Browsing by Author "Clary, Julie M."

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    Can emergency physicians diagnose and correctly classify diastolic dysfunction using bedside echocardiography?
    (Elsevier, 2015-09) Ehrman, Robert R.; Russell, Frances M.; Ansari, Asimul H.; Margeta, Bosko; Clary, Julie M.; Christian, Errick; Cosby, Karen S.; Bailitz, John; Department of Medicine, IU School of Medicine
    Objectives The goal of this study was to determine if emergency physicians (EPs) can correctly perform a bedside diastology examination (DE) and correctly grade the level of diastolic function with minimal additional training in echocardiography beyond what is learned in residency. We hypothesize that EPs will be accurate at detecting and grading diastolic dysfunction (DD) when compared to a criterion standard interpretation by a cardiologist. Methods We conducted a prospective, observational study on a convenience sample of adult patients who presented to an urban emergency department with a chief concern of dyspnea. All patients had a bedside echocardiogram, including a DE, performed by an EP-sonographer who had 3 hours of didactic and hands-on echocardiography training with a cardiologist. The DE was interpreted as normal, grade 1 to 3 if DD was present, or indeterminate, all based on predefined criteria. This interpretation was compared to that of a cardiologist who was blinded to the EPs’ interpretations. Results We enrolled 62 patients; 52% had DD. Using the cardiology interpretation as the criterion standard, the sensitivity and specificity of the EP-performed DE to identify clinically significant diastolic function were 92% (95% confidence interval [CI], 60-100) and 69% (95% CI, 50-83), respectively. Agreement between EPs and cardiology on grade of DD was assessed using κ and weighted κ: κ = 0.44 (95% CI, 0.29-0.59) and weighted κ = 0.52 (95% CI, 0.38-0.67). Overall, EPs rated 27% of DEs as indeterminate, compared with only 15% by cardiology. For DEs where both EPs and cardiology attempted an interpretation (indeterminates excluded) κ = 0.45 (95% CI, 0.26 to 0.65) and weighted κ = 0.54 (95% CI, 0.36-0.72). Conclusion After limited diastology-specific training, EPs are able to accurately identify clinically significant DD. However, correct grading of DD, when compared to a cardiologist, was only moderate, at best. Our results suggest that further training is necessary for EPs to achieve expertise in grading DD.
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    Emergency Physicians Are Able to Detect Right Ventricular Dilation With Good Agreement Compared to Cardiology
    (Wiley, 2017-07) Rutz, Matt A.; Clary, Julie M.; Kline, Jeffrey A.; Russell, Frances M.; Department of Emergency Medicine, IU School of Medicine
    Objective Focused cardiac ultrasound (FOCUS) is a useful tool in evaluating patients presenting to the emergency department (ED) with acute dyspnea. Prior work has shown that right ventricular (RV) dilation is associated with repeat hospitalizations and shorter life expectancy. Traditionally, RV assessment has been evaluated by cardiologist-interpreted comprehensive echocardiography. The primary goal of this study was to determine the inter-rater reliability between emergency physicians (EPs) and a cardiologist for determining RV dilation on FOCUS performed on ED patients with acute dyspnea. Methods This was a prospective, observational study at two urban academic EDs; patients were enrolled if they had acute dyspnea and a computed tomographic pulmonary angiogram without acute disease. All patients had an EP-performed FOCUS to assess for RV dilation. RV dilation was defined as an RV to left ventricular ratio greater than 1. FOCUS interpretations were compared to a blinded cardiologist FOCUS interpretation using agreement and kappa statistics. Results Of 84 FOCUS examinations performed on 83 patients, 17% had RV dilation. Agreement and kappa, for EP-performed FOCUS for RV dilation were 89% (95% confidence interval [CI] 80–95%) and 0.68 (95% CI 0.48–0.88), respectively. Conclusions Emergency physician sonographers are able to detect RV dilation with good agreement when compared to cardiology. These results support the wider use of EP-performed FOCUS to evaluate for RV dilation in ED patients with dyspnea.
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    Predicting In-Hospital Mortality in Patients Undergoing Percutaneous Coronary Intervention
    (Science Direct, 2021-07-20) Castro-Dominguez, Yulanka S.; Wang, Yongfei; Minges, Karl E.; McNamara, Robert L.; Spertus, John A.; Dehmer, Gregory J.; Messenger, John C.; Lavin, Kimberly; Anderson, Cornelia; Blankinship, Kristina; Mercado, Nestor; Clary, Julie M.; Osborne, Anwar D.; Curtis, Jeptha P.; Cavender, Matthew A.; Medicine, School of Medicine
    Background Standardization of risk is critical in benchmarking and quality improvement efforts for percutaneous coronary interventions (PCI). In 2018, the CathPCI Registry was updated to include additional variables to better classify higher-risk patients. Objectives We sought to develop a model for predicting in-hospital mortality risk following PCI incorporating these additional variables. Methods Data from 706,263 PCIs performed between 7/2018-6/2019 at 1,608 sites were used to develop and validate a new full and pre-catheterization model to predict in-hospital mortality, and a simplified bedside risk score. The sample was randomly split into a development (70%, n=495,005) and validation cohort (30%, n=211,258). We created 1,000 bootstrapped samples of the development cohort and used stepwise selection logistic regression on each sample. The final model included variables that were selected in at least 70% of the bootstrapped samples and those identified a priori due to clinical relevance. Results In-hospital mortality following PCI varied based on clinical presentation. Procedural urgency, cardiovascular instability, and level of consciousness after cardiac arrest were most predictive of in-hospital mortality. The full model performed well, with excellent discrimination (c-index: 0.943) in the validation cohort and good calibration across different clinical and procedural risk cohorts. The median hospital risk-standardized mortality rate was 1.9% and ranged from 1.1% to 3.3% (interquartile range: 1.7%-2.1%). Conclusions The risk of mortality following PCI can be predicted in contemporary practice by incorporating variables that reflect clinical acuity. This model, which includes data previously not captured, is a valid instrument for risk stratification and for quality improvement efforts.