ArticleBMC infectious diseases2026
Etiological characterization of acute respiratory tract infections and associated co-infections using Biofire respiratory 2.1 Plus panel.
Article in BMC infectious diseases, 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
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundFollowing the relaxation of non-pharmaceutical interventions post-COVID-19 pandemic, acute respiratory tract infections (ARTIs) have posed a substantial burden on healthcare settings, necessitating the implementation of rapid molecular diagnostic tools to improve pathogen identification and ensure early clinical management.
methodsWe conducted a retrospective study over one year (April 2024-March 2025) on 258 patients with ARTIs, admitted to a tertiary care hospital located in Egypt, to characterize their microbiological profile by Biofire respiratory 2.1 plus panel (RP 2.1). The demographic data and co-morbidities were systematically collected and analyzed from electronic medical records.
resultsOf 160 patients testing positive for at least one respiratory pathogen by RP2.1 plus, 147 (91.8%) were positive for viral pathogens, 8(5%) for mixed viral-bacterial detections, and 5(3.2%) for bacterial detections. Detection of a single respiratory pathogen was observed among 71.8% of cases, with a statistically significant difference during autumn (27%, p = 0.03), and co-detections with multiple pathogens were observed among 28.2% of patients. Human rhinovirus (HRV) was the most common detected virus (52.5%), followed by Parainfluenza virus 1-4 (PIV,16.9%), seasonal Coronavirus species (15.6%), severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2), and Influenza virus (INF) with equal frequency 10% each. Of 84 patients with HRV, 54 (64%) were infected with HRV only, and 30 (36%) had HRV co-detection. Patients with HRV co-detection were significantly more likely to be diagnosed with pneumonia than patients with HRV mono-detection (71.4% vs. 28.6%, p < 0.0001). Children in the age group less than 4 years old were more likely to be diagnosed with HRV co-detection than children with HRV only (60% versus 40% at p = 0.00). The most frequently detected respiratory pathogens with HRV were human coronavirus OC43 (4, 13.3%), followed by INFA (3,10%) and Mycoplasma pneumoniae (3,10%).
conclusionThe current surge of respiratory pathogens post-COVID-19 pandemic calls for continuous monitoring of seasonal as well as co-detection patterns to mitigate potential health care burden and guide targeted public health interventions. CLINICAL TRIAL NUMBER: Not applicable.
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.