Browsing by Subject "sensitivity"

Now showing 1 - 5 of 5
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    Development and Validation of Electronic Quality Measures to Assess Care for Patients With Transient Ischemic Attack and Minor Ischemic Stroke
    (AHA, 2017) Bravata, Dawn M.; Myers, Laura J.; Cheng, Eric; Reeves, Mathew; Baye, Fitsum; Zhangsheng, Yu; Damush, Teresa; Miech, Edward J.; Sico, Jason; Phipps, Michael; Zillich, Alan; Johanning, Jason; Chaturvedi, Seemant; Austin, Curt; Ferguson, Jared; Maryfield, Bailey; Snow, Kathy; Ofner, Susan; Graham, Glenn; Rhude, Rachel; Williams, Linda S.; Arling, Greg; Medicine, School of Medicine
    Background—Despite interest in using electronic health record (EHR) data to assess quality of care, the accuracy of such data is largely unknown. We sought to develop and validate transient ischemic attack and minor ischemic stroke electronic quality measures (eQMs) using EHR data. Methods and Results—A random sample of patients with transient ischemic attack or minor ischemic stroke, cared for in Veterans Health Administration facilities (fiscal year 2011), was identified. We constructed 31 eQMs based on existing quality measures. Chart review was the criterion standard for validating the eQMs. To evaluate eQMs in terms of eligibility, we calculated the proportion of patients who were genuinely not eligible to receive a process (based on chart review) and who were correctly identified as not eligible by the EHR data (specificity). To assess eQMs about classification of whether patients received a process, we calculated the proportion of patients who actually received the process (based on chart review) and who were classified correctly by the EHR data as passing (sensitivity). Seven hundred sixty-three patients were included. About eligibility, specificity varied from 25% (brain imaging; carotid imaging) to 99% (anticoagulation quality). About pass rates, sensitivity varied from 30% (antihypertensive class) to 100% (coronary risk assessment; international normalized ratio measured). The 16 eQMs with ≥70% specificity in eligibility and ≥70% sensitivity in pass rates included coronary risk assessment, international normalized ratio measured, HbA1c measurement, speech language pathology consultation, anticoagulation for atrial fibrillation, discharge on statin, lipid management, neurology consultation, Holter, deep vein thrombosis prophylaxis, oral hypoglycemic intensification, cholesterol medication intensification, antihypertensive intensification, antihypertensive class, carotid stenosis intervention, and substance abuse referral for alcohol. Conclusions—It is feasible to construct valid eQMs for processes of transient ischemic attack and minor ischemic stroke care. Healthcare systems with EHRs should consider using electronic data to evaluate care for their patients with transient ischemic attack and to complement and expand quality measurement programs currently focused on patients with stroke.
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    Drug Selection via Joint Push and Learning to Rank
    (IEEE, 2018-06) He, Yicheng; Liu, Junfeng; Ning, Xia; Medical and Molecular Genetics, School of Medicine
    Selecting the right drugs for the right patients is a primary goal of precision medicine. In this manuscript, we consider the problem of cancer drug selection in a learning-to-rank framework. We have formulated the cancer drug selection problem as to accurately predicting 1). the ranking positions of sensitive drugs and 2). the ranking orders among sensitive drugs in cancer cell lines based on their responses to cancer drugs. We have developed a new learning-to-rank method, denoted as pLETORg, that predicts drug ranking structures in each cell line via using drug latent vectors and cell line latent vectors. The pLETORg method learns such latent vectors through explicitly enforcing that, in the drug ranking list of each cell line, the sensitive drugs are pushed above insensitive drugs, and meanwhile the ranking orders among sensitive drugs are correct. Genomics information on cell lines is leveraged in learning the latent vectors. Our experimental results on a benchmark cell line-drug response dataset demonstrate that the new pLETORg significantly outperforms the state-of-the-art method in prioritizing new sensitive drugs.
