Major adverse cardiovascular events in patients undergoing percutaneous coronary intervention or coronary artery bypass graft with underlying chronic kidney disease.

OBJECTIVE: To assess early and late outcome in severe chronic kidney disease patients undergoing revascularisation. METHODS: The retrospective ambi-directional cohort study was conducted at Tabba Heart Institute, Karachi, and comprised data from May, 2012, to July,2016, related to severe chronic kidney disease patients with creatinine clearance <30ml/min or end-stage renal disease on haemodialysis who had undergone coronary artery bypass graft / percutaneous coronary intervention. Early outcome was in-hospital major adverse cardiac event, like mortality, stroke and new haemodialysis. Late outcome was major adverse cardiac event, like mortality, stroke, re infarction and re-revascularisation. Data was analysed using Stata 12.1. RESULTS: Of the 228 patients with mean age of 64.2±10.8 years, 109(47.8%) with a maen age of 65.4±11.6 had undergone percutaneous coronary intervention, and 119(52.2%) with a mean age of 64.2±10.8 years had undergone coronary artery bypass graft. Overall mortality was 36(15.8%) patients; 15(13.7%) percutaneous coronary intervention, 21(17.6%)coronary artery bypass graft (p>0.05). Predictors of in-hospital adverse events were coronary artery bypass graft and cardiogenic shock (p<0.05). Follow-up was available in 181(94.3%) patients with a mean duration of 22.0±13.9 months. Heart failure and post-procedure stroke were independent predictors of late outcome (p<0.05). CONCLUSIONS: Among patients with severe chronic kidney disease or end stage renal disease undergoing revascularisation, percutaneous coronary intervention PCI was performed in patients with less complex anatomy or as emergency for acute ST-elevation myocardial infarction. Coronary artery bypass graft patients had higher early mortality, but improved late survival.

Intelligent Machine Learning Approach for Effective Recognition of Diabetes in E-Healthcare Using Clinical Data.

Significant attention has been paid to the accurate detection of diabetes. It is a big challenge for the research community to develop a diagnosis system to detect diabetes in a successful way in the e-healthcare environment. Machine learning techniques have an emerging role in healthcare services by delivering a system to analyze the medical data for diagnosis of diseases. The existing diagnosis systems have some drawbacks, such as high computation time, and low prediction accuracy. To handle these issues, we have proposed a diagnosis system using machine learning methods for the detection of diabetes. The proposed method has been tested on the diabetes data set which is a clinical dataset designed from patient's clinical history. Further, model validation methods, such as hold out, K-fold, leave one subject out and performance evaluation metrics, includes accuracy, specificity, sensitivity, F1-score, receiver operating characteristic curve, and execution time have been used to check the validity of the proposed system. We have proposed a filter method based on the Decision Tree (Iterative Dichotomiser 3) algorithm for highly important feature selection. Two ensemble learning algorithms, Ada Boost and Random Forest, are also used for feature selection and we also compared the classifier performance with wrapper based feature selection algorithms. Classifier Decision Tree has been used for the classification of healthy and diabetic subjects. The experimental results show that the proposed feature selection algorithm selected features improve the classification performance of the predictive model and achieved optimal accuracy. Additionally, the proposed system performance is high compared to the previous state-of-the-art methods. High performance of the proposed method is due to the different combinations of selected features set and Plasma glucose concentrations, Diabetes pedigree function, and Blood mass index are more significantly important features in the dataset for prediction of diabetes. Furthermore, the experimental results statistical analysis demonstrated that the proposed method would effectively detect diabetes and can be deployed in an e-healthcare environment.

Brand versus generic dispensing trend for ciprofloxacin 500 mg, levofloxacin 500 mg, and moxifloxacin 400 mg (oral dosage forms) among pharmacies of Karachi, Pakistan.

INTRODUCTION: Pakistan spends 0.7% of its gross domestic product on health. The public sector health-care system provides services to 22% of population thus paving the way for a dominant private sector. Patients in Pakistan mostly pay their medical expenses directly, and 64% of the health expenditures are borne by the household. Expenditure on medicine constitutes 43% of the total household expenditure. METHODS: A quantitative cross-sectional study was conducted in Karachi, Pakistan, for a month. It was aimed at gathering response from different pharmacies to understand the brand versus generic dispensing trend of ciprofloxacin 500 mg, levofloxacin 500 mg, and moxifloxacin 400 mg oral dosage forms. The study employed convenience sampling and used a survey checklist. The data gathered was entered in SPSS version 22. RESULTS: The mean price per tablet for ciprofloxacin brand and generic was reported at Pakistani Rupees (PKR) 48.44 and PKR 26.85, respectively. The trend for dispensing ciprofloxacin highlighted a split in the market between brand (51%) and generic (49%). For levofloxacin brand and generic, the price per tablet was reported at PKR 36.50 and PKR 36.15 respectively, and despite same price, the market was dominated by generic levofloxacin (92%). Due to a price difference between brand and generic moxifloxacin, i.e., PKR 129.44 and PKR 71.91, respectively, the market was mostly occupied by the generic form (75%). CONCLUSION: Pricing mechanism must be revisited, and the authorities should take stern actions against any illegitimate price hike. The surging burden of drug expenditure on poorer sections of the society must be addressed by the government on an urgent basis.

Pleuro pericardial cyst.

A 68-year-old male, presented with exertional dyspnoea and chest pain in his anterior chest wall for 3 months. He had no previous history of cardiac disease. Clinical examination failed to show anything significant. Chest X-ray showed a mass superimposed over the upper cardiac silhouette. He was further evaluated by chest CT, which showed a cystic mass in the anterior mediastinum measuring 9 x 7 cm in its maximum diameter. On surgical excision and histopathological examination, findings were consistent with benign pleuropericardial cyst, confirming the earlier diagnosis.

Isolated tuberculous thyroiditis as solitary thyroid nodule.

Isolated involvement of the thyroid by tuberculosis is very rare as reported in literature. We are presenting a case of isolated tuberculous thyroiditis presented as a solitary thyroid nodule. The patient was treated with anti-tuberculous regimen and he responded well with disappearance of the nodule and normalization of the thyroid scan.