How are excellence and trust for using artificial intelligence ensured? Evaluation of its current use in EU healthcare

Context: Artificial intelligence (AI) could be a key driver in different healthcare dossiers, ranging from preventive to diagnostic and treatment purposes. The establishment of the Artificial Intelligence High-Level Expert Group in the European Commission, as well as their White Paper, show first attempts of creating policies in the domain of artificial intelligence in the EU. Despite these policy approaches, there is a need for a coherent regulatory framework that enables the efficient use of AI in the field of health. The aim of this policy brief is to evaluate current legislative gaps in terms of the introduction of AI in healthcare, focusing on the domains of Data Protection, Liability & Transparency, as well as Robustness & Accuracy. Policy Options: This policy brief identified a high degree of eHealth infrastructure fragmentation on member state level and limited action towards a structured and coherent framework for AI in healthcare, under the domains of Data Protection, Liability & Transparency, and Robustness & Accuracy. Recommendations: A unified approach at EU-level, based on proposed recommendations and merged into the form of a Directive, is advised. The development of the Health-AI-Directive will bring progress and improvement to legal certainty in the European AI-landscape. The introduction of the Health-AI-Directive is recommended to ensure trust and excellence in the use of AI in healthcare.   Acknowledgments: The authors of this policy brief would like to thank all our tutors, lecturers and professors of the M.Sc. Governance and Leadership in European Public Health, with special thanks to Kasia Czabanowska and Rok Hržič, for enabling and encouraging us in the creation of this policy brief. Authors’ contributions: All authors contributed equally to this work   Conflict of interest: None declared   Source of funding: None declare

How are excellence and trust for using artificial intelligence ensured? Evaluation of its current use in EU healthcare

Context: Artificial intelligence (AI) could be a key driver in different healthcare dossiers, ranging from preventive to diagnostic and treatment purposes. The establishment of the Artificial Intelligence High-Level Expert Group in the European Commission, as well as their White Paper, show first attempts of creating policies in the domain of artificial intelligence in the EU. Despite these policy approaches, there is a need for a coherent regulatory framework that enables the efficient use of AI in the field of health. The aim of this policy brief is to evaluate current legislative gaps in terms of the introduction of AI in healthcare, focusing on the domains of Data Protection, Liability & Transparency, as well as Robustness & Accuracy. Policy Options: This policy brief identified a high degree of eHealth infrastructure fragmentation on member state level and limited action towards a structured and coherent framework for AI in healthcare, under the domains of Data Protection, Liability & Transparency, and Robustness & Accuracy. Recommendations: A unified approach at EU-level, based on proposed recommendations and merged into the form of a Directive, is advised. The development of the Health-AI-Directive will bring progress and improvement to legal certainty in the European AI-landscape. The introduction of the Health-AI-Directive is recommended to ensure trust and excellence in the use of AI in healthcare

Sex differences in cerebral venous sinus thrombosis after adenoviral vaccination against COVID-19

Introduction: Cerebral venous sinus thrombosis associated with vaccine-induced immune thrombotic thrombocytopenia (CVST-VITT) is a severe disease with high mortality. There are few data on sex differences in CVST-VITT. The aim of our study was to investigate the differences in presentation, treatment, clinical course, complications, and outcome of CVST-VITT between women and men. Patients and methods: We used data from an ongoing international registry on CVST-VITT. VITT was diagnosed according to the Pavord criteria. We compared the characteristics of CVST-VITT in women and men. Results: Of 133 patients with possible, probable, or definite CVST-VITT, 102 (77%) were women. Women were slightly younger [median age 42 (IQR 28–54) vs 45 (28–56)], presented more often with coma (26% vs 10%) and had a lower platelet count at presentation [median (IQR) 50x109/L (28–79) vs 68 (30–125)] than men. The nadir platelet count was lower in women [median (IQR) 34 (19–62) vs 53 (20–92)]. More women received endovascular treatment than men (15% vs 6%). Rates of treatment with intravenous immunoglobulins were similar (63% vs 66%), as were new venous thromboembolic events (14% vs 14%) and major bleeding complications (30% vs 20%). Rates of good functional outcome (modified Rankin Scale 0-2, 42% vs 45%) and in-hospital death (39% vs 41%) did not differ. Discussion and conclusions: Three quarters of CVST-VITT patients in this study were women. Women were more severely affected at presentation, but clinical course and outcome did not differ between women and men. VITT-specific treatments were overall similar, but more women received endovascular treatment.</p

