Evidence map›Paper›PMID 42273392›Full record

ArticleInfection and drug resistance2026

Diagnostic Accuracy of the Biofire FilmArray Blood Culture Identification 2 (BCID2) for Bloodstream Infections in Limpopo, South Africa.

Nhlayiso Atalia Maswanganyi, Kabelo Gabriel Kaapu, Molebogeng Ruth Lekalakala-Mokaba, Ivy Rukasha

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Article in Infection and drug resistance, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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2 · The registry

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Nhlayiso Atalia MaswanganyiDepartment of Pathology, University of Limpopo, Polokwane, Limpopo, South Africa.ORCID 0000-0002-5928-156X
Kabelo Gabriel KaapuDepartment of Pathology, University of Limpopo, Polokwane, Limpopo, South Africa.ORCID 0000-0002-5351-7834
Molebogeng Ruth Lekalakala-MokabaDepartment of Pathology, University of Limpopo, Polokwane, Limpopo, South Africa.ORCID 0000-0001-8560-8581
Ivy RukashaDepartment of Pathology, University of Limpopo, Polokwane, Limpopo, South Africa.ORCID 0000-0002-6279-6409

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Bloodstream infections are a leading global cause of mortality and morbidity. Timely and accurate diagnosis improves outcomes, especially in resource-limited settings. Rapid and accurate diagnostic tools are essential for effective treatment, particularly in resource-limited settings. Our study aimed to evaluate the diagnostic performance of the BCID2 assay, comparing its effectiveness to the VITEK2 at a routine lab in Limpopo, South Africa, where alternative assays are necessary to overcome resource unavailability in areas located further away from major laboratories. Methods: This cross-sectional study was conducted from August to December 2023. A total of 247 positive blood culture bottles were tested using both BCID2 and VITEK2 systems. Statistical analysis, including specificity, sensitivity, and accuracy, was calculated using Medcalc and SPSS. Results: The BCID2 panel demonstrated a sensitivity, specificity, and accuracy of 95.7%, 95.5%, and 96%, respectively. Of the samples, 72% (179/247) were monomicrobial and 28% (68/247) were polymicrobial, with a total of 16 off-panel microorganisms identified across both groups. blaCTX-M was the most frequent Gram-negative resistance gene detected (55.2%, 80/145), while blaVIM was the least common (0.7%, 1/145). Conclusion: The study concluded that the BCID2 assay demonstrates excellent diagnostic accuracy, with sensitivity, specificity, and overall accuracy rates above 95%. Its ability to rapidly detect bloodstream infections and antimicrobial resistance markers makes it a highly effective tool, particularly in resource-limited settings like Limpopo, South Africa, where timely and accurate diagnosis is crucial to improving patient outcomes.

Indexed as

antimicrobial resistance genesblood culture identification 2 panelbloodstream infectionsmonomicrobial infectionspolymicrobial infections

Identifiers

PMID42273392
PMCPMC13248963

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.