Air Travel and Venous Thromboembolism: A Systematic Review

CONTEXT: Despite multiple attempts to document and quantify the danger of venous thromboembolism (VTE) following prolonged travel, there is still uncertainty about the magnitude of risk and what can be done to lower it. OBJECTIVES: To review the methodologic strength of the literature, estimate the risk of travel-related VTE, evaluate the efficacy of preventive treatments, and develop evidence-based recommendations for practice. DATA SOURCES: Studies identified from MEDLINE from 1966 through December 2005, supplemented by a review of the Cochrane Central Registry of Controlled Trials, the Database of Abstracts of Reviews of Effects, and relevant bibliographies. STUDY SELECTION: We included all clinical studies that either reported primary data concerning travel as a risk factor for VTE or tested preventive measures for travel-related VTE. DATA EXTRACTION AND ANALYSIS: Two reviewers reviewed each study independently to assess inclusion criteria, classify research design, and rate methodologic features. The effect of methodologic differences, VTE risk, and travel duration on VTE rate was evaluated using a logistic regression model. DATA SYNTHESIS: Twenty-four published reports, totaling 25 studies, met inclusion criteria (6 case-control studies, 10 cohort studies, and 9 randomized controlled trials). Method of screening for VTE [screening ultrasound compared to usual clinical care, odds ratio (OR) 390], outcome measure [all VTE compared to pulmonary embolism (PE) only, OR 21], duration of travel (<6 hours compared to 6–8 hours, OR 0.011), and clinical risk (“higher” risk travelers compared to “lower,” OR 3.6) were significantly related to VTE rate. Clinical VTE after prolonged travel is rare [27 PE per million flights diagnosed through usual clinical care, 0.05% symptomatic deep venous thrombosis (DVT) diagnosed through screening ultrasounds], but asymptomatic thrombi of uncertain clinical significance are more common. Graduated compression stockings prevented travel-related VTE (P < 0.05 in 4 of 6 studies), aspirin did not, and low-molecular-weight heparin (LMWH) showed a trend toward efficacy in one study. CONCLUSIONS: All travelers, regardless of VTE risk, should avoid dehydration and frequently exercise leg muscles. Travelers on a flight of less than 6 hours and those with no known risk factors for VTE, regardless of the duration of the flight, do not need DVT prophylaxis. Travelers with 1 or more risk factors for VTE should consider graduated compression stockings and/or LMWH for flights longer than 6 hours

Locating previously unknown patterns in data-mining results: a dual data- and knowledge-mining method

BACKGROUND: Data mining can be utilized to automate analysis of substantial amounts of data produced in many organizations. However, data mining produces large numbers of rules and patterns, many of which are not useful. Existing methods for pruning uninteresting patterns have only begun to automate the knowledge acquisition step (which is required for subjective measures of interestingness), hence leaving a serious bottleneck. In this paper we propose a method for automatically acquiring knowledge to shorten the pattern list by locating the novel and interesting ones. METHODS: The dual-mining method is based on automatically comparing the strength of patterns mined from a database with the strength of equivalent patterns mined from a relevant knowledgebase. When these two estimates of pattern strength do not match, a high "surprise score" is assigned to the pattern, identifying the pattern as potentially interesting. The surprise score captures the degree of novelty or interestingness of the mined pattern. In addition, we show how to compute p values for each surprise score, thus filtering out noise and attaching statistical significance. RESULTS: We have implemented the dual-mining method using scripts written in Perl and R. We applied the method to a large patient database and a biomedical literature citation knowledgebase. The system estimated association scores for 50,000 patterns, composed of disease entities and lab results, by querying the database and the knowledgebase. It then computed the surprise scores by comparing the pairs of association scores. Finally, the system estimated statistical significance of the scores. CONCLUSION: The dual-mining method eliminates more than 90% of patterns with strong associations, thus identifying them as uninteresting. We found that the pruning of patterns using the surprise score matched the biomedical evidence in the 100 cases that were examined by hand. The method automates the acquisition of knowledge, thus reducing dependence on the knowledge elicited from human expert, which is usually a rate-limiting step

Retrospective assessment of patient characteristics and healthcare costs prior to a diagnosis of Alzheimer’s disease in an administrative claims database

Abstract Background The objective of this study was to examine patient characteristics and health care resource utilization (HCRU) in the 36 months prior to a confirmatory diagnosis of Alzheimer’s disease (AD) compared to a matched cohort without dementia during the same time interval. Methods Patients newly diagnosed with AD (with ≥2 claims) were identified between January 1, 2013 to September 31, 2015, and the date of the second claim for AD was defined as the index date. Patients were enrolled for at least 36 months prior to index date. The AD cohort was matched to a cohort with no AD or dementia codes (1:3) on age, gender, race/ethnicity, and enrollment duration prior to the index date. Descriptive analyses were used to summarize patient characteristics, HCRU, and healthcare costs prior to the confirmatory AD diagnosis. The classification and regression tree analysis and logistic regression were used to identify factors associated with the AD diagnosis. Results The AD cohort (N = 16,494) had significantly higher comorbidity indices and greater odds of comorbid mental and behavioral diagnoses, including mild cognitive impairment, mood and anxiety disorders, behavioral disturbances, and cerebrovascular disease, heart disease, urinary tract infections, and pneumonia than the matched non-AD or dementia cohort (N = 49,482). During the six-month period before the confirmatory AD diagnosis, AD medication use and diagnosis of mild cognitive impairment, Parkinson’s disease, or mood disorder were the strongest predictors of a subsequent confirmatory diagnosis of AD. Greater HCRU and healthcare costs were observed for the AD cohort primarily during the six-month period before the confirmatory AD diagnosis. Conclusion The results of this study demonstrated a higher comorbidity burden and higher costs for patients prior to a diagnosis of AD in comparison to the matched cohort. Several comorbidities were associated with a subsequent diagnosis of AD

GeneX Va: VBC open source microarray database and analysis software

freeware database and bioinformatics analysis software for archiving and analyzing Affymetrix GeneChip ® data. It provides an integrated framework for management, documentation, and analysis of microarray experiments and data to support a range of users, from individual research laboratories to institutional microarray facilities. GeneX Va also provides web-based access to a PostgreSQL relational database system with a comprehensive security system. Data can be extracted from the database and delivered to interactive or scriptable statistical analysis protocols. The security system allows each investigator to manage their own array data and analysis output files and also provides custom access privileges for other users, groups, and internal/external collaborators. The analysis interface uses “Analysis Trees, ” an innovative user interface that allows researchers to interactively create a treestructured flow chart of analysis routines. The latest GeneX Va software is available from and can be freely downloaded at the Sourceforge web sit