• Use of granulocyte colony-stimulating factor and risk of relapse in pediatric patients treated for acute myeloid leukemia according to NOPHO-AML 2004 and DB AML-01.

      Løhmann, Ditte J A; Asdahl, Peter H; Abrahamsson, Jonas; Ha, Shau-Yin; Jónsson, Ólafur G; Kaspers, Gertjan J L; Koskenvuo, Minna; Lausen, Birgitte; De Moerloose, Barbara; Palle, Josefine; Zeller, Bernward; Hasle, Henrik; 1 Department of Pediatrics and Adolescent Medicine, Aarhus University Hospital, Aarhus, Denmark. 2 Department of Hematology, Aarhus University Hospital, Aarhus, Denmark. 3 Institution for Clinical Sciences, Department of Pediatrics, Queen Silvia Children's Hospital, Gothenburg, Sweden. 4 Department of Pediatrics, Queen Mary Hospital and Hong Kong Pediatric Hematology and Oncology Study Group (HKPHOSG), Hong Kong, China. 5 Department of Pediatrics, Landspitali University Hospital, Reykjavik, Iceland. 6 Department of Pediatrics, VU University Medical Center, Amsterdam, The Netherlands. 7 Princess Máxima Center for Pediatric Oncology, Utrecht, The Netherlands. 8 Dutch Childhood Oncology Group, The Hague, The Netherlands. 9 Division of Hematology-Oncology and Stem Cell Transplantation, New Children's Hospital, University of Helsinki and Helsinki University Hospital, Helsinki, Finland. 10 Department of Pediatrics and Adolescent Medicine, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark. 11 Department of Pediatric Hematology-Oncology and Stem Cell Transplantation, Ghent University Hospital, Ghent, Belgium. 12 Department of Woman´s and Children´s Health, Uppsala University, Uppsala, Sweden. 13 Division of Pediatric and Adolescent Medicine, Oslo University Hospital, Oslo, Norway. (Wiley, 2019-06-01)
      Supportive-care use of granulocyte colony-stimulating factor (G-CSF) in pediatric acute myeloid leukemia (AML) remains controversial due to a theoretical increased risk of relapse and limited impact on neutropenic complications. We describe the use of G-CSF in patients treated according to NOPHO-AML 2004 and DB AML-01 and investigated associations with relapse. Patients diagnosed with de novo AML completing the first week of therapy and not treated with hematopoietic stem cell transplantation in the first complete remission were included (n = 367). Information on G-CSF treatment after each course (yes/no) was registered prospectively in the study database and detailed information was gathered retrospectively from each center. Descriptive statistics were used to describe G-CSF use and Cox regression to assess the association between G-CSF and risk of relapse. G-CSF as supportive care was given to 128 (35%) patients after 268 (39%) courses, with a large variation between centers (0-93%). The use decreased with time-the country-adjusted odds ratio was 0.8/diagnostic year (95% confidence interval [CI] 0.7-0.9). The median daily dose was 5 μg/kg (range 3-12 μg/kg) and the median cumulative dose was 75 μg/kg (range 7-1460 μg/kg). Filgrastim was used in 82% of G-CSF administrations and infection was the indication in 44% of G-CSF administrations. G-CSF was associated with increased risk of relapse-the adjusted hazard ratio was 1.5 (95% CI 1.1-2.2). G-CSF as supportive care was used in a third of patients, and use decreased with time. Our results indicate that the use of G-CSF may be associated with an increased risk of relapse.
    • Group B Streptococcal Neonatal and Early Infancy Infections in Iceland, 1976-2015.

      Björnsdóttir, Erla S; Martins, Elisabete R; Erlendsdóttir, Helga; Haraldsson, Gunnsteinn; Melo-Cristino, José; Ramirez, Mário; Kristinsson, Karl G; 1 From the Department of Clinical Microbiology, Landspitali University Hospital, Reykjavik, Iceland. 2 BioMedical Centre of the University of Iceland, Reykjavik, Iceland. 3 Instituto de Microbiologia, Instituto de Medicina Molecular, Faculdade de Medicina, Universidade de Lisboa, Lisboa, Portugal. (Lippincott Williams & Wilkins, 2019-06)
      BACKGROUND: Despite a risk-based peripartum chemoprophylaxis approach in Iceland since 1996, Streptococcus agalactiae [group B streptococci (GBS)] remains an important cause of early-onset [<7 days, early-onset disease (EOD)] and late-onset disease (LOD; 7 days to 3 months). METHODS: We studied GBS invasive disease in children <1 year in Iceland in 1976-2015. Bacteria (n = 98) were characterized by susceptibility to a panel of antimicrobials, capsular serotyping, resistance genes, surface protein and pilus-locus profiling and multilocus sequence typing. RESULTS: Both EOD and LOD increased during the early years, but while EOD subsequently decreased from 0.7/1000 live births in 1991-1995 to 0.2/1000 in 2011-2015, LOD showed a nonsignificant decrease from its peak value of 0.6/1000 in 2001-2005 to 0.4/1000 in 2006-2015. Serotype III was the most frequently found (n = 48), represented mostly by the hypervirulent lineage CC17/III/rib/PI-1+PI-2b (62%), but also by CC19/III/rib/PI-1+PI-2a (35%) frequently associated with colonization. Serotype Ia (n = 22) was represented by CC23/Ia/eps/PI-2a (68%) and CC7/Ia/bca/PI-1+PI-2b (23%) of possible zoonotic origin. Resistance to erythromycin and clindamycin was increasingly detected in the last years of the study (5 of the 9 cases were isolated after 2013), including representatives of a multiresistant CC17/III/rib/PI-2b sublineage described recently in other countries and expressing resistance to erythromycin, clindamycin and streptomycin. CONCLUSIONS: The risk-based chemoprophylaxis adopted in Iceland possibly contributed to the decline of EOD but has had limited effect on LOD. GBS causing neonatal and early infancy invasive infections in Iceland are genetically diverse, and the recent emergence of antimicrobial resistant lineages may reduce the choices for prophylaxis and therapy of these infections.
    • A worldwide perspective of sepsis epidemiology and survival according to age: Observational data from the ICON audit.

      Kotfis, Katarzyna; Wittebole, Xavier; Jaschinski, Ulrich; Solé-Violán, Jordi; Kashyap, Rahul; Leone, Marc; Nanchal, Rahul; Fontes, Luis E; Sakr, Yasser; Vincent, Jean-Louis; 1 Dept of Anaesthesiology, Intensive Therapy and Acute Intoxications, Pomeranian Medical University, Szczecin, Poland. 2 Dept of Critical Care, Cliniques Universitaires St Luc, UCL, Brussels, Belgium. 3 Klinik für Anästhesiologie und Operative Intensivmedizin, Klinikum Augsburg, Augsburg, Germany. 4 Dept of Intensive Care, Hospital Universitario de Gran Canaria Dr. Negrín, Las Palmas de Gran Canaria, Spain. 5 Dept of Anesthesia & Perioperative Medicine, Mayo Clinic, Rochester, MN, USA. 6 Service d'Anesthésie et de Réanimation, Aix Marseille Université, APHM, Hôpital Nord, Marseille, France. 7 Department of Medicine, Medical College of Wisconsin, Milwaukee, WI, USA. 8 Department of Intensive Care and Evidence-Based Medicine, Hospital Alcides Carneiro, Petrópolis Medical School, Petrópolis, Brazil. 9 Department of Anesthesiology and Intensive Care, Uniklinikum Jena, Jena, Germany. 10 Department of Intensive Care, Erasme University Hospital, Université Libre de Bruxelles, Brussels, Belgium. Electronic address: jlvincent@intensive.org. (W.B. Saunders, 2019-06)
      PURPOSE: To investigate age-related differences in outcomes of critically ill patients with sepsis around the world. METHODS: We performed a secondary analysis of data from the prospective ICON audit, in which all adult (>16 years) patients admitted to participating ICUs between May 8 and 18, 2012, were included, except admissions for routine postoperative observation. For this sub-analysis, the 10,012 patients with completed age data were included. They were divided into five age groups - ≤50, 51-60, 61-70, 71-80, >80 years. Sepsis was defined as infection plus at least one organ failure. RESULTS: A total of 2963 patients had sepsis, with similar proportions across the age groups (≤50 = 25.2%; 51-60 = 30.3%; 61-70 = 32.8%; 71-80 = 30.7%; >80 = 30.9%). Hospital mortality increased with age and in patients >80 years was almost twice that of patients ≤50 years (49.3% vs 25.2%, p < .05). The maximum rate of increase in mortality was about 0.75% per year, occurring between the ages of 71 and 77 years. In multilevel analysis, age > 70 years was independently associated with increased risk of dying. CONCLUSIONS: The odds for death in ICU patients with sepsis increased with age with the maximal rate of increase occurring between the ages of 71 and 77 years.
    • Effects of an intervention program for reducing severe perineal trauma during the second stage of labor.

