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BackgroundSerum neurofilament light chain (sNfL) is an established biomarker of neuro-axonal damage in multiple neurological disorders. Raised sNfL levels have been reported in adults infected with pandemic coronavirus disease 2019 (COVID-19). Levels in children infected with COVID-19 have not as yet been reported.ObjectiveTo evaluate whether sNfL is elevated in children contracting COVID-19.MethodsBetween May 22 and July 22, 2020, a network of outpatient pediatricians in Bavaria, Germany, the Coronavirus antibody screening in children from Bavaria study network (CoKiBa), recruited healthy children into a cross-sectional study from two sources: an ongoing prevention program for 1–14 years, and referrals of 1–17 years consulting a pediatrician for possible infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We determined sNfL levels by single molecule array immunoassay and SARS-CoV-2 antibody status by two independent quantitative methods.ResultsOf the 2652 included children, 148 (5.6%) were SARS-CoV-2 antibody positive with asymptomatic to moderate COVID-19 infection. Neurological symptoms—headache, dizziness, muscle aches, or loss of smell and taste—were present in 47/148 cases (31.8%). Mean sNfL levels were 5.5 pg/ml (SD 2.9) in the total cohort, 5.1 (SD 2.1) pg/ml in the children with SARS-CoV-2 antibodies, and 5.5 (SD 3.0) pg/ml in those without. Multivariate regression analysis revealed age—but neither antibody status, antibody levels, nor clinical severity—as an independent predictor of sNfL. Follow-up of children with pediatric multisystem inflammatory syndrome (n = 14) showed no association with sNfL.ConclusionsIn this population study, children with asymptomatic to moderate COVID-19 showed no neurochemical evidence of neuronal damage.

The myotropic effects of growth hormone (GH) have long been known. An excess of GH as in acromegaly, causes various problems within the circulatory system including cardiac hypertrophy. Although the latter has not been reported as a complication of GH therapy in children, we assessed this possibility in 54 children. Ninety-six echocardiographic studies were performed, in which bisectional images were analysed by Simpson's rule to determine left ventricular volume and mass. Of special interest were 47 results obtained from girls with Ullrich-Turner-syndrome (UTS) treated with supraphysiological doses of GH. Our results showed a significant increase of the myocardial mass in children on GH therapy compared with untreated children, as well as a dose related effect of GH on cardiac mass in girls and cardiac volume in boys. No cardiac hypertrophy, however, could be observed; the increase in muscular mass merely amounting to a normalization of previously low values. [PUBLICATION ABSTRACT]

The myotropic effects of growth hormone (GH) have long been known. An excess of GH as in acromegaly, causes various problems within the circulatory system including cardiac hypertrophy. Although the latter has not been reported as a complication of GH therapy in children, we assessed this possibility in 54 children. Ninety-six echocardiographic studies were performed, in which bisectional images were analysed by Simpson's rule to determine left ventricular volume and mass. Of special interest were 47 results obtained from girls with Ullrich-Turner-syndrome (UTS) treated with supraphysiological doses of GH. Our results showed a significant increase of the myocardial mass in children on GH therapy compared with untreated children, as well as a dose related effect of GH on cardiac mass in girls and cardiac volume in boys. No cardiac hypertrophy, however, could be observed; the increase in muscular mass merely amounting to a normalization of previously low values.

Background The integration of real-world evidence (RWE) from real-world data (RWD) in clinical research is crucial for bridging the gap between clinical trial results and real-world outcomes. Analyzing routinely collected data to generate clinical evidence faces methodological concerns like confounding and bias, similar to prospectively documented observational studies. This study focuses on additional limitations frequently reported in the literature, providing an overview of the challenges and biases inherent to analyzing routine clinical care data, including health claims data (hereafter: routine data). Methods We conducted a literature search on routine data studies in four high-impact journals based on the Journal Citation Reports (JCR) category “Medicine, General & Internal” as of 2022 and three oncology journals, covering articles published from January 2018 to October 2023. Articles were screened and categorized into three scenarios based on their potential to provide meaningful RWE: (1) Burden of Disease, (2) Safety and Risk Group Analysis, and (3) Treatment Comparison. Limitations of this type of data cited in the discussion sections were extracted and classified according to different bias types: main bias categories in non-randomized studies (information bias, reporting bias, selection bias, confounding) and additional routine data-specific challenges (i.e., operationalization, coding, follow-up, missing data, validation, and data quality). These classifications were then ranked by relevance in a focus group meeting of methodological experts. The search was pre-specified and registered in PROSPERO (CRD42023477616). Results In October 2023, 227 articles were identified, 69 were assessed for eligibility, and 39 were included in the review: 11 on the burden of disease, 17 on safety and risk group analysis, and 11 on treatment comparison. Besides typical biases in observational studies, we identified additional challenges specific to RWE frequently mentioned in the discussion sections. The focus group had varied opinions on the limitations of Safety and Risk Group Analysis and Treatment Comparison but agreed on the essential limitations for the Burden of Disease category. Conclusion This review provides a comprehensive overview of potential limitations and biases in analyzing routine data reported in recent high-impact journals. We highlighted key challenges that have high potential to impact analysis results, emphasizing the need for thorough consideration and discussion for meaningful inferences.

Background Telemedicine improves the quality of acute stroke care in rural regions with limited access to specialized stroke care. We report the first 2 years’ experience of implementing a comprehensive telemedical stroke network comprising all levels of stroke care in a defined region. Methods The TRANSIT-Stroke network covers a mainly rural region in north-western Bavaria (Germany). All hospitals providing acute stroke care in this region participate in TRANSIT-Stroke, including four hospitals with a supra-regional certified stroke unit (SU) care (level III), three of those providing teleconsultation to two hospitals with a regional certified SU (level II) and five hospitals without specialized SU care (level I). For a two-year-period (01/2015 to 12/2016), data of eight of these hospitals were available; 13 evidence-based quality indicators (QIs) related to processes during hospitalisation were evaluated quarterly and compared according to predefined target values between level-I- and level-II/III-hospitals. Results Overall, 7881 patients were included (mean age 74.6 years ±12.8; 48.4% female). In level-II/III-hospitals adherence of all QIs to predefined targets was high ab initio. In level-I-hospitals, three patterns of QI-development were observed: a) high adherence ab initio (31%), mainly in secondary stroke prevention; b) improvement over time (44%), predominantly related to stroke specific diagnosis and in-hospital organization; c) no clear time trends (25%). Overall, 10 out of 13 QIs reached predefined target values of quality of care at the end of the observation period. Conclusion The implementation of the comprehensive TRANSIT-Stroke network resulted in an improvement of quality of care in level-I-hospitals.