. In the T2 stage, the RTRs had a significantly higher blood urea nitrogen level, lower albumin level, and estimated glomerular filtration rate. These findings indicate that deteriorating dietary intake in RTRs can adversely affect their nutritional status and transplanted kidney function over a 5-year period.

Objectives: The aim of this study was to assess the size, angles and positional characteristics of facial anthropometry between "acromegalic" patients and control subjects. We also identify possible facial soft tissue measurements for generating discriminant functions toward acromegaly determination in males and females for acromegaly early self-awareness., Material and Methods: This is a cross-sectional study. Subjects participating in this study included 70 patients diagnosed with acromegaly (35 females and 35 males) and 140 gender-matched control individuals. Three-dimensional facial images were collected via a camera system. Thirteen landmarks were selected. Eleven measurements from the three categories were selected and applied, including five frontal widths, three lateral depths and three lateral angular measurements. Descriptive analyses were conducted using means and standard deviations for each measurement. Univariate and multivariate discriminant function analyses were applied in order to calculate the accuracy of acromegaly detection., Results: Patients with acromegaly exhibit soft-tissue facial enlargement and hypertrophy. Frontal widths as well as lateral depth and angle of facial changes were evident. The average accuracies of all functions for female patient detection ranged from 80.0-91.40%. The average accuracies of all functions for male patient detection were from 81.0-94.30%. The greatest anomaly observed was evidenced in the lateral angles, with greater enlargement of "nasofrontal" angles for females and greater "mentolabial" angles for males. Additionally, shapes of the lateral angles showed changes. The majority of the facial measurements proved dynamic for acromegaly patients; however, it is problematic to detect the disease with progressive body anthropometric changes., Conclusion: The discriminant functions of detection developed in this study could help patients, their families, medical practitioners and others to identify and track progressive facial change patterns before the possible patients go to the hospital, especially the lateral "angles" which can be calculated by relative point-to-point changes derived from 2D lateral imagery without the 3D anthropometric measurements. This study tries to provide a novel and easy method to detect acromegaly when the patients start to have awareness of abnormal appearance because of facial measurement changes, and it also suggests that undiagnosed patients be urged to go to the hospital as soon as possible for acromegaly early diagnosis.

Background: Many health indices have a relationship with anthropometric indices. This research attempts to provide a new measurement: a chronic disease risk factor score built into the regression model. This new model will help people visualize their health status and get multiple information during the process of the healthy examination., Methods: Data from 8,034 subjects were collected from the data bank of the Health Examination Center in Chang Gung Memorial Hospital. Related anthropometric indices and biochemical factors were selected and used to construct a regression model. The anthropometric indices used were body mass index, waist hip ratio, waist hip area ratio, health index, waist leg ratio and trunk leg ratio. Biochemical data included blood pressure, glucose, triglyceride, cholesterol and uric acid, combined to form an anthropometric chronic disease risk factor score., Results: Subjects under 45 years of age had the highest chronic disease risk factor score, and were selected to construct a regression model. The R-square of this model is 0.355; its predictive error is near 12%. After verification with a testing group, the regression model could be used to predict health status., Conclusion: The purpose of this study was to develop a new anthropometric chronic disease risk factor score by combining anthropometric indices and biochemical data. A multiple regression model was used to illustrate health status via anthropometric chronic disease risk factor scores for the subjects participating in the health examination. The results show that the chronic disease risk factor score is useful for prescribing relevant medical treatment as well as for other research.