International trends in clinical characteristics and oral anticoagulation treatment for patients with atrial fibrillation: Results from the GARFIELD-AF, ORBIT-AF I, and ORBIT-AF II registries.

Atrial fibrillation (AF) is the most common cardiac arrhythmia in the world. We aimed to provide comprehensive data on international patterns of AF stroke prevention treatment. METHODS: Demographics, comorbidities, and stroke risk of the patients in the GARFIELD-AF (n=51,270), ORBIT-AF I (n=10,132), and ORBIT-AF II (n=11,602) registries were compared (overall N=73,004 from 35 countries). Stroke prevention therapies were assessed among patients with new-onset AF (≤6 weeks). RESULTS: Patients from GARFIELD-AF were less likely to be white (63% vs 89% for ORBIT-AF I and 86% for ORBIT-AF II) or have coronary artery disease (19% vs 36% and 27%), but had similar stroke risk (85% CHA2DS2-VASc ≥2 vs 91% and 85%) and lower bleeding risk (11% with HAS-BLED ≥3 vs 24% and 15%). Oral anticoagulant use was 46% and 57% for patients with a CHA2DS2-VASc=0 and 69% and 87% for CHA2DS2-VASc ≥2 in GARFIELD-AF and ORBIT-AF II, respectively, but with substantial geographic heterogeneity in use of oral anticoagulant (range: 31%-93% [GARFIELD-AF] and 66%-100% [ORBIT-AF II]). Among patients with new-onset AF, non-vitamin K antagonist oral anticoagulant use increased over time to 43% in 2016 for GARFIELD-AF and 71% for ORBIT-AF II, whereas use of antiplatelet monotherapy decreased from 36% to 17% (GARFIELD-AF) and 18% to 8% (ORBIT-AF I and II). CONCLUSIONS: Among new-onset AF patients, non-vitamin K antagonist oral anticoagulant use has increased and antiplatelet monotherapy has decreased. However, anticoagulation is used frequently in low-risk patients and inconsistently in those at high risk of stroke. Significant geographic variability in anticoagulation persists and represents an opportunity for improvement

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Literaturzusammenstellung zum Entwerfen, Konstruieren und Bauen von Silos, 1978 Mit Ergaenzung von 1984

SIGLETIB: K bau 391 / AC 7752 / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekDEGerman

Messungen an einem Zementsilo in Laegerdorf Bericht ueber das Forschungsvorhaben

SIGLETIB: AC 7714 / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekDEGerman

Machine learning does not improve upon traditional regression in predicting outcomes in atrial fibrillation: an analysis of the ORBIT-AF and GARFIELD-AF registries.

AIMS: Prediction models for outcomes in atrial fibrillation (AF) are used to guide treatment. While regression models have been the analytic standard for prediction modelling, machine learning (ML) has been promoted as a potentially superior methodology. We compared the performance of ML and regression models in predicting outcomes in AF patients. METHODS AND RESULTS: The Outcomes Registry for Better Informed Treatment of Atrial Fibrillation (ORBIT-AF) and Global Anticoagulant Registry in the FIELD (GARFIELD-AF) are population-based registries that include 74 792 AF patients. Models were generated from potential predictors using stepwise logistic regression (STEP), random forests (RF), gradient boosting (GB), and two neural networks (NNs). Discriminatory power was highest for death [STEP area under the curve (AUC) = 0.80 in ORBIT-AF, 0.75 in GARFIELD-AF] and lowest for stroke in all models (STEP AUC = 0.67 in ORBIT-AF, 0.66 in GARFIELD-AF). The discriminatory power of the ML models was similar or lower than the STEP models for most outcomes. The GB model had a higher AUC than STEP for death in GARFIELD-AF (0.76 vs. 0.75), but only nominally, and both performed similarly in ORBIT-AF. The multilayer NN had the lowest discriminatory power for all outcomes. The calibration of the STEP modelswere more aligned with the observed events for all outcomes. In the cross-registry models, the discriminatory power of the ML models was similar or lower than the STEP for most cases. CONCLUSION: When developed from two large, community-based AF registries, ML techniques did not improve prediction modelling of death, major bleeding, or stroke

Dental caries experience in 12-year-old schoolchildren in southeastern Brazil

The aim of this study was to evaluate the prevalence of caries-free children using DMFT and significant caries (SiC) indexes in different caries prevalence groups in cities of the region of Campinas, São Paulo State, Brazil. The methodology proposed by the World Health Organization (1997) was used for caries diagnosis in 2,378 individuals. According to the DMFT index obtained in each evaluated city, 3 prevalence groups with representative samples were formed, being classified as low, moderate and high. SiC index was used to classify the one third of the population with the highest caries prevalence. In the low prevalence group, 32.4% of the children were caries free (DMFT=0), with mean DMFT of 2.29 and SiC index of 4.93. In the moderate prevalence group, 21.8% of the children were caries free, with mean DMFT of 3.36 and SiC of 6.74. Only 6.9% of the children in the high prevalence group were caries free and the mean DMFT was 5.54 (SiC=9.62). There was a great heterogeneity in dental caries distribution within the studied population, as well as a high caries prevalence considering the 3 classifications. Other indexes besides DMFT could be used to improve oral health assessment during establishment of the treatment plan and intervention