ArticleBMC pediatrics2024
Coinfection of viruses in children with community-acquired pneumonia.
Article in BMC pediatrics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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
10 citing papers in PubMed.
- Application of targeted next-generation sequencing in children with community-acquired pneumonia.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2026Article
- Predicting societal risk factors for respiratory co-infections: a cross-sectional study based on multi-source fever clinic data.BMC infectious diseases · 2026Article
- Clinical characteristics, co-detection patterns and prognostic risk factors of human metapneumovirus infection in children: a retrospective study.Frontiers in cellular and infection microbiology · 2026Article
- Epidemiology of viral and atypical bacterial respiratory infections among children hospitalised at a Kenyan tertiary referral centre: a cross sectional multiplex PCR study.Frontiers in pediatrics · 2026Article
- Laboratory characteristics and immune-inflammatory profiles ofFrontiers in pediatrics · 2026Article
- Inflammatory Mediation of the Association Between Latent Clinical Phenotypes and Multidimensional Outcomes in Pediatric Community-Acquired Pneumonia.Journal of inflammation research · 2026Article
- Identification of clinical phenotypes and prediction model for the mixed-infection phenotype of pediatric community-acquired pneumonia based on unsupervised machine learning.Frontiers in pediatrics · 2026Article
- Respiratory virus genomic epidemiology during post-pandemic re-emergence of influenza in Australia.Virus evolution · 2026Article
- Predictive value of serological markers and immune indicators combined with early warning scoring system for prognosis in pediatric acute respiratory infections.Journal of medical biochemistry · 2025Article
- Surge in Mycoplasma Pneumoniae infection and Respiratory Viruses Co-infection in Children With Community-Acquired Pneumonia in the Post-Pandemic.Pediatric health, medicine and therapeutics · 2024Article
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
backgroundVirus, particularly respiratory tract virus infection is likely to co-occur in children with community-acquired pneumonia (CAP). Study focusing on the association between common viruses coinfection and children with CAP is rare. We aimed to study the association between seven common viruses coinfection and clinical/laboratory indexes in children with CAP.
methodsSix hundred and eighty-four CAP cases from our hospital were enrolled retrospectively. Seven common viruses, including influenza A (FluA), influenza B (FluB), human parainfluenza virus (HPIV), Esptein-Barr virus (EBV), coxsackie virus (CoxsV), cytomegalovirus (CMV), and herpes simplex virus (HSV) were investigated for their associations with CAP. We analyzed the differences of hospitalization days, white blood cell (WBC), c-reactive protein (CRP), platelet (PLT), erythrocyte sedimentation rate (ESR), procalcitonin (PCT), urine red blood cell (uRBC), blood urea nitrogen (BUN), serum creatinine (Scr), alanine aminotransferase (ALT), aspartate aminotransferase (AST), lactate dehydrogenase (LDH), creatine kinase (CK) and creatine kinase isoenzyme (CKMB) among different viruses coinfection groups by using one-way ANOVA analysis. The differences of clinical/laboratory indexes between ordinary and severe pneumonia groups, as well as non-virus vs multi co-infection viruses groups, and single vs multi co-infection viruses groups by using independent samples T test. Receiver operating characteristic (ROC) curve analyses were applied to test the the predictive value of the clinical/laboratory parameters for the risk of viruses coinfections among CAP. Binary logistic analysis was performed to test the association between various indexes and viruses co-infection.
resultsEighty-four multiple viruses coinfections yielded different prognosis compared with that in 220 single virus coinfection. CMV coinfection was associated with longest hospitalization days, highest ALT, AST and CKMB level. HSV coinfection was associated with highest WBC count, CRP, ESR, and BUN. EBV coinfection was associated with highest PLT and PCT level. FluB coinfection was associated with highest Scr level. CoxsV coinfection was associated with highest uRBC, LDH and CK level. ROC curve analyses showed that CK had the largest area under the curve (AUC: 0.672, p < 10
conclusionsMultiple viruses coinfections indicated different prognosis. Different viruses coinfection yielded varying degrees of effects on the cardiac, liver, kidney and inflamatory injury in CAP. The alterations of clinical/laboratory parameters, particularly CK may be associated with the risk of viruses coinfections in CAP.
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.