Automated Identification of Unhealthy Drinking Using Routinely Collected Data: A Machine Learning Approach

Background: Unhealthy drinking is prevalent in the United States and can lead to serious health and social consequences, yet it is under-diagnosed and under-treated. Identifying unhealthy drinkers can be time-consuming for primary care providers. An automated tool for identification would allow attention to be focused on patients most likely to need care and therefore increase efficiency and effectiveness. Objectives: To build a clinical prediction tool for unhealthy drinking based solely on routinely collected demographic and laboratory data. Methods: We obtained demographic and laboratory data on 89,325 adults seen at the University of Vermont Medical Center from 2011-2017. Logistic regression, support vector machines (SVM), k-nearest neighbor, and random forests were each used to build clinical prediction models. The model with the largest area under the receiver operator curve (AUC) was selected. Results: SVM with polynomials of degree 3 produced the largest AUC. The most influential predictors were alkaline phosphatase, gender, glucose, and serum bicarbonate. The optimum operating point had sensitivity 31.1%, specificity 91.2%, positive predictive value 50.4%, and negative predictive value 82.1%. Application of the tool increased the prevalence of unhealthy drinking from 18.3% to 32.4%, while reducing the target population by 22%. Limitations: Universal screening was not used during the time data was collected. The prevalence of unhealthy drinking among those screened was 60% suggesting the AUDIT-C was administered to confirm rather than screen for unhealthy drinking. Conclusion: An automated tool, using commonly available data, can identify a subset of patients who appear to warrant clinical attention for unhealthy drinking

Prevalence of antiplatelet therapy in patients with diabetes

OBJECTIVE: To determine the prevalence of, and patient characteristics associated with, antiplatelet therapy in a cohort of primary care patients with Type 1 or Type2 diabetes. METHODS: Subjects participating in a randomized trial of a decision support system were interviewed at home and medication usage verified by a research assistant. Eligibility for antiplatelet therapy was determined by American Diabetes Association criteria and clinical contraindications. The association between antiplatelet use and patient characteristics was examined using bivariate and multivariate logistic regression. RESULTS: The mean age of subjects was 64 years (range 31–93). The prevalence of antiplatelet use was 54% overall; 45% for subjects without known CVD vs. 78% for those with CVD; 46% for women vs. 63% for men; and 45% for younger subjects (age< 65) vs. 62% for senior citizens. After controlling for race/ethnicity, income, education, marital status, insurance status and prescription coverage, the following were associated with the use of antiplatelet therapy: presence of known CVD (OR 3.4 [2.2, 5.1]), male sex (OR 2.0 [1.4, 2.8]), and age > = 65 (OR 1.9 [1.3, 2.7]). The prevalence of antiplatelet therapy for younger women without CVD was 32.8% compared to a prevalence of 90.3% for older men with CVD. CONCLUSION: Despite clinical practice guidelines recommending antiplatelet therapy for patients with diabetes, there are still many eligible patients not receiving this beneficial therapy, particularly patients under 65, women, and patients without known CVD. Effective methods to increase antiplatelet use should be considered at the national, community, practice and provider level

Rare Kaon Decays

The current status of rare kaon decay experiments is reviewed. New limits in the search for Lepton Flavor Violation are discussed, as are new measurements of the CKM matrix.Comment: 8 pages, 3 figures, LaTeX, presented at the 3rd International Conference on B Phyiscs and CP Violation, Taipei December 3-7, 199

Astrophysical Model Selection in Gravitational Wave Astronomy

Theoretical studies in gravitational wave astronomy have mostly focused on the information that can be extracted from individual detections, such as the mass of a binary system and its location in space. Here we consider how the information from multiple detections can be used to constrain astrophysical population models. This seemingly simple problem is made challenging by the high dimensionality and high degree of correlation in the parameter spaces that describe the signals, and by the complexity of the astrophysical models, which can also depend on a large number of parameters, some of which might not be directly constrained by the observations. We present a method for constraining population models using a hierarchical Bayesian modeling approach which simultaneously infers the source parameters and population model and provides the joint probability distributions for both. We illustrate this approach by considering the constraints that can be placed on population models for galactic white dwarf binaries using a future space-based gravitational wave detector. We find that a mission that is able to resolve approximately 5000 of the shortest period binaries will be able to constrain the population model parameters, including the chirp mass distribution and a characteristic galaxy disk radius to within a few percent. This compares favorably to existing bounds, where electromagnetic observations of stars in the galaxy constrain disk radii to within 20%

Flavor-Changing Processes in Extended Technicolor

We analyze constraints on a class of extended technicolor (ETC) models from neutral flavor-changing processes induced by (dimension-six) four-fermion operators. The ETC gauge group is taken to commute with the standard-model gauge group. The models in the class are distinguished by how the left- and right-handed $(L,R)$ components of the quarks and charged leptons transform under the ETC group. We consider $K^{0} - \bar K^0$ and other pseudoscalar meson mixings, and conclude that they are adequately suppressed if the $L$ and $R$ components of the relevant quarks are assigned to the same (fundamental or conjugate-fundamental) representation of the ETC group. Models in which the $L$ and $R$ components of the down-type quarks are assigned to relatively conjugate representations, while they can lead to realistic CKM mixing and intra-family mass splittings, do not adequately suppress these mixing processes. We identify an approximate global symmetry that elucidates these behavioral differences and can be used to analyze other possible representation assignments. Flavor-changing decays, involving quarks and/or leptons, are adequately suppressed for any ETC-representation assignment of the $L$ and $R$ components of the quarks, as well as the leptons. We draw lessons for future ETC model building.Comment: 25 page