      Sveinsdottir, Edda; Gottfredsdottir, Helga; Vernhardsdottir, Anna S; Tryggvadottir, Gudny B; Geirsson, Reynir T; 1 Midwifery Division, Faculty of Nursing, University of Iceland, Reykjavik, Iceland. 2 Department of Obstetrics and Gynecology, Women's Clinic, Landspítali University Hospital, Reykjavik, Iceland. 3 Department of Social Sciences, University of Iceland, Reykjavik, Iceland. 4 Faculty of Medicine, University of Iceland, Reykjavik, Iceland. (Wiley, 2019-06)
      BACKGROUND: Obstetric anal sphincter injuries lead frequently to short- and long-term consequences for the mother, including perineal pain, genital prolapse, and sexual problems. The aim of the study was to evaluate whether the implementation of an intervention program in the second stage of labor involving altered perineal support techniques reduced severe perineal trauma. METHODS: All women reaching the second stage of labor and giving birth vaginally to singleton babies at Landspítali University Hospital (comprising 76% of births in Iceland in 2013) were enrolled in a cohort study. Data were recorded retrospectively for 2008-2010 and prospectively in 2012-2014, for a total of 16 336 births. During 2011, an intervention program was implemented, involving all midwives and obstetricians working in the labor wards. Two professionals assessed and agreed on classification of every perineal tear. RESULTS: The prevalence of obstetric anal sphincter injuries decreased from 5.9% to 3.7% after the implementation (P < 0.001). Third-degree tears decreased by 40%, and fourth-degree tears decreased by 56% (P < 0.001). The prevalence of first-degree tears increased from 25.8% to 33.1%, whereas second-degree tears decreased from 44.7% to 36.6% between the before and after study periods. Severe perineal trauma was linked to birthweight, and this did not change despite the new intervention. CONCLUSIONS: Active intervention to reduce perineal trauma was associated with an overall significant decrease in obstetric anal sphincter injuries. Good perineal visualization, manual perineal support, and controlled delivery of the fetal head were essential components for reducing perineal trauma.
    • The Robson 10-group classification in Iceland: Obstetric interventions and outcomes.

      Einarsdóttir, Kristjana; Sigurðardóttir, Hekla; Ingibjörg Bjarnadóttir, Ragnheiður; Steingrímsdóttir, Þóra; Smárason, Alexander K; 1 Centre of Public Health Sciences, Faculty of Medicine, University of Iceland, Reykjavík, Iceland. 2 Faculty of Medicine, University of Iceland, Reykjavík, Iceland. 3 Centre of Development, Primary Health Care of the Capital Area, Reykjavík, Iceland. 4 Department of Obstetrics and Gynaecology, Landspítali University Hospital, Reykjavík, Iceland. 5 Institution of Health Science Research, University of Akureyri and Akureyri Hospital, Akureyri, Iceland. (Wiley, 2019-06)
      BACKGROUND: Rising cesarean rates call for studies on which subgroups of women contribute to the rising rates, both in countries with high and low rates. This study investigated the cesarean rates and contributing groups in Iceland using the Robson 10-group classification system. METHODS: This study included all births in Iceland from 1997 to 2015, identified from the Icelandic Medical Birth Registry (81 839). The Robson distribution, cesarean rate, and contribution of each Robson group were analyzed for each year, and the distribution of other outcomes was calculated for each Robson group. RESULTS: The overall cesarean rate in the population was 16.4%. Robson groups 1 (28.7%) and 3 (38.0%) (spontaneous term births) were the largest groups, and groups 2b (0.4%) and 4b (0.7%) (prelabor cesareans) were small. The cesarean rate in group 5 (prior cesarean) was 55.5%. Group 5 was the largest contributing group to the overall cesarean rate (31.2%), followed by groups 1 (17.1%) and 2a (11.0%). The size of groups 2a (RR 1.04 [95% CI 1.01-1.08]) and 4a (RR 1.04 [95% CI 1.01-1.07]) (induced labors) increased over time, whereas their cesarean rates were stable (group 2a: P = 0.08) or decreased (group 4a: RR 0.95 [95% CI 0.91-0.98]). CONCLUSIONS: In comparison with countries with high cesarean rates, the prelabor cesarean groups (singleton term pregnancies) in Iceland were small, and in women with a previous cesarean, the cesarean rate was low. The size of the labor induction group increased, yet the cesarean rate in this group did not increase.
    • Asthma and selective migration from farming environments in a three-generation cohort study.

      Timm, Signe; Frydenberg, Morten; Abramson, Michael J; Bertelsen, Randi J; Bråbäck, Lennart; Benediktsdottir, Bryndis; Gislason, Thorarinn; Holm, Mathias; Janson, Christer; Jogi, Rain; Johannessen, Ane; Kim, Jeong-Lim; Malinovschi, Andrei; Mishra, Gita; Moratalla, Jesús; Sigsgaard, Torben; Svanes, Cecilie; Schlünssen, Vivi; 1 Department of Public Health, Danish Ramazzini Centre, Aarhus University, Bartholins Alle 2, Building 1260, 8000, Aarhus C, Denmark. signe.timm@ph.au.dk. 2 Department of Public Health, Danish Ramazzini Centre, Aarhus University, Bartholins Alle 2, Building 1260, 8000, Aarhus C, Denmark. 3 School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia. 4 Institute of Clinical Science, University of Bergen, Bergen, Norway. 5 Section of Sustainable Health, Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden. 6 Medical Faculty, University of Iceland, Reykjavík, Iceland. 7 Primary Health Care Center, Gardabaer, Iceland. 8 Department of Sleep, Landspitali University Hospital, Reykjavík, Iceland. 9 Section of Occupational and Environmental Medicine, Sahlgrenska University Hospital, Gothenburg, Sweden. 10 Department of Medical Sciences: Respiratory, Allergy and Sleep Research, Uppsala University, Uppsala, Sweden. 11 Department of Pulmonology (ARKS), University of Tartu, Tartu, Estonia. 12 Department of Global Public Health and Primary Care, Centre for International Health, University of Bergen, Bergen, Norway. 13 Department of Occupational Medicine, Haukeland University Hospital, Bergen, Norway. 14 Section of Occupational and Environmental Medicine, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden. 15 Department of Medical Sciences, Clinical Physiology, Uppsala University, Uppsala, Sweden. 16 School of Public Health, The University of Queensland, Brisbane, QLD, 4006, Australia. 17 Department of Internal Medicine, Albacete University Hospital, Albacete, Spain. 18 National Research Centre for The Working Environment, Copenhagen, Denmark. (Springer, 2019-06)
      Individuals raised on a farm appear to have less asthma than individual raised elsewhere. However, selective migration might contribute to this as may also the suggested protection from farm environment. This study investigated if parents with asthma are less likely to raise their children on a farm. This study involved three generations: 6045 participants in ECRHS/RHINE cohorts (born 1945-1973, denoted G1), their 10,121 parents (denoted G0) and their 8260 offspring participating in RHINESSA (born 1963-1998, denoted G2). G2-offspring provided information on parents not participating in ECRHS/RHINE. Asthma status and place of upbringing for all three generations were reported in questionnaires by G1 in 2010-2012 and by G2 in 2013-2016. Binary regressions with farm upbringing as outcome were performed to explore associations between parental asthma and offspring farm upbringing in G0-G1 and G1-G2. Having at least one parent with asthma was not associated with offspring farm upbringing, either in G1-G2 (RR 1.11, 95% CI 0.81-1.52) or in G0-G1 (RR 0.99, 0.85-1.15). G1 parents with asthma born in a city tended to move and raise their G2 offspring on a farm (RR 2.00, 1.12-3.55), while G1 parents with asthma born on a farm were less likely to raise their G2 offspring on a farm (RR 0.34, 0.11-1.06). This pattern was not observed in analyses of G0-G1. This study suggests that the protective effect from farm upbringing on subsequent asthma development could not be explained by selective migration. Intriguingly, asthmatic parents appeared to change environment when having children.
    • Molecularly confirmed Kabuki (Niikawa-Kuroki) syndrome patients demonstrate a specific cognitive profile with extensive visuospatial abnormalities.

