These findings indicate that the domain including the hydrophobic region of ATGL was essential for association with LDs.

OBJECTIVEWhether brachial-ankle pulse wave velocity (baPWV), a noninvasive marker for arterial stiffness, is a useful predictive maker for cardiovascular events in subjects with diabetes is not established. In the present cohort study, we evaluated the benefit of baPWV for the prediction of cardiovascular morbidity and mortality in subjects with diabetes. RESEARCH DESIGN AND METHODSA total of 4,272 outpatients with diabetes were enrolled in the Kyushu Prevention Study of Atherosclerosis. Of these, 3,628 subjects, excluding those with an ankle-brachial index of <0.9, were prospectively followed for 3.2 6 2.2 years. The baPWV at baseline was classified by recursive partitioning (RP) for each end point. We plotted the Kaplan-Meier curves for high-and low-baPWV groups, which were designated based on the cutoff points, and calculated Cox proportional hazards models. RESULTSThe elevation of baPWV quartiles was significantly correlated to the incidence of coronary artery events, cerebrovascular events, and all-cause mortality. RP revealed baPWVs of 14 and 24 m/s as statistically adequate cutoff points for cardiovascular events and mortality, respectively. High-baPWV classes showed significantly low event-free ratios in Kaplan-Meier curves for all end points and remained independent risks for all-cause mortality and cerebrovascular events, but not for coronary artery events after adjustments for age, sex, BMI, hypertension, hyperlipidemia, smoking, and hemoglobin A 1c by Cox proportional hazards models. CONCLUSIONSThis large-scale cohort study provided evidence that high baPWV is a useful independent predictor of mortality and cardiovascular morbidity in subjects with diabetes.

Objective Previous reports have demonstrated the association of serum bilirubin levels with the progression of diabetic nephropathy. The objective of this study is to assess the association of basal bilirubin levels with progressive renal decline (PRD) and end-stage kidney disease (ESKD). Methods A total of 298 patients with diabetes who visited Kyushu University Hospital (Japan) were recruited and followed up for 10 years. PRD was defined as a negative change in estimated glomerular filtration ratio (eGFR) >3.7%/year, 2.5th percentile. Logistic regression analysis was performed to evaluate the association of total bilirubin levels with PRD and its cut-off point was determined by receiver operating characteristic (ROC) analysis. Kaplan-Meier method and Cox hazard regression analysis were used to evaluate the predictive ability of its cut-off point for ESKD. Results Logistic regression model showed that total bilirubin levels were significantly associated with PRD, and ROC analysis showed that its cut-off point was 0.5 mg/dL. Kaplan-Meier method showed that the percent of patients who reached two endpoints, composite endpoint (ESKD or doubling of creatinine level) or 30% eGFR decline, was significantly higher in the low bilirubin group than in the high bilirubin group (18.5% vs 11.0%, P = 0.045; 49.1% vs 42.1%, P = 0.045, respectively, log-rank test). Cox hazard regression models confirmed the independence of the predictive ability of its cut-off point. Conclusions Serum total bilirubin levels were negatively associated with PRD in diabetic nephropathy and its cut-off point was 0.5 mg/dL. It may be clinically useful for identifying patients at high risk of ESKD.

Background: Although the side effects of cancer chemotherapy impair a patient's quality of life, family members' awareness of side effects may relieve patient anxiety and distress.Aim: We investigated whether patients and their families were consistent in recognizing the occurrence and severity of symptomatic side effects of chemotherapy treatment for cancer.Methods and results: This was a prospective observational study. We administered a questionnaire survey to patients and family members to assess the frequency of occurrence (1: never, 2: almost never, 3: sometimes, 4: frequently, 5: almost always, 6: unknown) and the degree of severity (1: mild, 2: moderate, 3: severe, 4: extremely severe, 5: unknown) of physical and psychological symptoms associated with cancer chemotherapy. Weighted Kappa and Cramer coefficients were used to assess consistency between the two groups. We surveyed 20 pairs of patients (5 men, 15 women) and their families (10 men, 10 women); 17 pairs lived together. The median age was 65.5 years (interquartile [IQR], 58.75, 69.25) for patients and 61.00 years (IQR, 47.25, 71.25) for family members. Of patients, 17 had solid cancer, and three had leukemia. Family members mostly recognized objectively visible symptoms such as hair loss and development of spots and keratinization. However, it was difficult for families to detect invisible subjective symptoms such as weakness, dysesthesia, depressed mood, and unarticulated anxiety. Conclusions:The results indicated that recognition of invisible subjective symptoms in patients undergoing chemotherapy was difficult even for family members. Therefore, a multidisciplinary approach in which various medical professionals actively communicate with both patients and families is important. Information sharing in collaboration with patients and families could increase understanding of the patient's condition and optimize patient care.

This study aimed to develop a simplified model for predicting end-stage kidney disease (ESKD) in patients with diabetes. The cohort included 2549 individuals who were followed up at Kyushu University Hospital (Japan) between January 1, 2008 and December 31, 2018. The outcome was a composite of ESKD, defined as an eGFR < 15 mL min−1 [1.73 m]−2, dialysis, or renal transplantation. The mean follow-up was 5.6 $$\pm$$ ± 3.7 years, and ESKD occurred in 176 (6.2%) individuals. Both a machine learning random forest model and a Cox proportional hazard model selected eGFR, proteinuria, hemoglobin A1c, serum albumin levels, and serum bilirubin levels in a descending order as the most important predictors among 20 baseline variables. A model using eGFR, proteinuria and hemoglobin A1c showed a relatively good performance in discrimination (C-statistic: 0.842) and calibration (Nam and D’Agostino $$\chi$$ χ 2 statistic: 22.4). Adding serum albumin and bilirubin levels to the model further improved it, and a model using 5 variables showed the best performance in the predictive ability (C-statistic: 0.895, $$\chi$$ χ 2 statistic: 7.7). The accuracy of this model was validated in an external cohort (n = 5153). This novel simplified prediction model may be clinically useful for predicting ESKD in patients with diabetes.