Distinguishing black-hole spin-orbit resonances by their gravitational wave signatures. II. Full parameter estimation

Gravitational waves from coalescing binary black holes encode the evolution of their spins prior to merger. In the post-Newtonian regime and on the precession time scale, this evolution has one of three morphologies, with the spins either librating around one of two fixed points ("resonances") or circulating freely. In this paper we perform full parameter estimation on resonant binaries with fixed masses and spin magnitudes, changing three parameters: a conserved "projected effective spin" ξ and resonant family ΔΦ=0,π (which uniquely label the source); the inclination θJN of the binary's total angular momentum with respect to the line of sight (which determines the strength of precessional effects in the waveform); and the signal amplitude. We demonstrate that resonances can be distinguished for a wide range of binaries, except for highly symmetric configurations where precessional effects are suppressed. Motivated by new insight into double-spin evolution, we introduce new variables to characterize precessing black hole binaries which naturally reflects the time scale separation of the system and therefore better encode the dynamical information carried by gravitational waves.D.T. is partially supported by the National Science Foundation through awards PHY-1067985, PHY-1404139, PHY-1055103 and PHY-1307020. D.T. is grateful for the support and hospitality of V. Kalogera's group and the Center for Interdisciplinary Exploration and Research in Astrophysics (CIERA) at Northwestern University, where this project was conceived. D.G. is supported by the UK STFC and the Isaac Newton Studentship of the University of Cambridge. E.B. is supported by NSF CAREER Grant PHY-1055103 and by FCT contract IF/00797/2014/CP1214/CT0012 under the IF2014 Programme. M.K. is supported by Alfred P. Sloan Foundation grant FG-2015-65299. T.B.L. acknowledges NSF award PHY-1307020. U.S. is supported by FP7-PEOPLE-2011-CIG Grant No. 293412, FP7-PEOPLE-2011-IRSES Grant No.295189, H2020-MSCA-RISE-2015 Grant No. StronGrHEP-690904, H2020 ERC Consolidator Grant Agreement No. MaGRaTh-646597, SDSC and TACC through XSEDE Grant No. PHY-090003 by the NSF, Finis Terrae through Grant No. ICTS-CESGA-249, STFC Roller Grant No. ST/L000636/1 and DiRAC's Cosmos Shared Memory system through BIS Grant No. ST/J005673/1 and STFC Grant Nos. ST/H008586/1, ST/K00333X/1. Computational resources were provided by the Northwestern University Grail cluster (CIERA) through NSF MRI award PHY-1126812, by the Atlas cluster at AEI Hannover, supported by the Max Planck Institute and by the Nemo 20 at cluster through NSF-092340

Analysis of Sub-threshold Short Gamma-ray Bursts in Fermi GBM Data

The Fermi Gamma-ray Burst Monitor (GBM) is currently the most prolific detector of Gamma-Ray Bursts (GRBs). Recently the detection rate of short GRBs (SGRBs) has been dramatically increased through the use of ground-based searches that analyze GBM continuous time tagged event (CTTE) data. Here we examine the efficiency of a method developed to search CTTE data for sub-threshold transient events in temporal coincidence with LIGO/Virgo compact binary coalescence triggers. This targeted search operates by coherently combining data from all 14 GBM detectors by taking into account the complex spatial and energy dependent response of each detector. We use the method to examine a sample of SGRBs that were independently detected by the Burst Alert Telescope on board the Neil Gehrels Swift Observatory, but which were too intrinsically weak or viewed with unfavorable instrument geometry to initiate an on-board trigger of GBM. We find that the search can successfully recover a majority of the BAT detected sample in the CTTE data. We show that the targeted search of CTTE data will be crucial in increasing the GBM sensitivity, and hence the gamma-ray horizon, to weak events such as GRB 170817A. We also examine the properties of the GBM signal possibly associated with the LIGO detection of GW150914 and show that it is consistent with the observed properties of other sub-threshold SGRBs in our sample. We find that the targeted search is capable of recovering true astrophysical signals as weak as the signal associated with GW150914 in the untriggered data.Comment: 10 pages, 9 figures, 1 table, submitted to Ap

Evaluation of co-morbidity indices in patients admitted for Chronic Obstructive Pulmonary Disease

Background. There is limited and conflicting information on the use of co-morbidity instruments to predict mortality in patients with chronic obstructive pulmonary disease (COPD). Methods. We sought to test the validity of the Charlson Index and another co-morbidity instrument, the Adult co-morbidity evaluation 27 (ACE-27), in patients admitted with COPD exacerbations. Co-morbidity scores were obtained by chart review. Information on mortality was retrieved from the Social Security Death Index. We examined the predictive validity of the Charlson and the ACE- 27 using survival analysis. Results. There were 112 patients eligible for the study. The ACE-27 but not the Charlson predicted survival, after adjusting for age, gender, and smoking history in Cox regression, hazard ratio (95% CI) of 1.99 (1.17-3.39). Conclusions. This study confirms earlier findings that the Charlson Index is not a reliable predictor of mortality in patients with COPD. However, the ACE-27 appears to be useful for predicting survival in this study