Cargando…

Systematic Review and Meta-Analysis of the Diagnostic Accuracy of Mobile-Linked Point-of-Care Diagnostics in Sub-Saharan Africa

Mobile health devices are emerging applications that could help deliver point-of-care (POC) diagnosis, particularly in settings with limited laboratory infrastructure, such as Sub-Saharan Africa (SSA). The advent of Severe acute respiratory syndrome coronavirus 2 has resulted in an increased deploym...

Descripción completa

Detalles Bibliográficos
Autores principales: Osei, Ernest, Nkambule, Sphamandla Josias, Vezi, Portia Nelisiwe, Mashamba-Thompson, Tivani P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8231511/
https://www.ncbi.nlm.nih.gov/pubmed/34204848
http://dx.doi.org/10.3390/diagnostics11061081
_version_ 1783713441171636224
author Osei, Ernest
Nkambule, Sphamandla Josias
Vezi, Portia Nelisiwe
Mashamba-Thompson, Tivani P.
author_facet Osei, Ernest
Nkambule, Sphamandla Josias
Vezi, Portia Nelisiwe
Mashamba-Thompson, Tivani P.
author_sort Osei, Ernest
collection PubMed
description Mobile health devices are emerging applications that could help deliver point-of-care (POC) diagnosis, particularly in settings with limited laboratory infrastructure, such as Sub-Saharan Africa (SSA). The advent of Severe acute respiratory syndrome coronavirus 2 has resulted in an increased deployment and use of mHealth-linked POC diagnostics in SSA. We performed a systematic review and meta-analysis to evaluate the accuracy of mobile-linked point-of-care diagnostics in SSA. Our systematic review and meta-analysis were guided by the Preferred Reporting Items requirements for Systematic Reviews and Meta-Analysis. We exhaustively searched PubMed, Science Direct, Google Scholar, MEDLINE, and CINAHL with full text via EBSCOhost databases, from mHealth inception to March 2021. The statistical analyses were conducted using OpenMeta-Analyst software. All 11 included studies were considered for the meta-analysis. The included studies focused on malaria infections, Schistosoma haematobium, Schistosoma mansoni, soil-transmitted helminths, and Trichuris trichiura. The pooled summary of sensitivity and specificity estimates were moderate compared to those of the reference representing the gold standard. The overall pooled estimates of sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio of mobile-linked POC diagnostic devices were as follows: 0.499 (95% CI: 0.458–0.541), 0.535 (95% CI: 0.401–0.663), 0.952 (95% CI: 0.60–1.324), 1.381 (95% CI: 0.391–4.879), and 0.944 (95% CI: 0.579–1.538), respectively. Evidence shows that the diagnostic accuracy of mobile-linked POC diagnostics in detecting infections in SSA is presently moderate. Future research is recommended to evaluate mHealth devices’ diagnostic potential using devices with excellent sensitivities and specificities for diagnosing diseases in this setting.
format Online
Article
Text
id pubmed-8231511
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-82315112021-06-26 Systematic Review and Meta-Analysis of the Diagnostic Accuracy of Mobile-Linked Point-of-Care Diagnostics in Sub-Saharan Africa Osei, Ernest Nkambule, Sphamandla Josias Vezi, Portia Nelisiwe Mashamba-Thompson, Tivani P. Diagnostics (Basel) Review Mobile health devices are emerging applications that could help deliver point-of-care (POC) diagnosis, particularly in settings with limited laboratory infrastructure, such as Sub-Saharan Africa (SSA). The advent of Severe acute respiratory syndrome coronavirus 2 has resulted in an increased deployment and use of mHealth-linked POC diagnostics in SSA. We performed a systematic review and meta-analysis to evaluate the accuracy of mobile-linked point-of-care diagnostics in SSA. Our systematic review and meta-analysis were guided by the Preferred Reporting Items requirements for Systematic Reviews and Meta-Analysis. We exhaustively searched PubMed, Science Direct, Google Scholar, MEDLINE, and CINAHL with full text via EBSCOhost databases, from mHealth inception to March 2021. The statistical analyses were conducted using OpenMeta-Analyst software. All 11 included studies were considered for the meta-analysis. The included studies focused on malaria infections, Schistosoma haematobium, Schistosoma mansoni, soil-transmitted helminths, and Trichuris trichiura. The pooled summary of sensitivity and specificity estimates were moderate compared to those of the reference representing the gold standard. The overall pooled estimates of sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio of mobile-linked POC diagnostic devices were as follows: 0.499 (95% CI: 0.458–0.541), 0.535 (95% CI: 0.401–0.663), 0.952 (95% CI: 0.60–1.324), 1.381 (95% CI: 0.391–4.879), and 0.944 (95% CI: 0.579–1.538), respectively. Evidence shows that the diagnostic accuracy of mobile-linked POC diagnostics in detecting infections in SSA is presently moderate. Future research is recommended to evaluate mHealth devices’ diagnostic potential using devices with excellent sensitivities and specificities for diagnosing diseases in this setting. MDPI 2021-06-12 /pmc/articles/PMC8231511/ /pubmed/34204848 http://dx.doi.org/10.3390/diagnostics11061081 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Osei, Ernest
Nkambule, Sphamandla Josias
Vezi, Portia Nelisiwe
Mashamba-Thompson, Tivani P.
Systematic Review and Meta-Analysis of the Diagnostic Accuracy of Mobile-Linked Point-of-Care Diagnostics in Sub-Saharan Africa
title Systematic Review and Meta-Analysis of the Diagnostic Accuracy of Mobile-Linked Point-of-Care Diagnostics in Sub-Saharan Africa
title_full Systematic Review and Meta-Analysis of the Diagnostic Accuracy of Mobile-Linked Point-of-Care Diagnostics in Sub-Saharan Africa
title_fullStr Systematic Review and Meta-Analysis of the Diagnostic Accuracy of Mobile-Linked Point-of-Care Diagnostics in Sub-Saharan Africa
title_full_unstemmed Systematic Review and Meta-Analysis of the Diagnostic Accuracy of Mobile-Linked Point-of-Care Diagnostics in Sub-Saharan Africa
title_short Systematic Review and Meta-Analysis of the Diagnostic Accuracy of Mobile-Linked Point-of-Care Diagnostics in Sub-Saharan Africa
title_sort systematic review and meta-analysis of the diagnostic accuracy of mobile-linked point-of-care diagnostics in sub-saharan africa
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8231511/
https://www.ncbi.nlm.nih.gov/pubmed/34204848
http://dx.doi.org/10.3390/diagnostics11061081
work_keys_str_mv AT oseiernest systematicreviewandmetaanalysisofthediagnosticaccuracyofmobilelinkedpointofcarediagnosticsinsubsaharanafrica
AT nkambulesphamandlajosias systematicreviewandmetaanalysisofthediagnosticaccuracyofmobilelinkedpointofcarediagnosticsinsubsaharanafrica
AT veziportianelisiwe systematicreviewandmetaanalysisofthediagnosticaccuracyofmobilelinkedpointofcarediagnosticsinsubsaharanafrica
AT mashambathompsontivanip systematicreviewandmetaanalysisofthediagnosticaccuracyofmobilelinkedpointofcarediagnosticsinsubsaharanafrica