Predictive value of a novel sub-item mortality risk score derived from the Norfolk Quality of Life in Diabetic Neuropathy questionnaire in Romanian participants with diabetes mellitus.

AIMS: To evaluate whether the Norfolk Quality of Life in Diabetic Neuropathy (QOL-DN) questionnaire and the novel Norfolk Mortality Risk Score (NMRS), comprising Norfolk QOL-DN items, can identify 4-year mortality risk in individuals with diabetes. METHODS: Of 21,756 adults completing Norfolk QOL-DN in 2012, two groups of surviving and deceased patients were identified in 2016: Group 1, from a county capital and Group 2, from six small cities. NMRS was calculated in Group 1 using the 2012 scores of Norfolk QOL-DN items that discriminate between deceased and surviving participants (p < 0.05) and was subsequently applied to Group 2. RESULTS: 763 participants were included (Group 1: 481 [450 surviving, 31 deceased]; Group 2: 282 [218 surviving, 64 deceased]). Total Norfolk QOL-DN score was significantly higher (worse) in deceased participants than in survivors in both groups (p ≤ 0.008). Optimal cut-off for the 25-item NMRS was 11.5 in Group 1. Individuals in Groups 1 and 2 with NMRS≥ 11.5 in 2012 had a 4-year mortality risk ratio of 4.24 (95 % confidence interval [CI]: 1.65-10.84) and 2.33 (95 % CI: 1.33-4.07), respectively, corresponding to 8 and 16 additional deaths/100 persons/4 years (p = 0.001). CONCLUSION: Norfolk QOL-DN and NMRS can identify individuals with diabetes at risk of 4-year mortality.

Factors influencing the quality of life over a 4-year period of time in Romanian patients with diabetes mellitus.

AIM: To evaluate the changes in quality of life (QOL), diabetic neuropathy (DN) and amputations over 4 years in patients with diabetes. METHODS: In 2012, 25,000 Romanian-translated Norfolk QOL-DN self-administered questionnaires were distributed during a cross-sectional study. Between March-December 2016, all patients identified from the 2012 cohort and enrolled in this follow-up study completed the Norfolk QOL-DN questionnaire; amputations suffered since 2012 were recorded. The influence of age and duration of diabetes (DD) on delta QOL scores (defined as the differences between 2012 and 2016 scores) and of sex, age, diabetes type, DD and declared DN on amputations was explored using multivariate linear and logistic regression, respectively. RESULTS: The mean (standard deviation) age of the 1865 participants was 60.6 (10.3) years. Mean total QOL-DN score increased from 2012 to 2016 by 4.39% (P = .079). Both DD (b = 0.39, 95% confidence interval [CI] 0.21-0.57, P < .001) and age (b = 0.25, 95% CI 0.13-0.36, P < .001) were significantly correlated with total QOL-DN score. Delta total QOL was higher in patients whose statement about having DN changed since 2012. Over 4 years, 36 patients suffered amputations. Male sex (OR = 3.11, 95% CI 1.46-6.62, P = .003), physical functioning/large-fibre neuropathy subscale score (OR = 1.04, 95% CI 1.001-1.09, P = .047), autonomic neuropathy subscale score (OR = 0.78, 95% CI 0.64-0.94, P = .011) and small-fibre neuropathy subscale score (OR = 1.21, 95% CI 1.05-1.40, P = .007) were significant predictors of amputations. Delta total QOL-DN score was 10 times higher in patients who suffered amputation(s) compared with their amputation-free counterparts. CONCLUSION: QOL deteriorates with age and DD. Norfolk QOL-DN subscale scores can predict amputations.

SERS-based quantification of albuminuria in the normal-to-mildly increased range.

The lack of an accurate point-of-care detection system for microalbuminuria represents an important unmet medical need that contributes to the morbidity and mortality of patients with kidney diseases. In this proof-of-concept study, we used SERS spectroscopy to detect urinary albumin concentrations in the normal-to-mildly increased albuminuria range, a strategy that could be useful for the early diagnosis of renal impairment due to uncontrolled hypertension, cardiovascular disease or diabetes. We analyzed 27 urine samples by SERS, using iodide-modified silver nanoparticles and we could discriminate between groups with high and low albumin concentrations with an overall accuracy of 89%, 93% and 89%, using principal component analysis-linear discriminant analysis and cut-off values of 3, 6 and 10 µg mL-1 for urinary albumin concentrations, respectively. We achieved a detection limit of 3 µg mL-1 for human serum albumin based on the 1002 cm-1 SERS band, attributed to the ring breathing vibration of phenylalanine. Our detection limit is similar to that of the immunoturbidimetric assays and around one order of magnitude below the detection limit of urinary dipsticks used to detect microalbuminuria. We used principal least squares regression for building a spectral model for quantifying albumin. Using an independent prediction set, the R2 and root mean squared error of prediction between predicted and reference values of human serum albumin concentrations were 0.982 and 2.82, respectively. Here, we show that direct SERS spectroscopy has the sensitivity required for detecting clinically relevant concentrations of urinary albumin, a strategy that could be used in the future for the point-of-care screening of microalbuminuria.

