Plasmapheresis for hypertriglyceridemia: The association between blood viscosity and triglyceride clearance rate.

OBJECTIVES: Several factors in double filtration plasmapheresis (DFPP) were associated with triglyceride (TG) clearance rate. This study examines whether baseline whole blood viscosity was a predictor for efficient TG removal. METHODS: Adult subjects who receiving DFPP for hyperlipidemia in Taoyuan General Hospital from January 2015 to March 2018 were classified into efficient and inefficient TG removal according to TG removal rate ≥50% vs <50%. TG removal rate was defined as following formula: (pre-apheresis TG- post-apheresis TG)/pre-apheresis TG. Whole blood viscosity (WBV) was estimated by following equation: WBV = 0.12 × hematocrit +0.17 × (total protein -2.07). Univariate linear regression was used to assess the association between TG removal rate and WBV. Odds ratios (ORs) and 95% confidence interval (95%CI) for associations between variables and efficient TG removal were evaluated by logistic regression model to including univariate and multivariate adjustment. RESULTS: From a total of 66 subjects receiving DFPP, 37 subjects reached efficient TG removal. The difference in pre-apheresis TG levels, hematocrit, and WBV between efficient vs. inefficient TG removal groups was 4.1 vs 6.7 mmol/L; 43.1% vs 39.5%; and 6.0cP vs 5.cP (Ps <0.05). After multivariate adjustment, WBC was a significant predictor for efficient TG removal (ORs and 95% CI were 3.192 (1.300-7.838), P < 0.05). The correlation between WBV and extraction of TG was significant (r = -0.255, P = 0.039). CONCLUSION: Hyperviscosity reduced the efficiency of TG removal in those receiving DFPP.

The association between serum testosterone and mortality among elderly men on hemodialysis.

OBJECTIVES: This study examines the associations between total testosterone levels and dialysis mortality. METHODS: Elderly men who initiate hemodialysis in Taoyuan General Hospital from January 2012 to June 2017 were enrolled. We reviewed clinical characteristics and biochemical data from start of dialysis and followed over a 5-year period after dialysis. Body composition parameters were assessed 3-6 months after dialysis. Skeletal muscle mass index (SMMI) was defined by skeletal muscle mass divided by squared height. We defined those with lowest tertile of testosterone values as low testosterone group. Adjusted hazard ratios (aHRs) and 95% confidence interval (95% CI) for mortality and cumulative survival curves were evaluated by Cox hazards model and Kaplan-Meier method. The discriminative power of SMMI and testosterone levels was calculated according to the area under the curve and the receiver operating characteristic curve (AUROC). RESULTS: From a total of 137 elderly hemodialysis patients, the range of lowest, middle, and highest tertile of testosterone values was <6.25 nmol/L, 6.25-10.5 nmol/L, and >10.5 nmol/L. After multivariate adjustment other than SMMI, total testosterone levels at baseline were a significant predictor for mortality aHR(95% CI): 0.79 (0.70-0.91). The unadjusted and adjusted c-statistics of SMMI vs testosterone values to predict overall were 770 (0.688-0.852) vs 0.779 (0.691-0.866) and 855 (0.812-0.886) vs 0.812 (0.744-0.856) (Ps < .05), whereas the capacity of c-statistics was similar (χ2  = 0.143 and 2.709, Ps > .05). CONCLUSIONS: Total testosterone value was a predictor for mortality. It was noninferior to SMMI in predicting dialysis mortality.

Association between obesity with low muscle mass and dialysis mortality.

BACKGROUND/AIM: To examine the association between body composition and dialysis mortality. METHODS: Adult patients who underwent haemodialysis in Taoyuan General Hospital from 2012 to 2016 were enrolled. We reviewed their baseline characteristics and followed up their treatment over 5 years after dialysis. Patients with body mass index >25 kg/m2 were defined as obese. High or low muscle mass were classified by skeletal muscle mass index (SMMI) based on consensus from Chinese population. All age-matched subjects were classified into four groups: (A) optimal; (B) obesity; (C) low muscle mass; and (D) obesity with low muscle mass. Adjusted hazard ratios for mortality and cumulative survival curves were evaluated by Cox proportional hazard model and Kaplan-Meier method. The discriminative power of SMMI was calculated according to the area under the curve and the receiver operating characteristic curve. RESULTS: From a total of 176 age-matched patients, the incidence rates of mortality for different groups were 3.7, 7.8, 10.3 and 16.5 per 1000 person-months. After adjusting for continuous variables, SMMI was independently associated with mortality. The difference between groups A and D was more significant in women than in men after multivariate adjustment (adjusted hazard ratios: 7.465 vs 1.682) (P = 0.035 and 0.553). The discriminative power of SMMI to predict 5-year mortality was 0.700 for men and 0.750 for women, and the best cut-off values were 11.1 and 8.4 kg/m2 CONCLUSIONS: Low muscle mass was associated with dialysis mortality. Obesity with low muscle mass was a predictor for dialysis mortality in women.

