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Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/12741

Title: Analysis of haematological parameters as predictors of malaria infection using a logistic regression model: a case study of a hospital in the Ashanti region of Ghana
Authors: Paintsil, Ellis Kobina
Omari-Sasu, Akoto Yaw
Addo, Matthew Glover
Boateng, Maxwell Akwasi
Issue Date: 21-May-2019
Publisher: Hindawi
Abstract: Malaria is the leading cause of morbidity in Ghana representing 40-60% of outpatient hospital attendance with about 10% endingup on admission. Microscopic examination of peripheral blood film remains the most preferred and reliable method for malariadiagnosis worldwide. But the level of skills required for microscopic examination of peripheral blood film is often lacking in Ghana.This study looked at determining the extent to which haematological parameters and demographic characteristics of patients couldbe used to predict malaria infection using logistic regression. The overall prevalence of malaria in the study area was determinedto be 25.96%; nonetheless, 45.30% of children between the ages of 5 and 14 tested positive. The binary logistic model developed forthis study identified age, haemoglobin, platelet, and lymphocyte as the most significant predictors. The sensitivity and specificity ofthe model were 77.4% and 75.7%, respectively, with a PPV and NPV of 52.72% and 90.51%, respectively. Similar to RDT this logisticmodel when used will reduce the waiting time and improve the diagnosis of malaria.
Description: An article published by Hindawi and also available at doi.org/10.1155/2019/1486370
URI: http://hdl.handle.net/123456789/12741
Appears in Collections:College of Science

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