Association between regional economic status and renal recovery of dialysis-requiring acute kidney injury among critically ill patients.

The association between regional economic status and the probability of renal recovery among patients with dialysis-requiring AKI (AKI-D) is unknown. The nationwide prospective multicenter study enrolled critically ill adult patients with AKI-D in four sampled months (October 2014, along with January, April, and July 2015) in Taiwan. The regional economic status was defined by annual disposable income per capita (ADIPC) of the cities the hospitals located. Among the 1,322 enrolled patients (67.1 ± 15.5 years, 36.2% female), 833 patients (63.1%) died, and 306 (23.1%) experienced renal recovery within 90 days following discharge. We categorized all patients into high (n = 992) and low economic status groups (n = 330) by the best cut-point of ADIPC determined by the generalized additive model plot. By using the Fine and Gray competing risk regression model with mortality as a competing risk factor, we found that the independent association between regional economic status and renal recovery persisted from model 1 (no adjustment), model 2 (adjustment to basic variables), to model 3 (adjustment to basic and clinical variables; subdistribution hazard ratio, 1.422; 95% confidence interval, 1.022-1.977; p = 0.037). In conclusion, high regional economic status was an independent factor for renal recovery among critically ill patients with AKI-D.

Hyperhomocysteinemia Associated with Low Muscle Mass, Muscle Function in Elderly Hemodialysis Patients: An Analysis of Multiple Dialysis Centers.

BACKGROUND: The hyperhomocysteinemia was with high prevalence and has been considered as a risk factor for cardiovascular disease in hemodialysis patients. These patients also experienced a high risk of muscle wasting caused by the comorbidity, malnutrition, and low physical activity. We investigated the associations of homocysteinemia with muscle mass, muscle function in elderly hemodialysis patients. METHODS: A clinical cross-sectional study was conducted on 138 hemodialysis patients aged 65 years and above in seven hospital-based hemodialysis centers in Taiwan. The data on anthropometry, laboratory, and 3-day dietary intake was examined. The skeletal muscle mass (SMM) was measured by the bioelectrical impedance analysis; the SMM was adjusted by height or weight as SMMHt2 (kg/m2) and SMMWt (%). Muscle function was defined as handgrip strength (HGS) (kg) measured by handgrip dynamometer. Statistical analyses were conducted using simple regression and multivariable stepwise regression analysis. RESULTS: In the total sample, 74.6 % of hemodialysis patients were hyperhomocysteinemia (≥ 15 µmol/L). The means of SMMHt2, SMMWt, arm lean mass, hand grip strength, and muscle quality were 8.7 ± 1.2, 37.7 ± 5.6, 1.7 ± 0.5, 21.1 ± 7.4, and 10.0 ± 3.0, respectively. The multivariable stepwise regression analysis showed that homocysteinemia level was significantly inversely associated with SMMWt (B-coeff. = -0.03, p = 0.02) in hemodialysis patients above 65 years old, but not with muscle function. CONCLUSIONS: Hyperhomocysteinemia is common and associated with decreased muscle mass in the elderly hemodialysis patients. Future studies are suggested to explore the impact of the homocysteine-lowering therapy on muscle decline.

Insulin Resistance and Cardiovascular Risks in Different Groups of Hemodialysis Patients: A Multicenter Study.

BACKGROUND: To investigate the association between insulin resistance (IR) and cardiovascular disease (CVD) risks among hemodialysis patients. METHODS: We conducted a cross-sectional study between 2013 and 2017, on 384 hemodialysis patients from seven hospital-based-dialysis centers. HOMA-IR is classified according to median value. The CVD risks were defined by the K/DOQI Guidelines. Logistic regression analysis was used. RESULTS: Patients' age was 60.9 ± 11.8, 58.1% men, and 40.3% overweight/obese. The median of HOMA-IR was 5.4, 82.8% high systolic blood pressure, and 85.7% hyperhomocysteinemia. In multivariate analysis, IR was significantly associated with higher odds of low high-density lipoprotein cholesterol, high triglyceride, and impaired fasting glucose in groups of normal weight, overweight/obese, nondiabetes, diabetes, and overall sample. IR linked with elevated high-sensitive C-reactive protein in normal weight patients (odd ratio, OR=2.21, 95% confidence interval, 1.16-4.22, p < .05), with hypoalbuminemia in normal weight patients (OR=8.31, 95% CI, 2.35-29.37, p < .01), in nondiabetes patients (OR=6.59, 95% CI, 1.81-23.95, p < .01), and overall sample (OR=3.07, 1.51-6.23, p < .01). CONCLUSIONS: The level of IR and prevalence of CVD risks were high in hemodialysis patients. IR was independently associated with CVD risks.

