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article · International Journal of Medicine and Health Development

Urine Versus Blood-Based Rapid Diagnostic Test for Diagnosis of Peripheral Malaria among Pregnant Women with Clinical Features of Malaria

Abstract

A bstract Background: Malaria in pregnancy is common but some other illnesses mimic its clinical manifestation. This underscores the need for its diagnosis before treatment. Objectives: The objectives of the study were to compare the accuracy of urine-based malaria test (UMT) with blood-based rapid diagnostic test (RDT) in detecting malaria among pregnant women with clinical features of malaria. Materials and Methods: This was a comparative cross-sectional study, in which urine and venous blood were collected from 310 eligible participants at a teaching hospital in Abakaliki, Nigeria, between June and November, 2019. UMT, blood-based RDT and microscopy (gold standard) were performed for each participant. Each selected participant served as her own control. Data analysis was done using Statistical Product and Service Solutions version 20. Chi-square test was used for comparison of categorical variables. P < 0.05 was considered statistically significant. Results: The prevalence of malaria parasitaemia among the participants was 91.6% ( n = 284/310). The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and overall accuracy of UMT were 85.0%, 76.2%, 97.9%, 27.6%, and 81.9%, respectively, while the sensitivity, specificity, PPV, NPV, and overall accuracy of blood-based RDT were 87.2%, 81.8%, 98.4%, 33.3%, and 84.8%, respectively. There was no difference between the accuracy of UMT and blood-based RDT ( P = 0.56). The area under the receiver operating characteristic curve of both UMT and blood-based RDT was 0.83 and 0.86, respectively. Conclusion: UMT performance is comparable to blood-based RDT in diagnosing malaria and could be considered as a non-invasive alternative to RDT in settings where microscopy is lacking.

Research topics

  • Malaria Research and Control
  • Digital Imaging for Blood Diseases
  • Hematological disorders and diagnostics

Sustainable Development Goals

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DOI: 10.4103/ijmh.ijmh_41_25

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