12 research outputs found

    Risk profiles and one-year outcomes of patients with newly diagnosed atrial fibrillation in India: Insights from the GARFIELD-AF Registry.

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    BACKGROUND: The Global Anticoagulant Registry in the FIELD-Atrial Fibrillation (GARFIELD-AF) is an ongoing prospective noninterventional registry, which is providing important information on the baseline characteristics, treatment patterns, and 1-year outcomes in patients with newly diagnosed non-valvular atrial fibrillation (NVAF). This report describes data from Indian patients recruited in this registry. METHODS AND RESULTS: A total of 52,014 patients with newly diagnosed AF were enrolled globally; of these, 1388 patients were recruited from 26 sites within India (2012-2016). In India, the mean age was 65.8 years at diagnosis of NVAF. Hypertension was the most prevalent risk factor for AF, present in 68.5% of patients from India and in 76.3% of patients globally (P < 0.001). Diabetes and coronary artery disease (CAD) were prevalent in 36.2% and 28.1% of patients as compared with global prevalence of 22.2% and 21.6%, respectively (P < 0.001 for both). Antiplatelet therapy was the most common antithrombotic treatment in India. With increasing stroke risk, however, patients were more likely to receive oral anticoagulant therapy [mainly vitamin K antagonist (VKA)], but average international normalized ratio (INR) was lower among Indian patients [median INR value 1.6 (interquartile range {IQR}: 1.3-2.3) versus 2.3 (IQR 1.8-2.8) (P < 0.001)]. Compared with other countries, patients from India had markedly higher rates of all-cause mortality [7.68 per 100 person-years (95% confidence interval 6.32-9.35) vs 4.34 (4.16-4.53), P < 0.0001], while rates of stroke/systemic embolism and major bleeding were lower after 1 year of follow-up. CONCLUSION: Compared to previously published registries from India, the GARFIELD-AF registry describes clinical profiles and outcomes in Indian patients with AF of a different etiology. The registry data show that compared to the rest of the world, Indian AF patients are younger in age and have more diabetes and CAD. Patients with a higher stroke risk are more likely to receive anticoagulation therapy with VKA but are underdosed compared with the global average in the GARFIELD-AF. CLINICAL TRIAL REGISTRATION-URL: http://www.clinicaltrials.gov. Unique identifier: NCT01090362

    Adaptive cluster sampling for forest inventories

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    Approximation of the breast height diameter distribution of two-cohort stands by mixture models. III. Kernel density estimators vs mixture models

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    Two−component mixtures of either the Weibull distribution or the gamma distribution and the kernel density estimator were used for describing the diameter at breast height (dbh) empirical distributions of two−cohort stands. The data consisted of study plots from the Świętokrzyski National Park (central Poland) and areas close to and including the North Carolina section of the Great Smoky Mountains National Park (USA; southern Appalachians). Kernel density estimators belong to a class of nonparametric density estimators. Nonparametric estimators have no fixed structure and depend upon all the data points to reach an estimate. In this study the Weibull and the gamma mixture distributions were the most versatile models. The results also support the conclusion that there are only minor differences between the parametric models and the kernel density estimates

    Approximation of the breast height diameter distribution of two-cohort stands by mixture models. II. Goodness-of-fit tests

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    The goals of this study are (1) to analyse the accuracy of the approximation of empirical distributions of diameter at breast height (dbh) using two−component mixtures of either the Weibull distribution or the gamma distribution in two−cohort stands, and (2) to discuss the procedure of choosing goodness−of−fit tests. The study plots were located in the Świętokrzyski National Park (central Poland) and in the Southern Appalachian Mountains (eastern USA). The results of the goodness−of−fit tests (chi−squared, Kolmogorov−Smirnov, Cramér−von Mises, and Anderson−Darling), normalised bias and normalised root mean square error, indicate that dbh empirical distributions of two−cohort stands are compatible with the mixture models investigated. The chi−squared test and the generalization of the Anderson−Darling test to discrete distributions should be used to assess whether empirical dbh data are consistent with a hypothesized null distribution

    Approximation of the breast height diameter distribution of two-cohort stands by mixture models. I. Parameter estimation

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    Study assessed the usefulness of various methods for choosing the initial values for the numerical procedures for estimating the parameters of mixture distributions and analysed variety of mixture models to approximate empirical diameter at breast height (dbh) distributions. Two−component mixtures of either the Weibull distribution or the gamma distribution were employed. The study plots, representing two−cohort stands, were located in the Świętokrzyski National Park (central Poland) and in the Southern Appalachian Mountains (eastern USA). A new strategy using three methods for choosing initial values (min.k/max.k for k=1, 5, 10; 0,5/1,5/mean; wp) for maximizing the likelihood during parameter estimation for mixture models for small and large plots is proposed
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