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Publisher Copyright: © 2022, The Author(s).Background: Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results: To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions: Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.Peer reviewe

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Funding GMP, PN, and CW are supported by NHLBI R01HL127564. GMP and PN are supported by R01HL142711. AG acknowledge support from the Wellcome Trust (201543/B/16/Z), European Union Seventh Framework Programme FP7/2007–2013 under grant agreement no. HEALTH-F2-2013–601456 (CVGenes@Target) & the TriPartite Immunometabolism Consortium [TrIC]-Novo Nordisk Foundation’s Grant number NNF15CC0018486. JMM is supported by American Diabetes Association Innovative and Clinical Translational Award 1–19-ICTS-068. SR was supported by the Academy of Finland Center of Excellence in Complex Disease Genetics (Grant No 312062), the Finnish Foundation for Cardiovascular Research, the Sigrid Juselius Foundation, and University of Helsinki HiLIFE Fellow and Grand Challenge grants. EW was supported by the Finnish innovation fund Sitra (EW) and Finska Läkaresällskapet. CNS was supported by American Heart Association Postdoctoral Fellowships 15POST24470131 and 17POST33650016. Charles N Rotimi is supported by Z01HG200362. Zhe Wang, Michael H Preuss, and Ruth JF Loos are supported by R01HL142302. NJT is a Wellcome Trust Investigator (202802/Z/16/Z), is the PI of the Avon Longitudinal Study of Parents and Children (MRC & WT 217065/Z/19/Z), is supported by the University of Bristol NIHR Biomedical Research Centre (BRC-1215–2001) and the MRC Integrative Epidemiology Unit (MC_UU_00011), and works within the CRUK Integrative Cancer Epidemiology Programme (C18281/A19169). Ruth E Mitchell is a member of the MRC Integrative Epidemiology Unit at the University of Bristol funded by the MRC (MC_UU_00011/1). Simon Haworth is supported by the UK National Institute for Health Research Academic Clinical Fellowship. Paul S. de Vries was supported by American Heart Association grant number 18CDA34110116. Julia Ramierz acknowledges support by the People Programme of the European Union’s Seventh Framework Programme grant n° 608765 and Marie Sklodowska-Curie grant n° 786833. Maria Sabater-Lleal is supported by a Miguel Servet contract from the ISCIII Spanish Health Institute (CP17/00142) and co-financed by the European Social Fund. Jian Yang is funded by the Westlake Education Foundation. Olga Giannakopoulou has received funding from the British Heart Foundation (BHF) (FS/14/66/3129). CHARGE Consortium cohorts were supported by R01HL105756. Study-specific acknowledgements are available in the Additional file 32: Supplementary Note. The views expressed in this manuscript are those of the authors and do not necessarily represent the views of the National Heart, Lung, and Blood Institute; the National Institutes of Health; or the U.S. Department of Health and Human Services.Peer reviewedPublisher PD

