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DC Field | Value | Language |
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dc.contributor.author | OGUNNIYI, A.O. | - |
dc.date.accessioned | 2019-07-24T16:37:45Z | - |
dc.date.available | 2019-07-24T16:37:45Z | - |
dc.date.issued | 2014-10 | - |
dc.identifier.uri | http://adhlui.com.ui.edu.ng/jspui/handle/123456789/998 | - |
dc.description | A Dissertation in the Department of Epidemiology and Medical Statistics submitted to the Faculty of Public Health, College of Medicine, University of Ibadan in partial fulfillment of the requirements for the Degree of Masters of Public Health (Laboratory Epidemiology Practice) of the University of Ibadan | en_US |
dc.description.abstract | The unavailability of accurate, rapid, reliable and cost effective malaria diagnostic instruments constitute a major challenge to malaria elimination campaign. This compels many laboratories to depend on the conventional method of detecting malaria parasitaemia using light microscopy. This method has challenges such as labour-intensiveness, poor expertise, resulting in delayed turnaround time for diagnosis and thereby promoting high morbidity and mortality. Alternative diagnostic instruments like cyscope fluorescent microscope (Cyscope), quantitative buffy coat fluorescent microscope (QBC) and CareStart™ rapid diagnostic kit (CareStart™) with the potential to address these challenges have been developed but their validity and cost effectiveness have not been determined in Nigeria. This study was, therefore, designed to validate these instruments and assess their comparative cost effectiveness. Using evaluative study design, five hundred and two (502) out of one thousand eight hundred (1,800) patients with signs and symptoms suggestive of malaria at the University College Hospital, Adeoyo State Hospital, and Kola Daisi Foundation Health center in Ibadan between January and April, 2014, were selected by systematic random sampling. Blood samples were collected and evaluated for malaria parasites; using Cyscope, QBC and CareStart™. The blood samples were then evaluated for malaria parasites using light microscopy as gold standard. For each instrument, validity indices assessed were sensitivity, specificity, Positive Predictive Value (PPV) and Negative Predictive Value (NPV). Cost per hour of use of each instrument was also determined. Data were analyzed with McNemar Chi-square and Kappa statistics at level of significance set at p = 0.05. Malaria prevalence in the samples was 19.5%, 21.7%, 30.7% and 32.7% for CareStart™, light microscopy, Cyscope, and QBC respectively. The sensitivity of the instruments compared with light microscopy was 76.0% for CareStart™, 95.0% for Cyscope and 98.1 % for QBC; while specificity for QBC was 85.5%, Cyscope had 87.3% and 96.0% for CareStart™. Positive Predictive Value for the instruments was 65.2% for QBC, 67.5% for Cyscope, and 84.7% for CareStart™; with Negative Predictive Value of 93.6%, 98.6% and 99.4% for CareStart™, Cyscope, and QBC respectively. Inter instrument agreement index, Kappa values (Ka) was 0.71 (CI= 0.64 - 0.77) for QBC, 0.72 (CI= 0.65 - 0.78) for Cyscope and 0.75 (CI= 0.68 - 0.82) for CareStart™. Average cost per hour of use for Cyscope was $2.04, CareStart™: $5.61, QBC: $5.89 and $10.77 for light microscopy. The turnaround time per result output was Cyscope: 5minutes, QBC: 10minutes, CareStart™: 20minutes and 45 minutes for light microscopy. Cyscope fluorescent microscope had the least turnaround diagnostic time and it is the most cost effective of all the laboratory diagnostic instruments evaluated. Cyscope fluorescent microscope is therefore strongly recommended for malaria parasite detection. | en_US |
dc.language.iso | en | en_US |
dc.subject | Malaria diagnosis | en_US |
dc.subject | Rapid diagnostic test | en_US |
dc.subject | Malaria parasites | en_US |
dc.subject | Cyscope microscope | en_US |
dc.title | VALIDATION AND COMPARISM OF CYSCOPE MICROSCOPE, QUALITATIVE BUFFY COAT MICROSCOPE AND RAPID DIAGNOSTIC KIT FOR MALARIA DIAGNOSIS AMONG CLINIC ATTENDEES IN IBADAN, NIGERIA | en_US |
dc.type | Thesis | en_US |
Appears in Collections: | Dissertations in Epidemiology and Medical Statistics |
Files in This Item:
File | Description | Size | Format | |
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UI_Dissertation_Ogunniyi_AO_Validation_2014.pdf | Dissertation | 13.51 MB | Adobe PDF | View/Open |
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