ArticleBMC infectious diseases2026
Predicting societal risk factors for respiratory co-infections: a cross-sectional study based on multi-source fever clinic data.
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
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThis study aimed to analyze epidemiological characteristics, clinical manifestations, and socio- environmental risk factors of viral-mycoplasma mixed respiratory infections in children presenting at fever clinics, providing evidence for clinical decision-making.
methodsIn this cross-sectional study, we analyzed clinical data from 132 pediatric patients with respiratory co-infections confirmed by direct immunofluorescence assay at the Second Affiliated Hospital of Fujian University of Traditional Chinese Medicine (May 1, 2023 - April 30, 2024). Data collection included demographic characteristics, clinical symptoms, laboratory results, and pathogen profiles. Social behaviors and environmental factors were also evaluated. An age- and season-matched comparison group of 185 children with single respiratory infections was included. Statistical analyses involved t-tests, χ² tests, and multivariate logistic regression.
resultsThe majority of patients were aged 4-9 years (75.76%), with a male predominance (64.39%). Adenovirus was the most frequently detected pathogen (100 cases) and demonstrated the highest co-infection rate with Mycoplasma pneumoniae. Cases were primarily concentrated in the main urban area of Fuzhou City, notably in Jin'an (38 cases) and Gulou (34 cases) districts. The co-infection group had a significantly longer duration of fever than the single infection group (P < 0.001) and more severe systemic clinical manifestations. Laboratory parameters, including white blood cell, neutrophil, and C-reactive protein levels, were significantly elevated in the co-infection group (P < 0.05). Among environmental factors, both low ambient temperature (P < 0.001) and humidity (P = 0.011) were significantly associated with co-infection. Multivariate logistic regression analysis identified several independent risk factors for co-infection: Low ambient temperature (OR = 1.144), poor hand hygiene practices (OR = 3.4691), attendance at childcare facilities (OR = 2.042), recent family member infection history (OR = 1.989), and not having received the influenza vaccine (OR = 2.266).
conclusionsViral-mycoplasma co-infections in pediatric patients demonstrate distinct epidemiological patterns and more severe outcomes. Social behaviors and environmental factors represent pivotal risk factors, warranting targeted public health interventions during high-risk periods and in key locations.
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.