Comparative effectiveness and safety of non-vitamin K antagonist oral anticoagulants and warfarin in patients with atrial fibrillation:propensity weighted nationwide cohort study

Objective To study the effectiveness and safety of the non-vitamin K antagonist oral anticoagulants (novel oral anticoagulants, NOACs) dabigatran, rivaroxaban, and apixaban compared with warfarin in anticoagulant naïve patients with atrial fibrillation. Design Observational nationwide cohort study. Setting Three Danish nationwide databases, August 2011 to October 2015. Participants 61 678 patients with non-valvular atrial fibrillation who were naïve to oral anticoagulants and had no previous indication for valvular atrial fibrillation or venous thromboembolism. The study population was distributed according to treatment type: warfarin (n=35 436, 57%), dabigatran 150 mg (n=12 701, 21%), rivaroxaban 20 mg (n=7192, 12%), and apixaban 5 mg (n=6349, 10%). Main outcome measures Effectiveness outcomes defined a priori were ischaemic stroke; a composite of ischaemic stroke or systemic embolism; death; and a composite of ischaemic stroke, systemic embolism, or death. Safety outcomes were any bleeding, intracranial bleeding, and major bleeding. Results When the analysis was restricted to ischaemic stroke, NOACs were not significantly different from warfarin. During one year follow-up, rivaroxaban was associated with lower annual rates of ischaemic stroke or systemic embolism (3.0% v 3.3%, respectively) compared with warfarin: hazard ratio 0.83 (95% confidence interval 0.69 to 0.99). The hazard ratios for dabigatran and apixaban (2.8% and 4.9% annually, respectively) were non-significant compared with warfarin. The annual risk of death was significantly lower with apixaban (5.2%) and dabigatran (2.7%) (0.65, 0.56 to 0.75 and 0.63, 0.48 to 0.82, respectively) compared with warfarin (8.5%), but not with rivaroxaban (7.7%). For the combined endpoint of any bleeding, annual rates for apixaban (3.3%) and dabigatran (2.4%) were significantly lower than for warfarin (5.0%) (0.62, 0.51 to 0.74). Warfarin and rivaroxaban had comparable annual bleeding rates (5.3%). Conclusion All NOACs seem to be safe and effective alternatives to warfarin in a routine care setting. No significant difference was found between NOACs and warfarin for ischaemic stroke. The risks of death, any bleeding, or major bleeding were significantly lower for apixaban and dabigatran compared with warfarin

Similarities and differences in systemic risk factors for retinal artery occlusion and stroke:A nationwide case-control study

BackgroundRetinal artery occlusion (RAO) has been considered a stroke equivalent. This study compares risk factor profiles for thromboembolism among patients with RAO and stroke, respectively.MethodsThis case-control study is based on 5683 RAO patients entered in the Danish National Patient Register between 1st of January 2000 and 31st of December 2018. Cases were matched on sex, year of birth, and age at event with 28,415 stroke patients. The Danish nationwide registries were used to collect information about age, sex, previous diagnoses, and drug prescriptions. Adjusted conditional logistic regression models were used to investigate the association between hypothesised risk factors and the patient outcome.ResultsFor atrial fibrillation, a substantially stronger association to stroke was found, with an odds ratio (OR) of 0.52 (95% CI: 0.47-0.58) when comparing RAO patients with stroke patients. RAO was stronger associated with arterial hypertension, peripheral artery disease, retinal vein occlusion, cataract, and glaucoma with OR's ranging from 1.21-11.70. The identified effect measures reached equivalence or was close to equivalence for diabetes, heart failure, ischemic heart disease, and renal disease.ConclusionThe differences in risk factor profiles between RAO and stroke suggests differences in the pathophysiology of the two diseases. These variations in pathophysiologies between the two diseases may indicate that different interventions are needed to ensure the optimal long-term prognosis for the patients

Assigning Diagnosis Codes Using Medication History

Diagnosis assignment is the process of assigning disease codes to patients. Automatic diagnosis assignment has the potential to validate code assignments, correct erroneous codes, and register completion. Previous methods build on text-based techniques utilizing medical notes but are inapplicable in the absence of these notes. We propose using patients' medication data to assign diagnosis codes. We present a proof-of-concept study using medical data from an American dataset (MIMIC-III) and Danish nationwide registers to train a machine-learning-based model that predicts an extensive collection of diagnosis codes for multiple levels of aggregation over a disease hierarchy. We further suggest a specialized loss function designed to utilize the innate hierarchical nature of the disease hierarchy. We evaluate the proposed method on a subset of 567 disease codes. Moreover, we investigate the technique's generalizability and transferability by (1) training and testing models on the same subsets of disease codes over the two medical datasets and (2) training models on the American dataset while evaluating them on the Danish dataset, respectively. Results demonstrate the proposed method can correctly assign diagnosis codes on multiple levels of aggregation from the disease hierarchy over the American dataset with recall 70.0% and precision 69.48% for top-10 assigned codes; thereby being comparable to text-based techniques. Furthermore, the specialized loss function performs consistently better than the non-hierarchical state-of-the-art version. Moreover, results suggest the proposed method is language and dataset-agnostic, with initial indications of transferability over subsets of disease codes

Sum rules for isospin centroids in pick-up reactions on general multishell target states

Sum Rules equations for pick-up reactions are presented for the first time for the energy centroids of states both for the isospin T_< (\equiv T_0 - 1 \over 2) and T_> (\equiv T_0 + {1 \over 2}) of the final nucleus when a nucleon is picked up from a general multishell target state with isospin T_0. These equations contain two-body correlation terms, , which, at the present moment, are difficult to handle analytically. These terms are managed by combining these equations with the known stripping reactions equations. Sample applications of these equations to experimental data are presented.Comment: 11 pages, LaTe