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    Finding the bottom and using it: Offsets and sensitivity in the detection of low intensity values in vivo with 2-photon microscopy
    (Taylor & Francis Online, 2014-03-01) Sandoval, Ruben M.; Wang, Exing; Molitoris, Bruce A.; Department of Medicine, School of Medicine
    Maximizing 2-photon parameters used in acquiring images for quantitative intravital microscopy, especially when high sensitivity is required, remains an open area of investigation. Here we present data on correctly setting the black level of the photomultiplier tube amplifier by adjusting the offset to allow for accurate quantitation of low intensity processes. When the black level is set too high some low intensity pixel values become zero and a nonlinear degradation in sensitivity occurs rendering otherwise quantifiable low intensity values virtually undetectable. Initial studies using a series of increasing offsets for a sequence of concentrations of fluorescent albumin in vitro revealed a loss of sensitivity for higher offsets at lower albumin concentrations. A similar decrease in sensitivity, and therefore the ability to correctly determine the glomerular permeability coefficient of albumin, occurred in vivo at higher offset. Finding the offset that yields accurate and linear data are essential for quantitative analysis when high sensitivity is required.
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    Selection for High Alcohol Preference Drinking in Mice Results in Heightened Sensitivity and Rapid Development of Acute Functional Tolerance to Alcohol’s Ataxic Effects
    (Wiley, 2013-02) Fritz, Brandon M.; Grahame, Nicholas J.; Boehm, Stephen L. II; Department of Psychology, School of Science
    Selection for High Alcohol Preference Drinking in Mice Results in Heightened Sensitivity and Rapid Development of Acute Functional Tolerance to Alcohol’s Ataxic Effects Brandon M. Fritz , Nicholas J. Grahame , and Stephen L. Boehm II Indiana Alcohol Research Center and Department of Psychology, Indiana University – Purdue University Indianapolis, Indianapolis, IN 46202 Abstract Propensity to develop acute functional (or within session) tolerance to alcohol (ethanol) may influence the amount of alcohol consumed, with higher drinking associated with greater acute functional tolerance (AFT). The goal of the current study was to assess this potential correlated response between alcohol preference and AFT in second and third replicate lines of mice selectively bred for high (HAP2&3) and low (LAP2&3) alcohol preference drinking. Male and female mice were tested for development of AFT on a static dowel task which requires that animals maintain balance on a wooden dowel in order to prevent falling. On test day, each mouse received one (1.75g/kg; Experiment 1) or two (1.75g/kg and 2.0g/kg; Experiment 2) injections of ethanol; an initial administration before being placed on the dowel and in Experiment 2, an additional administration after the first regain of balance on the dowel. Blood samples were taken immediately after loss of balance (when BECs were rising) and at recovery (during falling BECs) in Experiment 1, and after first and second recovery in Experiment 2. It was found that HAP mice fell from the dowel significantly earlier and at lower BECs than LAP mice following the initial injection of ethanol and were therefore more sensitive to its early effects. Furthermore, Experiment 1 detected significantly greater AFT development (BECfalling - BECrising) in HAP mice as compared to LAP mice which occurred within ~30 min, supporting our hypothesis. However, AFT was not different between lines in Experiment 2, indicating that ~30–60 min following alcohol administration, AFT development was similar in both lines. These data show that high alcohol drinking genetically associates with both high initial sensitivity and very early tolerance to the ataxic effects of ethanol.
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    Sensitivity Analysis in Poro-Elastic and Poro-Visco-Elastic Models with Respect to Boundary Data
    (AMS, 2017) Banks, Harvey Thomas; Bekele-Maxwell, Kidist; Bociu, Lorena; Noorman, M.; Guidoboni, Giovanna; Ophthalmology, School of Medicine
    In this article we consider poro-elastic and poro-visco-elastic models inspired by problems in medicine and biology, and we perform sensitivity analysis on the solutions of these fluid-solid mixture problems with respect to the imposed boundary data, which are the main drivers of the system. Moreover, we compare the results obtained in the elastic case vs. visco-elastic case, as it is known that structural viscosity of biological tissues decreases with age and disease. Sensitivity analysis is the first step towards optimization and control problems associated with these models, which is our ultimate goal.