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Abstract Background Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Funding Information: GMP, PN, and CW are supported by NHLBI R01HL127564. GMP and PN are supported by R01HL142711. AG acknowledge support from the Wellcome Trust (201543/B/16/Z), European Union Seventh Framework Programme FP7/2007–2013 under grant agreement no. HEALTH-F2-2013–601456 (CVGenes@Target) & the TriPartite Immunometabolism Consortium [TrIC]-Novo Nordisk Foundation’s Grant number NNF15CC0018486. JMM is supported by American Diabetes Association Innovative and Clinical Translational Award 1–19-ICTS-068. SR was supported by the Academy of Finland Center of Excellence in Complex Disease Genetics (Grant No 312062), the Finnish Foundation for Cardiovascular Research, the Sigrid Juselius Foundation, and University of Helsinki HiLIFE Fellow and Grand Challenge grants. EW was supported by the Finnish innovation fund Sitra (EW) and Finska Läkaresällskapet. CNS was supported by American Heart Association Postdoctoral Fellowships 15POST24470131 and 17POST33650016. Charles N Rotimi is supported by Z01HG200362. Zhe Wang, Michael H Preuss, and Ruth JF Loos are supported by R01HL142302. NJT is a Wellcome Trust Investigator (202802/Z/16/Z), is the PI of the Avon Longitudinal Study of Parents and Children (MRC & WT 217065/Z/19/Z), is supported by the University of Bristol NIHR Biomedical Research Centre (BRC-1215–2001) and the MRC Integrative Epidemiology Unit (MC_UU_00011), and works within the CRUK Integrative Cancer Epidemiology Programme (C18281/A19169). Ruth E Mitchell is a member of the MRC Integrative Epidemiology Unit at the University of Bristol funded by the MRC (MC_UU_00011/1). Simon Haworth is supported by the UK National Institute for Health Research Academic Clinical Fellowship. Paul S. de Vries was supported by American Heart Association grant number 18CDA34110116. Julia Ramierz acknowledges support by the People Programme of the European Union’s Seventh Framework Programme grant n° 608765 and Marie Sklodowska-Curie grant n° 786833. Maria Sabater-Lleal is supported by a Miguel Servet contract from the ISCIII Spanish Health Institute (CP17/00142) and co-financed by the European Social Fund. Jian Yang is funded by the Westlake Education Foundation. Olga Giannakopoulou has received funding from the British Heart Foundation (BHF) (FS/14/66/3129). CHARGE Consortium cohorts were supported by R01HL105756. Study-specific acknowledgements are available in the Additional file : Supplementary Note. The views expressed in this manuscript are those of the authors and do not necessarily represent the views of the National Heart, Lung, and Blood Institute; the National Institutes of Health; or the U.S. Department of Health and Human Services. Publisher Copyright: © 2022, The Author(s).Background: Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results: To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions: Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.Peer reviewe

Artificial intelligence in Emergency Medical Services dispatching:assessing the potential impact of an automatic speech recognition software on stroke detection taking the Capital Region of Denmark as case in point

BACKGROUND AND PURPOSE: Stroke recognition at the Emergency Medical Services (EMS) impacts the stroke treatment and thus the related health outcome. At the EMS Copenhagen 66.2% of strokes are detected by the Emergency Medical Dispatcher (EMD) and in Denmark approximately 50% of stroke patients arrive at the hospital within the time-to-treatment. An automatic speech recognition software (ASR) can increase the recognition of Out-of-Hospital cardiac arrest (OHCA) at the EMS by 16%. This research aims to analyse the potential impact an ASR could have on stroke recognition at the EMS Copenhagen and the related treatment. METHODS: Stroke patient data (n = 9049) from the years 2016-2018 were analysed retrospectively, regarding correlations between stroke detection at the EMS and stroke specific, as well as personal characteristics such as stroke type, sex, age, weekday, time of day, year, EMS number contacted, and treatment. The possible increase in stroke detection through an ASR and the effect on stroke treatment was calculated based on the impact of an existing ASR to detect OHCA from CORTI AI. RESULTS: The Chi-Square test with the respective post-hoc test identified a negative correlation between stroke detection and females, the 1813-Medical Helpline, as well as weekends, and a positive correlation between stroke detection and treatment and thrombolysis. While the association analysis showed a moderate correlation between stroke detection and treatment the correlation to the other treatment options was weak or very weak. A potential increase in stroke detection to 61.19% with an ASR and hence an increase of thrombolysis by 5% in stroke patients calling within time-to-treatment was predicted. CONCLUSIONS: An ASR can potentially improve stroke recognition by EMDs and subsequent stroke treatment at the EMS Copenhagen. Based on the analysis results improvement of stroke recognition is particularly relevant for females, younger stroke patients, calls received through the 1813-Medical Helpline, and on weekends. TRIAL REGISTRATION: This study was registered at the Danish Data Protection Agency (PVH-2014-002) and the Danish Patient Safety Authority (R-21013122)

Expanding the Burkholderia pseudomallei complex with the addition of two novel species: Burkholderia mayonis sp. nov. and Burkholderia savannae sp. nov.

