60 research outputs found

    Admission rates and clinical profiles of children and youth with eating disorders treated as inpatients before and during the COVID-19 pandemic in a German university hospital

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    IntroductionChildren and youth at risk for mental health disorders, such as eating disorders (ED), were particularly affected by the COVID-19 pandemic, yet evidence for the most seriously affected and thus hospitalized youth in Germany is scarce.MethodsThis crosssectional study investigated anonymized routine hospital data (demographic information, diagnoses, treatment modalities) of patients admitted (n = 2,849) to the Department of Child and Adolescence Psychiatry, Psychosomatics and Psychotherapy (DCAPPP) of a German University Hospital between 01/2016 and 02/2022. Absolute and relative number of inpatients with or without ED prior to (01/2016–02/2020) and during the COVID-19 pandemic (03/2020–02/2022) were compared. The effect of school closures as part of social lockdown measures for COVID-19 mitigation on inpatient admission rate was explored as it has been discussed as a potential risk factor for mental health problems in youth.ResultsDuring the COVID-19 pandemic, ED inpatient admission rate increased from 10.5 to 16.7%, primarily driven by Anorexia Nervosa (AN). In contrast to previous reports, we found no change in somatic and mental disorder comorbidity, age or sexratio for hospitalized youth with ED. However, we did observe a shortened length of hospital stay (LOS) for hospitalized youth with and without ED. In addition, non-ED admissions presented with an increased number of mental disorder comorbidities. In contrast to our hypothesis, school closures were not related to the observed increase in ED.DiscussionIn summary, the COVID-19 pandemic was associated with an increased rate of inpatient treatment for youth suffering from AN, and of youth affected by multiple mental disorders. Accordingly, we assume that inpatient admission was prioritized for individuals with a higher burden of disease during the COVID-19 pandemic. Our findings pinpoint the need for adequate inpatient mental health treatment capacities during environmental crises, and a further strengthening of child and adolescence psychiatry services in Germany

    Refining Kidney Survival in 383 Genetically Characterized Patients With Nephronophthisis

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    Introduction: Nephronophthisis (NPH) comprises a group of rare disorders accounting for up to 10% of end-stage kidney disease (ESKD) in children. Prediction of kidney prognosis poses a major challenge. We assessed differences in kidney survival, impact of variant type, and the association of clinical characteristics with declining kidney function. Methods: Data was obtained from 3 independent sources, namely the network for early onset cystic kidney diseases clinical registry (n = 105), an online survey sent out to the European Reference Network for Rare Kidney Diseases (n = 60), and a literature search (n = 218). Results: A total of 383 individuals were available for analysis: 116 NPHP1, 101 NPHP3, 81 NPHP4 and 85 NPHP11/TMEM67 patients. Kidney survival differed between the 4 cohorts with a highly variable median age at onset of ESKD as follows: NPHP3, 4.0 years (interquartile range 0.3–12.0); NPHP1, 13.5 years (interquartile range 10.5–16.5); NPHP4, 16.0 years (interquartile range 11.0–25.0); and NPHP11/TMEM67, 19.0 years (interquartile range 8.7–28.0). Kidney survival was significantly associated with the underlying variant type for NPHP1, NPHP3, and NPHP4. Multivariate analysis for the NPHP1 cohort revealed growth retardation (hazard ratio 3.5) and angiotensin-converting enzyme inhibitor (ACEI) treatment (hazard ratio 2.8) as 2 independent factors associated with an earlier onset of ESKD, whereas arterial hypertension was linked to an accelerated glomerular filtration rate (GFR) decline. Conclusion: The presented data will enable clinicians to better estimate kidney prognosis of distinct patients with NPH and thereby allow personalized counseling

    Wie viel Medizinische Informatik (MI) braucht AAL?

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    DNN-basiertes Multi-Level-System zur semantischen Inhaltsanalyse von MRT-Bildern in Bezug auf HCC

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    Analyse groĂźer Datenmengen aus AAL - Herausforderungen an die Medizinische Informatik

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