      Harris, J; Mahone, E M; Bjornsson, H T; 1 Department of Neurogenetics, Kennedy Krieger Institute, Baltimore, MD, USA. 2 McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University, Baltimore, MD, USA. 3 Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, MD, USA. 4 Department of Neuropsychology, Kennedy Krieger Institute, Baltimore, MD, USA. 5 Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA. 6 Faculty of Medicine, University of Iceland, Reykjavik, Iceland. 7 Department of Genetics and Molecular Medicine, Landspitali University Hospital, Reykjavik, Iceland. (Wiley, 2019-06)
      BACKGROUND: Kabuki (Niikawa-Kuroki) syndrome (KS) is caused by disease-causing variants in either of two components (KMT2D and KDM6A) of the histone methylation machinery. Nearly all individuals with KS have cognitive difficulties, and most have intellectual disability. Recent studies on a mouse model of KS suggest disruption of normal adult neurogenesis in the granule cell layer of the dentate gyrus of the hippocampus. These mutant mice also demonstrate hippocampal memory defects compared with littermates, but this phenotype is rescued postnatally with agents that target the epigenetic machinery. If these findings are relevant to humans with KS, we would expect significant and disproportionate disruption of visuospatial functioning in these individuals. METHODS: To test this hypothesis, we have compiled a battery to robustly explore visuospatial function. We prospectively recruited 22 patients with molecularly confirmed KS and 22 IQ-matched patients with intellectual disability. RESULTS: We observed significant deficiencies in visual motor, visual perception and visual motor memory in the KS group compared with the IQ-matched group on several measures. In contrast, language function appeared to be marginally better in the KS group compared with the IQ-matched group in a sentence comprehension task. CONCLUSIONS: Together, our data suggest specific disruption of visuospatial function, likely linked to the dentate gyrus, in individuals with KS and provide the groundwork for a novel and specific outcome measure for a clinical trial in a KS population.
    • Minimal residual disease quantification by flow cytometry provides reliable risk stratification in T-cell acute lymphoblastic leukemia.

      Modvig, S; Madsen, H O; Siitonen, S M; Rosthøj, S; Tierens, A; Juvonen, V; Osnes, L T N; Vålerhaugen, H; Hultdin, M; Thörn, I; Matuzeviciene, R; Stoskus, M; Marincevic, M; Fogelstrand, L; Lilleorg, A; Toft, N; Jónsson, O G; Pruunsild, K; Vaitkeviciene, G; Vettenranta, K; Lund, B; Abrahamsson, J; Schmiegelow, K; Marquart, H V; 1 Department of Clinical Immunology, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark. 2 Helsinki University Ctrl. Hospital, Helsinki, Finland. 3 Section of Biostatistics, University of Copenhagen, Copenhagen, Denmark. 4 Laboratory Medicine Program, University Health Network and University of Toronto, Toronto, ON, Canada. 5 Department of Pathology, University Hospital of Oslo, Oslo, Norway. 6 Department of Clinical Chemistry and Laboratory Division, University of Turku and Turku University Hospital, Turku, Finland. 7 Department of Immunology, Oslo University Hospital Rikshospitalet, Oslo, Norway. 8 Department of Pathology, Laboratory of Molecular Pathology, Oslo University Hospital, Oslo, Norway. 9 Department of Medical Biosciences, Pathology, Umeå University, Umeå, Sweden. 10 Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden. 11 Department of Physiology, Biochemistry, Microbiology and Laboratory Medicine, Institute of Biomedical Sciences, Faculty of Medicine, Vilnius University, Vilnius, Lithuania. 12 Centre of Laboratory Medicine, Vilnius University Hospital Santaros Klinikos, Vilnius, Lithuania. 13 Hematology, Oncology and Transfusion Medicine Centre, Vilnius University Hospital Santaros Klinikos, Vilnius, Lithuania. 14 Department of Clinical Chemistry, Sahlgrenska University Hospital, and Department of Clinical Chemistry and Transfusion Medicine, Institute of Biomedicine, Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden. 15 Department of Clinical Immunology, North Estonia Medical Centre, Tallinn, Estonia. 16 Department of Hematology, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark. 17 Children's Hospital, Landspitali University Hospital, Reykjavik, Iceland. 18 Tallinn Children's Hospital, Tallinn, Estonia. 19 Children's Hospital, Affiliate of Vilnius University Hospital Santariskiu Klinikos, Vilnius, Lithuania. 20 Department of Pediatrics, Helsinki University Children's Hospital and University of Helsinki, Helsinki, Finland. 21 Department of Pediatrics, St. Olavs University Hospital and Department of Clinical and Molecular Medicine, NTNU, Trondheim, Norway. 22 Institution of Clinical Sciences, Department of Pediatrics, Sahlgrenska University Hospital, Gothenburg, Sweden. 23 Department of Pediatrics and Adolescent Medicine, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark. 24 The Institute of Clinical medicine, The Faculty of Medicine, University of Copenhagen, Copenhagen, Denmark. 25 Department of Clinical Immunology, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark. hanne.marquart@regionh.dk. (Nature Publishing Group, 2019-06)
      Minimal residual disease (MRD) measured by PCR of clonal IgH/TCR rearrangements predicts relapse in T-cell acute lymphoblastic leukemia (T-ALL) and serves as risk stratification tool. Since 10% of patients have no suitable PCR-marker, we evaluated flowcytometry (FCM)-based MRD for risk stratification. We included 274 T-ALL patients treated in the NOPHO-ALL2008 protocol. MRD was measured by six-color FCM and real-time quantitative PCR. Day 29 PCR-MRD (cut-off 10-3) was used for risk stratification. At diagnosis, 93% had an FCM-marker for MRD monitoring, 84% a PCR-marker, and 99.3% (272/274) had a marker when combining the two. Adjusted for age and WBC, the hazard ratio for relapse was 3.55 (95% CI 1.4-9.0, p = 0.008) for day 29 FCM-MRD ≥ 10-3 and 5.6 (95% CI 2.0-16, p = 0.001) for PCR-MRD ≥ 10-3 compared with MRD < 10-3. Patients stratified to intermediate-risk therapy on day 29 with MRD 10-4-<10-3 had a 5-year event-free survival similar to intermediate-risk patients with MRD < 10-4 or undetectable, regardless of method for monitoring. Patients with day 15 FCM-MRD < 10-4 had a cumulative incidence of relapse of 2.3% (95% CI 0-6.8, n = 59). Thus, FCM-MRD allows early identification of patients eligible for reduced intensity therapy, but this needs further studies. In conclusion, FCM-MRD provides reliable risk prediction for T-ALL and can be used for stratification when no PCR-marker is available.
    • Publisher Correction: GWAS of bone size yields twelve loci that also affect height, BMD, osteoarthritis or fractures.

