Preparation and in Vitro Evaluation of Griseofulvin Microparticles Using Chitosan and Ethyl Cellulose

The present studt preparation and evaluation of microparticles containing Griseofulvlin using chitosan and ethyl cellulose were compared Estimation of the drug encapsulation efficiency of chitosan microparticles an ethyl cellulose microparticles: Different batches containing various concentrations of drug and same concentration of the polymers were prepared and estimated for the amount of drug loaded in each batch. A comparative result revealed that may be a maximum of 30 mg could be incorporated in both polymers. A comparison of the drug binding capacity of the microparticles containing two polymers showed that the drug bound to chitosan was greater than ethyl cellulose. In vitro release studies: The release pattern of the chitosan microparticles revealed a faster release (28.29%) in the first two hours (because of burst release) but ethyl cellulose showed a sustained release through the period. The the results obtained it is evident that microparticles containing Griseofulvin prepared using chitosan exhibited better yield, drug encapsulation and fast release when compared to ethyl cellulose microparticles. The fast release of chitosan microparticle may be due to the chemical cross-linking of the polymer glutaraldehyde

Adjustment of the GRACE score by 2-hour post-load glucose improves prediction of long-term major adverse cardiac events in acute coronary syndrome in patients without known diabetes

Aims Global Registry of Acute Coronary Events (GRACE) risk score (GRS), a powerful predictor of prognosis after ACE, does not include a glucometabolic measure. We investigate whether 2 hour post-load plasma glucose (2h-PG) could improve GRS based prognostic models in ACE patients without known diabetes mellitus (DM). Methods Retrospective cohort study of 1056 ACE survivors without known DM who had fasting (FPG) and 2h-PG measured pre-discharge. Death and non-fatal myocardial infarction (MI) were recorded as major adverse cardiac events (MACE) during follow up. GRS for discharge to 6 months was calculated. Cox proportional-hazards regression was used to identify predictors of event free survival. The predictive value of 2h-PG alone and combined with GRS was estimated using Likelihood ratio test, Akaike's Information criteria, continuous net reclassification improvement (NRI>0) and integrated discrimination improvement (IDI). Results During 40.8 months follow up 235 MACEs (22.3%) occurred, more frequently in the upper 2h-PG quartiles. 2h-PG, but not FPG, adjusted for GRS independently predicted MACE (HR 1.091; 95 % CI 1.043-1.142; p=0.0002). Likelihood ratio test showed that 2h-PG significantly improved the prognostic models including GRS (χ2=20.56, 1 df, p=0.000). Models containing GRS and 2h-PG yielded lowest corrected Akaike's Information criteria, compared to that with only GRS. 2h-PG, when added to GRS, improved net reclassification significantly (NRIe>0 6.4%, NRIne>0 24%, NRI>0 0.176, p = 0.017 at final follow up). 2h-PG, improved integrated discrimination of models containing GRS (IDI of 0.87%, p=0.008 at final follow up). Conclusion Two-hour PG, but not FPG, is an independent predictor of adverse outcome after ACE even after adjusting for the GRS. Two-hour PG, but not FPG, improves the predictability of prognostic models containing GRS

Postload glucose spike but not fasting glucose determines prognosis after myocardial infarction in patients without known or newly diagnosed diabetes

Background: The effect of postload glucose spikes (PGS), the difference between 2 hour post-load plasma glucose (2hPLPG) and fasting plasma glucose (FPG), on post–myocardial infarction (post-MI) prognosis in nondiabetic patients is unexplored. Methods: This is a retrospective cohort analysis of 847 nondiabetic post-MI survivors who underwent a predischarge oral glucose tolerance test (median PGS: 2.4 mmol/L). Patients were divided into the unmatched groups 1 and 2 (PGS ≤ and > 2.4 mmol/L) and the propensity score-matched groups 1M and 2M (355 pairs assembled from the overall cohort), and these groups were compared. Major adverse cardiac events (MACE: death and nonfatal reinfarction) were recorded during follow-up (median: 3.4 years). Event-free survival was compared by the Kaplan-Meier method. Multivariate Cox proportional hazards regression determined the predictors of MACE. C-statistics (change in area under the curve, δAUC), continuous net reclassification improvement (NRI>0), and integrated discrimination improvement (IDI) were used to compare models. Results: The number of MACE was higher in groups 2 (27.3% vs 14.2%,

Two-Hour Post-Load Plasma Glucose, a Biomarker to Improve the GRACE Score in Patients without Known Diabetes

