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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: | Malaria Research and Treatment |
Citation: | Malaria Research and Treatment, Volume 2019 |
Abstract: | Malaria is the leading cause of morbidity in Ghana representing 40-60% of outpatient hospital attendance with about 10% ending
up on admission. Microscopic examination of peripheral blood film remains the most preferred and reliable method for malaria
diagnosis worldwide. But the level of skills required formicroscopic examination of peripheral blood film is often lacking inGhana.
This study looked at determining the extent to which haematological parameters and demographic characteristics of patients could
be used to predict malaria infection using logistic regression.The overall prevalence of malaria in the study area was determined
to be 25.96%; nonetheless, 45.30% of children between the ages of 5 and 14 tested positive. The binary logistic model developed for
this study identified age, haemoglobin, platelet, and lymphocyte as themost significant predictors.The sensitivity and specificity of
themodel were 77.4% and 75.7%, respectively, with a PPV and NPV of 52.72% and 90.51%, respectively. Similar to RDT this logistic
model when used will reduce the waiting time and improve the diagnosis of malaria |
Description: | This article has been published in Malaria Research and Treatment and is available at https://doi.org/10.1155/2019/1486370 |
URI: | 10.1155/2019/1486370 http://hdl.handle.net/123456789/13052 |
Appears in Collections: | College of Science
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