681 research outputs found

    Reimplanting Previously Infected Device in the Same Patient: A Clever Way to Provide Essential Therapy

    Full text link
    Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/108366/1/pace12457.pd

    Cardiac Device Reutilization: Is It Time to “Go Green” in Underserved Countries?

    Full text link
    Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/86826/1/j.1540-8159.2011.03060.x.pd

    When Zebras Run with Horses: The Diagnostic Dilemma of Acute Aortic Dissection Complicated by Myocardial Infarction

    Full text link
    Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/72234/1/j.1540-8183.2002.tb01107.x.pd

    Neural Networks, Logistic Regression, and Calibration: A Reply

    Full text link
    Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/68566/2/10.1177_0272989X9801800414.pd

    The Addition of the Charlson Comorbidity Index to the GRACE Risk Prediction Index Improves Prediction of Outcomes in Acute Coronary Syndrome

    Full text link
    Patients with cardiovascular disease have increased risk of poor outcomes when coexisting illnesses are present. Clinicians, administrators, and health services researchers utilize risk adjustment indices to stratify patients for various outcomes. The GRACE Risk Prediction Index (GRPI) was developed to risk stratify patients who experienced an acute coronary syndrome (ACS) event. GRPI does not account for the presence of comorbid conditions. The objective of this study was to compare the ability of the GRPI and the Charlson Comorbidity Index (CCI), used independently or combined, to predict mortality or secondary coronary events in patients admitted for ACS. Data were obtained from an academic health system's ACS registry. Outcomes included inpatient and 6-month postdischarge mortality and occurrence of secondary cardiovascular events or revascularization procedures. Logistic regression derived C statistics for CCI, GRPI, and CCI-GRPI predictive models for each outcome. Likelihood ratio tests determined the contribution of CCI when added to GRPI models. Complete data were available for 1202 patients. The GRPI model had the greatest C statistic when predicting inpatient mortality (0.73); the GRPI-CCI combined model C statistic was 0.81 when predicting death during the follow-up period; and C statistics for all 3 models were similar in predicting secondary events (0.57?0.60). The likelihood ratio analysis demonstrated that adding CCI to GRPI models was beneficial primarily for predicting secondary events. CCI is a useful addition to GRPI when predicting future cardiac-related events or mortality after an ACS event. It is an acceptable alternative to the GRPI model if data to construct GRPI are not available. (Population Health Management 2014;17:54?59)Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/140179/1/pop.2012.0117.pd

    Rethinking cardiac risk reduction after noncardiac surgery: The postoperative Carpe diem

    Full text link
    Patients undergoing noncardiac surgery frequently experience major adverse cardiac events. As a significant proportion of these patients develop cardiac complications despite optimal use of preoperative clinical risk‐prediction algorithms, physicians have long searched for better methods of forecasting and ameliorating cardiac risk in this population. Recently, postoperative troponin levels have been found to be powerful and independent predictors of cardiovascular mortality in patients undergoing noncardiac surgery. Importantly, the predictive properties of these markers outperform preoperative clinical risk‐prediction algorithms. We thus posit that the assessment of postoperative troponin represents an as yet untapped “golden opportunity” for cardiac risk reduction. As cardiac troponin isolates an unusually high‐risk subgroup, we outline a strategy that utilizes this marker to improve cardiac outcomes. Where pertinent, strengths and limitations of this approach are discussed and areas of uncertainty identified. As with all hypotheses, this proposition fuels many questions and calls for a research agenda dedicated to quantifying risk or benefit, and defining best practices. Journal of Hospital Medicine 2012. © 2012 Society of Hospital MedicinePeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/94474/1/1975_ftp.pd

    Low Molecular Weight Heparin in Atrial Fibrillation Management: Facts, Fiction, Future

    Full text link
    Background: Atrial fibrillation (AF) is the most common sustained arrhythmia and various AF disease management strategies can be utilized.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/44690/1/10572_2004_Article_5264621.pd
    • 

    corecore