Background:The First Basal Insulin Evaluation (FINE) Asia study is a multinational, prospective, observational study of insulin-naïve Type 2 diabetes mellitus (T2DM) patients in Asia, uncontrolled (A1c ≥ 8%) on oral hypoglycemic agents, designed to evaluate the impact of basal insulin initiation.Methods:Basal insulin was initiated with or without concomitant oral therapy and doses were adjusted individually. All treatment choices, including the decision to initiate insulin, were at the physician's discretion to reflect real-life practice.Results:Patients (n= 2679) from 11 Asian countries were enrolled (mean [±SD] duration of diabetes 9.3 ± 6.5 years; weight 68.1 ± 12.7 kg; A1c 9.8 ± 1.6%). After 6 months of basal insulin (NPH insulin, insulin glargine, or insulin detemir), A1c decreased to 7.7 ± 1.4%; 33.7% patients reached A1c <7%. Fasting blood glucose (FBG) decreased from 11.7 ± 3.6 to 7.2 ± 2.5 mmol/L and 36.8% of patients reached FBG <6.1 mmol/L. The mean daily insulin dose prescribed increased marginally from 0.18 to 0.23 U/kg per day at baseline to 0.22–0.24 U/kg per day at Month 6. Mean changes in body weight and reported rates of hypoglycemia were low over the duration of the study.Conclusions:Initiation of insulin therapy is still being delayed by approximately 9 years, resulting in many Asian patients developing severe hyperglycemia. Initiating insulin treatment with basal insulin was effective and safe in Asian T2DM patients in a real-world setting, but insulin needs may differ from those in Western countries.

Background & Objective: Microvascular complications are the major outcome of type 2 Diabetes Mellitus progression, which reduce the quality of life, incur heavy economic burdens to the health care system and increase diabetic mortality. The aims of this study were to assess the prevalence of microvascular complications among newly diagnosed type 2 diabetic patients and to analyze the association between these complications and poor glycemic control. Methods: This cross sectional hospital based study was carried out in Diabetic Clinic of Shaikh Zayed Postgraduate Medical Institute, Lahore Pakistan. The study was conducted from November 2011 to November 2012 among newly diagnosed type 2 diabetic patients. Relevant information of all patients was recorded with the help of a proforma. They were investigated for retinopathy, nephropathy and neuropathy. Results: We have divided the patients into two groups: Group I with good glycemic control (HbA1c <6.5) and group II with poor glycemic control (HbA1c >6.5). In group II microvascular complications were 89.8%. Neuropathy, nephropathy and retinopathy were present in 68.5%, 56.2% and 31.4% respectively. These similar percentages in Group I were 50%, 0% and 31% respectively and are significantly lower. Conclusion: The study showed that even in newly diagnosed type 2 diabetic patients who had poor glycemic control, frequency of microvascular complications is much higher as compared to those who had average glycemic control. Thus tight glycemic control does count even in newly diagnosed type 2 diabetics to prevent and minimize the occurrence of complications.

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Online reviews regarding different products or services have become the main source to determine public opinions. Consequently, manufacturers and sellers are extremely concerned with customer reviews as these have a direct impact on their businesses. Unfortunately, to gain profits or fame, spam reviews are written to promote or demote targeted products or services. This practice is known as review spamming. In recent years, the spam review detection problem has gained much attention from communities and researchers, but still there is a need to perform experiments on real-world large-scale review datasets. This can help to analyze the impact of widespread opinion spam in online reviews. In this work, two different spam review detection methods have been proposed: (1) Spam Review Detection using Behavioral Method (SRD-BM) utilizes thirteen different spammer's behavioral features to calculate the review spam score which is then used to identify spammers and spam reviews, and (2) Spam Review Detection using Linguistic Method (SRD-LM) works on the content of the reviews and utilizes transformation, feature selection and classification to identify the spam reviews. Experimental evaluations are conducted on a real-world Amazon review dataset which analyze 26.7 million reviews and 15.4 million reviewers. The evaluations show that both proposed models have significantly improved the detection process of spam reviews. Specifically, SRD-BM achieved 93.1% accuracy whereas SRD-LM achieved 88.5% accuracy in spam review detection. Comparatively, SRD-BM achieved better accuracy because it works on utilizing rich set of spammers behavioral features of review dataset which provides in-depth analysis of spammer behaviour. Moreover, both proposed models outperformed existing approaches when compared in terms of accurate identification of spam reviews. To the best of our knowledge, this is the first study of its kind which uses large-scale review dataset to analyze different spammers' behavioral features and linguistic method utilizing different available classifiers. INDEX TERMS Online product reviews, spam reviews, spam review detection, linguistic features, spammer behavioral features.

Requirements Elicitation phase in RequirementsEngineering (RE) is found to be very complex and demands more attention when software development is performed on the global scale. The available approaches of requirements elicitation require vigilant application in different scenarios of GSD and may need further improvement when considering challenges of distributed development. In this paper, a comprehensive survey of requirements elicitation approaches and challenges is performed which describes the limitations in applying the current elicitation approaches in GSD scenarios. Considering these constraints, an iterative framework for elicitation (IRE) in Requirements engineering is proposed. The case study analysis of the proposed model shows the effectiveness of iterative approach. The results show that IRE approach is more effective in satisfying the customer requirements than existing elicitation approaches.