Early-onset epileptic encephalopathy (EE) and combined developmental and epileptic encephalopathies (DEE) are clinically and genetically heterogeneous severely devastating conditions. Recent studies emphasized de novo variants as major underlying cause suggesting a generally low-recurrence risk. In order to better understand the full genetic landscape of EE and DEE, we performed high-resolution chromosomal microarray analysis in combination with whole-exome sequencing in 63 deeply phenotyped independent patients. After bioinformatic filtering for rare variants, diagnostic yield was improved for recessive disorders by manual data curation as well as molecular modeling of missense variants and untargeted plasma-metabolomics in selected patients. In total, we yielded a diagnosis in ∼42% of cases with causative copy number variants in 6 patients (∼10%) and causative sequence variants in 16 established disease genes in 20 patients (∼32%), including compound heterozygosity for causative sequence and copy number variants in one patient. In total, 38% of diagnosed cases were caused by recessive genes, of which two cases escaped automatic calling due to one allele occurring de novo. Notably, we found the recessive gene SPATA5 causative in as much as 3% of our cohort, indicating that it may have been underdiagnosed in previous studies. We further support candidacy for neurodevelopmental disorders of four previously described genes (PIK3AP1, GTF3C3, UFC1, and WRAP53), three of which also followed a recessive inheritance pattern. Our results therefore confirm the importance of de novo causative gene variants in EE/DEE, but additionally illustrate the major role of mostly compound heterozygous or hemizygous recessive inheritance and consequently high-recurrence risk.

There are no reliable signs or symptoms that differentiate Mycoplasma pneumoniae (Mp) infection in community-acquired pneumonia (CAP) from other etiologies. Additionally, current diagnostic tests do not reliably distinguish between Mp infection and carriage. We previously determined that the measurement of Mp-specific immunoglobulin M antibody-secreting cells (ASCs) by enzyme-linked immunospot assay allowed for differentiation between infection and carriage. Using this new diagnostic test, we aimed to identify clinical and laboratory features associated with Mp infection. This is a prospective cohort study of children, 3–18 years of age, with CAP from 2016 to 2017. Clinical features and biomarkers were compared between Mp-positive and -negative groups by Mann-Whitney U test or Fisher exact test, as appropriate. Area under the receiver operating characteristic curve (AUC) differences and optimal thresholds were determined by using the DeLong test and Youden J statistic, respectively. Of 63 CAP patients, 29 were Mp-positive (46%). Mp positivity was statistically associated with older age (median, 8.6 vs 4.7 years), no underlying disease, family with respiratory symptoms, prior antibiotic treatment, prolonged prodromal respiratory symptoms and fever, and extrapulmonary (skin) manifestations. Lower levels of C-reactive protein, white blood cell count, absolute neutrophil count, and procalcitonin (PCT), specifically PCT 5 years (AUC = 0.77), prodromal fever and respiratory symptoms >6 days (AUC = 0.79), and PCT <0.25 μg/L (AUC = 0.81) improved diagnostic performance (AUC = 0.90) (P = .05). A combination of clinical features and biomarkers may aid physicians in identifying patients at high risk for Mp CAP.

Background: Research into artificial intelligence (AI)-based fracture detection in children is scarce and has disregarded the detection of indirect fracture signs and dislocations. Objective: To assess the diagnostic accuracy of an existing AI-tool for the detection of fractures, indirect fracture signs, and dislocations. Materials and methods: An AI software, BoneView (Gleamer, Paris, France), was assessed for diagnostic accuracy of fracture detection using paediatric radiology consensus diagnoses as reference. Radiographs from a single emergency department were enrolled retrospectively going back from December 2021, limited to 1,000 radiographs per body part. Enrolment criteria were as follows: suspected fractures of the forearm, lower leg, or elbow; age 0–18 years; and radiographs in at least two projections. Results: Lower leg radiographs showed 607 fractures. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were high (87.5%, 87.5%, 98.3%, 98.3%, respectively). Detection rate was low for toddler’s fractures, trampoline fractures, and proximal tibial Salter-Harris-II fractures. Forearm radiographs showed 1,137 fractures. Sensitivity, specificity, PPV, and NPV were high (92.9%, 98.1%, 98.4%, 91.7%, respectively). Radial and ulnar bowing fractures were not reliably detected (one out of 11 radial bowing fractures and zero out of seven ulnar bowing fractures were correctly detected). Detection rate was low for styloid process avulsions, proximal radial buckle, and complete olecranon fractures. Elbow radiographs showed 517 fractures. Sensitivity and NPV were moderate (80.5%, 84.7%, respectively). Specificity and PPV were high (94.9%, 93.3%, respectively). For joint effusion, sensitivity, specificity, PPV, and NPV were moderate (85.1%, 85.7%, 89.5%, 80%, respectively). For elbow dislocations, sensitivity and PPV were low (65.8%, 50%, respectively). Specificity and NPV were high (97.7%, 98.8%, respectively). Conclusions: The diagnostic performance of BoneView is promising for forearm and lower leg fractures. However, improvement is mandatory before clinicians can rely solely on AI-based paediatric fracture detection using this software. Graphical

Background: Factors leading to the wide range of manifestations associated with Mycoplasma pneumoniae (Mp) infection are unclear. We investigated whether Mp genotypes are associated with specific clinical outcomes. Methods: We compared Mp loads and genotypes of children with mucocutaneous disease to those with pneumonia, family members with upper respiratory tract infection (URTI), and carriers from a prospective cohort study (n=47; 2016–2017), and to other children with mucocutaneous disease from a case series (n=7; 2017–2020). Genotyping was performed using macrolide resistance determination, P1 subtyping, multilocus variable-number tandem-repeat analysis (MLVA), and multilocus sequence typing (MLST). Comparisons were performed with pairwise Wilcoxon rank sum test and Fisher exact test with corrections for multiple testing, as appropriate. Results:Mp loads did not statistically differ between patients with mucocutaneous disease and pneumonia or carriers. Macrolide resistance was detected in 1 (1.9%) patient with mucocutaneous disease. MLVA types from 2016–2017 included 3–5–6–2 (n=21, 46.7%), 3–6–6–2 (n=2, 4.4%), 4–5–7–2 (n=14, 31.1%), and 4–5–7–3 (n=8, 17.8%), and they correlated with P1 subtypes and MLST types. MLVA types were not associated with specific outcomes such as mucocutaneous disease, pneumonia, URTI, or carriage. They were almost identical within families, but varied over geographic location. MLVA types in patients with mucocutaneous disease differed between 2016–2017 (3–5–6–2, n=5, 62.5%) and 2017–2020 (4–5–7–2, n=5, 71.4%) (P=0.02). Conclusions: Our results suggest that Mp genotypes may not determine specific clinical outcomes.