Prevalence and predictors of non-alcoholic fatty liver disease as defined by the fatty liver index in a type 2 diabetes population.

BACKGROUND AND AIMS: We aimed to study the prevalence and the predictive factors of non-alcoholic fatty liver disease (NAFLD) defined by the fatty liver index (FLI) in type 2 diabetic patients (T2DM). METHODS: Three hundred and eighty-one T2DM outpatients who regularly attended a Consulting Clinic in Cluj were retrospectivelly included. FLI, a surrogate steatosis biomarker based on body mass index (BMI), waist circumference (WC), triglycerides (TGL) and gammaglutamyl-transferase (GGT) was used to assess NAFLD in all patients. Anthropometric and biochemical parameters were measured. Hepatic steatosis (HS) was evaluated by ultrasonography. RESULTS: NAFLD-FLI (defined as FLI>60) was correlated with HS evaluated by ultrasound (r=0.28; p<0.001). NAFLD-FLI was detected in 79% of T2DM. The prevalence of obesity in NAFLD-FLI patients was 80%. Of the patients with normal alanine aminotransferase (ALAT), 73.8 % had NAFLD. At univariate analysis, NAFLD-FLI was correlated with age (r= -0.14; p=0.007), sex (r=0.20; p<0.001), LDL cholesterol (r=0.12; p=0.032), HDL cholesterol (r = -0.13; p=0.015), ALAT (r=0.20; p<0.001) and ASAT (r=0.19; p<0.001). At multiple regression analysis, sex, ALAT and LDL-cholesterol were independent predictors of NAFLD-FLI. After logistic regression model, ALAT, LDL-cholesterol, HOMA-IR were good independent predictors of NAFLD-FLI. CONCLUSIONS: NAFLD-FLI could be useful to identify NAFLD in T2DM patients. Subjects with T2DM had a high prevalence of NADLD-FLI even with normal ALAT levels. Our findings showed that sex, ALAT, LDL cholesterol and IR were significant and independent factors associated with the presence of NAFLD in T2DM subjects.

Age, abdominal obesity, and glycated hemoglobin are associated with carotid atherosclerosis in type 2 diabetes patients with nonalcoholic fatty liver disease.

AIM: The aim of this study was to evaluate the impact of clinical parameters and indices of body composition on the relation between non-alcoholic fatty liver disease (NAFLD) and carotid intima-media thickness (cIMT), in a type 2 diabetes mellitus population (T2DM). MATERIAL AND METHODS: We retrospectively enrolled 336 T2DM outpatients who regularly attended Regina Maria Clinic in Cluj. Clinical, anthropometric and biochemical parameters were measured. Ultrasonography (US) was used to assess hepatic steatosis (HS) in all patients and cIMT in 146 subjects. Body composition was assessed by bioelectric impedance (BIA, InBody 720) in all patients. RESULTS: cIMT was correlated with age (r=0.25; p=0.004), systolic blood pressure (r=0.18; p=0.041), glycated haemoglobin A1C (HbA1C, r=0.20; p=0.04), and with coronary artery disease (r=0.20; p=0.007). HS did not correlate with cIMT (r=0.04; p=0.64). cIMT was correlated with visceral fatty area (VFA, r=0.18; p=0.014) but not with other indices of body composition. Homeostasis model assessment for insulin resistance (HOMA-IR) was not correlated with cIMT (r=0.17; p=0.086). After multivariate analysis, age, HbA1c, and VFA were good independent predictors of cIMT (r=0.45; p < 0.001). CONCLUSIONS: These results are suggestive that in T2DM patients, fatty liver is not a direct mediator of early carotid atherosclerosis. Our data indicate that visceral fat accumulation and HbA1C are determinant factors of cIMT sugesting that controlling abdominal obesity and hyperglicemia might reduce atherosclerotic disease risk in NAFLD-T2DM subjects.