Adaptation and Validation of Alternative Healthy Eating Index in Hemodialysis Patients (AHEI-HD) and Its Association with all-Cause Mortality: A Multi-Center Follow-Up Study.

A valid diet quality assessment scale has not been investigated in hemodialysis patients. We aimed to adapt and validate the alternative healthy eating index in hemodialysis patients (AHEI-HD), and investigate its associations with all-cause mortality. A prospective study was conducted on 370 hemodialysis patients from seven hospital-based dialysis centers. Dietary data (using three independent 24-hour dietary records), clinical and laboratory parameters were collected. The construct and criterion validity of original AHEI-2010 with 11 items and the AHEI-HD with 16 items were examined. Both scales showed reasonable item-scale correlations and satisfactory discriminant validity. The AHEI-HD demonstrated a weaker correlation with energy intake compared with AHEI-2010. Principle component analysis yielded the plateau scree plot line in AHEI-HD but not in AHEI-2010. In comparison with patients in lowest diet quality (tertile 1), those in highest diet quality (tertile 3) had significantly lower risk for death, with a hazard ratio (HR) and 95% confidence intervals (95%CI) of HR: 0.40; 95%CI: 0.18 - 0.90; p = 0.028, as measured by AHEI-2010, and HR: 0.37; 95%CI: 0.17-0.82; p = 0.014 as measured by AHEI-HD, respectively. In conclusion, AHEI-HD was shown to have greater advantages than AHEI-2010. AHEI-HD was suggested for assessments of diet quality in hemodialysis patients.

Impact of Percent Body Fat on All-Cause Mortality among Adequate Dialysis Patients with and without Insulin Resistance: A Multi-Center Prospective Cohort Study.

The association between body fat and mortality in hemodialysis patients remains controversial. We examined the effect of percent body fat (PBF) on all-cause mortality among adequate hemodialysis patients with and without insulin resistance (IR). A prospective cohort study was conducted on 365 adequate hemodialysis patients (equilibrated Kt/V ≥ 1.2) from seven hospitals. Patients' characteristics and clinical and biochemical parameters were assessed at baseline between September 2013 and April 2017. Patients were followed up for all-cause mortality until April 2018. The median value of homeostatic model assessment (HOMA-IR) was used to classify IR. Cox proportional hazard models were utilized to examine predictors of all-cause mortality. During 1.4 (1.0-3.2) years of follow-up, 46 patients died. In patients with IR (HOMA-IR ≥ 5.18), PBF was significantly higher in the survival group than in the death group (31.3 ± 9.0 vs. 25.4 ± 8.2, p = 0.005). After controlling for confounding factors, PBF was significantly associated with lower risk for all-cause mortality in patients with IR (hazard ratio, 0.94; 95% confidence interval, 0.89-1.00; p = 0.033). The association was not observed in patients without IR. In conclusion, percent body fat shows a protective effect on survival in hemodialysis patients with IR.

Mid-arm circumference, body fat, nutritional and inflammatory biomarkers, blood glucose, dialysis adequacy influence all-cause mortality in hemodialysis patients: A prospective cohort study.

