| 1. |
|
|
| 2. |
|
|
| 3. |
- Batra, Gorav, et al.
(författare)
-
Antithrombotic therapy after myocardial infarction in patients with atrial fibrillation undergoing percutaneous coronary intervention
- 2018
-
Ingår i: European Heart Journal - Cardiovascular Pharmacotherapy. - : Oxford University Press (OUP). - 2055-6837 .- 2055-6845. ; 4:1, s. 36-45
-
Tidskriftsartikel (refereegranskat)abstract
- Aims Optimal antithrombotic therapy after percutaneous coronary intervention (PCI) in patients with myocardial infarction (MI) and atrial fibrillation is uncertain. In this study, we compared antithrombotic regimes with regard to a composite cardiovascular outcome of all-cause mortality, MI or ischaemic stroke, and major bleeds. Methods and results Patients between October 2005 and December 2012 were identified in Swedish registries, n = 7116. Landmark 0-90 and 91-365 days of outcome were evaluated with Cox-regressions, with dual antiplatelet therapy as reference. At discharge, 16.2% received triple therapy (aspirin, clopidogrel, and warfarin), 1.9% aspirin plus warfarin, 7.3% clopidogrel plus warfarin, and 60.8% dual antiplatelets. For cardiovascular outcome, adjusted hazard ratio with 95% confidence interval (HR) for triple therapy was 0.86 (0.70-1.07) for 0-90 days and 0.78 (0.58-1.05) for 91-365 days. A HR of 2.16 (1.48-3.13) and 1.61 (0.98-2.66) during 0-90 and 91-365 days, respectively, was observed for major bleeds. For aspirin plus warfarin, HR 0.82 (0.54-1.26) and 0.62 (0.48-0.79) was observed for cardiovascular outcome and 1.30 (0.60-2.85) and 1.01 (0.63-1.62) for major bleeds during 0-90 and 91-365 days, respectively. For clopidogrel plus warfarin, HR of 0.90 (0.68-1.19) and 0.68 (0.49-0.95) was observed for cardiovascular outcome and 1.28 (0.71-2.32) and 1.08 (0.57-2.04) for major bleeds during 0-90 and 91-365 days, respectively. Conclusion Compared to dual antiplatelets, aspirin or clopidogrel plus warfarin therapy was associated with similar 0-90 days and lower 91-365 days of risk of the cardiovascular outcome, without higher risk of major bleeds. Triple therapy was associated with non-significant lower risk of cardiovascular outcome and higher risk of major bleeds.
|
|
| 4. |
|
|
| 5. |
- Gedeborg, Rolf, et al.
(författare)
-
Increased availability of paracetamol in Sweden and incidence of paracetamol poisoning : using laboratory data to increase validity of a population-based registry study
- 2017
-
Ingår i: Pharmacoepidemiology and Drug Safety. - : WILEY. - 1053-8569 .- 1099-1557. ; 26:5, s. 518-527
-
Tidskriftsartikel (refereegranskat)abstract
- Purpose: To estimate the incidence trend and outcome of paracetamol poisoning, in relation to increased availability of paracetamol from non-pharmacy outlets in 2009.Method: Patients' serum paracetamol results over 14years (2000-2013) from 20 (out of 21) regions in Sweden were linked to national registers of hospital care, cause of death, and prescriptions. Paracetamol poisonings were defined by serum paracetamol levels, hospital diagnoses, or cause of death. The change in incidence of poisonings following increased availability of paracetamol was analysed by using segmental regression of time series.Results: Of the 12068 paracetamol poisonings, 85% were classified as intentional self-harm. Following increased availability from non-pharmacy outlets, there was a 40.5% increase in the incidence of paracetamol poisoning, from 11.5/100000 in 2009 to 16.2/100000 in 2013. Regression analyses indicated a change in the trend (p<0.0001) but not an immediate jump in the incidence (p=0.5991) following the increased availability. Adjusting for trends in hospital episodes for self-harm, suicides, and the sales volume of paracetamol did not influence the result. All-cause mortality at 30days (3.2%) did not change over time.Conclusions: The incidence of paracetamol poisoning in Sweden has increased since 2009, contrasting the decreased incidence in the period of 2007-2009. The change in trend was temporally associated with the introduction of availability of paracetamol from non-pharmacy outlets but did not appear to be related to sales volume of paracetamol or general trends in self-harm or suicides.
|
|
| 6. |
- Gedeborg, Rolf, et al.
