Epidemiology of Multiple Congenital Anomalies in Europe: A EUROCAT Population-Based Registry Study

Background: This study describes the prevalence, associated anomalies, and demographic characteristics of cases of multiple congenital anomalies (MCA) in 19 population-based European registries (EUROCAT) covering 959,446 births in 2004 and 2010. Methods: EUROCAT implemented a computer algorithm for classification of congenital anomaly cases followed by manual review of potential MCA cases by geneticists. MCA cases are defined as cases with two or more major anomalies of different organ systems, excluding sequences, chromosomal and monogenic syndromes. Results: The combination of an epidemiological and clinical approach for classification of cases has improved the quality and accuracy of the MCA data. Total prevalence of MCA cases was 15.8 per 10,000 births. Fetal deaths and termination of pregnancy were significantly more frequent in MCA cases compared with isolated cases (p<0.001) and MCA cases were more frequently prenatally diagnosed (p<0.001). Live born infants with MCA were more often born preterm (p<0.01) and with birth weight<2500 grams (p<0.01). Respiratory and ear, face, and neck anomalies were the most likely to occur with other anomalies (34% and 32%) and congenital heart defects and limb anomalies were the least likely to occur with other anomalies (13%) (p<0.01). However, due to their high prevalence, congenital heart defects were present in half of all MCA cases. Among males with MCA, the frequency of genital anomalies was significantly greater than the frequency of genital anomalies among females with MCA (p<0.001). Conclusion: Although rare, MCA cases are an important public health issue, because of their severity. The EUROCAT database of MCA cases will allow future investigation on the epidemiology of these conditions and related clinical and diagnostic problems

Prevalence, prenatal diagnosis and clinical features of oculo-auriculo-vertebral spectrum: a registry-based study in Europe

Oculo-auriculo-vertebral spectrum is a complex developmental disorder characterised mainly by anomalies of the ear, hemifacial microsomia, epibulbar dermoids and vertebral anomalies. The aetiology is largely unknown, and the epidemiological data are limited and inconsistent. We present the largest population-based epidemiological study to date, using data provided by the large network of congenital anomalies registries in Europe. The study population included infants diagnosed with oculo-auriculovertebral spectrum during the 1990-2009 period from 34 registries active in 16 European countries. Of the 355 infants diagnosed with oculo-auriculo-vertebral spectrum, there were 95.8% (340/355) live born, 0.8% (3/355) fetal deaths, 3.4% (12/355) terminations of pregnancy for fetal anomaly and 1.5% (5/340) neonatal deaths. In 18.9%, there was prenatal detection of anomaly/anomalies associated with oculo-auriculo-vertebral spectrum, 69.7% were diagnosed at birth, 3.9% in the first week of life and 6.1% within 1 year of life. Microtia (88.8%), hemifacial microsomia (49.0%) and ear tags (44.4%) were the most frequent anomalies, followed by atresia/stenosis of external auditory canal (25.1%), diverse vertebral (24.3%) and eye (24.3%) anomalies. There was a high rate (69.5%) of associated anomalies of other organs/systems. The most common were congenital heart defects present in 27.8% of patients. The prevalence of oculo-auriculo-vertebral spectrum, defined as microtia/ ear anomalies and at least one major characteristic anomaly, was 3.8 per 100 000 births. Twinning, assisted reproductive techniques and maternal pre-pregnancy diabetes were confirmed as risk factors. The high rate of different associated anomalies points to the need of performing an early ultrasound screening in all infants born with this disorder

How can we better measure the demand for AI and other skills on the labour market?

A large body of research literature shows thattechnological change has a significant impact onlabour markets, as modern digital technologies arechanging the demand for certain skills. On the onehand, new technologies can replace some humanactivities. On the other hand, they can create or complementnew activities (Acemoglu et al., 2015; Acemoglu&amp; Restrepo, 2018, 2019, 2020). With the proliferationof artificial intelligence (AI) in recent years,certain questions are becoming increasingly importantin public debate and research: Is the demand forAI skills also growing on the German labour market?Does the increasing demand for AI skills mean thatother skills - among low, medium and highly qualifiedworkers - are less in demand? The aim of thisresearch project is to create a reliable data basis inorder to be able to answer such questions in a moreinformed way in the future.Developments in generative AI, particularly toolssuch as ChatGPT, have significantly intensified thediscussion about the impact of AI on the labour market,both in academia and in public debate and policy.While computers and software have transformedthe world of work by performing routine tasks moreprecisely and efficiently, modern AI systems can nowtake on complex, non-routine tasks without relying ondetailed instructions or repetitive rules (Brynjolfssonet al., 2025). As a result, many are optimistic about theproductive potential of this new technology. Others,however, fear that AI could disrupt labour markets.In the course of the intensive scientific and publicdebate on AI, there is a growing body of literaturethat deals with the effects of AI on labour markets.These initially focus on specific occupations suchas call centre workers (Brynjolfsson et al., 2025, Dijksmanet al., 2024), consultants (Dell’ et al., 2023),writers or developers (Peng et al., 2023). However, amajor challenge is to measure how the demand forand supply of skills has changed in the wake of theemergence of AI

Major Congenital Anomalies in Babies Born With Down Syndrome: A EUROCAT Population-Based Registry Study

