Diabetic neuropathy (DN) is a prevalent complication of Type 2 Diabetes Mellitus (T2DM) with a major impact on the health of the affected patient. We hypothesized that mediated by the dysfunctionalities associated with DN’s three major components: sensitive (lack of motion associated sensory), motor (impairments in movement coordination) and autonomic (the presence of postural hypotension), the presence of DN may impair the balance in the affected patients. Our study’s main aim is to evaluate the possible association between the presence and severity of DN and both the balance impairment and the risk of falls in patients with T2DM. In this cross-sectional study we enrolled, according to a consecutive-case population-based setting 198 patients with T2DM. The presence and severity of DN was evaluated using the Michigan Neuropathy Screening Instrument, a tool which allows both diagnosing and severity staging of DN. The balance impairment and the risk of falls were evaluated using four validated and standardized tools: Berg Balance Scale (BBS), Timed-up and Go test (TUG), Single Leg Stand test (SLS) and Fall Efficacy Scale (FES-I). The presence of DN was associated with significant decreases in the BBS score (40.5 vs. 43.7 points; p<0.001) and SLS time (9.3 vs. 10.3 seconds; p = 0.003) respectively increases in TUG time (8.9 vs. 7.6 seconds; p = 0.002) and FES-I score (38 vs. 33 points; p = 0.034). The MNSI score was reverse and significantly correlated with both BBS score (Spearman’s r = -0.479; p<0.001) and SLS time (Spearman’s r = -0.169; p = 0.017). In the multivariate regression model, we observed that patient’s age, DN severity and depression’s symptoms acted as independent, significant predictors for the risk of falls in patients with T2DM. The presence of DN in patients with DM is associated with impaired balance and with a consecutively increase in the risk of falls.

The present study aimed to assess the phenolic content of eight ethanolic propolis samples (P1–P8) harvested from different regions of Western Romania and their antioxidant activity. The mean value of total phenolic content was 214 ± 48 mg gallic acid equivalents (GAE)/g propolis. All extracts contained kaempferol (514.02 ± 114.80 μg/mL), quercetin (124.64 ± 95.86 μg/mL), rosmarinic acid (58.03 ± 20.08 μg/mL), and resveratrol (48.59 ± 59.52 μg/mL) assessed by LC-MS. The antioxidant activity was evaluated using 2 methods: (i) DPPH (2,2-diphenyl-1-picrylhydrazyl) assay using ascorbic acid as standard antioxidant and (ii) FOX (Ferrous iron xylenol orange OXidation) assay using catalase as hydrogen peroxide (H₂O₂) scavenger. The DPPH radical scavenging activity was determined for all samples applied in 6 concentrations (10, 5, 3, 1.5, 0.5 and 0.3 mg/mL). IC₅₀ varied from 0.0700 to 0.9320 mg/mL (IC₅₀ of ascorbic acid = 0.0757 mg/mL). The % of H₂O₂ inhibition in FOX assay was assessed for P1, P2, P3, P4 and P8 applied in 2 concentrations (5 and 0.5 mg/mL). A significant H₂O₂% inhibition was obtained for these samples for the lowest concentration. We firstly report the presence of resveratrol as bioactive compound in Western Romanian propolis. The principal component analysis revealed clustering of the propolis samples according to the polyphenolic profile similarity.

Over recent decades, a dramatic increase in infections caused by multidrug-resistant pathogens has been observed worldwide. The aim of the present study was to investigate the relationship between local resistance bacterial patterns and antibiotic consumption in an intensive care unit in a Romanian university hospital. A prospective study was conducted between 1st January 2012 and 31st December 2013. Data covering the consumption of antibacterial drugs and the incidence density for the main resistance phenotypes was collected on a monthly basis, and this data was aggregated quarterly. The relationship between the antibiotic consumption and resistance was investigated using cross-correlation, and four regression models were constructed, using the SPSS version 20.0 (IBM, Chicago, IL) and the R version 3.2.3 packages. During the period studied, the incidence of combined-resistant and carbapenem-resistant P. aeruginosa strains increased significantly [(gradient = 0.78, R2 = 0.707, p = 0.009) (gradient = 0.74, R2 = 0.666, p = 0.013) respectively], mirroring the increase in consumption of β-lactam antibiotics with β-lactamase inhibitors (piperacillin/tazobactam) and carbapenems (meropenem) [(gradient = 10.91, R2 = 0.698, p = 0.010) and (gradient = 14.63, R2 = 0.753, p = 0.005) respectively]. The highest cross-correlation coefficients for zero time lags were found between combined-resistant vs. penicillins consumption and carbapenem-resistant P. aeruginosa strains vs. carbapenems consumption (0.876 and 0.928, respectively). The best model describing the relation between combined-resistant P. aeruginosa strains and penicillins consumption during a given quarter incorporates both the consumption and the incidence of combined-resistant strains in the hospital department during the previous quarter (multiple R2 = 0.953, p = 0.017). The best model for explaining the carbapenem resistance of P. aeruginosa strains based on meropenem consumption during a given quarter proved to be the adjusted model which takes into consideration both previous consumption and incidence density of strains during the previous quarter (Multiple R2 = 0.921, p = 0.037). The cross-correlation coefficients and the fitted regression models provide additional evidence that resistance during the a given quarter depends not only on the consumption of antibacterial chemotherapeutic drugs in both that quarter and the previous one, but also on the incidence of resistant strains circulating during the previous quarter.

