The diagnosis of central nervous system infections in resource-limited settings and the use of novel and molecular diagnostic platforms to improve diagnosis

Figures & data

Table 1. List of pathogens detected in BioFIRE FilmArray-Meningitis/Encephalitis and QIAstat-dx meningitis/Encephalitis panel.

Potential CNS pathogen	Classification (genome type)	BioFIRE Filmrray-Meningitis/encephalitis	QIAstat-Dx Meningitis/Encephalitis
Escherichia coli K1	Bacterium (DNA)	X	X
Haemophilus influenzae	Bacterium (DNA)	X	X
Listeria monocytogenes	Bacterium (DNA)	X	X
Mycoplasma pneumonia	Bacterium (DNA)		X
Neisseria meningitidis	Bacterium (DNA)	X	X
Streptococcus agalacticae	Bacterium (DNA)	X	X
Streptococcus pneumoniae	Bacterium (DNA)	X	X
Streptococcus pyogenes	Bacterium (DNA)		X
Cytomegalovirus	Herpesvirus (DNA)	X
Herpes simplex virus 1	Herpesvirus (DNA)	X	X
Herpes simplex virus 2	Herpesvirus (DNA)	X	X
Human herpesvirus 6	Herpesvirus (DNA)	X	X
Enterovirus	Picornavirus (RNA)	X	X
Human parechovirus	Picornavirus (RNA)	X	X
Varicella zoster virus	Herpesvirus (DNA)	X	X
Cryptococcus neoformans/gattii	Yeast (DNA)	X	X

Table 2. Major studies implementing BioFIRE FilmArray-ME in resource-limited settings in which data on BioFIRE FilmArray-ME could be disaggregated. Diagnostic yield displayed excludes PCR detection of Cryptococcus neoformans that was concordant with conventional techniques (e.g. CSF CrAg testing) with higher sensitivity. This was to display a more representative diagnostic yield as some of the larger studies in Uganda included a high proportion of HIV-positive patients with cryptococcal meningitis.

	Criteria for CSF analysis with BioFIRE FilmArray-ME diagnostics	Number of samples analyzed	Number of patients with multiple pathogens detected in CSF	Diagnostic yield of molecular diagnostics (excluding Cryptococcus PCR detections)	Most commonly detected pathogens
Rhein et al., 2016 [82] Uganda	HIV positive individuals with suspected CNSI	69 25 negative for cryptococcosis 44 positive for cryptococcosis	2	7%	2.9% Varicella zoster virus 2.9% Cytomegalovirus 1.4% Human herpesvirus-6
Barnes et al., 2018 [83] Ethiopia	Any patient with suspected CNSI	218 216 negative for cryptococcosis 2 positive for cryptococcosis	0	9.2%	2.3% Human herpesvirus-6 1.4% Herpes simplex virus-1 0.9% Enterovirus
Tarai and Das, 2019 [85] India	Any patient with suspected CNSI	969 962 negative for cryptococcosis 7 positive for cryptococcosis*	1	9.6%	2.4% Enterovirus 1.0% Varicella zoster virus 0.9% Herpes simplex virus-1
Ellis et al., 2019 [11]. Uganda	HIV positive individuals with suspected CNSI and negative CSF CrAg and negative Xpert MTB/RIF Ultra	45 45 negative for cryptococcosis 0 positive for cryptococcosis	2	17.8%	4.4% Herpes simplex virus-1 All other detections occurred at same frequency
Pe$\tilde{n}$ata et al., 2020 [86] Colombia	Any patient with suspected CNSI	638 637 negative for cryptococcosis 11 positive for cryptococcosis	3	13.5%	2.5% Streptococcus pneumoniae 1.6% Herpes simplex virus-1 1.3% Varicella zoster virus
Bridge et al., 2021 [16] Uganda	HIV positive adults with suspected CNSI 106 with negative CSF CrAg and negative Xpert MTB/RIF Ultra 152 with positive CSF CrAg Any child with suspected CNSI	258 baseline/admission samples 106 negative for cryptococcosis 152 positive for cryptococcosis	26	21.3% in HIV positive adults 7.1% in children	4.7% Human herpesvirus-6 4.3% Cytomegalovirus 4.3% Streptococcus pneumoniae
Debbagh et al., 2023 [84] Morocco	Any patient with suspected CNSI admitted to intensive care unit	112 111 negative for cryptococcosis 1 positive for cryptococcosis	0	17.1%	8.0% Streptococcus pneumoniae 3.6% Herpes simplex virus-1 2.7% Haemophilus influenzae

*3 negative CSF CrAg tests. Cryptococcosis diagnosed through India ink or culture.

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