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ObjectivesTo summarize the clinical characteristics, outcomes and identify risk factors of Acinetobacter baumannii (AB) meningitis in children.MethodsThis was a single-center, retrospective study. Children hospitalized between January 2016 and December 2021 who were diagnosed with AB meningitis were included. The clinical characteristics and outcomes were reviewed. Risk factors were determined using univariate analyses (chi-square and Mann-Whitney U tests).ResultsSeventeen patients were included; 15 cases were secondary to neurosurgery, and two were neonates with primary bacterial meningitis. Common symptoms included fever, convulsions and nervous system abnormalities. Cerebrospinal fluid (CSF) tests typically showed increased white blood cell counts dominated by neutrophils, reduced glucose levels and elevated protein levels. Ten patients were successfully treated (successful treatment [ST] group); seven had failed treatment (failed treatment [FT] group). Univariate analyses revealed that mechanical ventilation, routine white cell counts in the peripheral blood, procalcitonin, protein in the CSF, septic shock and carbapenem-resistant AB (CRAB) differed significantly between the groups.ConclusionAB meningitis in children has a high mortality rate. FT was associated with mechanical ventilation, septic shock, CRAB, lower peripheral leukocyte counts, higher protein levels in the CSF and procalcitonin. Larger studies are needed to identify independent risk factors for adverse outcomes.

Objectives: Chronic hepatitis B (CHB) is associated with high morbidity and mortality. We aimed to investigate associations between hepatic histology and clinical characteristics in treatment-naïve children with CHB in Shanghai, China. Methods: The liver biopsy specimens of 278 treatment-naïve children with CHB virus infection were scored for inflammation and fibrosis, and correlations with clinical and laboratory data were determined. Results: CHB clinical, virologic, and pathologic features were studied in 278 treatment-naïve children (177 [63.7%] males) in Shanghai, China. Maternal sera were positive for hepatitis B surface antigen for 277 children. At biopsy, 87.4% of patients were hepatitis B e antigen–positive. The median age at biopsy was 5.1 years (interquartile range 2.8-8.4 years). Hepatitis B virus (HBV) deoxyribonucleic acid levels were generally high (mean 7.4 log10 IU/ml), as were levels of serum alanine aminotransferase (ALT, median 105 U/l). Using the Metavir histology activity index scoring system, no, mild, moderate, and severe inflammation were seen in 2.9%, 22.3%, 73.4%, and 1.4% of patients, respectively. No fibrosis, mild fibrosis, moderate fibrosis, and cirrhosis were seen in 11.5%, 32.7%, 47.5%, and 8.3% of patients, respectively. When the serum ALT level was ≤80 (two times the upper limit of normal) and >80 U/l, the inflammation score (P 3 years (P 80 U/l may be a strong indicator of the degree of hepatic inflammation and fibrosis severity. Moderate fibrosis and cirrhosis can appear in children aged 3 years or younger.

Background: Assessment of renal lesions and deficiency accurately remains critical in the diagnosis of congenital anomalies of the kidneys and urinary tracts (CAKUT) in children. Advanced imaging such as Magnetic resonance Imaging (MRI) and Diffusion weighted Imaging (DWI) allows structural and functional insufficiency to be detected. Currently, radiomics machine learning models are being explored as full-automated diagnostic tools. We aimed to develop a machine learning integrated radiomics model to predict renal anomalies and deficiency in children.Methods: A retrospective study of 280 children with MRI/DWI were enrolled between 2018 and 202 at a children’s hospital. A total of 1,037 radiomics features were extracted from the DWI images of each participant, which were divided into training set and test set (8:2 split). Using 5-fold cross-validated method, multiple machine learning algorithms were employed to predict renal lesions and deficiency when compared with the radiologist’s diagnosis based on DWI, 99mTc-labeled dimercaptosuccinic acid (DMSA) SPECT cortical renal scintigraphy or 99mTc-labeled diethylenetriamine pentaacetate (DTPA) renal scan.Results: For detecting the kidney lesions, the LASSO + Random Forest algorithm outperformed other classifiers with an accuracy of 0.750 (95% confidence interval, 0.734–0.766) and area under the curve (AUC) of 0.765 (95% confidence interval, 0.700–0.831). The performance of classifiers did not show a significant difference (p > 0.05) in detecting bilateral or unilateral kidney lesions by DWI scanning. The classifiers performed significantly better in bilateral kidney deficit than in unilateral kidney deficit (p < 0.05). We next built prediction models for renal deficiency using the radiomics signature and clinical features compared to renal scintigraphy. The ensemble model had a high-test accuracy of 80.9% ± 4.2% and a sensitivity of 91.7% ± 7.1% with a moderate calibration.Conclusion: An ensemble model integrated with DWI-radiomic and clinical features can be utilized to predict renal lesions and deficiency in children with CAKUT.

ABSTRACTBalamuthia amoebic encephalitis has a subacute-to-chronic course and is almost invariably fatal owing to delayed diagnosis and a lack of effective therapy. Here, we report a 13-year-old girl with cutaneous lesions and multifocal granulomatous encephalitis. The patient underwent a series of tests and was suspected as having tuberculosis. She was treated with various empiric therapies without improvement. She was finally correctly diagnosed via next-generation sequencing of the cerebrospinal fluid. The patient deteriorated rapidly and died 2 months after being diagnosed with Balamuthia mandrillaris encephalitis. This study highlights the important clinical significance of next-generation sequencing, which provides better diagnostic testing for unexplained paediatric encephalitis, especially that caused by rare or emerging pathogens.