The purpose of this study was to compare the effect of tooth related and patient related factors on the success of non-surgical and surgical periodontal therapy. In 41 patients (22 female) with untreated and/or recurrent periodontitis, no therapy, scaling and root planing (SRP), or access flap (AF) were assigned according to probing pocket depth (PPD). PPD and vertical relative attachment level (RAL-V) were obtained initially, 3 and 6 months after therapy. Baseline data were compared according to therapy, jaw, tooth type, and site. Factors influencing clinical parameters were identified using multilevel analyses. Baseline PPDs were deeper interproximally, in the maxilla and at premolars compared to buccal/oral sites, mandibular, and anterior teeth. At 6 months, PPD reduction and RAL-V gain were significantly greater at sites receiving SRP and AF as compared to untreated sites (p < 0.001). PPD reduction and RAL-V gain were significantly less (p < 0.005) in smokers as compared to nosmokers and at interproximal sites (p < 0.0001) as compared to buccal/oral sites. RAL-V gain was less in aggressive periodontitis, and PPD reduction was less in the maxilla (p < 0.001). In sites with greater bone loss and infrabony defects, a poorer response was observed regarding RAL-V gain or PPD reduction, respectively. The conclusions of the study are the following: (1) Nonsurgical and surgical periodontal therapies are effective in single-rooted teeth; (2) severe interproximal bone loss and infrabony defects deteriorate clinical results; and (3) there seem to be more defect-associated (tooth, site) factors influencing treatment outcome than patient-associated factors.

In patients with type 1 diabetes mellitus (T1DM), glucose dynamics are influenced by insulin reactions, diet, lifestyle, etc., and characterized by instability and nonlinearity. With the objective of a dependable decision support system for T1DM self-management, we aim to model glucose dynamics using their nonlinear chaotic properties. A group of patients was monitored via continuous glucose monitoring (CGM) sensors for several days under free-living conditions. We assessed the glycemic variability (GV) and chaotic properties of each time series. Time series were subsequently transformed into the phase-space and individual autoregressive (AR) models were applied to predict glucose values over 30-minute and 60-minute prediction horizons (PH). The logistic smooth transition AR (LSTAR) model provided the best prediction accuracy for patients with high GV. For a PH of 30 minutes, the average values of root mean squared error (RMSE) and mean absolute error (MAE) for the LSTAR model in the case of patients in the hypoglycemia range were 5.83 ( ± 1.95) mg/dL and 5.18 ( ± 1.64) mg/dL, respectively. For a PH of 60 minutes, the average values of RMSE and MAE were 7.43 ( ± 1.87) mg/dL and 6.54 ( ± 1.6) mg/dL, respectively. Without the burden of measuring exogenous information, nonlinear regime-switching AR models provided fast and accurate results for glucose prediction.

Purpose: To evaluate the impact of several factors on the patient’s perception on quality of life in a group of patients with type 2 diabetes mellitus (T2DM). Patients and methods: In this cross-sectional study, 198 patients with T2DM were enrolled according to a consecutive-case population-based study design. In all participants, the perception on the quality of life was measured using the quality of life index – diabetes version III proposed by Ferrans and Powers. We evaluated the impact of several anthropometric and diabetes-related (ie, diabetes history and quality of glycemic control) factors on the patient’s perception on the quality of life. Results: The presence of diabetes complications was associated with a decreased quality of life: retinopathy (1 vs 5 points; P<0.001), chronic kidney disease (-1 vs 5 points; P<0.001), and neuropathy (-1 vs 5 points; P<0.001). A significant reverse correlation was found between the patient’s quality of life and depression’s severity (Spearman’s r=-0.345; P<0.001) and body mass index (Spearman’s r=-0.158; P=0.026). A positive association between the quality of life and the quality of diabetes-related self-care activities was found (Spearman’s r=0.338; P<0.001). No significant association was found between the patient’s quality of life and the quality of glycemic control, diabetes duration, age, gender, or smoking status. Conclusion: To improve the patient’s quality of life, special care should be given to the modifiable diabetes-related factors: the prevention and treatment of diabetes complications, treatment of depression, and weight loss in obese and overweight patients.