Kirsten Thisted og Ann-Sofie N. Gremaud (red.), Denmark and the New North Atlantic: Narratives and Memories in a Former Empire, Vol. 1 and 2. Aarhus: Aarhus University Press, 2020
A new local government structure is announced for Greenland from 2009. If the reform is carried through, Nanortalik the most southerly town will come together with Qaqortoq, then the new centre, and Narsaq. A suggestion by the mayor of Nanortalik about the number of civil servants that should move to the centre is the basis for calculating the potential loss of gross income (wages and profits) in the first years of the reform. With the civil servants follow some adults and children. On top of the direct loss of income come derived losses determined by a multiplier process. The size of the multiplier is estimated to be around 1,25. This is based on assumptions about income levels, expenditure patterns, and local income parts of sales. Full implementation of the reform could mean a loss of 5 plus percent of gross income. If other probable losses (e.g. fewer elected members of the local authority) are added in, the loss could rise to more than 7 percent. Tax rates are assumed not to be lowered by the departure of civil servants to the centre. To the contrary an increase in the tax rate for Nanortalik is envisaged as this small town in these years enjoys an advantage from taxing local people and foreign skilled workers operating a nearby gold mine. It is stressed that the paper doesn't evaluate the proposal for a reform, neither for the South of Greenland nor for Greenland as a whole. It is about possible very short term local effects
Background-Whereas heart failure (HF) is a complex clinical syndrome, conventional approaches to its management have treated it as a singular disease, leading to inadequate patient care and inefficient clinical trials. We hypothesized that applying advanced analytics to a large cohort of HF patients would improve prognostication of outcomes, identify distinct patient phenotypes, and detect heterogeneity in treatment response. Methods and Results-The Swedish Heart Failure Registry is a nationwide registry collecting detailed demographic, clinical, laboratory, and medication data and linked to databases with outcome information. We applied random forest modeling to identify predictors of 1-year survival. Cluster analysis was performed and validated using serial bootstrapping. Association between clusters and survival was assessed with Cox proportional hazards modeling and interaction testing was performed to assess for heterogeneity in response to HF pharmacotherapy across propensity-matched clusters. Our study included 44 886 HF patients enrolled in the Swedish Heart Failure Registry between 2000 and 2012. Random forest modeling demonstrated excellent calibration and discrimination for survival (C-statistic=0.83) whereas left ventricular ejection fraction did not (C-statistic=0.52): there were no meaningful differences per strata of left ventricular ejection fraction (1-year survival: 80%, 81%, 83%, and 84%). Cluster analysis using the 8 highest predictive variables identified 4 clinically relevant subgroups of HF with marked differences in 1-year survival. There were significant interactions between propensity-matched clusters (across age, sex, and left ventricular ejection fraction and the following medications: diuretics, angiotensin-converting enzyme inhibitors, )i-blockers, and nitrates, Pamp;lt;0.001, all). Conclusions-Machine learning algorithms accurately predicted outcomes in a large data set of HF patients. Cluster analysis identified 4 distinct phenotypes that differed significantly in outcomes and in response to therapeutics. Use of these novel analytic approaches has the potential to enhance effectiveness of current therapies and transform future HF clinical trials. ; Funding Agencies|Swedish Federal Government; Swedish Research Council; Swedish Heart-Lung Foundation; Stockholm County Council
