Fingerprinting hyperglycemia using predictive modelling approach based on low-cost routine CBC and CRP diagnostics.

Hyperglycemia is an outcome of dysregulated glucose homeostasis in the human body and may induce chronic elevation of blood glucose levels. Lifestyle factors such as overnutrition, physical inactivity, and psychosocials coupled with systemic low-grade inflammation have a strong negative impact on glucose homeostasis, in particular, insulin sensitivity. Together, these factors contribute to the pathophysiology of diabetes (DM) and expanding landscape of its prevalence regionally and globally. The rapid rise in the prevalence of type 2 diabetes, therefore, underscores the need for its early diagnosis and treatment. In this work, we have evaluated the discriminatory capacity of different diagnostic markers including inflammatory biomolecules and RBC (Red Blood Cell) indices in predicting the risk of hyperglycemia and borderline hyperglycemia. For that, 208,137 clinical diagnostic entries obtained over five years from Chugtai Labs, Pakistan, were retrospectively evaluated. The dataset included HbA1c (n = 142,011), complete blood count (CBC, n = 84,263), fasting blood glucose (FBG, n = 35,363), and C-reactive protein (CRP, n = 9035) tests. Our results provide four glycemic predictive models for two cohorts HbA1c and FBG) each having an overall predictive accuracy of more than 80% (p-value < 0.0001). Next, multivariate analysis (MANOVA) followed by univariate analysis (ANOVA) was employed to identify predictors with significant discriminatory capacity for different levels of glycemia. We show that the interplay between inflammation, hyperglycemic-induced derangements in RBC indices, and altered glucose homeostasis could be employed for prognosticating hyperglycemic outcomes. Our results then conclude a glycemic predictor with high sensitivity and specificity, employing inflammatory markers coupled with RBC indices, to predict glycemic outcomes (ROC p-value < 0.0001). Taken together, this study outlines a predictor of glycemic outcomes which could assist as a prophylactic intervention in predicting the early onset of hyperglycemia and borderline hyperglycemia.

Cost effectiveness evaluation of hepatitis C therapy in Lahore.

Approximately 10 million Pakistan's of population is a victim of Hepatitis C virus. A comparative study of two treatments for Hepatitis C being provided in private clinics and government hospitals was conducted to evaluate the cost effectiveness of these treatments. The quality adjusted life years (QALYs) for each treatment plan was determined with the help of health utilities, using EQ-5D scores. A comprehensive data collection form aided in scrutinizing the cause and effect of each treatment on the patient's quality of life. The total sample size for this study is 200 total from the public and private sectors. For both the treatment strategies, values for quality adjusted life years (QALYs), incremental cost effective ratio (ICER) and cost effective analysis (CEA) were calculated. The Hepatitis C virus 3a and 3b genotypic patients who were treated with pegylated interferon α-2a and ribavirin combination (strategy 2) showed an increased quality adjusted life years (QALYs) of two years, as compared to those who received interferon α-2a and ribavirin regimen (strategy 1). An incremental cost effectiveness ratio (ICER) of Rs 144673.5 per quality adjusted life year (QALYs) was gained by patients treated with strategy 2. The therapy followed by the government sector (strategy 1) is relatively inexpensive accounting for Rs 654.5/quality adjusted life years (QALY) and therapy provided at the clinic sector (strategy 2) is relatively expensive Rs 5620.6/ quality adjusted life years (QALY). However, the cost effectiveness analysis for the pegylated interferon therapy is quite comparable with the other standard treatments; hence it can be called cost effective according to the quality adjusted life years (QALYs) gained and efficacy of the said therapy.