A study of haematological profile in Human Immune Deficiency Virus infection: Correlation with CD4 counts
Keywords:
HIV, CD4 counts, haematological parameters, anemia, thrombocytopeniaAbstract
Introduction:Â Hematologic defects are a common complication of human immunodeficiency virus (HIV) infection and result from several influences on the hematopoietic tissue. These abnormalities reflect the underlying immune status and may be prevented or corrected by the use of highly active antiretroviral therapy (HAART). Anemia commonly occurs during HIV infection and has been associated with increased progression to acquired immune deficiency syndrome (AIDS) and reduced survival.
Aims:Â The aim of this study was to study the hematologicalprofile in HIV patients, to evaluate the various hematological parameters and their association with CD4 counts.
Methods: One hundred HIV-positive patients, symptomatic as well as asymptomatic, diagnosed by enzyme-linked immunosorbent assay (ELISA) method according to the National AIDS Control Organization (NACO) guidelines were included. Complete hematologic profile was recorded. Relationship between CD4 counts and various hematologic parameters was analyzed. Descriptive statistics were applied. Association between two attributes was calculated by chi-square test and P value less than 0.05 was considered statistically significant.
Results:Â The most common hematologic abnormality was anemia, seen in 85% (n=85) of the patients. Normocytic normochromic anemia was seen in 57 patients,which was the most common type. A strong association between anemia and CD4 counts was observed. The hemoglobin, red blood cell count and hematocrit also showed corresponding low values with decreasing CD4 counts. Thrombocytopenia was the second common abnormality and had no significant relationship with CD4 counts.
Conclusion: HIV affects virtually all organ systems, with well-known abnormalities related to hematopoietic system. Anemia being the most common abnormality has strong correlation with CD4 counts and therefore could be used to predict the development of a more advanced disease.
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