Aims Left ventricular ejection fraction (EF) is required to categorize heart failure (HF) [i.e. HF with preserved (HFpEF), mid-range (HFmrEF), and reduced (HFrEF) EF] but is often not captured in population-based cohorts or non-HF registries. The aim was to create an algorithm that identifies EF subphenotypes for research purposes. Methods and results We included 42 061 HF patients from the Swedish Heart Failure Registry. As primary analysis, we performed two logistic regression models including 22 variables to predict (i) EF >= vs. = vs. = 50% and 0.76 (95% CI 0.75-0.76) for EF >= 40%. Similar results were achieved for HFrEF and HFpEF in the multinomial model, but the C-statistic for HFmrEF was lower: 0.63 (95% CI 0.63-0.64). The external validation showed similar discriminative ability to the development cohort. Conclusions Routine clinical characteristics could potentially be used to identify different EF subphenotypes in databases where EF is not readily available. Accuracy was good for the prediction of HFpEF and HFrEF but lower for HFmrEF. The proposed algorithm enables more effective research on HF in the big data setting. ; Funding Agencies|Swedish National Board of Health and Welfare; Swedish Association of Local Authorities and Regions; Swedish Society of Cardiology; Swedish Heart-Lung FoundationSwedish Heart-Lung Foundation; Servier, the NetherlandsNetherlands Government; EU/EFPIA Innovative Medicines Initiative 2 Joint Undertaking BigData@Heart [116074]; Swedish Research CouncilSwedish Research Council [2013-23897-104604-23, 523-2014-2336]; Swedish Heart Lung FoundationSwedish Heart-Lung Foundation [20150557, 20170841]; Stockholm County CouncilStockholm County Council [20140220, 20170112]; UCL Hospitals NIHR Biomedical Research Centre; Dutch Heart Foundation, a part of Facts and Figures
In: Lund , L C , Kristensen , K B , Reilev , M , Christensen , S , Thomsen , R W , Christiansen , C F , Støvring , H , Johansen , N B , Brun , N C , Hallas , J & Pottegård , A 2020 , ' Adverse outcomes and mortality in users of non-steroidal anti-inflammatory drugs who tested positive for SARS-CoV-2 : A Danish nationwide cohort study ' , PLOS Medicine , vol. 17 , no. 9 , e1003308 . https://doi.org/10.1371/journal.pmed.1003308
BACKGROUND: Concerns over the safety of non-steroidal anti-inflammatory drug (NSAID) use during severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection have been raised. We studied whether use of NSAIDs was associated with adverse outcomes and mortality during SARS-CoV-2 infection. METHODS AND FINDINGS: We conducted a population-based cohort study using Danish administrative and health registries. We included individuals who tested positive for SARS-CoV-2 during the period 27 February 2020 to 29 April 2020. NSAID users (defined as individuals having filled a prescription for NSAIDs up to 30 days before the SARS-CoV-2 test) were matched to up to 4 non-users on calendar week of the test date and propensity scores based on age, sex, relevant comorbidities, and use of selected prescription drugs. The main outcome was 30-day mortality, and NSAID users were compared to non-users using risk ratios (RRs) and risk differences (RDs). Secondary outcomes included hospitalization, intensive care unit (ICU) admission, mechanical ventilation, and acute renal replacement therapy. A total of 9,236 SARS-CoV-2 PCR-positive individuals were eligible for inclusion. The median age in the study cohort was 50 years, and 58% were female. Of these, 248 (2.7%) had filled a prescription for NSAIDs, and 535 (5.8%) died within 30 days. In the matched analyses, treatment with NSAIDs was not associated with 30-day mortality (RR 1.02, 95% CI 0.57 to 1.82, p = 0.95; RD 0.1%, 95% CI -3.5% to 3.7%, p = 0.95), risk of hospitalization (RR 1.16, 95% CI 0.87 to 1.53, p = 0.31; RD 3.3%, 95% CI -3.4% to 10%, p = 0.33), ICU admission (RR 1.04, 95% CI 0.54 to 2.02, p = 0.90; RD 0.2%, 95% CI -3.0% to 3.4%, p = 0.90), mechanical ventilation (RR 1.14, 95% CI 0.56 to 2.30, p = 0.72; RD 0.5%, 95% CI -2.5% to 3.6%, p = 0.73), or renal replacement therapy (RR 0.86, 95% CI 0.24 to 3.09, p = 0.81; RD -0.2%, 95% CI -2.0% to 1.6%, p = 0.81). The main limitations of the study are possible exposure misclassification, as not all individuals who fill an NSAID prescription use the drug continuously, and possible residual confounding by indication, as NSAIDs may generally be prescribed to healthier individuals due to their side effects, but on the other hand may also be prescribed for early symptoms of severe COVID-19. CONCLUSIONS: Use of NSAIDs was not associated with 30-day mortality, hospitalization, ICU admission, mechanical ventilation, or renal replacement therapy in Danish individuals who tested positive for SARS-CoV-2. TRIAL REGISTRATION: The European Union electronic Register of Post-Authorisation Studies EUPAS34734.
