Neurological manifestations and risk factors associated with poor prognosis in hospitalized children with Omicron variant infection.

There are increasing reports of neurological manifestation in children with coronavirus disease 2019 (COVID-19). However, the frequency and clinical outcomes of in hospitalized children infected with the Omicron variant are unknown. The aim of this study was to describe the clinical characteristics, neurological manifestations, and risk factor associated with poor prognosis of hospitalized children suffering from COVID-19 due to the Omicron variant. Participants included children older than 28 days and younger than 18 years. Patients were recruited from December 10, 2022 through January 5, 2023. They were followed up for 30 days. A total of 509 pediatric patients hospitalized with the Omicron variant infection were recruited into the study. Among them, 167 (32.81%) patients had neurological manifestations. The most common manifestations were febrile convulsions (n = 90, 53.89%), viral encephalitis (n = 34, 20.36%), epilepsy (n = 23, 13.77%), hypoxic-ischemic encephalopathy (n = 9, 5.39%), and acute necrotizing encephalopathy (n = 6, 3.59%). At discharge, 92.81% of patients had a good prognosis according to the Glasgow Outcome Scale (scores ≥ 4). However, 7.19% had a poor prognosis. Eight patients died during the follow-up period with a cumulative 30-day mortality rate of 4.8% (95% confidence interval (CI) 1.5-8.1). Multivariate analysis revealed that albumin (odds ratio 0.711, 95% CI 0.556-0.910) and creatine kinase MB (CK-MB) levels (odds ratio 1.033, 95% CI 1.004-1.063) were independent risk factors of poor prognosis due to neurological manifestations. The area under the curve for the prediction of poor prognosis with albumin and CK-MB was 0.915 (95%CI 0.799-1.000), indicating that these factors can accurately predict a poor prognosis.          Conclusion: In this study, 32.8% of hospitalized children suffering from COVID-19 due to the Omicron variant infection experienced neurological manifestations. Baseline albumin and CK-MB levels could accurately predict poor prognosis in this patient population. What is Known: • Neurological injury has been reported in SARS-CoV-2 infection; compared with other strains, the Omicron strain is more likely to cause neurological manifestations in adults. • Neurologic injury in adults such as cerebral hemorrhage and epilepsy has been reported in patients with Omicron variant infection. What is New: • One-third hospitalized children with Omicron infection experience neurological manifestations, including central nervous system manifestations and peripheral nervous system manifestations. • Albumin and CK-MB combined can accurately predict poor prognosis (AUC 0.915), and the 30-day mortality rate of children with Omicron variant infection and neurological manifestations was 4.8%.

Machine learning versus multivariate logistic regression for predicting severe COVID-19 in hospitalized children with Omicron variant infection.

With the emergence of the Omicron variant, the number of pediatric Coronavirus Disease 2019 (COVID-19) cases requiring hospitalization and developing severe or critical illness has significantly increased. Machine learning and multivariate logistic regression analysis were used to predict risk factors and develop prognostic models for severe COVID-19 in hospitalized children with the Omicron variant in this study. Of the 544 hospitalized children including 243 and 301 in the mild and severe groups, respectively. Fever (92.3%) was the most common symptom, followed by cough (79.4%), convulsions (36.8%), and vomiting (23.2%). The multivariate logistic regression analysis showed that age (1-3 years old, odds ratio (OR): 3.193, 95% confidence interval (CI): 1.778-5.733], comorbidity (OR: 1.993, 95% CI:1.154-3.443), cough (OR: 0.409, 95% CI:0.236-0.709), and baseline neutrophil-to-lymphocyte ratio (OR: 1.108, 95% CI: 1.023-1.200), lactate dehydrogenase (OR: 1.993, 95% CI: 1.154-3.443), blood urea nitrogen (OR: 1.002, 95% CI: 1.000-1.003) and total bilirubin (OR: 1.178, 95% CI: 1.005-3.381) were independent risk factors for severe COVID-19. The area under the curve (AUC) of the prediction models constructed by multivariate logistic regression analysis and machine learning (RandomForest + TomekLinks) were 0.7770 and 0.8590, respectively. The top 10 most important variables of random forest variables were selected to build a prediction model, with an AUC of 0.8210. Compared with multivariate logistic regression, machine learning models could more accurately predict severe COVID-19 in children with Omicron variant infection.

[Analysis of a novel JAG1 variant and clinical phenotype in a family affected with Alagille syndrome].

OBJECTIVE: To explore the genetic basis of a pedigree affected with Alagille syndrome (ALGS). METHODS: Targeted capture and next generation sequencing was carried out for the proband. Candidate variants were verified by Sanger sequencing among his family members. Their pathogenicity of the variant was predicted with bioinformatic analysis. Clinical characteristics and genotype-phenotype correlation were analyzed. RESULTS: The proband, his elder sister and mother were found to carry a heterozygous c.1270dupG (p.Ala424Glyfs*5) variant of the JAG1 gene, which may lead to premature termination of translation and a truncated protein with loss of function. The variant was unreported previously. The phenotypes of the proband (cholestasis, pulmonary artery stenosis and peculiar faces) have differed from those of his elder sister (cholestasis with pruritus, posterior embryonic ring of cornea) and mother (with no clinical manifestation). Cholestasis and peculiar face of the proband became insignificant with age. CONCLUSION: The c.1270dupG (p.Ala424Glyfs*5) variant of the JAG1 gene probably underlay the ALGS in this pedigree with incomplete penetrance.

