Past alcohol consumption and incident atrial fibrillation: The Atherosclerosis Risk in Communities (ARIC) Study.

BackgroundAlthough current alcohol consumption is a risk factor for incident atrial fibrillation (AF), the more clinically relevant question may be whether alcohol cessation is associated with a reduced risk.Methods and resultsWe studied participants enrolled in the Atherosclerosis Risk in Communities Study (ARIC) between 1987 and 1989 without prevalent AF. Past and current alcohol consumption were ascertained at baseline and at 3 subsequent visits. Incident AF was ascertained via study ECGs, hospital discharge ICD-9 codes, and death certificates. Of 15,222 participants, 2,886 (19.0%) were former drinkers. During a median follow-up of 19.7 years, there were 1,631 cases of incident AF, 370 occurring in former consumers. Former drinkers had a higher rate of AF compared to lifetime abstainers and current drinkers. After adjustment for potential confounders, every decade abstinent from alcohol was associated with an approximate 20% (95% CI 11-28%) lower rate of incident AF; every additional decade of past alcohol consumption was associated with a 13% (95% CI 3-25%) higher rate of AF; and every additional drink per day during former drinking was associated with a 4% (95% CI 0-8%) higher rate of AF.ConclusionsAmong former drinkers, the number of years of drinking and the amount of alcohol consumed may each confer an increased risk of AF. Given that a longer duration of abstinence was associated with a decreased risk of AF, earlier modification of alcohol use may have a greater influence on AF prevention

Assisting Forensic Identification through Unsupervised Information Extraction of Free Text Autopsy Reports: The Disappearances Cases during the Brazilian Military Dictatorship

Anthropological, archaeological, and forensic studies situate enforced disappearance as a strategy associated with the Brazilian military dictatorship (1964–1985), leaving hundreds of persons without identity or cause of death identified. Their forensic reports are the only existing clue for people identification and detection of possible crimes associated with them. The exchange of information among institutions about the identities of disappeared people was not a common practice. Thus, their analysis requires unsupervised techniques, mainly due to the fact that their contextual annotation is extremely time-consuming, difficult to obtain, and with high dependence on the annotator. The use of these techniques allows researchers to assist in the identification and analysis in four areas: Common causes of death, relevant body locations, personal belongings terminology, and correlations between actors such as doctors and police officers involved in the disappearances. This paper analyzes almost 3000 textual reports of missing persons in São Paulo city during the Brazilian dictatorship through unsupervised algorithms of information extraction in Portuguese, identifying named entities and relevant terminology associated with these four criteria. The analysis allowed us to observe terminological patterns relevant for people identification (e.g., presence of rings or similar personal belongings) and automate the study of correlations between actors. The proposed system acts as a first classificatory and indexing middleware of the reports and represents a feasible system that can assist researchers working in pattern search among autopsy reportsThis research was partially funded by Spanish Ministry of Economy, Industry and 5 Competitiveness under its Competitive Juan de la Cierva Postdoctoral Research Programme, grant FJCI-2016-6 28032 and from the European Union, through the Marie Skłodowska-Curie Innovative Training Network ‘CHEurope: Critical Heritage Studies and the Future of Europe’ H2020 Marie Skłodowska-Curie Actions, grant 722416S

Knowledge dependencies in fuzzy information systems evaluation

Experience and research within the field of Information Systems Evaluation (ISE), has traditionally centered on providing tools and techniques for investment justification and appraisal, based upon explicit knowledge which encodes financial and other direct situational factors (such as accounting, costing and risk metrics). However, such approaches tend not to include additional causal interdependencies that are based upon tacit knowledge and are inherent within such a decision-making task. The authors show the results of applying a cognitive mapping approach, in the guise of a Fuzzy Cognitive Mapping (FCM) simulation, i.e. Fuzzy Information Systems Evaluation (F-ISE), in order to highlight the usefulness of applying such a technique. The authors highlight those contingent and necessary knowledge dependencies, in an exploratory sense, which relate to the investment appraisal decision-making task, in terms of the interplay between tacit and explicit knowledge, in this regard

Machine Learning Outperforms ACC / AHA CVD Risk Calculator in MESA.