      Styrkarsdottir, Unnur; Stefansson, Olafur A; Gunnarsdottir, Kristbjorg; Thorleifsson, Gudmar; Lund, Sigrun H; Stefansdottir, Lilja; Juliusson, Kristinn; Agustsdottir, Arna B; Zink, Florian; Halldorsson, Gisli H; Ivarsdottir, Erna V; Benonisdottir, Stefania; Jonsson, Hakon; Gylfason, Arnaldur; Norland, Kristjan; Trajanoska, Katerina; Boer, Cindy G; Southam, Lorraine; Leung, Jason C S; Tang, Nelson L S; Kwok, Timothy C Y; Lee, Jenny S W; Ho, Suzanne C; Byrjalsen, Inger; Center, Jacqueline R; Lee, Seung Hun; Koh, Jung-Min; Lohmander, L Stefan; Ho-Pham, Lan T; Nguyen, Tuan V; Eisman, John A; Woo, Jean; Leung, Ping-C; Loughlin, John; Zeggini, Eleftheria; Christiansen, Claus; Rivadeneira, Fernando; van Meurs, Joyce; Uitterlinden, Andre G; Mogensen, Brynjolfur; Jonsson, Helgi; Ingvarsson, Thorvaldur; Sigurdsson, Gunnar; Benediktsson, Rafn; Sulem, Patrick; Jonsdottir, Ingileif; Masson, Gisli; Holm, Hilma; Norddahl, Gudmundur L; Thorsteinsdottir, Unnur; Gudbjartsson, Daniel F; Stefansson, Kari; 1 deCODE genetics/Amgen Inc., Reykjavik, 101, Iceland. unnur.styrkarsdottir@decode.is. 2 deCODE genetics/Amgen Inc., Reykjavik, 101, Iceland. 3 Faculty of Medicine, University of Iceland, Reykjavik, 101, Iceland. 4 Department of Epidemiology, ErasmusMC, 3015 GD, Rotterdam, The Netherlands. 5 Department of Internal Medicine, ErasmusMC, 3015 GD, Rotterdam, The Netherlands. 6 Wellcome Trust Sanger Institute, Hinxton, CB10 1SA, UK. 7 Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK. 8 Jockey Club Centre for Osteoporosis Care and Control, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, China. 9 Faculty of Medicine, Department of Chemical Pathology and Laboratory for Genetics of Disease Susceptibility, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, China. 10 CUHK Shenzhen Research Institute, Shenzhen, 518000, China. 11 Department of Medicine and Therapeutics, Prince of Wales Hospital, Hong Kong, China. 12 Faculty of Medicine, Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, China. 13 Department of Medicine, Alice Ho Miu Ling Nethersole Hospital and Tai Po Hospital, Hong Kong, China. 14 JC School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, China. 15 Nordic Bioscience A/S, 2730, Herlev, Denmark. 16 Bone Biology Division, Garvan Institute of Medical Research, Sydney, NSW, 2010, Australia. 17 School of Medicine Sydney, University of Notre Dame Australia, Sydney, NSW, 2010, Australia. 18 St Vincent's Clinical School, University of New South Wales, Sydney, NSW, 2010, Australia. 19 Division of Endocrinology and Metabolism, Asan Medical Center, University of Ulsan College of Medicine, Seoul, 05505, Korea. 20 Orthopaedics, Department of Clinical Sciences Lund, Lund University, SE-22 100, Lund, Sweden. 21 Bone and Muscle Research Lab, Ton Duc Thang University, Ho Chi Minh City, 700000, Vietnam. 22 School of Biomedical Engineering, University of Technology Sydney, Sydney, NSW, 2007, Australia. 23 Clinical Translation and Advanced Education, Garvan Institute of Medical Research, Sydney, NSW, 2010, Australia. 24 Institute of Chinese Medicine, The Chinese University of Hong Kong, Hong Kong, China. 25 Institute of Genetic Medicine, Newcastle University, Newcastle-upon-Tyne, NE1 7RU, UK. 26 Institute of Translational Genomics, Helmholtz Zentrum München, 85764, München, Germany. 27 Department of Emergengy Medicine, Landspitali, The National University Hospital of Iceland, 101, Reykjavik, Iceland. 28 Research Institute in Emergency Medicine, Landspitali, The National University Hospital of Iceland, and University of Iceland, 101, Reykjavik, Iceland. 29 Department of Medicine, Landspitali-The National University Hospital of Iceland, 101, Reykjavik, Iceland. 30 Department of Orthopedic Surgery, Akureyri Hospital, 600, Akureyri, Iceland. 31 Institution of Health Science, University of Akureyri, 600, Akureyri, Iceland. 32 Research Service Center, Reykjavik, 201, Iceland. 33 Department of Endocrinology and Metabolism, Landspitali, The National University Hospital of Iceland, 101, Reykjavik, Iceland. 34 Department of Immunology, Landspitali-The National University Hospital of Iceland, 101, Reykjavik, Iceland. 35 School of Engineering and Natural Sciences, University of Iceland, Reykjavik, 107, Iceland. 36 deCODE genetics/Amgen Inc., Reykjavik, 101, Iceland. kstefans@decode.is. 37 Faculty of Medicine, University of Iceland, Reykjavik, 101, Iceland. kstefans@decode.is. (Nature Publishing Group, 2019-05-24)
      The original HTML version of this Article was updated shortly after publication to add links to the Peer Review file.In addition, affiliations 16 and 17 incorrectly read 'School of Medicine Sydney, University of Notre Dame Australia, Sydney, WA, 6160, Australia' and 'St Vincent's Clinical School, University of New South Wales Medicine, University of New South Wales, Sydney, NSW, 2052, Australia.' This has now been corrected in both the PDF and HTML versions of the Article.
    • Dampness, mould, onset and remission of adult respiratory symptoms, asthma and rhinitis.

      Wang, Juan; Pindus, Mihkel; Janson, Christer; Sigsgaard, Torben; Kim, Jeong-Lim; Holm, Mathias; Sommar, Johan; Orru, Hans; Gislason, Thorarinn; Johannessen, Ane; Bertelsen, Randi J; Norbäck, Dan; 1 Dept of Medical Sciences, Occupational and Environmental Medicine, Uppsala University, Uppsala, Sweden. 2 These authors contributed equally to this work. 3 Institute of Family Medicine and Public Health, University of Tartu, Tartu, Estonia. 4 Dept of Medical Sciences, Respiratory, Allergy and Sleep Research, Uppsala University, Uppsala, Sweden. 5 Dept of Public Health, Section for Environment, Occupation and Health, Aarhus University, Danish Ramazzini Centre, Aarhus, Denmark. 6 Occupational and Environmental Medicine, Gothenburg University, Gothenburg, Sweden. 7 Occupational and Environmental Medicine, Dept of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden. 8 Landspitali University Hospital (E7), Reykjavik, Iceland. 9 Centre for International Health, Dept of Global Public Health and Primary Care, University of Bergen, Bergen, Norway. 10 Dept of Occupational Medicine, Haukeland University Hospital, Bergen, Norway. 11 Dept of Clinical Science, University of Bergen, Bergen, Norway. (European Respiratory Society, 2019-05-23)
      STUDY QUESTION: Is dampness and indoor mould associated with onset and remission of respiratory symptoms, asthma and rhinitis among adults? MATERIALS AND METHODS: Associations between dampness, mould and mould odour at home and at work and respiratory health were investigated in a cohort of 11 506 adults from Iceland, Norway, Sweden, Denmark and Estonia. They answered a questionnaire at baseline and 10 years later, with questions on respiratory health, home and work environment. RESULTS: Baseline water damage, floor dampness, mould and mould odour at home were associated with onset of respiratory symptoms and asthma (OR 1.23-2.24). Dampness at home during follow-up was associated with onset of respiratory symptoms, asthma and rhinitis (OR 1.21-1.52). Dampness at work during follow-up was associated with onset of respiratory symptoms, asthma and rhinitis (OR 1.31-1.50). Combined dampness at home and at work increased the risk of onset of respiratory symptoms and rhinitis. Dampness and mould at home and at work decreased remission of respiratory symptoms and rhinitis. THE ANSWER TO THE QUESTION: Dampness and mould at home and at work can increase onset of respiratory symptoms, asthma and rhinitis, and decrease remission.
    • Development of a novel benchmark method to identify and characterize best practices in home care across six European countries: design, baseline, and rationale of the IBenC project.

      van der Roest, Henriëtte G; van Eenoo, Liza; van Lier, Lisanne I; Onder, Graziano; Garms-Homolová, Vjenka; Smit, Johannes H; Finne-Soveri, Harriet; Jónsson, Pálmi V; Draisma, Stasja; Declercq, Anja; Bosmans, Judith E; van Hout, Hein P J; 1 Department of General Practice and Elderly Care Medicine, Amsterdam Public Health research institute, Amsterdam UMC, VU University medical center, Van der Boechorststraat 7, 1081, BT, Amsterdam, The Netherlands. hg.vanderroest@gmail.com. 2 LUCAS Centre for Care Research and Consultancy, KU Leuven, Leuven, Belgium. 3 Department of General Practice and Elderly Care Medicine, Amsterdam Public Health research institute, Amsterdam UMC, VU University medical center, Van der Boechorststraat 7, 1081, BT, Amsterdam, The Netherlands. 4 Department of Geriatrics, Neuroscience and Orthopedics, Agostino Gemelli University Hospital, Università Cattolica del Sacro Cuore, Rome, Italy. 5 Department of Economics and Law, HTW Berlin, University of Applied Sciences, Berlin, Germany. 6 Department of Psychiatry, Amsterdam Public Health research institute, Amsterdam UMC, Vrije Universiteit Amsterdam, The Netherlands & GGZ inGeest Specialized Mental Health Care, Research and Innovation, Amsterdam, The Netherlands. 7 Department of Wellbeing, National Institute for Health and Welfare, Helsinki, Finland. 8 Department of Geriatrics, Landspitali University Hospital, and Faculty of Medicine, University of Iceland, Reykjavík, Iceland. 9 Department of Health Sciences, Faculty of Science, Amsterdam Public Health research institute, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands. (BioMed Central, 2019-05-15)
      BACKGROUND: Europe's ageing society leads to an increased demand for long-term care, thereby putting a strain on the sustainability of health care systems. The 'Identifying best practices for care-dependent elderly by Benchmarking Costs and outcomes of Community Care' (IBenC) project aims to develop a new benchmark methodology based on quality of care and cost of care utilization to identify best practices in home care. The study's baseline data, methodology, and rationale are reported. METHODS: Home care organizations in Belgium, Finland, Germany, Iceland, Italy, and the Netherlands, home care clients of 65 years and over receiving home care, and professionals working in these organizations were included. Client data were collected according to a prospective longitudinal design with the interRAI Home Care instrument. Assessments were performed at baseline, after six and 12 months by trained (research) nurses. Characteristics of home care organizations and professionals were collected cross-sectionally with online surveys. RESULTS: Thirty-eight home care organizations, 2884 home care clients, and 1067 professionals were enrolled. Home care clients were mainly female (66.9%), on average 82.9 years (± 7.3). Extensive support in activities of daily living was needed for 41.6% of the sample, and 17.6% suffered cognitive decline. Care professionals were mainly female (93.4%), and over 45 years (52.8%). Considerable country differences were found. CONCLUSION: A unique, international, comprehensive database is established, containing in-depth information on home care organizations, their clients and staff members. The variety of data enables the development of a novel cost-quality benchmark method, based on interRAI-HC data. This benchmark can be used to explore relevant links between organizational efficiency and organizational and staff characteristics.
    • Reducing recurrence in non-muscle-invasive bladder cancer by systematically implementing guideline-based recommendations: effect of a prospective intervention in primary bladder cancer patients.

