Nanostructured silver fabric as a free-standing NanoZyme for colorimetric detection of glucose in urine.

Enzyme-mimicking catalytic nanoparticles, more commonly known as NanoZymes, have been at the forefront for the development of new sensing platforms for the detection of a range of molecules. Although solution-based NanoZymes have shown promise in glucose detection, the ability to immobilize NanoZymes on highly absorbent surfaces, particularly on free-standing substrates that can be feasibly exposed and removed from the reaction medium, can offer significant benefits for a range of biosensing and catalysis applications. This work, for the first time, shows the ability of Ag nanoparticles embedded within the 3D matrix of a cotton fabric to act as a free-standing peroxidase-mimic NanoZyme for the rapid detection of glucose in complex biological fluids such as urine. The use of cotton fabric as a template not only allows high number of catalytically active sites to participate in the enzyme-mimic catalytic reaction, the absorbent property of the cotton fibres also helps in rapid absorption of biological molecules such as glucose during the sensing event. This, in turn, brings the target molecule of interest in close proximity of the NanoZyme catalyst enabling accurate detection of glucose in urine. Additionally, the ability to extract the free-standing cotton fabric-supported NanoZyme following the reaction overcomes the issue of potential interference from colloidal nanoparticles during the assay. Based on these unique characteristics, nanostructured silver fabrics offer remarkable promise for the detection of glucose and other biomolecules in complex biological and environmental fluids.

Predicting long-term survival after coronary artery bypass graft surgery.

OBJECTIVES: To develop a model for predicting long-term survival following coronary artery bypass graft surgery. METHODS: This study included 46 573 patients from the Australian and New Zealand Society of Cardiac and Thoracic Surgeons (ANZCTS) registry, who underwent isolated coronary artery bypass graft surgery between 2001 and 2014. Data were randomly split into development (23 282) and validation (23 291) samples. Cox regression models were fitted separately, using the important preoperative variables, for 4 'time intervals' (31-90 days, 91-365 days, 1-3 years and >3 years), with optimal predictors selected using the bootstrap bagging technique. Model performance was assessed both in validation data and in combined data (development and validation samples). Coefficients of all 4 final models were estimated on the combined data adjusting for hospital-level clustering. RESULTS: The Kaplan-Meier mortality rates estimated in the sample were 1.7% at 90 days, 2.8% at 1 year, 4.4% at 2 years and 6.1% at 3 years. Age, peripheral vascular disease, respiratory disease, reduced ejection fraction, renal dysfunction, arrhythmia, diabetes, hypercholesterolaemia, cerebrovascular disease, hypertension, congestive heart failure, steroid use and smoking were included in all 4 models. However, their magnitude of effect varied across the time intervals. Harrell's C-statistics was 0.83, 0.78, 0.75 and 0.74 for 31-90 days, 91-365 days, 1-3 years and >3 years models, respectively. Models showed excellent discrimination and calibration in validation data. CONCLUSIONS: Models were developed for predicting long-term survival at 4 time intervals after isolated coronary artery bypass graft surgery. These models can be used in conjunction with the existing 30-day mortality prediction model.

Lower muscle tissue is associated with higher pulse wave velocity: A systematic review and meta-analysis of observational study data.

Muscle loss and arterial stiffness share common risk factors and are commonly seen in the elderly. We aimed to synthesise the existing literature on studies that have examined this association. We searched electronic databases for studies reporting correlations or associations between a measure of muscle tissue and a measure of arterial stiffness. Meta-analysis was conducted using Fisher's Z-transformed r-correlation (rZ ) values. Pooled weighted rZ and 95% confidence intervals were calculated in an inverse-variance, random-effects model. Heterogeneity was assessed by the inconsistency index (I2 ). Study quality was assessed on a checklist using items from validated quality appraisal guidelines. 1195 records identified, 21 satisfied our inclusion criteria totalling 8558 participants with mean age 52±4 years (range 23-74). Most studies reported an inverse relationship between muscle tissue and arterial stiffness. Eight studies had data eligible for meta-analysis. Muscle tissue was inversely associated with pulse wave velocity in healthy individuals [rZ =-.15 (95% CI -0.24, -0.07); P=.0006; I2 =85%; n=3577] and in any population [rZ =-.18 (-0.26, -0.10); P<.0001; I2 =81%; n=3930]. In a leave-one-out sensitivity analysis, the results remained unchanged. Lower muscle tissue was associated with arterial stiffness. Studies were limited by cross-sectional design. Cardiovascular risk monitoring may be strengthened by screening for low muscle mass and maintaining muscle mass may be a primary prevention strategy.

When is 'Urgent' Really Urgent and Does it Matter? Misclassification of Procedural Status and Implications for Risk Assessment in Cardiac Surgery.