Previous studies have shown that over 40% of babies with Down syndrome have a major cardiac anomaly and are more likely to have other major congenital anomalies. Since 2000, many countries in Europe have introduced national antenatal screening programs for Down syndrome. This study aimed to determine if the introduction of these screening programs and the subsequent termination of prenatally detected pregnancies were associated with any decline in the prevalence of additional anomalies in babies born with Down syndrome. The study sample consisted of 7,044 live births and fetal deaths with Down syndrome registered in 28 European population-based congenital anomaly registries covering seven million births during 2000-2010. Overall, 43.6% (95% CI: 42.4-44.7%) of births with Down syndrome had a cardiac anomaly and 15.0% (14.2-15.8%) had a non-cardiac anomaly. Female babies with Down syndrome were significantly more likely to have a cardiac anomaly compared to male babies (47.6% compared with 40.4%, P&#8201;<&#8201;0.001) and significantly less likely to have a non-cardiac anomaly (12.9% compared with 16.7%, P&#8201;<&#8201;0.001). The prevalence of cardiac and non-cardiac congenital anomalies in babies with Down syndrome has remained constant, suggesting that population screening for Down syndrome and subsequent terminations has not influenced the prevalence of specific congenital anomalies in these babies.

Interventions for ingrowing toenails

Minor Ailment

Experiences with experimental research Lessons from a co-creative research project on AI effects in companies

The use of intelligent technologies in companies is changing the way we work. Artificial intelligence (AI) has a direct impact on how work is organised. This leads to changes in work tasks, skill requirements and productivity. AI also has an indirect impact on working conditions and the well-being of employees in the workplace. The transdisciplinary research project ai:conomics aims to expand the scientific knowledge about the effects of AI on work and employees and make it available to a broad audience. The project thus creates a better, evidence-based foundation to better shape the future of work and the use of human-centred AI (further information can be found on the project website

Experiences with experimental research Lessons from a co-creative research project on AI effects in companies

The use of intelligent technologies in companies is changing the way we work. Artificial intelligence (AI) has a direct impact on how work is organised. This leads to changes in work tasks, skill requirements and productivity. AI also has an indirect impact on working conditions and the well-being of employees in the workplace. The transdisciplinary research project ai:conomics aims to expand the scientific knowledge about the effects of AI on work and employees and make it available to a broad audience. The project thus creates a better, evidence-based foundation to better shape the future of work and the use of human-centred AI (further information can be found on the project website

Wie lässt sich die Nachfrage nach KIund anderen Kompetenzen auf dem Arbeitsmarkt besser messen?

Eine umfangreiche Forschungsliteratur zeigt, dassder technologische Wandel erhebliche Auswirkungenauf die Arbeitsmärkte hat, da moderne digitale Technologiendie Nachfrage nach bestimmten Kompetenzenverändern. Zum einen können neue Technologieneinige menschliche Tätigkeiten ersetzen. Zum anderenSeite können sie neue Tätigkeiten schaffen oderergänzen (Acemoglu et al., 2015; Acemoglu &amp; Restrepo,2018, 2019, 2020). Mit der starken VerbreitungKünstlicher Intelligenz in den letzten Jahren gewinnenbestimmte Fragen in der öffentlichen Diskussionund der Forschung zunehmend an Bedeutung:Wächst die Arbeitsnachfrage nach KI-Kompetenzenauch auf dem deutschen Arbeitsmarkt? Führt diesteigende Nachfrage nach KI-Kompetenzen dazu,dass andere Kompetenzen – bei niedrig-, mittel- undhochqualifizierten Arbeitskräften – weniger gefragtsind? Ziel dieses Forschungsprojekts ist es, eine belastbareDatengrundlage zu schaffen, um solche Fragenin Zukunft fundierter beantworten zu können.Die Entwicklungen bei generativer KünstlicherIntelligenz, insbesondere von Tools wie ChatGPT, hatdie Diskussion über die Auswirkungen von KI auf denArbeitsmarkt sowohl in der Wissenschaft als auchin der öffentlichen Debatte und in der Politik deutlichverstärkt. Während Computer und Software dieArbeitswelt durch die präzisere und effizientere Ausführungroutinemäßiger Aufgaben verändert haben,können moderne KI-Systeme nun komplexe, nichtroutinemäßigeAufgaben übernehmen, ohne aufdetaillierte Anweisungen oder wiederholende Regelnangewiesen zu sein (Brynjolfsson et al., 2025). Infolgedessensehen viele das produktive Potenzial dieserneuen Technologie optimistisch. Andere hingegenbefürchten, dass KI die Arbeitsmärkte disruptiv verändernkönnte.</div

Erfahrungen mit experimenteller Forschung: Erkenntnisse aus einem ko-kreativenForschungsprojekt zu den Auswirkungen von KI in Unternehmen

Der Einsatz intelligenter Technologien in Unternehmen verändert unsere Arbeitswelt. Künstliche Intelligenz (KI) wirkt sich direkt darauf aus, wie die Arbeit organisiert wird. Dies führt zu Veränderungen bei Arbeitsaufgaben, Kompetenzbedarfe (Skills demands) und Produktivität. KI wirkt sich auch indirekt auf die Arbeitsbedingungen und das Wohlbefinden vonArbeitnehmer:innen am Arbeitsplatz aus. Das transdisziplinäre Forschungsprojekt ai:conomics hat zum Ziel, das wissenschaftlich fundierte Wissen über die Auswirkungen von KI auf Arbeit und Beschäftigte zu erweitern und neue Erkenntnisse der Öffentlichkeit zugänglich zu machen. Das Projekt schafft so eine verbesserte, evidenzbasierte Grundlage, um die Zukunft der Arbeit und den Einsatz menschzentrierter KI besser zu gestalten (weitere Informationen finden Sie auf der Projektwebsite