(författare)
-
Prediction of mortality risk in victims of violent crimes
- 2017
-
Ingår i: Forensic Science International. - : Elsevier BV. - 0379-0738 .- 1872-6283. ; 281, s. 92-97
-
Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: To predict mortality risk in victims of violent crimes based on individual injury diagnoses and other information available in health care registries.METHODS: Data from the Swedish hospital discharge registry and the cause of death registry were combined to identify 15,000 hospitalisations or prehospital deaths related to violent crimes. The ability of patient characteristics, injury type and severity, and cause of injury to predict death was modelled using conventional, Lasso, or Bayesian logistic regression in a development dataset and evaluated in a validation dataset.RESULTS: Of 14,470 injury events severe enough to cause death or hospitalization 3.7% (556) died before hospital admission and 0.5% (71) during the hospital stay. The majority (76%) of hospital survivors had minor injury severity and most (67%) were discharged from hospital within 1day. A multivariable model with age, sex, the ICD-10 based injury severity score (ICISS), cause of injury, and major injury region provided predictions with very good discrimination (C-index=0.99) and calibration. Adding information on major injury interactions further improved model performance. Modeling individual injury diagnoses did not improve predictions over the combined ICISS score.CONCLUSIONS: Mortality risk after violent crimes can be accurately estimated using administrative data. The use of Bayesian regression models provides meaningful risk assessment with more straightforward interpretation of uncertainty of the prediction, potentially also on the individual level. This can aid estimation of incidence trends over time and comparisons of outcome of violent crimes for injury surveillance and in forensic medicine.
|
|
| 7. |
- Grimfjärd, Per, et al.
(författare)
-
Low real-world early stent thrombosis rates in ST-elevation myocardial infarction patients and the use of bivalirudin, heparin alone or glycoprotein IIb/IIIa inhibitor treatment : A nationwide Swedish registry report
- 2016
-
Ingår i: American Heart Journal. - : Elsevier BV. - 0002-8703 .- 1097-6744. ; 176, s. 78-82
-
Tidskriftsartikel (refereegranskat)abstract
- Background In recent studies of primary percutaneous coronary intervention (PCI), bivalirudin compared with heparin has been associated with increased risk of stent thrombosis (ST). Our aim was to describe incidence and outcome of definite, early ST in a large contemporary primary PCI population divided in antithrombotic therapy subgroups. Methods and Results A prospective, observational cohort study of all 31,258 ST-elevation myocardial infarction patients who received a stent in Sweden from January 2007 to July 2014 in the SWEDEHEART registry was conducted. Patients were divided into 3 groups: bivalirudin, heparin alone, or glycoprotein IIb/IIIa inhibitor treated. Primary outcome measure was incidence of definite early ST (within 30 days of PCI). Secondary outcomes included all-cause mortality. Incidence of early ST was low, regardless of bivalirudin, heparin alone, or glycoprotein IIb/IIIa inhibitor treatment (0.84%, 0.94%, and 0.83%, respectively). All-cause mortality at 1 year was 20.7% for all ST patients (n = 265), compared with 9.1% in those without ST (n = 31,286; P < .001). Patients with ST days 2-30 had numerically higher all-cause mortality at 1 year compared with patients with ST days 0-1 (23% vs 16%, P =.20). Conclusion In this real-world observational study of 31,258 ST-elevation myocardial infarction patients, the incidence of early ST was low, regardless of antithrombotic treatment strategy. Early ST was associated with increased mortality. Numerically higher all-cause mortality at 1 year was noted with ST days 2-30 compared with ST days 0-1 post-PCI.
|
|
| 8. |
- Grimfjärd, Per, et al.
(författare)
-
Unfractionated heparin versus bivalirudin in patients undergoing primary percutaneous coronary intervention : a SWEDEHEART study
- 2017
-
Ingår i: EuroIntervention. - 1774-024X .- 1969-6213. ; 12:16, s. 2009-2017
-
Tidskriftsartikel (refereegranskat)abstract
- Aims: The aim of the stud was to compare outcomes in unfractionated heparin (UM) and bivalirudintreated patients undergoing primary percutaneous coronary intervention (PPCI). Methods and results: This observational study contained 20,612 PPCT patients treated with either GM monotherapv or bivalirudin with or without concomitant UFE. Patients with oral anticoagulant or glycoprotein IIb/IIIa inhibitor (GPI) treatment were excluded. The primary outcome measure was definite early stent thrombosis (Si) that occurred at low and similar rates in UNA only and bivalirudin-treated patients: 0.9% vs. 0.8% (adjusted hazard ratio [HR] 1.08, 95% confidence interval [CI]: 0.7-1.65). All-cause death at 30 days occurred in 6.9% vs. 5.4% of patients (adjusted HR 1.23, 95% Cl: 1.05-1.44) and within 365 days in 12.1% vs. 8.9% (adjusted HR 1.34, 95% CI: 1.19-1.52) in the two groups, respectively. The incidence of major bleeding within 30 days was 0.8% vs. 0.6% (adjusted HR 1.54, 95% CI: 0.97-2.45). The incidence of reinfarction within 365 days and stroke within 30 days was similar between groups. Conclusions: In this large, nationwide observational study we found low and similar rates of early ST in UFH only and bivalirudin-treated patients undergoing primary PCI. Mortality was higher in IJFH compared with bivalirudin-treated patients.