Aims Patients with advanced heart failure (AdHF) who are ineligible for heart transplantation (HTx) can become candidates for treatment with a left ventricular assist device (LVAD) in some countries, but not others. This reflects the lack of a systematic analysis of the usefulness of LVAD systems in this context, and of their benefits, limitations and cost-effectiveness. The SWEdish evaluation of left Ventricular Assist Device (SweVAD) study is a Phase IV, prospective, 1:1 randomized, non-blinded, multicentre trial that will examine the impact of assignment to mechanical circulatory support with guideline-directed LVAD destination therapy (GD-LVAD-DT) using the HeartMate 3 (HM3) continuous flow pump vs. guideline-directed medical therapy (GDMT) on survival in a population of AdHF patients ineligible for HTx. Methods A total of 80 patients will be recruited to SweVAD at the seven university hospitals in Sweden. The study population will comprise patients with AdHF (New York Heart Association class IIIB-IV, INTERMACS profile 2-6) who display signs of poor prognosis despite GDMT and who are not considered eligible for HTx. Participants will be followed for 2 years or until death occurs. Other endpoints will be determined by blinded adjudication. Patients who remain on study-assigned interventions beyond 2 years will be asked to continue follow-up for outcomes and adverse events for up to 5 years. Conclusion The SweVAD study will compare survival, medium-term benefits, costs and potential hazards between GD-LVAD-DT and GDMT and will provide a valuable reference point to guide destination therapy strategies for patients with AdHF ineligible for HTx. ; Funding Agencies|Sahlgrenska University Hospital; Swedish Research CouncilSwedish Research Council; Swedish Heart-Lung FoundationSwedish Heart-Lung Foundation; Swedish Federal Government under the ALF agreement [ALFGBG-775351, 447561, 726481]
Aims We aimed to derive and validate clinically useful clusters of patients with heart failure with preserved ejection fraction (HFpEF; left ventricular ejection fraction >= 50%). Methods and results We derived a cluster model from 6909 HFpEF patients from the Swedish Heart Failure Registry (SwedeHF) and externally validated this in 2153 patients from the Chronic Heart Failure ESC-guideline based Cardiology practice Quality project (CHECK-HF) registry. In SwedeHF, the median age was 80 [interquartile range 72-86] years, 52% of patients were female and most frequent comorbidities were hypertension (82%), atrial fibrillation (68%), and ischaemic heart disease (48%). Latent class analysis identified five distinct clusters: cluster 1 (10% of patients) were young patients with a low comorbidity burden and the highest proportion of implantable devices; cluster 2 (30%) patients had atrial fibrillation, hypertension without diabetes; cluster 3 (25%) patients were the oldest with many cardiovascular comorbidities and hypertension; cluster 4 (15%) patients had obesity, diabetes and hypertension; and cluster 5 (20%) patients were older with ischaemic heart disease, hypertension and renal failure and were most frequently prescribed diuretics. The clusters were reproduced in the CHECK-HF cohort. Patients in cluster 1 had the best prognosis, while patients in clusters 3 and 5 had the worst age- and sex-adjusted prognosis. Conclusions Five distinct clusters of HFpEF patients were identified that differed in clinical characteristics, heart failure drug therapy and prognosis. These results confirm the heterogeneity of HFpEF and form a basis for tailoring trial design to individualized drug therapy in HFpEF patients. ; Funding Agencies|Swedish National Board of Health and Welfare; Swedish Association of Local Authorities and Regions; Swedish Society of Cardiology; Swedish Heart-Lung FoundationSwedish Heart-Lung Foundation; Servier, the NetherlandsNetherlands Government; EU/EFPIA Innovative Medicines Initiative 2 Joint Undertaking BigData@Heart grant [116074]; Swedish Research CouncilSwedish Research CouncilEuropean Commission [2013-23897-104604-23, 523-2014-2336]; Swedish Heart Lung FoundationSwedish Heart-Lung Foundation [20150557, 20170841]; Stockholm County CouncilStockholm County Council [20140220, 20170112]; UCL Hospitals NIHR Biomedical Research Centre; Dutch Heart Foundation, as part of Facts and Figures
In: Pottegård , A , Kristensen , K B , Reilev , M , Lund , L C , Ernst , M T , Hallas , J , Thomsen , R W , Christiansen , C F , Sørensen , H T , Johansen , N B , Støvring , H , Christensen , S , Thomsen , M K , Husby , A , Voldstedlund , M , Kjær , J & C. Brun , N 2020 , ' Existing Data Sources in Clinical Epidemiology : The Danish COVID-19 Cohort ' , Clinical Epidemiology , vol. 12 , no. 2020 , pp. 875-881 . https://doi.org/10.2147/clep.s257519
Background: To facilitate research on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a prospective cohort of all Danish residents tested for SARS-CoV-2 in Denmark is established. Data Structure: All Danish residents tested by reverse transcriptase polymerase chain reactions (RT-PCR) for SARS-CoV-2 in Denmark are included. The cohort is identified using the Danish Microbiology Database. Individual-level record linkage between administrative and health-care registries is facilitated by the Danish Civil Registration System. Information on outcomes related to SARS-CoV-2 infection includes hospital admission, intensive care unit admission, mechanical ventilation, and death and is retrieved from the five administrative Danish regions, the Danish National Patient Registry, and the Danish Register of Causes of Death. The Patient Registry further provides a complete hospital contact history of somatic and psychiatric conditions and procedures. Data on all prescriptions filled at community pharmacies are available from the Danish National