      Sörenby, Anne; Baseckas, Gediminas; Bendahl, Pär-Ola; Brändstedt, Johan; Håkansson, Ulf; Nilsson, Stefan; Patschan, Oliver; Tinzl, Martina; Wokander, Mats; Liedberg, Fredrik; Gudjonsson, Sigurdur; 1 a Department of Urology , Skåne University Hospital , Malmö , Sweden. 2 b Department of Translational Medicine , Lund University , Malmö , Sweden. 3 c Division of Oncology and Pathology, Department of Clinical Sciences Lund , Lund University, Medicon Village , Lund , Sweden. 4 d Department of Urology , Landspitali University Hospital , Reykjavik , Iceland. (Taylor & Francis, 2019-05-08)
      OBJECTIVE: In non-muscle-invasive bladder cancer (NMIBC), local recurrence after transurethral resection of the bladder (TURB) is common. Outcomes vary between urological centres, partly due to the sub-optimal surgical technique and insufficient application of measures recommended in the guidelines. This study evaluated early recurrence rates after primary TURB for NMIBC before and after introducing a standardized treatment protocol. METHODS: Medical records of all patients undergoing primary TURB for NMIBC in 2010 at Skåne University Hospital, Malmö, Sweden, were reviewed. A new treatment protocol for NMIBC was defined and introduced in 2013, and results documented during the first year thereafter were compared with those recorded in 2010 prior to the intervention. The primary endpoint was early recurrence at first control cystoscopy. Comparisons were made by Chi-square analysis and Fisher's exact test. Recurrence-free survival (RFS) in the two cohorts was also investigated. RESULTS: TURB was performed on 116 and 159 patients before and after the intervention, respectively. The early recurrence rate decreased from 22% to 9.6% (p = 0.005) at the first control cystoscopy after treatment. Residual/Recurrent tumour at the first control cystoscopy after the primary TURB (i.e. at second-look resection or first control cystoscopy) decreased from 31% to 20% (p = 0.038). The proportion of specimens containing muscle in T1 tumours increased from 55% to 94% (p < 0.001). RFS was improved in the intervention group (HR = 0.65, CI = 0.43-1.0; p = 0.05). CONCLUSIONS: Introduction of a standardized protocol and reducing the number of surgeons for primary treatment of NMIBC decreased the early recurrence rate from 22% to 9.6% and lowered the recurrence incidence by 35%.
    • GBA and APOE ε4 associate with sporadic dementia with Lewy bodies in European genome wide association study.

      Rongve, Arvid; Witoelar, Aree; Ruiz, Agustín; Athanasiu, Lavinia; Abdelnour, Carla; Clarimon, Jordi; Heilmann-Heimbach, Stefanie; Hernández, Isabel; Moreno-Grau, Sonia; de Rojas, Itziar; Morenas-Rodríguez, Estrella; Fladby, Tormod; Sando, Sigrid B; Bråthen, Geir; Blanc, Frédéric; Bousiges, Olivier; Lemstra, Afina W; van Steenoven, Inger; Londos, Elisabet; Almdahl, Ina S; Pålhaugen, Lene; Eriksen, Jon A; Djurovic, Srdjan; Stordal, Eystein; Saltvedt, Ingvild; Ulstein, Ingun D; Bettella, Francesco; Desikan, Rahul S; Idland, Ane-Victoria; Toft, Mathias; Pihlstrøm, Lasse; Snaedal, Jon; Tárraga, Lluís; Boada, Mercè; Lleó, Alberto; Stefánsson, Hreinn; Stefánsson, Kári; Ramírez, Alfredo; Aarsland, Dag; Andreassen, Ole A; 1 Haugesund Hospital, Helse Fonna, Department of Research and Innovation, Haugesund, Norway. arvid.rongve@helse-fonna.no. 2 The University of Bergen, Department of Clinical Medicine (K1), Bergen, Norway. arvid.rongve@helse-fonna.no. 3 NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway. 4 Institute of Clinical Medicine, University of Oslo, Oslo, Norway. 5 Memory Clinic and Research Center of Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya (UIC), Barcelona, Spain. 6 Department of Neurology, IIB Sant Pau, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain. 7 Center for Networker Biomedical Research in Neurodegenerative Diseases (CIBERNED), Madrid and Barcelona, Spain. 8 Institute of Human Genetics, University of Bonn, Bonn, Germany. 9 Department of Genomics, Life & Brain Center, University of Bonn, Bonn, Germany. 10 Department of Neurology, Akershus University Hospital, Lørenskog, Norway. 11 University of Oslo, AHUS Campus, Oslo, Norway. 12 Department of Neuromedicine and Movement Science, Norwegian University of Science and Technology, Trondheim, Norway. 13 Department of Neurology, St Olav's Hospital, Trondheim, Norway. 14 University Hospital of Strasbourg, CMRR (Memory Resources and Research Centre), Geriatrics Department, Strasbourg, France. 15 University of Strasbourg and CNRS, ICube laboratory and FMTS, team IMIS/Neurocrypto, Strasbourg, France. 16 University Hospital of Strasbourg, CMRR (Memory Resources and Research Centre), Laboratory of Biochemistry and Molecular Biology, Strasbourg, France. 17 University of Strasbourg and CNRS, Laboratoire de Neurosciences Cognitives et Adaptatives (LNCA), UMR7364, 67000, Strasbourg, France. 18 Alzheimercenter & Department of Neurology VU University Medical Center, Amsterdam, the Netherlands. 19 Lund University, Skane University Hospital, Institute of Clinical Sciences, Malmö, Sweden. 20 Department of Geriatric Psychiatry, Oslo University Hospital, Oslo, Norway. 21 Department of Medical Genetics, Oslo University Hospital, Oslo, Norway. 22 NORMENT, KG Jebsen Centre for Psychosis Research, Department of Clinical Science, University of Bergen, Bergen, Norway. 23 Department of Psychiatry, Namsos Hospital, Namsos, Norway. 24 Department of Mental Health, Norwegian University of Science and Technology, Trondheim, Norway. 25 Department of Geriatrics, St. Olav's Hospital, Trondheim, Norway. 26 Departments of Radiology and Biomedical Imaging, Neurology and Pediatrics, UCSF, San Francisco, USA. 27 Oslo Delirium Research Group, Department of Geriatric Medicine, Institute of Clinical Medicine, University of Oslo, Oslo, Norway. 28 Research Group for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Oslo, Norway. 29 Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway. 30 Department of Neurology, Oslo University Hospital, Oslo, Norway. 31 Landspitali University Hospital, Reykjavik, Iceland. 32 DeCODE genetics, Reykjavik, Iceland. 33 Division for Neurogenetics and Molecular Psychiatry, Department of Psychiatry and Psychotherapy, Medical Faculty, University of Cologne, 50924, Cologne, Germany. 34 Department for Neurodegenerative Diseases and Geriatric Psychiatry, University of Bonn, 53127, Bonn, Germany. 35 Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK. daarsland@gmail.com. 36 Center for Age-Related Diseases, Stavanger University Hospital, Stavanger, Norway. daarsland@gmail.com. 37 NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway. ole.andreassen@medisin.uio.no. 38 Institute of Clinical Medicine, University of Oslo, Oslo, Norway. ole.andreassen@medisin.uio.no. (Nature Publishing Group, 2019-05-07)
      Dementia with Lewy Bodies (DLB) is a common neurodegenerative disorder with poor prognosis and mainly unknown pathophysiology. Heritability estimates exceed 30% but few genetic risk variants have been identified. Here we investigated common genetic variants associated with DLB in a large European multisite sample. We performed a genome wide association study in Norwegian and European cohorts of 720 DLB cases and 6490 controls and included 19 top-associated single-nucleotide polymorphisms in an additional cohort of 108 DLB cases and 75545 controls from Iceland. Overall the study included 828 DLB cases and 82035 controls. Variants in the ASH1L/GBA (Chr1q22) and APOE ε4 (Chr19) loci were associated with DLB surpassing the genome-wide significance threshold (p < 5 × 10-8). One additional genetic locus previously linked to psychosis in Alzheimer's disease, ZFPM1 (Chr16q24.2), showed suggestive association with DLB at p-value < 1 × 10-6. We report two susceptibility loci for DLB at genome-wide significance, providing insight into etiological factors. These findings highlight the complex relationship between the genetic architecture of DLB and other neurodegenerative disorders.
    • GWAS of bone size yields twelve loci that also affect height, BMD, osteoarthritis or fractures.