Associations among Serum Beta 2 Microglobulin, Malnutrition, Inflammation, and Advanced Cardiovascular Event in Patients with Chronic Kidney Disease.

OBJECTIVES: This study examines the associations among serum ß2 microglobulin (B2M), malnutrition, inflammation, and atherosclerosis (MIA) in those with chronic kidney disease (CKD). METHODS: CKD patients who were followed in Taoyuan General Hospital from 2009 to 2015 were enrolled. Demographic and biochemical data, including B2M and C-reactive protein (CRP) were reviewed. The participants were stratified according to B2M tertiles. Adjusted hazard ratios (AHRs) and cumulative survival curves for death and MIA syndrome were evaluated by Cox hazard model and Kaplan-Meier method. We also calculated the area under the curve for the receiver operating characteristic curve (AUROC). RESULTS: From a total of 312 CKD patients, mean follow-up time was 39.7 months. Compared to those with lowest tertile of B2M, the highest tertile group had lower serum albumin, hemoglobin, and estimated glomerular filtration rate. After multivariate adjustment, the associations among tertiles of B2M, death or dialysis, cardiovascular events (CVEs), and MIA syndrome remained significant. The AHRs for the highest tertile group in death or dialysis, CVEs, and MIA syndrome were 25.91 and 65.84 and 152.50(all Ps <0.05).The AUROC for B2M in death or dialysis, CVEs, and MIA syndrome were greater than that for creatinine. The best cut-off value of B2M for predicting death or dialysis, CVEs, and MIA syndrome were 5.39 mg/dL(sensitivity: 67.1%, specificity 62.5%), 4.21 mg/dL(sensitivity: 85.1%, specificity 52.1%), and 5.40 mg/dL(sensitivity: 79.7%, specificity 64.1%). CONCLUSIONS: In those with CKD, serum B2M was more sensitive than creatinine in predicting CVEs and MIA syndrome.

Incidence and mortality of postoperative acute kidney injury in non-dialysis patients: comparison between the AKIN and KDIGO criteria.

OBJECTIVES: This retrospective study determines whether the kidney disease: improving global outcomes (KDIGO) criteria are superior to acute kidney injury network (AKIN) criteria in detecting non-dialysis AKI events and predicting mortality in chronic kidney disease (CKD) patients after surgery. METHODS: Surgical patients who were admitted to the intensive care unit were enrolled. Non-dialysis AKI cases were defined using either KDIGO or AKIN creatinine criteria and stratified by CKD stages. The adjusted hazard ratios (AHRs) for in-hospital mortality are compared to those without AKI. The cumulative survival curves and the predictability for mortality are accessed by Kaplan-Meier method and calculating the area under the curve (AUC) for the receiver operating characteristic (ROC) curve, respectively. RESULTS: From a total of 826 postoperative patients, the overall in-hospital mortality rate was 11.6% (96 cases) and that for AKI according to KDIGO and AKIN criteria was 30.0% (248 cases) and 31.0% (256 cases). The cumulative survival curve stratified by CKD and AKI stages were comparable between KDIGO and AKIN criteria. The discriminative power for mortality stratified by CKD stages for KDIGO and AKIN criteria are as followed: all subjects: 0.678 versus 0.670 (both ps <0.001); non-CKD: 0.800 versus 0.809 (both ps <0.001); early-stage CKD: 0.676 versus 0.676 (both ps <0.001); late-stage CKD: 0.674 versus 0.660 (ps were <0.001 and 0.003). CONCLUSION: The KDIGO criteria are superior to AKIN criteria in predicting mortality after surgery, especially in those with advanced CKD.

Associations among time-average mineral values, mortality and cardiovascular events in hemodialysis patients.