Prescription Registry. Health-care authorization status is obtained from the Danish Register of Healthcare Professionals. Finally, selected laboratory values are obtained from the Register of Laboratory Results for Research. The cohort is governed by a steering committee with representatives from the Danish Medicines Agency, Statens Serum Institut, the Danish Health Authority, the Danish Health Data Authority, Danish Patients, the Faculties of Health Sciences at the Danish universities, and Danish regions. The steering committee welcomes suggestions for research studies and collaborations. Research proposals will be prioritized based on timeliness and potential clinical and public health implications. All research protocols assessing specific hypotheses for medicines will be made publicly available using the European Union electronic Register of Post-Authorisation Studies. Conclusion: The Danish COVID-19 cohort includes all Danish residents with an RT-PCR test for SARS-CoV-2. Through individual-level linkage with existing Danish health and administrative registries, this is a valuable data source for epidemiological research on SARS-CoV-2.
BACKGROUND: To facilitate research on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a prospective cohort of all Danish residents tested for SARS-CoV-2 in Denmark is established. DATA STRUCTURE: All Danish residents tested by reverse transcriptase polymerase chain reactions (RT-PCR) for SARS-CoV-2 in Denmark are included. The cohort is identified using the Danish Microbiology Database. Individual-level record linkage between administrative and health-care registries is facilitated by the Danish Civil Registration System. Information on outcomes related to SARS-CoV-2 infection includes hospital admission, intensive care unit admission, mechanical ventilation, and death and is retrieved from the five administrative Danish regions, the Danish National Patient Registry, and the Danish Register of Causes of Death. The Patient Registry further provides a complete hospital contact history of somatic and psychiatric conditions and procedures. Data on all prescriptions filled at community pharmacies are available from the Danish National Prescription Registry. Health-care authorization status is obtained from the Danish Register of Healthcare Professionals. Finally, selected laboratory values are obtained from the Register of Laboratory Results for Research. The cohort is governed by a steering committee with representatives from the Danish Medicines Agency, Statens Serum Institut, the Danish Health Authority, the Danish Health Data Authority, Danish Patients, the Faculties of Health Sciences at the Danish universities, and Danish regions. The steering committee welcomes suggestions for research studies and collaborations. Research proposals will be prioritized based on timeliness and potential clinical and public health implications. All research protocols assessing specific hypotheses for medicines will be made publicly available using the European Union electronic Register of Post-Authorisation Studies. CONCLUSION: The Danish COVID-19 cohort includes all Danish residents with an RT-PCR test for ...
In: Pottegård , A , Kristensen , K B , Reilev , M , Lund , L C , Ernst , M T , Hallas , J , Thomsen , R W , Christiansen , C F , Sørensen , H T , Johansen , N B , Støvring , H , Christensen , S , Kragh Thomsen , M , Husby , A , Voldstedlund , M , Kjær , J & Brun , N C 2020 , ' Existing Data Sources in Clinical Epidemiology : The Danish COVID-19 Cohort ' , Clinical epidemiology , vol. 12 , no. 12 , pp. 875-881 . https://doi.org/10.2147/CLEP.S257519
Background: To facilitate research on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a prospective cohort of all Danish residents tested for SARS-CoV-2 in Denmark is established. Data Structure: All Danish residents tested by reverse transcriptase polymerase chain reactions (RT-PCR) for SARS-CoV-2 in Denmark are included. The cohort is identified using the Danish Microbiology Database. Individual-level record linkage between administrative and health-care registries is facilitated by the Danish Civil Registration System. Information on outcomes related to SARS-CoV-2 infection includes hospital admission, intensive care unit admission, mechanical ventilation, and death and is retrieved from the five administrative Danish regions, the Danish National Patient Registry, and the Danish Register of Causes of Death. The Patient Registry further provides a complete hospital contact history of somatic and psychiatric conditions and procedures. Data on all prescriptions filled at community pharmacies are available from the Danish National Prescription Registry. Health-care authorization status is obtained from the Danish Register of Healthcare Professionals. Finally, selected laboratory values are obtained from the Register of Laboratory Results for Research. The cohort is governed by a steering committee with representatives from the Danish Medicines Agency, Statens Serum Institut, the Danish Health Authority, the Danish Health Data Authority, Danish Patients, the Faculties of Health Sciences at the Danish universities, and Danish regions. The steering committee welcomes suggestions for research studies and collaborations. Research proposals will be prioritized based on timeliness and potential clinical and public health implications. All research protocols assessing specific hypotheses for medicines will be made publicly available using the European Union electronic Register of Post-Authorisation Studies. Conclusion: The Danish COVID-19 cohort includes all Danish residents with an RT-PCR test for SARS-CoV-2. Through individual-level linkage with existing Danish health and administrative registries, this is a valuable data source for epidemiological research on SARS-CoV-2.
