A COMPARISON OF RAPID DIAGNOSTIC TEST AND MODIFIED ZIEHL-NEELSEN METHOD IN THE DIAGNOSIS OF CRYPTOSPORIDIOSIS.

Abstract

Background: Cryptosporidium parvum as a leading cause of persistent diarrhoea in developing countries causes a more severe illness in patients infected with human immunodeficiency virus (HIV). The intermittent shedding of Cryptosporidium parvum oocysts in stool, even in patients with massive diarrhoea, makes diagnosis difficult. This study evaluated the validity of Crypto-Strip test in comparison to the modified Ziehl-Neelsen for the diagnosis of Cryptosporidium infection using polymerase chain reaction (PCR) as gold standard. Methods: This was a hospital based cross-sectional study of 100 HIV positive patients with diarrhoea at a tertiary health facility in Jos, Nigeria. We collected 15mls of stool sample and relevant information from patients who gave informed consent. The oocytes of Cryptosporidium parvum were identified in the stool samples using modified Ziehl-Neelsen stain and Rapid diagnostic test (Crypto-Strip). We also ran all samples using polymerase chain reaction (PCR). Statistical analysis was with statistical package for Social Sciences (SPSS) version 21. Result: Out of the 100 stool samples analysed, 13 (13%) were positive for cryptosporidiosis by PCR. Crypto- Strips recorded 12 (12%) positive with one (1) being false negative as compared to PCR. Conversely, eight (8%) of the 100 samples collected were positive for Cryptosporidium oocysts using modified Ziehl Neelsen (mZN) stain. Out of the eight positives by mZN stain, two were false positive as both tested negative by the PCR. The Crypto-Strip test kit had a sensitivity of 92.3% and a specificity of 100.0% and also positive and negative predictive values of 100.0% and 98.9%, respectively. Whereas, the modified Ziehl Neelsen stain had a sensitivity of 46.2% and a specificity of 97.7% with a positive and negative predictive value of 75.0% and 92.4%, respectively. Conclusion: In this study, we have shown that Crypto-Strip test was a better diagnostic method for the diagnosis of crypto