      Styrkarsdottir, Unnur; Stefansson, Olafur A; Gunnarsdottir, Kristbjorg; Thorleifsson, Gudmar; Lund, Sigrun H; Stefansdottir, Lilja; Juliusson, Kristinn; Agustsdottir, Arna B; Zink, Florian; Halldorsson, Gisli H; Ivarsdottir, Erna V; Benonisdottir, Stefania; Jonsson, Hakon; Gylfason, Arnaldur; Norland, Kristjan; Trajanoska, Katerina; Boer, Cindy G; Southam, Lorraine; Leung, Jason C S; Tang, Nelson L S; Kwok, Timothy C Y; Lee, Jenny S W; Ho, Suzanne C; Byrjalsen, Inger; Center, Jacqueline R; Lee, Seung Hun; Koh, Jung-Min; Lohmander, L Stefan; Ho-Pham, Lan T; Nguyen, Tuan V; Eisman, John A; Woo, Jean; Leung, Ping-C; Loughlin, John; Zeggini, Eleftheria; Christiansen, Claus; Rivadeneira, Fernando; van Meurs, Joyce; Uitterlinden, Andre G; Mogensen, Brynjolfur; Jonsson, Helgi; Ingvarsson, Thorvaldur; Sigurdsson, Gunnar; Benediktsson, Rafn; Sulem, Patrick; Jonsdottir, Ingileif; Masson, Gisli; Holm, Hilma; Norddahl, Gudmundur L; Thorsteinsdottir, Unnur; Gudbjartsson, Daniel F; Stefansson, Kari; 1 deCODE genetics/Amgen Inc., Reykjavik, 101, Iceland. unnur.styrkarsdottir@decode.is. 2 deCODE genetics/Amgen Inc., Reykjavik, 101, Iceland. 3 Faculty of Medicine, University of Iceland, Reykjavik, 101, Iceland. 4 Department of Epidemiology, ErasmusMC, 3015 GD, Rotterdam, The Netherlands. 5 Department of Internal Medicine, ErasmusMC, 3015 GD, Rotterdam, the Netherlands. 6 Wellcome Trust Sanger Institute, Hinxton, CB10 1SA, UK. 7 Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK. 8 Jockey Club Centre for Osteoporosis Care and Control, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, China. 9 Faculty of Medicine, Department of Chemical Pathology and Laboratory for Genetics of Disease Susceptibility, Li Ka Shing Institute of Health Sciences,, The Chinese University of Hong Kong, Hong Kong, China. 10 CUHK Shenzhen Research Institute, Shenzhen, 518000, China. 11 Department of Medicine and Therapeutics, Prince of Wales Hospital, Hong Kong, China. 12 Faculty of Medicine, Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, China. 13 Department of Medicine, Alice Ho Miu Ling Nethersole Hospital and Tai Po Hospital, Hong Kong, China. 14 JC School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, China. 15 Nordic Bioscience A/S, 2730, Herlev, Denmark. 16 Bone Biology Division, Garvan Institute of Medical Research, Sydney, NSW, 2010, Australia. 17 School of Medicine Sydney, University of Notre Dame Australia, Sydney, NSW, 2010, Australia. 18 St Vincent's Clinical School, University of New South Wales, Sydney, NSW, 2010, Australia. 19 Division of Endocrinology and Metabolism, Asan Medical Center, University of Ulsan College of Medicine, Seoul, 05505, Korea. 20 Orthopaedics, Department of Clinical Sciences Lund, Lund University, SE-22 100, Lund, Sweden. 21 Bone and Muscle Research Lab, Ton Duc Thang University, Ho Chi Minh City, 700000, Vietnam. 22 School of Biomedical Engineering, University of Technology Sydney, Sydney, NSW, 2007, Australia. 23 Clinical Translation and Advanced Education, Garvan Institute of Medical Research, Sydney, NSW, 2010, Australia. 24 Institute of Chinese Medicine, The Chinese University of Hong Kong, Hong Kong, China. 25 Institute of Genetic Medicine, Newcastle University, Newcastle-upon-Tyne, NE1 7RU, UK. 26 Institute of Translational Genomics, Helmholtz Zentrum München, 85764, München, Germany. 27 Department of Emergengy Medicine, Landspitali, The National University Hospital of Iceland, 101, Reykjavik, Iceland. 28 Research Institute in Emergency Medicine, Landspitali, The National University Hospital of Iceland, and University of Iceland, 101, Reykjavik, Iceland. 29 Department of Medicine, Landspitali-The National University Hospital of Iceland, 101, Reykjavik, Iceland. 30 Department of Orthopedic Surgery, Akureyri Hospital, 600, Akureyri, Iceland. 31 Institution of Health Science, University of Akureyri, 600, Akureyri, Iceland. 32 Research Service Center, Reykjavik, 201, Iceland. 33 Department of Endocrinology and Metabolism, Landspitali, The National University Hospital of Iceland, 101, Reykjavik, Iceland. 34 Department of Immunology, Landspitali-The National University Hospital of Iceland, 101, Reykjavik, Iceland. 35 School of Engineering and Natural Sciences, University of Iceland, Reykjavik, 107, Iceland. 36 deCODE genetics/Amgen Inc., Reykjavik, 101, Iceland. kstefans@decode.is. 37 Faculty of Medicine, University of Iceland, Reykjavik, 101, Iceland. kstefans@decode.is. (Nature Publishing Group, 2019-05-03)
      Bone area is one measure of bone size that is easily derived from dual-energy X-ray absorptiometry (DXA) scans. In a GWA study of DXA bone area of the hip and lumbar spine (N ≥ 28,954), we find thirteen independent association signals at twelve loci that replicate in samples of European and East Asian descent (N = 13,608 - 21,277). Eight DXA area loci associate with osteoarthritis, including rs143384 in GDF5 and a missense variant in COL11A1 (rs3753841). The strongest DXA area association is with rs11614913[T] in the microRNA MIR196A2 gene that associates with lumbar spine area (P = 2.3 × 10-42, β = -0.090) and confers risk of hip fracture (P = 1.0 × 10-8, OR = 1.11). We demonstrate that the risk allele is less efficient in repressing miR-196a-5p target genes. We also show that the DXA area measure contributes to the risk of hip fracture independent of bone density.
    • Variability in functional outcome and treatment practices by treatment center after out-of-hospital cardiac arrest: analysis of International Cardiac Arrest Registry.