Anton Pottegård,1 Kasper Bruun Kristensen,1 Mette Reilev,1 Lars Christian Lund,1 Martin Thomsen Ernst,1 Jesper Hallas,1,2 Reimar Wernich Thomsen,3 Christian Fynbo Christiansen,3 Henrik Toft Sørensen,3,4 Nanna Borup Johansen,5 Henrik Støvring,1,6 Steffen Christensen,7 Marianne Kragh Thomsen,8 Anders Husby,9 Marianne Voldstedlund,10 Jesper Kjær,11 Nikolai C Brun5 1Clinical Pharmacology and Pharmacy, Department of Public Health, University of Southern Denmark, Odense, Denmark; 2Department of Clinical Biochemistry and Clinical Pharmacology, Odense University Hospital, Odense, Denmark; 3Department of Clinical Epidemiology, Aarhus University Hospital, Aarhus, Denmark; 4Department of Epidemiology and Population Health, Stanford University, Stanford, CA, USA; 5Department of Medical Evaluation and Biostatistics, Danish Medicines Agency, Copenhagen, Denmark; 6Department of Public Health – Biostatistics, Aarhus University, Aarhus, Denmark; 7Department of Anesthesia and Intensive Care Medicine, Aarhus University Hospital, Aarhus, Denmark; 8Department of Clinical Microbiology, Aarhus University Hospital, Aarhus, Denmark; 9Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark; 10Infection Preparedness, Statens Serum Institut, Copenhagen, Denmark; 11Data Analytics Center, Danish Medicines Agency, Copenhagen, DenmarkCorrespondence: Anton PottegårdClinical Pharmacology and Pharmacy, Department of Public Health, University of Southern Denmark, JB Winsløws Vej 19, 2, Odense DK-5000, DenmarkTel +45 28913340Email apottegaard@health.sdu.dkBackground: To facilitate research on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a prospective cohort of all Danish residents tested for SARS-CoV-2 in Denmark is established.Data Structure: All Danish residents tested by reverse transcriptase polymerase chain reactions (RT-PCR) for SARS-CoV-2 in Denmark are included. The cohort is identified using the Danish Microbiology Database. Individual-level record linkage between administrative and health-care registries is facilitated by the Danish Civil Registration System. Information on outcomes related to SARS-CoV-2 infection includes hospital admission, intensive care unit admission, mechanical ventilation, and death and is retrieved from the five administrative Danish regions, the Danish National Patient Registry, and the Danish Register of Causes of Death. The Patient Registry further provides a complete hospital contact history of somatic and psychiatric conditions and procedures. Data on all prescriptions filled at community pharmacies are available from the Danish National Prescription Registry. Health-care authorization status is obtained from the Danish Register of Healthcare Professionals. Finally, selected laboratory values are obtained from the Register of Laboratory Results for Research. The cohort is governed by a steering committee with representatives from the Danish Medicines Agency, Statens Serum Institut, the Danish Health Authority, the Danish Health Data Authority, Danish Patients, the Faculties of Health Sciences at the Danish universities, and Danish regions. The steering committee welcomes suggestions for research studies and collaborations. Research proposals will be prioritized based on timeliness and potential clinical and public health implications. All research protocols assessing specific hypotheses for medicines will be made publicly available using the European Union electronic Register of Post-Authorisation Studies.Conclusion: The Danish COVID-19 cohort includes all Danish residents with an RT-PCR test for SARS-CoV-2. Through individual-level linkage with existing Danish health and administrative registries, this is a valuable data source for epidemiological research on SARS-CoV-2.Keywords: Covid-19, SARS-CoV-2, epidemiology, follow-up, database, prognosis, prospective cohort