High throughput prediction of chylomicron triglycerides in human plasma by nuclear magnetic resonance and chemometrics

<p>Abstract</p> <p>Background</p> <p>The lipid content of the chylomicrons is a key biomarker and risk factor of cardiovascular diseases and for the understanding of obesity. A high throughput determination of chylomicrons in human blood plasma is outlined.</p> <p>Methods</p> <p>The new method, which uses a combination of Nuclear Magnetic Resonance (NMR) analysis and multivariate calibration analysis (chemometrics), is based on a correlation analysis towards the established standard method (ultracentrifugation and colorimetric test kit) and enables extraordinarily fast, inexpensive, and robust prediction of triglyceride (TG) content in chylomicrons. It is the position and shape of the complex lipid methylene resonance band that determines the chylomicron TG status and this information is extracted by the multivariate regression method.</p> <p>Results</p> <p>The resulting method is a relatively simple multivariate model that facilitates parsimonious and accurate prediction of chylomicron lipids from NMR spectra of blood. The chemometric model predicts the chylomicron TG content with a correlation coefficient (R) of 0.96 when plotted against density gradient ultracentrifugation data.</p> <p>Conclusions</p> <p>The new rapid method facilitates large scale clinical and nutritional trials with inclusion of diagnostics of chylomicron status and thus creates new opportunities for research in lifestyle diseases and obesity.</p

Temporal Trends in Incidence, Prevalence, and Mortality of Atrial Fibrillation in Primary Care

Background Incidence and prevalence of atrial fibrillation ( AF ) are expected to increase dramatically; however, we currently lack comprehensive data on temporal trends in unselected clinical populations. Methods and Results Analysis of the UK Clinical Practice Research Datalink ( CPRD ) from 1998 to 2010 of patients with incident AF , excluding major valvular disease, linked to hospital admission data and national statistics. Fifty‐seven thousand eight hundred eighteen adults were identified with mean age 74.2 ( SD , 11.7) years and 48.3% women. Overall age‐adjusted incidence of AF per 1000 person years was 1.11 (95% CI , 1.09–1.13) in 1998–2001, 1.33 (1.31–1.34) in 2002–2006, and 1.33 (1.31–1.35) in 2007–2010. Ongoing increases in incidence were noted for patients aged ≥75 years, with similar temporal patterns in women and men. Associated comorbidities varied over time, with a constant prevalence of previous stroke, increases in hypertension and diabetes mellitus, and decreases in ischemic heart disease. Among patients aged 55 to 74 years, there was a significant reduction in mortality over time ( P &lt;0.001), but mortality rates in patients aged ≥75 years remained static at 14% to 15% per year ( P =0.84). Projections of AF prevalence demonstrated a constant yearly rise, increasing from 700 000 patients in 2010 to between 1.3 and 1.8 million patients with AF in the United Kingdom by 2060. Conclusions In a large general practice population, incident AF increased and then plateaued overall, with a continued increase in patients aged ≥75 years. The large projected increase in AF prevalence associated with temporal changes in AF ‐related comorbidities suggests the need for comprehensive implementation of AF prevention and management strategies. </jats:sec

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

Noncatalytic Direct Liquefaction of Biorefinery Lignin by Ethanol

There is a growing interest in lignin valorization to biofuels and chemicals. Here, we propose a novel and simple noncatalytic process to directly liquefy lignin rich solid residual from second generation bioethanol production by solvolysis with ethanol. Through an extensive parameter study in batch autoclaves assessing the effects of varying reaction temperature, reaction time, and solvent:lignin ratio, it is shown that hydrothermally pretreated enzymatic hydrolysis lignin solvolysis in supercritical ethanol can produce a heptane soluble bio-oil without the need for exhaustive deoxygenation. The process does not require addition of catalyst or a reducing agent such as hydrogen. The process is advantageously carried out with a low reaction period (<1 h) and with a reduced amount of solvent to lignin feedstock (ethanol:lignin (w/w) ratio of 2:1) which is a previously unexplored domain for lignin solvolysis. The resulting bio-oil product is mainly a mixture of di- and monomeric lignin species where the original lignin unit linkages have been broken. The oxygen content is lowered to <10 wt % (corresponding to an HHV of 36 MJ/kg) and the bio-oil is stable and acid free (verified by NMR), and due to the use of sulfur free lignin rich residual as feedstock, the resulting oil product is equally sulfur free. The residual solid product (char) has a reduced oxygen content relative to the lignin feed and equally increased higher heating value, making it a candidate for use as a biochar

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