Modeling the CD4 decline in HIV with Low Cost Predictors for Effective HIV Management in Resource Poor Settings

Pushpavalli, K (2008) Modeling the CD4 decline in HIV with Low Cost Predictors for Effective HIV Management in Resource Poor Settings. Masters thesis, College of Pharmacy, Sri Ramakrishna Institute of Paramedical Sciences, Coimbatore.


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INTRODUCTION: Human immunodeficiency virus type1 is a primary cause of AIDS, which is a slow and degenerative disease of human immune system. The pathogenesis of HIV-1 is complex and characterized by interplay of both host and viral factors. Most researchers believe that HIV originated in sub-Saharan Africa during 20th century and is now a pandemic, with an estimated 33.2 million people now living with the disease worldwide. As of January 2006, the United Nations Programme on HIV/AIDS (UNAIDS) and World Health Organization (WHO) estimated that AIDS has killed more than 25 million people since it was first recognized on June 5, 19812, making it one of the most destructive epidemics in recorded history. OBJECTIVE OF STUDY: 1. To integrate the different ways of HIV classification and to develop a classification model which will be more relevant for resource limited settings. 2. To study the interrelationship between the cheaply available markers, (Hb & TLC) with CD4 and to develop a model for “CD4 decline in HIV” for therapeutic decision making. 3. To derive an algorithm based on HGB and TLC measurement for guide to initiation of ART 4. To review the molecular strategies against target in HIV replication cycle. MATERIALS AND METHODS: Instruments Required: (1) Sysmex Kx-21 – Automatic Blood Content Analyzer. (2) Flow Cytometer- Becton Dickinson _ CD4 Counter. Protocol for Complete blood Count: HIV patients Blood (iv source). b) Diluation: 20μl blood diluted with 300μl cell pack which contains, HGB/WBC lyse reagent – Stromolyser, cell clean- detergent and diluent by machine itself. c) Detection: HGB Detected by photo electric method using 540nm Principle behind it is Cyanomethaemoglobin method. d) Determination of HGB: Direct reading from report. e) Determination of TLC: Multiply the WBC with lymphocyte % obtained from reading. Protocol for CD4 count: a) Sample: Peripheral blood of HIV patients. collect into EDTA coated tubes (367856, Becton and Dickinson). Mix thoroughly with the anti coagulant by gently inverting the tube .about 8-10 mts. b) Cell staining: Add 20μl of antibody (stand) to 50μl of blood sample gently mix it by vortexer. Incubate the sample in the dark for 15mts c) Fixation and rbc analysis: 450μl of IX lysis buffer to each sample.vortex it and incubate for 15mts. Add 25 μl of fluorescent beads to each sample. d) Calibration of the flow cytometer. e) Detection: - FACS method. f) Determination of CD4 = Gated cell count × Bead count per test. Gated bead count Test volume. METHODOLOGY: Data collection: Collection of data from out sources; Data of demographic, general, clinical characteristics and laboratory profile of HIV positive patients in all stages, collected and reviewed from net sources to find out the changes of the marker trend in all stages of HIV and analyzed their symptoms persist in different stages of disease. Collection of Existing data: Comparison of results obtained from analysis of net sources with experimental work or existing work is essential for conclude the research work. Due to limitation and precaution of handling of HIV patient’s blood, existing work collected for further analysis. Data of 50 HIV +ve patients include general characteristics, clinical profile and lab parameters collected from their records in all departments in 500 bedded multi speciality private tertiary care teaching hospital. SUMMARY AND CONCLUSION: HIV infection is associated with numerous co morbidities and opportunistic infection. It affects total immune system of human. Deterioration of immunological parameters is widely used as predictor as well as prognostic marker. Current recommendations of initiating HAART is based on CD4 count decline. But cost of each test is so high in resource poor settings. So searching of alternative low cost predictors in HIV progression is paramount important in HIV infection for poor resource settings. Symptoms also important thing in HIV patients. WHO grouped the symptoms into 4 categories and CDC grouped the symptoms into 3 categories, which includes changes of marker trend into this; it will come into seven categories. This integrated model helps us to categorize the HIV patient where they are falling in HIV age and can able to predict the CD4 count for HIV patients from TLC measurement, Hemoglobin measurement and combined effect of these two measurements. From our analysis correlation of both Hemoglobin and total lymphocyte count with CD4 are significant. We conclude that TLC and HGB are good predictors for HIV progression in resource limited settings, also combined effect of both is high compared than Individual.

Item Type: Thesis (Masters)
Additional Information: Reg No.26063655
Uncontrolled Keywords: Modeling the CD4 decline in HIV with Low Cost Predictors for Effective HIV Management in Resource Poor Settings
Subjects: PHARMACY > Pharmaceutical Biotechnology
Depositing User: Ravindran C
Date Deposited: 12 Jul 2017 06:22
Last Modified: 15 May 2018 16:35

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