Development and Validation of 3-Year Atrial Fibrillation Prediction Models Using Electronic Health Record With or Without Standardized Electrocardiogram Diagnosis and a Performance Comparison Among Models.

Background Improved prediction of atrial fibrillation (AF) may allow for earlier interventions for stroke prevention, as well as mortality and morbidity from other AF-related complications. We developed a clinically feasible and accurate AF prediction model using electronic health records and computerized ECG interpretation. Methods and Results A total of 671 318 patients were screened from 3 tertiary hospitals. After careful exclusion of cases with missing values and a prior AF diagnosis, AF prediction models were developed from the derivation cohort of 25 584 patients without AF at baseline. In the internal/external validation cohort of 117 523 patients, the model using 6 clinical features and 5 ECG diagnoses showed the highest performance for 3-year new-onset AF prediction (C-statistic, 0.796 [95% CI, 0.785-0.806]). A more simplified model using age, sex, and 5 ECG diagnoses (atrioventricular block, fusion beats, marked sinus arrhythmia, supraventricular premature complex, and wide QRS complex) had comparable predictive power (C-statistic, 0.777 [95% CI, 0.766-0.788]). The simplified model showed a similar or better predictive performance than the previous models. In the subgroup analysis, the models performed relatively better in patients without risk factors. Specifically, the predictive power was lower in patients with heart failure or decreased renal function. Conclusions Although the 3-year AF prediction model using both clinical and ECG variables showed the highest performance, the simplified model using age, sex, and 5 ECG diagnoses also had a comparable prediction power with broad applicability for incident AF

Galactic and Extragalactic Samples of Supernova Remnants: How They Are Identified and What They Tell Us

Supernova remnants (SNRs) arise from the interaction between the ejecta of a supernova (SN) explosion and the surrounding circumstellar and interstellar medium. Some SNRs, mostly nearby SNRs, can be studied in great detail. However, to understand SNRs as a whole, large samples of SNRs must be assembled and studied. Here, we describe the radio, optical, and X-ray techniques which have been used to identify and characterize almost 300 Galactic SNRs and more than 1200 extragalactic SNRs. We then discuss which types of SNRs are being found and which are not. We examine the degree to which the luminosity functions, surface-brightness distributions and multi-wavelength comparisons of the samples can be interpreted to determine the class properties of SNRs and describe efforts to establish the type of SN explosion associated with a SNR. We conclude that in order to better understand the class properties of SNRs, it is more important to study (and obtain additional data on) the SNRs in galaxies with extant samples at multiple wavelength bands than it is to obtain samples of SNRs in other galaxiesComment: Final 2016 draft of a chapter in "Handbook of Supernovae" edited by Athem W. Alsabti and Paul Murdin. Final version available at https://doi.org/10.1007/978-3-319-20794-0_90-

Socioeconomic disparities in behavioral risk factors and health outcomes by gender in the Republic of Korea

<p>Abstract</p> <p>Background</p> <p>Few studies have examined socioeconomic disparities in health and behavioral risk factors by gender in Asian countries and in South Korea, specifically. We investigated the relationship between socioeconomic position (education, income, and occupation) and subjective and acute and chronic health outcomes and behavioral risk factors by gender, and compared results from 1998 and 2005, in the Republic of Korea.</p> <p>Methods</p> <p>We examined data from a nationally representative stratified random sample of 4213 men and 4618 women from the 1998 Korea National Health and Nutrition Examination Survey, and 8289 men and 8827 women from the 2005 Korea National Health and Nutrition Examination Survey using General Linear Modeling and multiple logistic regression methods.</p> <p>Results</p> <p>Controlling for behavioral risk factors (smoking, drinking, obesity, exercise, and sleep), those in lower socioeconomic positions had poorer health outcomes in both self-reported acute and chronic disease and subjective measures; differences were especially pronounced among women. A socioeconomic gradient for education and income was found for both men and women for morbidity and self-reported health status, but the gradient was more pronounced in women. In 1998, the odds ratios (ORs) of higher morbidity for illiterate vs. college educated females was 5.4:1 and 1.9:1 for females in the lowest income quintile vs. the highest. The OR for education decreased in 2005 to 2.9:1 and that for income quintiles remained the same at 1.9:1. The OR of lower self-reported health status for illiterate vs. college educated females was 2.9:1 and 1.6:1 for females in the lowest income quintile vs. the highest in 1998, and 3.3:1 and 2.3:1 in 2005.</p> <p>Conclusions</p> <p>Among Korean adults, men and women in lower socioeconomic position, as denoted by education, income, and somewhat less by occupation, experience significantly higher levels of morbidity and lower self-reported health status, even after controlling for standard behavioral risk factors. Disparities were more pronounced for women than for men. Efforts to reduce health disparities in South Korea require attention to the root causes of socioeconomic inequality and gender differences in the impact of socioeconomic position on health.</p