      May, Teresa L; Lary, Christine W; Riker, Richard R; Friberg, Hans; Patel, Nainesh; Søreide, Eldar; McPherson, John A; Undén, Johan; Hand, Robert; Sunde, Kjetil; Stammet, Pascal; Rubertsson, Stein; Belohlvaek, Jan; Dupont, Allison; Hirsch, Karen G; Valsson, Felix; Kern, Karl; Sadaka, Farid; Israelsson, Johan; Dankiewicz, Josef; Nielsen, Niklas; Seder, David B; Agarwal, Sachin; 1 Department of Critical Care Services, Maine Medical Center, 22 Bramhall St, Portland, ME, 04102, USA. tmay@mmc.org. 2 Clinical and Translational Science Institute, Tufts University, Boston, ME, 02111, USA. tmay@mmc.org. 3 Center for Outcomes Research, Maine Medical Center, Portland, ME, USA. 4 Department of Critical Care Services, Maine Medical Center, 22 Bramhall St, Portland, ME, 04102, USA. 5 Department of Anesthesia and Intensive Care, Skåne University Hospital, Lund University, Lund, Sweden. 6 Division of Cardiovascular Medicine, Lehigh Valley Hospital and Health Network, Allentown, PA, USA. 7 Critical Care and Anesthesiology Research Group, Stavanger University Hospital, Stavanger, Norway. 8 Department Clinical Medicine, University of Bergen, Bergen, Norway. 9 Division of Cardiovascular Medicine, Vanderbilt University Medical Center, Nashville, TN, USA. 10 Department of Clinical Sciences, Lund University, Getingevägen, 22185, Lund, Sweden. 11 Department of Intensive and Perioperative Care, Skåne University Hospital, Malmö, Sweden. 12 Department of Critical Care, Eastern Maine Medical Center, Bangor, ME, USA. 13 Department of Anaesthesiology, Division of Emergencies and Critical Care, Oslo University Hospital, Oslo, Norway. 14 Institute of Clinical Medicine, University of Oslo, Oslo, Norway. 15 Medical Department National Rescue Services, Luxembourg, 14, rue Stümper, 2557, Luxembourg, Luxembourg. 16 Department of Surgical Sciences/Anesthesiology and Intensive Care, Uppsala University, Uppsala, Sweden. 17 Department of Internal Medicine II, Cardiovascular Medicine, General Teaching Hospital and 1st Medical School, Charles University in Prague, Prague, Czech Republic. 18 Department of Cardiology, Northeast Georgia Medical Center, Gainesville, Georgia, USA. 19 Stanford Neurocritical Care Program, Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA. 20 Department of Anesthesia and Intensive Care, Landspitali University Hospital, Reykyavik, Iceland. 21 Division of Cardiology, Sarver Heart Center, University of Arizona, Tucson, USA. 22 Mercy Hospital St Louis, St Louis University, St. Louis, MO, USA. 23 Department of Internal Medicine, Division of Cardiology, Kalmar County Hospital, Kalmar, Sweden. 24 Department of Intensive and Perioperative Care, Skåne University Hospital, Lund, Sweden. 25 Department of Clinical Sciences, Anesthesia and Intensive Care, Lund University, Helsingborg Hospital, Helsingborg, Sweden. 26 Department of Neurology, Columbia-Presbyterian Medical Center, New York, NY, USA. (Springer, 2019-05-01)
      Functional outcomes vary between centers after out-of-hospital cardiac arrest (OHCA) and are partially explained by pre-existing health status and arrest characteristics, while the effects of in-hospital treatments on functional outcome are less understood. We examined variation in functional outcomes by center after adjusting for patient- and arrest-specific characteristics and evaluated how in-hospital management differs between high- and low-performing centers. Analysis of observational registry data within the International Cardiac Arrest Registry was used to perform a hierarchical model of center-specific risk standardized rates for good outcome, adjusted for demographics, pre-existing functional status, and arrest-related factors with treatment center as a random effect variable. We described the variability in treatments and diagnostic tests that may influence outcome at centers with adjusted rates significantly above and below registry average. A total of 3855 patients were admitted to an ICU following cardiac arrest with return of spontaneous circulation. The overall prevalence of good outcome was 11-63% among centers. After adjustment, center-specific risk standardized rates for good functional outcome ranged from 0.47 (0.37-0.58) to 0.20 (0.12-0.26). High-performing centers had faster time to goal temperature, were more likely to have goal temperature of 33 °C, more likely to perform unconscious cardiac catheterization and percutaneous coronary intervention, and had differing prognostication practices than low-performing centers. Center-specific differences in outcomes after OHCA after adjusting for patient-specific factors exist. This variation could partially be explained by in-hospital management differences. Future research should address the contribution of these factors to the differences in outcomes after resuscitation.
    • Oral anticoagulant monitoring: Are we on the right track?

      Onundarson, Pall T; Flygenring, Bjorn; 1 Landspitali/The National University Hospital of Iceland, Reykjavik, Iceland. 2 Faculty of Medicine, University of Iceland, Reykjavik, Iceland. (Wiley, 2019-05-01)
      Vitamin K antagonists (VKAs) cannot be administered without regular monitoring in order to assure their efficacy and safety. Indeed, if well managed, the VKAs appear to be no less efficacious or safe than the newer direct oral anticoagulants (DOACs). Although it is claimed that no regular monitoring of the DOACs is needed, their levels are increasingly being measured under a variety of circumstances, for example, prior to surgery, in suspected overdose, to confirm effective reversal, in patients with malabsorption and to assess patient compliance. Although no therapeutic range has been identified for the DOACs, it has been demonstrated for dabigatran and edoxaban that their antithrombotic effect increases gradually with increasing concentrations and that the risk of major bleeding also gradually increases. Furthermore, it has been determined that almost all dabigatran-related thrombotic events occur in patients with the lowest quartile concentration of the drug. This suggests that to assure an ideal effect of DOACs in all patients taking them, some form of regular monitoring and dose tailoring should be performed. For the vitamin K antagonists, the best outcome is obtained using formal algorithms and centralized management. Furthermore, data suggest that replacing the standard prothrombin time as a monitoring test may increase the stability of VKA anticoagulation with consequent reduction in thromboembolism without an increase in bleeding. Thus, it is likely that the outcome of all current oral anticoagulants can be improved in the coming years by improving monitoring and tailoring their effect.
    • Outcomes after STEMI in old multimorbid patients with complex health needs and the effect of invasive management.

      Gudnadottir, Gudny Stella; James, Stefan Karl; Andersen, Karl; Lagerqvist, Bo; Thrainsdottir, Inga Sigurros; Ravn-Fischer, Annica; Varenhorst, Christoph; Gudnason, Thorarinn; 1 Department of Geriatrics, Sahlgrenska University Hospital, Gothenburg, Sweden; Department of Cardiology and Cardiovascular Research Centre, Landspitali University Hospital, Reykjavik, Iceland; School of Health Sciences, University of Iceland, Reykjavik, Iceland. Electronic address: gudnystella@gmail.com. 2 Uppsala Clinical Research Centre (UCR); Department of Medical Sciences, Cardiology, Uppsala University, Uppsala, Sweden. 3 Department of Cardiology and Cardiovascular Research Centre, Landspitali University Hospital, Reykjavik, Iceland; School of Health Sciences, University of Iceland, Reykjavik, Iceland. 4 Department of Cardiology and Cardiovascular Research Centre, Landspitali University Hospital, Reykjavik, Iceland. 5 Department of Cardiology, Sahlgrenska University Hospital, Gothenburg, Sweden. 6 Department of Medical Sciences, Cardiology, Uppsala University, Uppsala, Sweden; Pfizer AB, Sollentuna, Sweden. (Mosby-Elsevier, 2019-05)
      The aim of this study was to assess one-year outcomes of invasive and non-invasive strategies in ST-elevation myocardial infarction (STEMI) among multimorbid older people with complex health needs. We included patients, registered between 2006 and 2013 in the SWEDEHEART registry, who were 70 years old or older with STEMI, had multimorbidity and complex health needs and were discharged alive. The one-year outcomes of patients who underwent invasive strategy (examined with coronary angiography ≤14 days) were compared to those who did not. The primary event was a composite of all-cause death, admission due to new acute coronary syndrome, stroke or transient ischemic attack. We identified patients, and 1089 were managed invasively and 570 non-invasively. The mean age was 79 years and 83 years in the 2 groups, respectively. After multivariable adjustment for baseline differences between the groups, including propensity scores, the primary event occurred in 31% of patients in the invasive group and 55% in the non-invasive group, adjusted hazard ratio (95% confidence intervals): 0.67 (0.54-0.83). One-year mortality was 18% in the invasive group and 45% in the non-invasive group, adjusted hazard ratio 0.51 (0.39-0.65). Multimorbid older people with complex health needs and STEMI had high rates of new ischemic events and death. In this cohort of older, high risk STEMI patients, an invasive strategy was associated with lower event rates. Randomized studies are needed to clarify whether these high risk patients who might benefit from invasive care are being managed too conservatively.
    • A Missense Variant in PTPN22 is a Risk Factor for Drug-induced Liver Injury.

