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1.
BMC Infect Dis ; 23(1): 856, 2023 Dec 06.
Article in English | MEDLINE | ID: mdl-38057734

ABSTRACT

BACKGROUND: The neurological symptoms caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are of increasing concern. Convulsions are among the main neurological manifestations reported in children with coronavirus disease-2019 (COVID-19), and cause serious harm to physical and mental health. This study aimed to investigate the risk factors for convulsion in children with COVID-19. METHODS: This prospective study was conducted at the Children's Hospital of Soochow University. In total, 102 COVID-19 patients with convulsion, 172 COVID-19 patients without convulsion, and 50 healthy controls were enrolled in the study. The children's clinical and laboratory data were analyzed to assess the risk factors for convulsion in COVID-19 patients. RESULTS: Convulsions occurred in 37.2% of children, mostly those aged 1-3 years, who were hospitalized with the Omicron variant. The neutrophil count, neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), platelet-to-lymphocyte ratio (PLR), and mean platelet volume-to-platelet ratio (MPR) were significantly higher in the convulsion group than those in the non-convulsion and control groups (P < 0.01). However, the counts of lymphocytes, eosinophils, platelets, lymphocyte subsets, CD3+ T cells, CD4+ T cells, CD8+ T cells, and NK cells were lower in the convulsion group than those in the non-convulsion and control groups (P < 0.01). Multivariate regression analysis indicated that NK cell count (OR = 0.081, 95% CI: 0.010-0.652) and a history of febrile seizure (OR = 10.359, 95% CI: 2.115-50.746) were independent risk factors for the appearance of convulsions in COVID-19. CONCLUSIONS: History of febrile seizure and decreased NK cell count were high-risk factors for convulsions in COVID-19 patients.


Subject(s)
COVID-19 , Seizures, Febrile , Child , Humans , COVID-19/complications , SARS-CoV-2 , CD8-Positive T-Lymphocytes , Seizures, Febrile/etiology , Prospective Studies , Leukocyte Count , Lymphocyte Count , Killer Cells, Natural , Neutrophils , Risk Factors , Retrospective Studies
2.
Klin Padiatr ; 235(4): 221-227, 2023 Jul.
Article in English | MEDLINE | ID: mdl-37116540

ABSTRACT

OBJECTIVE: This study aims to explore the ability of adenosine deaminase (ADA) to discriminate atypical Epstein Barr virus (EBV) infection in children from acute febrile illness. METHODS: All children admitted to the Children's Hospital of Soochow University between 2018 and 2019, who were acute febrile patients and subjected to the plasma EBV-DNA polymerase chain reaction (PCR) and indirect immunofluorescence (IIF) assay for EBV-specific antibodies assays. The diagnostic value of each detection index was compared by the area under the ROC curve. RESULTS: In children with atypical Epstein Barr virus infection, the sensitivity, specificity, positive predictive value, negative predictive value and Youden index were 62.87%, 100.00%,100.00%, 61.73% and 0.63 for EBV-DNA PCR assay, 80.84%, 100.00%, 100.00%, 75.76% and 0.81 for VCA-IgG avidity and 89.22%, 87.00%, 91.98%, 82.86% and 0.76 for ADA. VCA-IgG avidity (AUC=0.904, P<0.01) and ADA (AUC=0.881, P<0.01) assays had the great diagnostic efficiency. In addition, the sensitivity, specificity and AUC were 92.75%,91.43% and 0.921(95%CI: 0.856-0.985) for ADA in the course≤3 days group, respectively. CONCLUSIONS: ADA has a good diagnostic value in the early stage of atypical EBV infection, and is not affected by primary EBV infection and reactivation. SCHLüSSELWöRTER: Adenosine deaminase, Epstein -Barr virus, Biomarker, children.


Subject(s)
Epstein-Barr Virus Infections , Humans , Child , Epstein-Barr Virus Infections/diagnosis , Herpesvirus 4, Human/genetics , Adenosine Deaminase , Antibodies, Viral , Immunoglobulin G , Biomarkers , DNA
3.
BMC Pediatr ; 23(1): 69, 2023 02 09.
Article in English | MEDLINE | ID: mdl-36759812

ABSTRACT

BACKGROUND: The early diagnosis and treatment of bacterial meningitis (BM) in young infants was very critical. But, it was difficult to make a definite diagnosis in the early stage due to nonspecific clinical symptoms. Our objectives were to find the risk factors associated with BM and develop a prediction model of BM especially for young infants. METHODS: We retrospectively reviewed the clinical data of young infants with meningitis between January 2011 and December 2020 in Children's Hospital of Soochow University. The independent risk factors of young infants with BM were screened using univariate and multivariate logistic regression analyses. The independent risk factors were used to construct a new scoring model and compared with Bacterial Meningitis Score (BMS) and Meningitis Score for Emergencies (MSE) models. RESULTS: Among the 102 young infants included, there were 44 cases of BM and 58 of aseptic meningitis. Group B Streptococcus (22, 50.0%) and Escherichia coli (14, 31.8%) were the main pathogens of BM in the young infants. Multivariate logistic regression analysis identified procalcitonin (PCT), cerebrospinal fluid (CSF) glucose, CSF protein as independent risk factors for young infants with BM. We assigned one point for CSF glucose ≤ 1.86 mmol/L, two points were assigned for PCT ≥ 3.80 ng/ml and CSF protein ≥ 1269 mg/L. Using the not low risk criterion (score ≥ 1) with our new prediction model, we identified the young infantile BM with 100% (95% CI 91.9%-100%) sensitivity and 60.3% (95% CI 46.4%-72.9%) specificity. Compared with BMS and MSE model, our prediction model had larger area under receiver operating characteristic curve and higher specificity, the differences were statistically significant. CONCLUSION: Our new scoring model for young infants can facilitate early identification of BM and has a better performance than BMS and MSE models.


Subject(s)
Meningitis, Bacterial , Child , Humans , Infant , Retrospective Studies , Diagnosis, Differential , Meningitis, Bacterial/microbiology , ROC Curve , Procalcitonin , Glucose , Sensitivity and Specificity
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