BACKGROUND: Many patients classified as "urgent" in Australia New Zealand Society of Cardiac and Thoracic Surgeons (ANZSCTS) registry contradict the prescribed definition (surgery within 72hours of angiogram or unplanned admission). The aim was to examine the impacts of this misclassification on the prediction of 30-day mortality following cardiac surgery. METHODS: The 'reported clinical status' was compared with a 'corrected clinical status' following reclassification based on the standard definition calculated from raw data. Observed-to-predicted risk ratios (OPRs) of 30-day mortality were calculated for the model using reported status and corrected status and compared. A Bland-Altman plot was generated to examine the level of agreement between the two OPRs. RESULTS: Of 18496 cases reported as urgent, 49.9% were operated after 72hours, leading to misclassification of 14.6% in the registry. Misclassified patients had significantly higher mortality (3.5%) than true urgent patients (2.9%). Underweight (OR:1.6,CI:1.2-2.1), dialysis (OR:1.4,CI:1.1-1.7), endocarditis (OR:2.1,CI:1.7-2.5), shock (OR:1.6,CI:1.3-2.0) and poor ejection fraction (OR:1.2,CI:1.1-1.4) were significant predictors of misclassification. Bland- Altman plot demonstrates significant disagreement between two risk estimates (P<0.001). Misclassification results in overestimation of risk by 9.1%. Observed-to-predicted risk increased with corrected definition (0.8975 vs 0.9875), suggesting poorer calibration with reported status. CONCLUSIONS: In the ANZSCTS database, misclassification prevalence is 14.6%. Misclassification compromises the discrimination capacity and calibration of the model and results in overestimation of mortality risk.

Pattern and predictors of dyslipidemia in patients with type 2 diabetes mellitus.

Dyslipidemia is a major risk factor for macro-vascular complications in patients with type 2 diabetes mellitus (T2DM). Present study explored pattern and predictors of dyslipidemia in Bangladeshi T2DM patients. The cross-sectional study is conducted among 366 consecutive eligible T2DM patients aged >30 years, BIRDEM diabetic hospital, during July-to-December 2010. Physical examination, diabetic profile, lipid profile and serum createnine was performed. Adjusted odds ratio and confidence limit were generated through binary logistic regression. Most frequent form (59.3%) of dyslipidemia is low HDL. Duration of T2DM is significantly correlated with TC (P<0.05), HDL (P<0.05) and LDL (P<0.05) in both male and female. Glycemic control in terms of HbA1c >7% appeared as predictor of dyslipidemia (P<0.01). Duration T2DM is associated with increased risk of having higher TC (P<0.05), LDL (P<0.05) and lower HDL (P<0.01) and does not seem to affect triglyceride (P>0.05). T2DM with comorbid hypertension seems to predict hyper tri-glyceridemia and lower HDL. Both TC-HDL ratio and LDL-HDL ratio appeared as good predictor of all four parameters of dyslipidemia (P<0.01). The characteristic features of diabetic dyslipidemia are low HDL, high triglyceride and LDL cholesterol level. Low HDL level is the most frequent type of abnormality. Poor glycemic control, prolonged duration, coexisting hypertension predicts dyslipidemia in T2DM.

Risk factors of diabetic retinopathy in Bangladeshi type 2 diabetic patients.

AIMS: To determine the risk factors associated with diabetic retinopathy (DR) in Bangladeshi type 2 diabetic subjects. METHODS: A cohort of 977 type-2 diabetic patients was recruited retrospectively based on hospital records in 2008, who were naïve type-2 diabetes during 1993. Data on diabetes and lipid profile with serum creatinine and biophysical measures were obtained at baseline, 5, 10 and 15 years. DR was diagnosed by retinal color photography. Generalized linear models were used to assess the associations of clinical, biochemical and anthropometric variables with retinopathy at three follow-up. Cumulative exposures were determined based on average exposure to individual attribute. IRR and 95% CI were generated through Poisson regression model, adjusting for age-at-diagnosis of diabetes, baseline BMI, end-line waist-to-hip ratio and present physical activity status. RESULTS: DR patients had significantly poorer glycemic control at all three follow-ups. Age, residence, physical activity, serum creatinine and hypertension appeared as independent risk factors for DR in all three follow-up points. Poisson regression model identified glucose deregulation (IRR 1.8; CI 1.5-2.1), hypertension (IRR 1.5; CI 1.2-1.8) and raised serum creatinine (IRR 1.9; CI 1.5-2.3) as significant predictors for DR adjusted for possible confounders. Work related moderate-to-heavy physical activity (IRR 0.2; CI 0.1-0.3) appeared as protective. CONCLUSIONS: Along with poor glycemic control, hypertension, nephropathy are independent risk factor retinopathy.