|
|
| 9. |
- Grundvold, Irene, et al.
(författare)
-
Body weight and risk of atrial fibrillation in 7,169 patients with newly diagnosed type 2 diabetes; an observational study
- 2015
-
Ingår i: Cardiovascular Diabetology. - : Springer Science and Business Media LLC. - 1475-2840. ; 14
-
Tidskriftsartikel (refereegranskat)abstract
- Background: Obesity, type 2 diabetes and atrial fibrillation (AF) are closely associated, but the underlying mechanisms are not fully understood. We aimed to explore associations between body mass index (BMI) or weight change with risk of AF in patients with type 2 diabetes. Methods: A total of 7,169 participations with newly diagnosed type 2 diabetes were stratified according to baseline BMI, and after a second BMI measurement within 18 months, further grouped according to relative weight change as "weight gain" (> 1 BMI unit), " stable weight" (+/- 1 BMI unit) and " weight loss" (< 1 BMI unit). The mean follow-up period was 4.6 years, and the risk of AF was estimated using adjusted Cox regression models. Results: Average age at diabetes diagnosis was 60 years and the patients were slightly obese (mean BMI 30.2 kg/m(2)). During follow-up, 287 patients developed incident AF, and those with overweight or obesity at baseline had 1.9 fold and 2.9-fold higher risk of AF, respectively, than those with normal BMI. The 14% of the patients with subsequent weight gain had 1.5-fold risk of AF compared with those with stable weight or weight loss. Conclusions: In patients with newly diagnosed type 2 diabetes, baseline overweight and obesity, as well as modest weight increase during the first 18 months after diagnosis, were associated with a substantially increased risk of incident AF. Patients with type 2 diabetes may benefit from efforts to prevent weight gain in order to reduce the risk of incident AF.
|
|
| 10. |
- Hemingway, Harry, et al.
(författare)
-
Big data from electronic health records for early and late translational cardiovascular research : challenges and potential
- 2018
-
Ingår i: European Heart Journal. - : Oxford University Press (OUP). - 0195-668X .- 1522-9645. ; 39:16, s. 1481-1495
-
Tidskriftsartikel (refereegranskat)abstract
- Aims: Cohorts of millions of people's health records, whole genome sequencing, imaging, sensor, societal and publicly available data present a rapidly expanding digital trace of health. We aimed to critically review, for the first time, the challenges and potential of big data across early and late stages of translational cardiovascular disease research.Methods and results: We sought exemplars based on literature reviews and expertise across the BigData@Heart Consortium. We identified formidable challenges including: data quality, knowing what data exist, the legal and ethical framework for their use, data sharing, building and maintaining public trust, developing standards for defining disease, developing tools for scalable, replicable science and equipping the clinical and scientific work force with new inter-disciplinary skills. Opportunities claimed for big health record data include: richer profiles of health and disease from birth to death and from the molecular to the societal scale; accelerated understanding of disease causation and progression, discovery of new mechanisms and treatment-relevant disease sub-phenotypes, understanding health and diseases in whole populations and whole health systems and returning actionable feedback loops to improve (and potentially disrupt) existing models of research and care, with greater efficiency. In early translational research we identified exemplars including: discovery of fundamental biological processes e.g. linking exome sequences to lifelong electronic health records (EHR) (e.g. human knockout experiments); drug development: genomic approaches to drug target validation; precision medicine: e.g. DNA integrated into hospital EHR for pre-emptive pharmacogenomics. In late translational research we identified exemplars including: learning health systems with outcome trials integrated into clinical care; citizen driven health with 24/7 multi-parameter patient monitoring to improve outcomes and population-based linkages of multiple EHR sources for higher resolution clinical epidemiology and public health.Conclusion: High volumes of inherently diverse ('big') EHR data are beginning to disrupt the nature of cardiovascular research and care. Such big data have the potential to improve our understanding of disease causation and classification relevant for early translation and to contribute actionable analytics to improve health and healthcare.
|
|
