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The Use of Screening Algorithm to Defer Blood Donors with Subclinical Malaria.

Desmond Omane AcheampongEnoch Aninagyei
Published in: Journal of tropical medicine (2021)
Plasmodium falciparum infection in blood donors is common in malaria endemic countries, including Ghana. To date, there are no established exclusion criteria to defer a donor carrying malaria parasites. Therefore, based on significant independent variables identified in this study, donor malaria screening algorithm was developed to be used by blood banks to screen blood donors for subclinical malaria. Each significant variable was weighted one (1) point and its alternative response was weighted negative one (-1) point. Accumulation of the points determines the risk level of the donor. These weighted points were used to categorize infected donors as having negligible (<2 points), tolerable (3-4 points), undesirable (5-8 points), or intolerable (>9 points) risk. Based on accumulated weight of ≥5 points, the algorithm was 94.7% (54/57) sensitive but 82% (298/364) specific. With this level of specificity, 18% of the blood donors without malaria would have been deferred. Therefore, it is imperative that all donors with accumulated risk ≥5 be screened for malaria using either malaria rapid test kit or microscopy.
Keyphrases
  • plasmodium falciparum
  • machine learning
  • deep learning
  • physical activity
  • magnetic resonance imaging
  • high throughput
  • computed tomography
  • high speed
  • body weight