OBJECTIVE: To evaluate the feasibility of automated malaria detection with the Cell-Dyn 3700 (Abbott Diagnostics, Santa Clara, CA, USA) haematology analyser for diagnosing malaria in northern Namibia. METHODS: From April to June 2003, all patients with a positive blood smear result and a subset of patients with no suspicion of malaria were included. Blood smear and a venous blood sample (to determine haemoglobin, platelet and malaria pigment levels) were collected from each patient. Malaria pigment test characteristics, correlations with blood parameters and pigment clearance time were calculated. Finally, a subset of blood samples was run twice to evaluate the consistency of test outcome. RESULTS: Two hundred and eight patients were included. Ninety had a positive blood smear result of which 84 tested positive for malaria pigment and 118 patients had a negative blood smear result of which four tested positive for malaria pigment. Test characteristics as compared with microscopy were as follows: sensitivity 0.93, specificity 0.97, positive predictive value 0.95, negative predictive value 0.95. Rerun of the blood samples resulted in a change of diagnosis in 14%. After 4 weeks, 33% of patients with an initially positive pigment result still tested positive. Malaria pigment was found to be negatively correlated with haemoglobin. CONCLUSIONS: Automated detection of malaria pigment is a useful diagnostic tool in this semi-rural area. In low-risk malaria season, the test can be used for diagnosing malaria because of the high sensitivity. In high-risk malaria season, the test can be used for excluding malaria in case of a negative pigment result because of the high specificity.
OBJECTIVE: To evaluate the feasibility of automated malaria detection with the Cell-Dyn 3700 (Abbott Diagnostics, Santa Clara, CA, USA) haematology analyser for diagnosing malaria in northern Namibia. METHODS: From April to June 2003, all patients with a positive blood smear result and a subset of patients with no suspicion of malaria were included. Blood smear and a venous blood sample (to determine haemoglobin, platelet and malaria pigment levels) were collected from each patient. Malaria pigment test characteristics, correlations with blood parameters and pigment clearance time were calculated. Finally, a subset of blood samples was run twice to evaluate the consistency of test outcome. RESULTS: Two hundred and eight patients were included. Ninety had a positive blood smear result of which 84 tested positive for malaria pigment and 118 patients had a negative blood smear result of which four tested positive for malaria pigment. Test characteristics as compared with microscopy were as follows: sensitivity 0.93, specificity 0.97, positive predictive value 0.95, negative predictive value 0.95. Rerun of the blood samples resulted in a change of diagnosis in 14%. After 4 weeks, 33% of patients with an initially positive pigment result still tested positive. Malaria pigment was found to be negatively correlated with haemoglobin. CONCLUSIONS: Automated detection of malaria pigment is a useful diagnostic tool in this semi-rural area. In low-risk malaria season, the test can be used for diagnosing malaria because of the high sensitivity. In high-risk malaria season, the test can be used for excluding malaria in case of a negative pigment result because of the high specificity.
Authors: Thomas Hänscheid; Rosangela Frita; Matthias Längin; Peter G Kremsner; Martin P Grobusch Journal: Malar J Date: 2009-11-16 Impact factor: 2.979
Authors: Thomas Hänscheid; Matthias Längin; Bertrand Lell; Marc Pötschke; Sunny Oyakhirome; Peter G Kremsner; Martin P Grobusch Journal: Malar J Date: 2008-06-12 Impact factor: 2.979