The global prevalence ptxP3 lineage of Bordetella pertussis was rare in young children with the co-purified aPV vaccination: a 5 years retrospective study.

BACKGROUND: The global prevalent ptxP3 strains varies from about 10% to about 50% of circulating B. pertussis population in different areas of China. METHODS: To investigate the difference of vaccination status between different genotypes in the circulating B. pertussis after 10 years of acellular pertussis vaccine (aPV) used in China. The nasopharyngeal swabs and isolates of B. pertussis from these patients were used to perform genotyping of antigen genes. We use antibiotic susceptibility test against erythromycin and sequencing methods for site 2047 of 23S rRNA to determine the resistance status. RESULTS: The ptxP1 allele with erythromycin resistant (ER) B. pertussis infection (total of 449 subjects) consisted of 84.70 to 96.70% from 2012 to 2016 in this study. Vaccinated with co-purified aPV was found in 133(133/403,33.0%), 1(1/9,11.1%) and 2(2/21,9.5%) in ptxP1/fhaB3-ER, ptxP1/fhaB2-ES and ptxP3/fhaB2-ES B. pertussis infected children each, which showed a significant difference (χ2 = 6.87, P = 0.032). CONCLUSIONS: The ptxP3-ES B. pertussis was rare while the ptxP1-ER B. pertussis was steadily increased in Xi'an, China from 2012 to 2016, where co-purified aPV was prevalent used. This pose a hypothesis that the co-purified aPV might protect against ptxP3 strains more efficient, which generated a rare chance for ptxP3 strains to be under the antibiotic pressure and further developed to be erythromycin resistance. A further cohort study and the mechanisms of the additional antigen proteins of co-purified aPV protected against B. pertussis should be consideration.

Comparison of Pulmonary Artery Pressure Measurement With Doppler Echocardiography or With Right Heart Catheterization in Patients With Congenital Heart Disease.

Background: Doppler echocardiography (D-ECHO) is a commonly used imaging tool for both diagnosis and follow-up examination of congenital heart disease (CHD). The goal of this study is to evaluate the accuracy of D-ECHO as used to measure an estimate sPAP in pediatric patients with CHD. Methods: A prospective study in 397 pediatric patients with CHD has been carried out to compare estimate sPAP measured with D-ECHO to that measured with right heart catheterization (RHC). Pearson correlation analyses were used to calculate the correlation coefficients between RHC and D-ECHO. Bland-Altman analyses were carried out to assess the agreement between the two methods. Results: Our data have demonstrated a significant underestimation of sPAP by D-ECHO compared to that by RHC. A strong correlation (r = 0.957, p < 0.01) was found between sPAP (36.1 ± 14.9 mmHg) and RVSP (36.0 ± 14.5 mmHg) measured with RHC. However, a relatively weak correlation (r = 0.219, p < 0.01) was observed between sPAP (36.1 ± 14.9 mmHg) measured during RHC and sPAP (28.7 ± 9.7 mmHg) as estimated using D-ECHO. The Bland-Altman analysis demonstrated that the bias for D-ECHO sPAP estimates was 6.6 mmHg with 95% limits of agreement ranging from -23.6 to 36.8 mmHg. A total of 57.5% of D-ECHO measurements were found to be accurate, with accuracy predefined as 95% of agreement within ±10 mmHg for sPAP estimates. Conclusions: sPAP measured with D-ECHO may be underestimated in pediatric patients with CHD.

Rate-dependent phase transitions in Li2FeSiO4 cathode nanocrystals.

Nanostructured lithium metal orthosilicate materials hold a lot of promise as next generation cathodes but their full potential realization is hampered by complex crystal and electrochemical behavior. In this work Li2FeSiO4 crystals are synthesized using organic-assisted precipitation method. By varying the annealing temperature different structures are obtained, namely the monoclinic phase at 400°C, the orthorhombic phase at 900°C, and a mixed phase at 700°C. The three Li2FeSiO4 crystal phases exhibit totally different charge/discharge profiles upon delithiation/lithiation. Thus the 400°C monoclinic nanocrystals exhibit initially one Li extraction via typical solid solution reaction, while the 900°C orthorhombic crystals are characterized by unacceptably high cell polarization. In the meantime the mixed phase Li2FeSiO4 crystals reveal a mixed cycling profile. We have found that the monoclinic nanocrystals undergo phase transition to orthorhombic structure resulting in significant progressive deterioration of the material's Li storage capability. By contrast, we discovered when the monoclinic nanocrystals are cycled initially at higher rate (C/20) and subsequently subjected to low rate (C/50) cycling the material's intercalation performance is stabilized. The discovered rate-dependent electrochemically-induced phase transition and stabilization of lithium metal silicate structure provides a novel and potentially rewarding avenue towards the development of high capacity Li-ion cathodes.