Hemodialysis patients are at the high risk for morbidity and mortality. Evaluation and management of body composition and biochemical values are important to improve dialysis outcomes. We aimed to examine the effects of the mid-arm circumference, body fat, nutritional and inflammatory biomarkers, blood glucose, and dialysis adequacy on the mortality.A prospective cohort study was conducted on 375 patients from 7 hospital-based dialysis centers. At baseline between September 2013 and April 2017, we assessed patients' characteristics using chart review, body composition using the bioelectrical impedance analysis, and biochemical parameters using available laboratory tests. Patients were followed-up for all-cause mortality until April 2018. Kaplan-Meier Curves with Log-rank test, and Cox proportional hazards models were used to analyze the effects of assessed factors on the mortality.During the median of follow-up time of 1.4 (1.0-3.2) years, 47 (12.5%) patients died. In the multivariate analysis, mid-arm circumference (hazard ratio, HR, 0.90; 95% confidence interval, 95%CI, 0.82-0.99; P = .036), body fat mass (HR, 0.95; 95%CI, 0.91-1.00; P = .031), percent body fat (HR, 0.96; 95%CI, 0.92-0.99; P = .024), serum creatinine (HR, 0.81; 95%CI, 0.68-0.96; P = .015), and eKt/V (HR, 0.07; 95%CI, 0.01-0.33; P = .001) reduced the mortality risk. Inflammation (HR, 2.90; 95%CI, 1.59-5.27; P < .001), hyperglycemia (HR, 2.16; 95%CI, 1.06-4.40; P = .033), and low serum uric acid (HR, 2.22; 95%CI, 1.15-4.31; P = .018) increased the death risk.In hemodialysis patients, the higher values of the mid-arm circumference, body fat, serum creatinine, uric acid, and dialysis adequacy were associated with lower mortality, whereas, inflammation and hyperglycemia associated with higher mortality.

Inadequate dietary energy intake associates with higher prevalence of metabolic syndrome in different groups of hemodialysis patients: a clinical observational study in multiple dialysis centers.

BACKGROUND: Metabolic syndrome (MetS) has been established as a risk for cardiovascular diseases and mortality in hemodialysis patients. Energy intake (EI) is an important nutritional therapy for preventing MetS. We examined the association of self-reported dietary EI with metabolic abnormalities and MetS among hemodialysis patients. METHODS: A cross-sectional study design was carried out from September 2013 to April 2017 in seven hemodialysis centers. Data were collected from 228 hemodialysis patients with acceptable EI report, 20 years old and above, underwent three hemodialysis sessions a week for at least past 3 months. Dietary EI was evaluated by a three-day dietary record, and confirmed by 24-h dietary recall. Body compositions were measured by bioelectrical impedance analysis. Biochemical data were analyzed using standard laboratory tests. The cut-off values of daily EI were 30 kcal/kg, and 35 kcal/kg for age ≥ 60 years and < 60 years, respectively. MetS was defined by the American Association of Clinical Endocrinologists (AACE-MetS), and Harmonizing Metabolic Syndrome (HMetS). Logistic regression models were utilized for examining the association between EI and MetS. Age, gender, physical activity, hemodialysis vintage, Charlson comorbidity index, high sensitive C-reactive protein, and interdialytic weight gains were adjusted in the multivariate analysis. RESULTS: The prevalence of inadequate EI, AACE-MetS, and HMetS were 60.5%, 63.2%, and 53.9%, respectively. Inadequate EI was related to higher proportion of metabolic abnormalities and MetS (p <  0.05). Results of the multivariate analysis shows that inadequate EI was significantly linked with higher prevalence of impaired fasting glucose (OR = 2.42, p <  0.01), overweight/obese (OR = 6.70, p <  0.001), elevated waist circumference (OR = 8.17, p <  0.001), AACE-MetS (OR = 2.26, p <  0.01), and HMetS (OR = 3.52, p <  0.01). In subgroup anslysis, inadequate EI strongly associated with AACE-MetS in groups of non-hypertension (OR = 4.09, p = 0.004), and non-cardiovascular diseases (OR = 2.59, p = 0.012), and with HMetS in all sub-groups of hypertension (OR = 2.59~ 5.33, p <  0.05), diabetic group (OR = 8.33, p = 0.003), and non-cardiovascular diseases (OR = 3.79, p <  0.001). CONCLUSIONS: Inadequate EI and MetS prevalence was high. Energy intake strongly determined MetS in different groups of hemodialysis patients.