ArticleMicroorganisms2026
Analytical Performance and Clinical Evaluation of a Fully Automated Multiplex RT-qPCR Platform for Rapid Detection of Central Nervous System Pathogens.
Article in Microorganisms, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Meningitis and encephalitis necessitate rapid pathogen identification to guide therapy, as conventional methods are time-consuming. This study evaluated both the wet-lab analytical performance and the clinical performance evaluation of the Bioeksen Meningitis/Encephalitis Panel (BS-MEP) integrated onto the fully automated, high-throughput Sigmoida Lab platform. Analytical limits of detection (LoD) were defined via Probit analysis (95% threshold) by spiking negative cerebrospinal fluid (CSF) matrices. Target detection was verified using characterized reference materials for all 14 analytes, and in silico primer/probe coverage was assessed against taxon-specific sequence databases. Cross-reactivity was evaluated using high-prevalence non-target organisms. Clinical performance was evaluated retrospectively using 500 archived, anonymized CSF specimens from a single-center repository, with analyte-specific classifications compared with prespecified routine comparator methods. The automated platform provided an 80-min sample-to-result turnaround for up to 23 samples. Verified LoDs ranged from 472 to 2118 genome copies/mL. All inclusivity strains were successfully detected in 5/5 replicates. In silico coverage exceeded 98% combined, and zero wet-lab cross-reactivity was observed. Precision coefficients of variation (CVs) were consistently ≤1.38%. In the clinical evaluation, the pooled clinical agreement was high, with PPA ranging from 90.9% to 100% and NPA of 100% across the evaluated analytes. Analyte-level clinical sensitivity ranged from 90.9% to 100%, with zero false-positive results across all targets. The fully automated molecular system demonstrates excellent analytical robustness and strong clinical agreement for syndromic detection of major CNS pathogens. The automated workflow combines broad pathogen coverage with an approximately 80-min sample-to-result turnaround and warrants further prospective evaluation in routine clinical settings.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.