Background Studies have demonstrated that the current US guidelines based on American College of Cardiology/American Heart Association (ACC/AHA) Pooled Cohort Equations Risk Calculator may underestimate risk of atherosclerotic cardiovascular disease ( CVD ) in certain high-risk individuals, therefore missing opportunities for intensive therapy and preventing CVD events. Similarly, the guidelines may overestimate risk in low risk populations resulting in unnecessary statin therapy. We used Machine Learning ( ML ) to tackle this problem. Methods and Results We developed a ML Risk Calculator based on Support Vector Machines ( SVM s) using a 13-year follow up data set from MESA (the Multi-Ethnic Study of Atherosclerosis) of 6459 participants who were atherosclerotic CVD-free at baseline. We provided identical input to both risk calculators and compared their performance. We then used the FLEMENGHO study (the Flemish Study of Environment, Genes and Health Outcomes) to validate the model in an external cohort. ACC / AHA Risk Calculator, based on 7.5% 10-year risk threshold, recommended statin to 46.0%. Despite this high proportion, 23.8% of the 480 "Hard CVD " events occurred in those not recommended statin, resulting in sensitivity 0.76, specificity 0.56, and AUC 0.71. In contrast, ML Risk Calculator recommended only 11.4% to take statin, and only 14.4% of "Hard CVD " events occurred in those not recommended statin, resulting in sensitivity 0.86, specificity 0.95, and AUC 0.92. Similar results were found for prediction of "All CVD " events. Conclusions The ML Risk Calculator outperformed the ACC/AHA Risk Calculator by recommending less drug therapy, yet missing fewer events. Additional studies are underway to validate the ML model in other cohorts and to explore its ability in short-term CVD risk prediction

Contribution of patient, physician, and environmental factors to demographic and health variation in colonoscopy follow-up for abnormal colorectal cancer screening test results

BACKGROUND: Patient, physician, and environmental factors were identified, and the authors examined the contribution of these factors to demographic and health variation in colonoscopy follow-up after a positive fecal occult blood test/fecal immunochemical test (FOBT/FIT) screening. METHODS: In total, 76,243 FOBT/FIT-positive patients were identified from 120 Veterans Health Administration (VHA) facilities between August 16, 2009 and March 20, 2011 and were followed for 6 months. Patient demographic (race/ethnicity, sex, age, marital status) and health characteristics (comorbidities), physician characteristics (training level, whether primary care provider) and behaviors (inappropriate FOBT/FIT screening), and environmental factors (geographic access, facility type) were identified from VHA administrative records. Patient behaviors (refusal, private sector colonoscopy use) were estimated with statistical text mining conducted on clinic notes, and follow-up predictors and adjusted rates were estimated using hierarchical logistic regression. RESULTS: Roughly 50% of individuals completed a colonoscopy at a VHA facility within 6 months. Age and comorbidity score were negatively associated with follow-up. Blacks were more likely to receive follow-up than whites. Environmental factors attenuated but did not fully account for these differences. Patient behaviors (refusal, private sector colonoscopy use) and physician behaviors (inappropriate screening) fully accounted for the small reverse race disparity and attenuated variation by age and comorbidity score. Patient behaviors (refusal and private sector colonoscopy use) contributed more to variation in follow-up rates than physician behaviors (inappropriate screening). CONCLUSIONS: In the VHA, blacks are more likely to receive colonoscopy follow-up for positive FOBT/FIT results than whites, and follow-up rates markedly decline with advancing age and comorbidity burden. Patient and physician behaviors explain race variation in follow-up rates and contribute to variation by age and comorbidity burden. Cancer 2017;123:3502-12. Published 2017. This article is a US Government work and is in the public domain in the USA

Using Data in Undergraduate Science Classrooms

Provides pedagogical insight concerning the skill of using data The resource being annotated is: http://www.dlese.org/dds/catalog_DATA-CLASS-000-000-000-007.htm

Reading in the Disciplines: The Challenges of Adolescent Literacy

A companion report to Carnegie's Time to Act, focuses on the specific skills and literacy support needed for reading in academic subject areas in higher grades. Outlines strategies for teaching content knowledge and reading strategies together

Game of Tenure: the role of “hidden” citations on researchers’ ranking in Ecology

Field ecologists and macroecologists often compete for the same grants and academic positions, with the former producing primary data that the latter generally use for model parameterization. Primary data are usually cited only in the supplementary materials, thereby not counting formally as citations, creating a system where field ecologists are routinely under-acknowledged and possibly disadvantaged in the race for funding and positions. Here, we explored how the performance of authors producing novel ecological data would change if all the citations to their work would be accounted for by bibliometric indicators. We collected the track record of >2300 authors from Google Scholar and citation data from 600 papers published in 40 ecology journals, including field-based, conservation, general ecology, and macroecology studies. Then we parameterized a simulation that mimics the current publishing system for ecologists and assessed author rankings based on number of citations, H-Index, Impact Factor, and number of publications under a scenario where supplementary citations count. We found weak evidence for field ecologists being lower ranked than macroecologists or general ecologists, with publication rate being the main predictor of author performance. Current ranking dynamics were largely unaffected by supplementary citations as they are 10 times less than the number of main text citations. This is further exacerbated by the common practice of citing datasets assembled by previous research or data papers instead of the original articles. While accounting for supplementary citations does not appear to offer a solution, researcher performance evaluations should include criteria that better capture authors’ contribution of new, publicly available data. This could encourage field ecologists to collect and store new data in a systematic manner, thereby mitigating the data patchiness and bias in macroecology studies, and further accelerating the advancement of ecology and related areas of biogeography