Distinct Burkholderia strains were isolated from soil samples collected in tropical northern Australia (Northern Territory and the Torres Strait Islands, Queensland). Phylogenetic analysis of 16S rRNA and whole genome sequences revealed these strains were distinct from previously described Burkholderia species and assigned them to two novel clades within the B. pseudomallei complex (Bpc). Because average nucleotide identity and digital DNA-DNA hybridization calculations are consistent with these clades representing distinct species, we propose the names Burkholderia mayonis sp. nov. and Burkholderia savannae sp. nov. Strains assigned to B. mayonis sp. nov. include type strain BDU6T (=TSD-80; LMG 29941; ASM152374v2) and BDU8. Strains assigned to B. savannae sp. nov. include type strain MSMB266T (=TSD-82; LMG 29940; ASM152444v2), MSMB852, BDU18, and BDU19. Comparative genomics revealed unique coding regions for both putative species, including clusters of orthologous genes associated with phage. Type strains of both B. mayonis sp. nov. and B. savannae sp. nov. yielded biochemical profiles distinct from each other and other species in the Bpc, and profiles also varied among strains within B. mayonis sp. nov. and B. savannae sp. nov. Matrix-assisted laser desorption ionization–time of flight analysis revealed a B. savannae sp. nov. cluster separate from other species, whereas B. mayonis sp. nov. strains did not form a distinct cluster. Neither B. mayonis sp. nov. nor B. savannae sp. nov. caused mortality in mice when delivered via the subcutaneous route. The addition of B. mayonis sp. nov. and B. savannae sp. nov. results in eight species currently in the Bpc

Burkholderia humptydooensis sp. nov., a New Species Related to Burkholderia thailandensis and the Fifth Member of the Burkholderia pseudomallei Complex.

During routine screening for Burkholderia pseudomallei from water wells in northern Australia in areas where it is endemic, Gram-negative bacteria (strains MSMB43T, MSMB121, and MSMB122) with a similar morphology and biochemical pattern to B. pseudomallei and B. thailandensis were coisolated with B. pseudomallei on Ashdown's selective agar. To determine the exact taxonomic position of these strains and to distinguish them from B. pseudomallei and B. thailandensis, they were subjected to a series of phenotypic and molecular analyses. Biochemical and fatty acid methyl ester analysis was unable to distinguish B. humptydooensis sp. nov. from closely related species. With matrix-assisted laser desorption ionization-time of flight analysis, all isolates grouped together in a cluster separate from other Burkholderia spp. 16S rRNA and recA sequence analyses demonstrated phylogenetic placement for B. humptydooensis sp. nov. in a novel clade within the B. pseudomallei group. Multilocus sequence typing (MLST) analysis of the three isolates in comparison with MLST data from 3,340 B. pseudomallei strains and related taxa revealed a new sequence type (ST318). Genome-to-genome distance calculations and the average nucleotide identity of all isolates to both B. thailandensis and B. pseudomallei, based on whole-genome sequences, also confirmed B. humptydooensis sp. nov. as a novel Burkholderia species within the B. pseudomallei complex. Molecular analyses clearly demonstrated that strains MSMB43T, MSMB121, and MSMB122 belong to a novel Burkholderia species for which the name Burkholderia humptydooensis sp. nov. is proposed, with the type strain MSMB43T (American Type Culture Collection BAA-2767; Belgian Co-ordinated Collections of Microorganisms LMG 29471; DDBJ accession numbers CP013380 to CP013382).IMPORTANCEBurkholderia pseudomallei is a soil-dwelling bacterium and the causative agent of melioidosis. The genus Burkholderia consists of a diverse group of species, with the closest relatives of B. pseudomallei referred to as the B. pseudomallei complex. A proposed novel species, B. humptydooensis sp. nov., was isolated from a bore water sample from the Northern Territory in Australia. B. humptydooensis sp. nov. is phylogenetically distinct from B. pseudomallei and other members of the B. pseudomallei complex, making it the fifth member of this important group of bacteria