ArticleItalian journal of pediatrics2024
The epidemiology and the pathogen distribution of pediatric dacryocystitis in Chinese population 2017-2022.
Article in Italian journal of pediatrics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed, 4 citations in OpenAlex.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundDacryocystitis is a common disease in pediatric ophthalmology. Analysis of basic information, flora distribution, and characteristics of information on drug-resistant bacteria in children with dacryocystitis for 6 years, providing evidence for ophthalmologic infection prevention and clinical management strategies.
methodsA retrospective cohort study was conducted to evaluate the demographics of dacryocystitis in children and microbiological characteristics of secretion cultures, and to analyze the basic information, distribution of pathogenic bacteria, drug resistance, and to plot trendsand distribution pie charts according to the years.
resultsThis study recruited 5791 specimens. Decreased incidence of dacryocystitis from 2020 to 2022 (including the COVID-19 pandemic). The age of highest incidence of dacryocystitis is infancy, followed by the neonatal period, and the incidence decreased with age. Streptococcus pneumoniae had the highest percentage in 2017, and the overall trend was decreasing, the difference was statistically significant (p < 0.001); Streptococcus mitis showed an overall increasing trend, with the highest incidence in 2022 and the lowest in 2017, with a statistically significant difference (p < 0.001); Haemophilus influenzae was the most common gram-negative bacteria with an overall decreasing trend (p < 0.001); The incidence of Catamoeba and Stenotrophomonas varied from year to year, with statistically significant differences (p = 0.010, p = 0.033, respectively). Methicillin-resistant Staphylococcus aureus (MRSA) had the lowest incidence in 2017 and 2022 the highest incidence in 2022, with a statistically significant difference in incidence between years (p = 0.003); β-lactamase-positive was the most common type of resistance, and MRSA was the second, with statistically significant differences between years (p = 0.003, p < 0.001, respectively). Streptococcus pneumoniae is a common etiologic agent of dacryocystitis in all age groups.
conclusionsDacryocystitis in children is significantly associated with age characteristics and infection-related pathogens, and infection prevention and control can help reduce the infection of related pathogens and the increase of new drug-resistant strains. Close monitoring of changes in pathogen distribution in ocular secretion cultures can help in early intervention and treatment of infectious dacryocystitis.
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.