Difference-based clustering of short time-course microarray data with replicates

<p>Abstract</p> <p>Background</p> <p>There are some limitations associated with conventional clustering methods for short time-course gene expression data. The current algorithms require prior domain knowledge and do not incorporate information from replicates. Moreover, the results are not always easy to interpret biologically.</p> <p>Results</p> <p>We propose a novel algorithm for identifying a subset of genes sharing a significant temporal expression pattern when replicates are used. Our algorithm requires no prior knowledge, instead relying on an observed statistic which is based on the first and second order differences between adjacent time-points. Here, a pattern is predefined as the sequence of symbols indicating direction and the rate of change between time-points, and each gene is assigned to a cluster whose members share a similar pattern. We evaluated the performance of our algorithm to those of K-means, Self-Organizing Map and the Short Time-series Expression Miner methods.</p> <p>Conclusions</p> <p>Assessments using simulated and real data show that our method outperformed aforementioned algorithms. Our approach is an appropriate solution for clustering short time-course microarray data with replicates.</p

Global, regional, and national trends in opioid analgesic consumption from 2015 to 2019: a longitudinal study.

BACKGROUND: Previous studies have reported an extremely unbalanced global access to opioid analgesics. We aimed to determine contemporary trends and patterns of opioid analgesic consumption at the global, regional, and national levels. METHODS: We analysed the global pharmaceutical sales data of 66 countries or regions from the IQVIA-Multinational Integrated Data Analysis System database on opioid analgesics between 2015 and 2019. Opioid analgesic consumption was measured in milligram morphine equivalent per 1000 inhabitants per day (MME per 1000/day). The global, regional, and national trend changes were estimated using linear regressions. Factors associated with consumption patterns and trend changes were explored in multivariable linear regression analyses. FINDINGS: Overall opioid analgesic sales in the 66 countries or regions increased from 27·52 MME per 1000/day (16·63-45·54) in 2015 to 29·51 MME per 1000/day (17·85-48·79) in 2019 (difference per year 3·96%, 95% CI 0·26 to 7·80). Sales reduced yearly in North America (-12·84%; 95% CI -15·34 to -10·27) and Oceania (-2·96%; -4·20 to -1·70); increased in South America (28·69%; 7·18 to 54·53), eastern Europe (7·68%; 3·99 to 11·49), Asia (5·74%; 0·61 to 11·14), and western and central Europe (1·64%; 0·52 to 2·78); and did not differ in Africa or central America and the Caribbean. The global opioid consumption patterns were associated with country-level Human Development Index (p=0·040), cancer death rate excluding leukaemia (p=0·0072), and geographical location (p<0·0001). In 2019, opioid analgesic consumption ranged from 0·01 MME per 1000/day to 5·40 MME per 1000/day in the 17 countries and regions in the lowest consumption quartile, despite high income levels and cancer death rates in some of them. INTERPRETATION: Global opioid analgesic consumption increased from 2015 to 2019. The trend changes were distinctive across regions, which could reflect the different actions in response to known issues of opioid use and misuse. Disparities in opioid analgesic consumption remained, indicating potential inadequate access to essential pain relief in countries with low consumption. FUNDING: None