      Cirulli, Elizabeth T; Nicoletti, Paola; Abramson, Karen; Andrade, Raul J; Bjornsson, Einar S; Chalasani, Naga; Fontana, Robert J; Hallberg, Pär; Li, Yi Ju; Lucena, M Isabel; Long, Nanye; Molokhia, Mariam; Nelson, Matthew R; Odin, Joseph A; Pirmohamed, Munir; Rafnar, Thorunn; Serrano, Jose; Stefánsson, Kári; Stolz, Andrew; Daly, Ann K; Aithal, Guruprasad P; Watkins, Paul B; 1 Duke Center for applied Genomics and Precision Medicine, Duke University, Durham, North Carolina. 2 Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, New York; Sema4, a Mount Sinai venture, Stamford, Connecticut. Electronic address: paola.nicoletti@mssm.edu. 3 Duke Molecular Physiology Institute, Duke University, Durham, North Carolina. 4 UGC Digestivo, Instituto de Investigación Biomédica de Málaga (IBIMA), Hospital Universitario Virgen de la Victoria, Universidad de Málaga, Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Málaga, Spain. 5 Department of Internal Medicine, Landspitali University Hospital, Reykjavik, Iceland. 6 Division of Gastroenterology and Hepatology, Indiana University School of Medicine, Indianapolis, Indiana. 7 University of Michigan, Ann Arbor, Michigan. 8 Department of Medical Sciences and Science for Life Laboratory, Uppsala University, Uppsala, Sweden. 9 Duke Molecular Physiology Institute, Duke University, Durham, North Carolina; Department of Biostatistics and Bioinformatics, Duke University, Durham, North Carolina. 10 Institute for Cyber-enabled Research, Michigan State University, East Lansing, Michigan. 11 School of Population Health & Environmental Sciences, King's College, London, UK. 12 Target Sciences, GSK, King of Prussia, Pennsylvania. 13 Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, New York. 14 Department of Molecular and Clinical Pharmacology, University of Liverpool, Liverpool, UK. 15 deCODE genetics, 101 Reykjavik, Iceland. 16 National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, Maryland. 17 University of Southern California, Los Angeles, California. 18 Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne, UK. 19 Nottingham Digestive Diseases Centre and National Institute for Health Research (NIHR) Nottingham Biomedical Research Centre at the Nottingham University Hospital NHS Trust and University of Nottingham, Nottingham, UK. 20 UNC Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, North Carolina; University of North Carolina Institute for Drug Safety Sciences, Research Triangle Park, North Carolina. (W B SAUNDERS CO-ELSEVIER INC, 2019-05)
      We performed genetic analyses of a multiethnic cohort of patients with idiosyncratic drug-induced liver injury (DILI) to identify variants associated with susceptibility. We performed a genome-wide association study of 2048 individuals with DILI (cases) and 12,429 individuals without (controls). Our analysis included subjects of European (1806 cases and 10,397 controls), African American (133 cases and 1,314 controls), and Hispanic (109 cases and 718 controls) ancestry. We analyzed DNA from 113 Icelandic cases and 239,304 controls to validate our findings. We associated idiosyncratic DILI with rs2476601, a nonsynonymous polymorphism that encodes a substitution of tryptophan with arginine in the protein tyrosine phosphatase, nonreceptor type 22 gene (PTPN22) (odds ratio [OR] 1.44; 95% confidence interval [CI] 1.28-1.62; P = 1.2 × 10 In a genome-wide association study, we identified rs2476601 in PTPN22 as a non-HLA variant that associates with risk of liver injury caused by multiple drugs and validated our finding in a separate cohort. This variant has been associated with increased risk of autoimmune diseases, providing support for the concept that alterations in immune regulation contribute to idiosyncratic DILI.
    • COPD patients' experiences, self-reported needs, and needs-driven strategies to cope with self-management

      Sigurgeirsdottir, Jonina; Halldorsdottir, Sigridur; Arnardottir, Ragnheidur Harpa; Gudmundsson, Gunnar; Bjornsson, Eythor Hreinn; [ 1 ] Univ Iceland, Fac Med, Reykjavik, Iceland [ 2 ] Reykjalundur Rehabil Ctr, Mosfellsbaer, Iceland [ 3 ] Univ Akureyri, Sch Hlth Sci, Akureyri, Iceland [ 4 ] Akureyri Hosp, Dept Rehabil, Akureyri, Iceland [ 5 ] Uppsala Univ, Dept Med Sci Resp Allergy & Sleep Res, Uppsala, Sweden Show more [ 6 ] Landspitali Univ Hosp, Dept Resp Med, Reykjavik, Iceland (DOVE Medical Press, 2019-05)
      Background: COPD is a common cause of morbidity and mortality. The aim of this study was to explore patients' experiences, self-reported needs, and needs-driven strategies to cope with self-management of COPD. Patients and methods: In this phenomenological study, 10 participants with mild to severe COPD were interviewed 1-2 times, until data saturation was reached. In total, 15 in-depth interviews were conducted, recorded, transcribed, and analyzed. Results: COPD negatively affected participants' physical and psychosocial well-being, their family relationships, and social life. They described their experiences of COPD like fighting a war without weapons in an ever-shrinking world with a loss of freedom at most levels, always fearing possible breathlessness. Fourteen needs were identified and eight clusters of needs-driven strategies that participants used to cope with self-management of COPD. Coping with the reality of COPD, a life-threatening disease, meant coping with dyspnea, feelings of suffocation, indescribable smoking addiction, anxiety, and lack of knowledge about the disease. Reduced participation in family and social life meant loss of ability to perform usual and treasured activities. Having a positive mindset, accepting help and assuming healthy lifestyle was important, as well as receiving continuous professional health care services. The participants' needs-driven strategies comprised conducting financial arrangements, maintaining hope, and fighting their smoking addiction, seeking knowledge about COPD, thinking differently, facing the broken chain of health care, and struggling with accepting support. Procrastination and avoidance were also evident. Finally, the study also found that participants experienced a perpetuating cycle of dyspnea, anxiety, and fear of breathlessness due to COPD which could lead to more severe dyspnea and even panic attacks. Conclusion: COPD negatively affects patients' physical and psychosocial well-being, family relationships and, social life. Identifying patients' self-reported needs and needs-driven strategies can enable clinicians to empower patients by educating them to improve their self-management.
    • Cardiovascular risk factors and incident giant cell arteritis: a population-based cohort study.

      Tomasson, G; Bjornsson, J; Zhang, Y; Gudnason, V; Merkel, P A; 1 a Department of Epidemiology and Biostatistics, Faculty of Medicine , University of Iceland , Reykjavik , Iceland. 2 b Department of Rheumatology , University Hospital , Reykjavik , Iceland. 3 c Centre for Rheumatology Research , University Hospital , Reykjavik , Iceland. 4 d Department of Pathology , Akureyri Regional Hospital , Akureyri , Iceland. 5 e Clinical Epidemiology Research and Training Unit , Boston University School of Medicine , Boston , MA , USA. 6 f Faculty of Medicine , University of Iceland , Reykjavik , Iceland. 7 g Icelandic Heart Association , Kopavogur , Iceland. 8 h Division of Rheumatology , University of Pennsylvania , Philadelphia , PA , USA. 9 i Department of Biostatistics, Epidemiology, and Informatics , University of Pennsylvania , Philadelphia , PA , USA. (Taylor & Francis, 2019-05)
      OBJECTIVE: To assess the strength of the effect of cardiovascular risk factors on the incidence of giant cell arteritis (GCA) in a general population context. METHOD: Data from the Reykjavik Study (RS), a population-based cohort study focusing on cardiovascular disease, were used. Everyone born in 1907-1935 living in Reykjavik, Iceland, or adjacent communities on 1 December 1967 were invited to participate. Subjects attended a study visit in 1967-1996 and information on cardiovascular risk factors [smoking habits, blood pressure, diabetes, body mass index (BMI), and serum cholesterol] was obtained. All temporal artery biopsies obtained from members of the RS cohort were re-examined by a single pathologist with expertise in vascular pathology. Effects of risk factors on GCA occurrence are expressed as incidence rate ratios (IRRs) with 95% confidence intervals (CIs). RESULTS: Altogether, 19 241 subjects contributed a median of 23.1 (interquartile range 17.6-29.4) years after the age of 50 to this analysis. During 444 126 person-years of follow-up, 194 subjects developed GCA, corresponding to an incidence rate of 43.6 (95% CI 37.8-50.2) per 100 000 person-years. Being overweight or obese were inversely associated with GCA, especially in women [IRRs 0.70 (0.48-1.02) and 0.31 (0.14-0.71), respectively]. There was a weaker association between BMI and incident GCA in men. Smoking was inversely associated with GCA in men [IRR 0.47 (0.27-0.81)], but not in women. CONCLUSIONS: The incidence of GCA in Iceland is very high. High BMI protects against the occurrence of GCA, and smoking may protect against GCA in men.