© 2020 S. Karger AG, Basel. All rights reserved. Objective: To assess improvement in predictive performance of Global Registry of Acute Coronary Events risk score (GRS) by addition of a glucose matrix. Methods: 1,056 acute coronary syndrome (ACS) survivors without known diabetes had pre-discharge fasting (FPG) and 2-h post-load plasma glucose (2h-PG) measured. GRS was calculated. Major adverse cardiac events (MACE; death and non-fatal myocardial infarction) were recorded during follow-up. Cox proportional hazard regression predicted event-free survival. Likelihood ratio test, Akaike's information criteria, continuous net reclassification index (NRI 0), and integrated discrimination improvement (IDI) were used to test the additional prognostic value of glycaemic indices over GRS. Results: During a median follow-up of 36.5 months, 211 MACEs (20.0%), 96 deaths (9.1%), and 115 non-fatal re-infarctions (10.9%), occurred. 2h-PG, but not FPG, independently predicted MACE-free survival at all time points (HR 1.08, 95% CI 1.03-1.13, p = 0.002, at 3 years). Risk of MACE increased by 8-11% with every 1 mmol/L rise in 2h-PG. 2h-PG significantly improved the prognostic models containing GRS. Models containing GRS and 2h-PG yielded lowest corrected Akaike's information criteria compared to that with only GRS. 2h-PG, but not FPG, improved NRI0 (NRI0 0.169, p = 0.028 at 3 years) and IDI (IDI of 0.66%, p = 0.018 at 3 years) significantly at all time points during the follow-up. Conclusions: 2h-PG, but not FPG, improves performance of GRS-containing models in predicting post-ACS prognosis in the short to medium term

Two-hour post-challenge glucose is a better predictor of adverse outcome after myocardial infarction than fasting or admission glucose in patients without diabetes

AimsWe evaluate prevalence of new abnormal glucose tolerance (AGT) in post-MI survivors without known diabetes (DM) if guidelines are followed and compare the ability of admission (APG), fasting (FPG) and 2-h post-load plasma glucose (2h-PG) to predict prognosis.MethodsA total of 674 patients were followed up for 4 years for incidence of major adverse cardiovascular events (MACE) of cardiovascular death, non-fatal re-infarction or non-haemorrhagic stroke. Ability of models including APG, FPG and 2h-PG to predict MACE was compared.ResultsOf the total, 93–96% of impaired glucose tolerance and 64–75% of DM would be missed with current guidelines. MACE was higher in the upper quartiles of 2h-PG. When 2h-PG and FPG were included simultaneously in models, only 2h-PG predicted MACE (HR 1.12, CI 1.04–1.20, p = 0.0012), all cause mortality (HR 1.17, CI 1.05–1.30, p = 0.0039), cardiovascular mortality (HR 1.17, CI 1.02–1.33, p = 0.0205) and non-fatal MI (HR 1.10, CI 1.01–1.20, p = 0.0291). Adding 2h-PG significantly improved ability of models including FPG (χ2 = 16.01, df = 1, p = 0.0001) or FPG and APG (χ2 = 17.36, df = 1, p = 0.000) to predict MACE. Model including 2h-PG only had the lowest Akaike’s information criteria and highest Akaike weights suggesting that this was the best in predicting events. Adding 2h-PG to models including FPG or APG with other co-variates yielded continuous net reclassification improvement (NRI) of 0.22 (p = 0.026) and 0.27 (p = 0.005) and categorical NRI of 0.09 (p = 0.032) and 0.12 (p = 0.014), respectively. Adding 2 h-PG to models including only FPG, only APG and both yielded integrated discrimination improvement of 0.012 (p = 0.015), 0.022 (p = 0.001) and 0.013 (p = 0.014), respectively.ConclusionsAGT is under-diagnosed on current guidelines. 2h-PG is a better predictor of prognosis compared to APG and FPG

Investigation on extendable multiport DC–DC boost converter for hybrid renewable energy systems

In this work, the integration of renewable hybrid energy (RHE) resources using extendable multiport DC–DC boost converter is investigated. Three renewable energy sources such as solar photovoltaic (PV) system, wind energy system and fuel cell (FC) are integrated into the grid via this converter and grid-tied inverter. The output voltage of the multiport DC–DC boost converter is controlled using adaptive neuro fuzzy inference system-based controller. The overall system model is developed and tested in the MATLAB simulation software and also implemented in real time. The overall system is tested for different operating conditions such as change in irradiance condition of the solar PV panel, change in wind speed condition of the wind turbine, change in hydrogen pressure conditions of the FC and sudden change in load conditions and corresponding results are measured and analysed. The efficiency of the proposed system is about 98.21%. Finally, experimental results of the proposed model are also presented to examine the suitability of the system