Sox7 promotes high-grade glioma by increasing VEGFR2-mediated vascular abnormality

High-grade glioma (HGG) is highly angiogenic, but antiangiogenic therapy has transient clinical benefit in only a fraction of patients. Vascular regulators of these heterogeneous responses remain undetermined. We found up-regulation of Sox7 and down-regulation of Sox17 in tumor endothelial cells (tECs) in mouse HGG.Sox7deletion suppressed VEGFR2 expression, vascular abnormality, hypoxia-driven invasion, regulatory T cell infiltration, and tumor growth. Conversely,Sox17deletion exacerbated these phenotypes by up-regulating Sox7 in tECs. Anti-VEGFR2 antibody treatment delayed tumor growth by normalizingSox17-deficient abnormal vessels with high Sox7 levels but promoted it by regressingSox7-deficient vessels, recapitulating variable therapeutic responses to antiangiogenic therapy in HGG patients. Our findings establish that Sox7 promotes tumor growth via vessel abnormalization, and its level determines the therapeutic outcome of VEGFR2 inhibition in HGG. In 189 HGG patients, Sox7 expression was heterogeneous in tumor vessels, and high Sox7 levels correlated with poor survival, early recurrence, and impaired vascular function, emphasizing the clinical relevance of Sox7 in HGG

Functional Promoter -31G>C Variant in Survivin Gene Is Associated with Risk and Progression of Renal Cell Cancer in a Chinese Population

BACKGROUND: Survivin is an inhibitor of apoptosis protein and is involved in the occurrence and progression of human malignancies. Recently, a functional polymorphism (-31G>C, rs9904341) in the promoter of survivin has been shown to influence its expression and confer susceptibility to different types of cancer. The present study was aimed to investigate whether the polymorphism also influences susceptibility and progression of renal cell cancer (RCC) in a Chinese population. METHODS: We genotyped this polymorphism using the TaqMan assay in a case-control study comprised of 710 RCC patients and 760 controls. The logistic regression was used to assess the genetic association with occurrence and progression of RCC. RESULTS: Compared with the genotypes containing G allele (GG and GC), we found a statistically significant increased occurrence of RCC associated with the CC genotype [P = 0.006, adjusted odds ratio (OR) = 1.38, 95% confidence interval (CI) = 1.08-1.76]. The polymorphism was associated with risk of developing advanced stage (OR = 2.02, 95%CI = 1.34-3.07) and moderately differentiated (OR = 1.75; 95%CI = 1.20-2.54) RCC. Furthermore, the patients carrying the CC genotype had a significantly greater prevalence of high clinical stage disease (P(trend) = 0.003). Similar results were also observed when we restricted the analysis to clear cell RCC, a major histological type of RCC. CONCLUSIONS: Our results suggest that the functional -31G>C polymorphism in the promoter of survivin may influence the susceptibility and progression of RCC in the Chinese population. Large population-based prospective studies are required to validate our findings

Surveillance of Airborne Adenovirus and Mycoplasma pneumoniae in a Hospital Pediatric Department

This investigation evaluated the distributions of airborne adenovirus and Mycoplasma pneumoniae in public areas in the pediatric department of Children's Hospital in northern Taiwan. The airborne viral and bacterial concentrations were evaluated twice a week for a year using filter sampling with an airflow rate of 12 liters per minute for eight hours in the pediatric outpatient department and 24 hours in the pediatric emergency room. Real-time polymerase chain reaction assays were conducted for analysis. Approximately 18% of the air samples from the pediatric emergency room were found to contain adenovirus. Approximately forty-six percent of the air samples from the pediatric outpatient department contained Mycoplasma pneumoniae DNA products. High detection rates of airborne adenovirus DNA were obtained in July and August in the pediatric public areas. Airborne Mycoplasma pneumoniae was detected only in July in the pediatric emergency room and the peak levels were found from August to January in the pediatric outpatient department. Airborne particles that contained adenovirus and Mycoplasma pneumoniae were the most prevalent in the pediatric public areas. The potential relationship between these airborne viral/bacterial particles and human infection should be examined further