UNLABELLED: Mineral and bone disease (CKD-MBD), disorders of mineral metabolism, is associated with mortality and cardiovascular disease in dialysis patients. However, the associations among time average mineral values (P, Ca and PTH) and clinical outcomes are not well investigated. OBJECTIVES: This study examines the associations among mineral values and clinical outcomes from a single medical center. METHODS: Adult patients who initiate hemodialysis in Taoyuan General Hospital from 2008 to 2013 were enrolled. We examined these associations using baseline and time-average model. The clinical outcomes included mortality, major adverse cardiovascular events (MACE) and cardiovascular events. We also examined the association between achieve K/DOQI guidelines' targets and clinical outcomes. RESULTS: From a total of 284 hemodialysis patients, none of the baseline mineral values is associated with mortality and cardiovascular event, except hyperphosphatemia. Compared to patients achieved K/DOQI guidelines' targets, time average hyperphosphatemia is associated with MACE and first cardiovascular event [the adjusted hazard ratios (AHRs) are 6.343 and 3.278); whereas time average hypercalcemia is associated with MACE marginally (the AHR is 5.964). None of above clinical outcomes is related to hyperparathyroidism. The AHRs for mortality in those who only met PTH targets and none of the mineral value targets are 1.73 and 1.74, whereas the AHRs for cardiovascular events in those who met only Ca, only PTH, and none of the targets are 1.73, 1.81 and 2.54 (all ps < 0.05). CONCLUSION: Time-average phosphate is associated with cardiovascular events after initiation of dialysis. Among mineral values, serum phosphate is still the strongest predictor for mortality and cardiovascular events.

The association between the duration of postoperative acute kidney injury and in-hospital mortality in critically ill patients after non-cardiac surgery: an observational cohort study.

OBJECTIVES: The severity of acute kidney injury (AKI) has been a well-known predictor for in-hospital mortality. Whether AKI duration could predict in-hospital mortality is not clear. This study determines the association between the in-hospital mortality and AKI duration in patients after non-cardiac surgery. MATERIALS AND METHODS: Surgical patients who were admitted to the ICU were enrolled. AKI cases were defined using KDIGO guidelines and categorized according to the tertiles of AKI duration (1st tertile: 2 days, 2nd tertile: 3-6 days and 3rd tertile: 7 days). The adjusted hazard ratios (HRs) for in-hospital mortality are compared to those without AKI. The predictability of mortality is accessed by calculating the area under the curve (AUC) for the receiver operating characteristic (ROC) curve. RESULTS: From a total of 318 postoperative patients, 98 developed AKI (1st tertile: 34 cases, 2nd tertile: 30 cases and 3rd tertile: 34 cases) and 220 had no AKI. The in-hospital mortality rates are 6.8% (non-AKI), 50% (1st tertile), 46.7% (2nd tertile) and 47% (3rd tertile). The HR's for in-hospital mortality are 7.92, 6.68 and 1.68, compared to the non-AKI group (p = 0.006, 0.021 and 0.476). Cumulative in-hospital survival rates are significantly different for the non-AKI group and the AKI groups (p < 0.001). The AUC for AKI duration and stage together (0.804) is higher than that for AKI stage and AKI duration alone (0.803 and 0.777) (both ps < 0.001). CONCLUSION: In addition to severity, the duration of AKI may be a predictor of in-hospital mortality in patients, after non-cardiac surgery.

Association between management of metabolic syndrome and progression of early-stage chronic kidney disease: an observational cohort study.

OBJECTIVES: To analyze the effect of treating metabolic syndrome (MetS) on further kidney function decline in patients with early-stage chronic kidney disease (CKD). METHODS: In a study period of 24 months, 162 patients with early stage CKD were enrolled. Baseline and follow-up data related to the occurrence of MetS and glomerular filtration rate (GFR) were assessed. Subjects were classified into controlled MetS (group 1) and uncontrolled MetS (group 2). Furthermore, they were subdivided into four subgroups: (A) controlled MetS at baseline and at follow-up, (B) uncontrolled MetS at baseline but controlled MetS at follow-up visits, (C) controlled MetS at baseline but uncontrolled MetS at follow-up visits, and (D) uncontrolled MetS at baseline and follow-up visits. RESULTS: Final GFR was lower in group 2 versus group 1 (69.21 ± 20.20 vs. 82.86 ± 22.33 mL/min/1.73 m(2), p <0.001). The presence of MetS had high risk to develop late-stage CKD (HR = 3.279, 95% CI: 1.545-6.958, p = 0.002). Moreover, subgroup D (HR = 2.982, 95% CI: 1.287-6.908, p = 0.011) and the presence of three (p = 0.026) or four (p = 0.049) metabolic components had high risk to develop late-stage CKD. CONCLUSION: Treating MetS slows CKD progression in patients with early-stage of CKD.