TY - JOUR
T1 - Performance of a smartphone-based malaria screener in detecting malaria in people living with Sickle cell disease
AU - Sarpong Obeng, Deborah Nimako
AU - Osei, Samuel
AU - Brown, Nii Kpakpo
AU - Adjei, David Nana
AU - Amoah, Linda Eva
AU - Ampadu Owusu, Ewurama Dedea
N1 - Publisher Copyright:
© 2025 Obeng et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
PY - 2025/6
Y1 - 2025/6
N2 - Novel automated digital malaria diagnostic tests are being developed with the advancement of diagnostic tools. Whilst these tools are being evaluated and implemented in the general population, there is the need to focus on special populations such as individuals with Sickle Cell Disease (SCD) who have altered red blood cell morphology and atypical immune responses, which can obscure parasite detection. This study aimed to evaluate the diagnostic performance of one of such tools, the National Library of Medicine (NLM) malaria screener app in people living with sickle cell disease in a malaria-endemic country, Ghana. A descriptive cross-sectional study was conducted among SCD patients attending the Sickle Cell Clinic at Korle Bu Teaching Hospital in Accra, Ghana. Following informed consent, whole blood samples were collected and analyzed using the NLM malaria screener app, conventional microscopy, RDT, and Polymerase Chain Reaction (PCR), with PCR as the reference standard. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of each diagnostic method were compared against PCR results. The NLM app identified the highest number of positive malaria cases, with 110 positive cases (36.2%), while both RDT and microscopy reported the highest number of negatives, with 287 negative cases (94.4%). Compared to PCR, the NLM app demonstrated a sensitivity of 89.5% and a specificity of 67.4%. RDT and microscopy displayed the same sensitivity as the NLM app, each achieving 89.5%. However, while RDT and microscopy had a specificity of 100%, the NLM app had a considerably lower specificity of 67.4%.The NLM malaria screener app shows promise as a preliminary screening tool for malaria in individuals with SCD. However, its lower specificity indicates a need for confirmatory testing to avoid potential overdiagnosis and mismanagement. Enhancements in the app’s specificity could further support its utility in rapid and accessible malaria diagnosis for people with SCD, aiding in timely management and treatment.
AB - Novel automated digital malaria diagnostic tests are being developed with the advancement of diagnostic tools. Whilst these tools are being evaluated and implemented in the general population, there is the need to focus on special populations such as individuals with Sickle Cell Disease (SCD) who have altered red blood cell morphology and atypical immune responses, which can obscure parasite detection. This study aimed to evaluate the diagnostic performance of one of such tools, the National Library of Medicine (NLM) malaria screener app in people living with sickle cell disease in a malaria-endemic country, Ghana. A descriptive cross-sectional study was conducted among SCD patients attending the Sickle Cell Clinic at Korle Bu Teaching Hospital in Accra, Ghana. Following informed consent, whole blood samples were collected and analyzed using the NLM malaria screener app, conventional microscopy, RDT, and Polymerase Chain Reaction (PCR), with PCR as the reference standard. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of each diagnostic method were compared against PCR results. The NLM app identified the highest number of positive malaria cases, with 110 positive cases (36.2%), while both RDT and microscopy reported the highest number of negatives, with 287 negative cases (94.4%). Compared to PCR, the NLM app demonstrated a sensitivity of 89.5% and a specificity of 67.4%. RDT and microscopy displayed the same sensitivity as the NLM app, each achieving 89.5%. However, while RDT and microscopy had a specificity of 100%, the NLM app had a considerably lower specificity of 67.4%.The NLM malaria screener app shows promise as a preliminary screening tool for malaria in individuals with SCD. However, its lower specificity indicates a need for confirmatory testing to avoid potential overdiagnosis and mismanagement. Enhancements in the app’s specificity could further support its utility in rapid and accessible malaria diagnosis for people with SCD, aiding in timely management and treatment.
UR - https://www.scopus.com/pages/publications/105007607135
U2 - 10.1371/journal.pdig.0000884
DO - 10.1371/journal.pdig.0000884
M3 - Article
AN - SCOPUS:105007607135
SN - 2767-3170
VL - 4
JO - PLOS Digital Health
JF - PLOS Digital Health
IS - 6 June
M1 - e0000884
ER -
