BACKGROUND: The rapid detection of left ventricular systolic dysfunction (LVSD) is an important step in the clinical management of patients admitted with acute decompensated heart failure, because it allows the initiation of treatment specific to LVSD and avoidance of contraindicated therapies. The aim of this study was to determine whether internal medicine residents with limited ultrasound training could use hand-carried ultrasound (HCU) to identify LVSD. METHODS: Fifty patients admitted with acute decompensated heart failure were imaged from the parasternal window at the bedside with an HCU device by residents blinded to all clinical data, who had undergone limited cardiac ultrasound training (20 practice studies). Ejection fraction (EF) on HCU was graded as >40% or <40%. HCU EF and a number of physical exam findings and electrocardiographic and laboratory variables were compared for their ability to predict to formal echocardiographic left ventricular EF. RESULTS: The average formal EF was 32 ± 16% (range, 7%-70%), with 66% of patients having EFs < 40%. The residents' ability to detect an EF < 40% with HCU was excellent (sensitivity, 94%; specificity, 94%; negative predictive value, 88%; positive predictive value, 97%). Binary logistic regression demonstrated that HCU EF was the most powerful predictor of EF < 40%, with minimal additional value from clinical, exam, lab, and electrocardiographic variables. The time interval between clinical assessment and availability of formal echocardiographic results was 22 ± 17 hours. CONCLUSIONS: Residents with limited training in cardiac ultrasound were able to identify LVSD in patients with acute decompensated heart failure with superior accuracy compared with clinical, physical exam, lab, and electrocardiographic findings and an average of 22 hours before the results of formal echocardiography were available.
BACKGROUND: The rapid detection of left ventricular systolic dysfunction (LVSD) is an important step in the clinical management of patients admitted with acute decompensated heart failure, because it allows the initiation of treatment specific to LVSD and avoidance of contraindicated therapies. The aim of this study was to determine whether internal medicine residents with limited ultrasound training could use hand-carried ultrasound (HCU) to identify LVSD. METHODS: Fifty patients admitted with acute decompensated heart failure were imaged from the parasternal window at the bedside with an HCU device by residents blinded to all clinical data, who had undergone limited cardiac ultrasound training (20 practice studies). Ejection fraction (EF) on HCU was graded as >40% or <40%. HCU EF and a number of physical exam findings and electrocardiographic and laboratory variables were compared for their ability to predict to formal echocardiographic left ventricular EF. RESULTS: The average formal EF was 32 ± 16% (range, 7%-70%), with 66% of patients having EFs < 40%. The residents' ability to detect an EF < 40% with HCU was excellent (sensitivity, 94%; specificity, 94%; negative predictive value, 88%; positive predictive value, 97%). Binary logistic regression demonstrated that HCU EF was the most powerful predictor of EF < 40%, with minimal additional value from clinical, exam, lab, and electrocardiographic variables. The time interval between clinical assessment and availability of formal echocardiographic results was 22 ± 17 hours. CONCLUSIONS: Residents with limited training in cardiac ultrasound were able to identify LVSD in patients with acute decompensated heart failure with superior accuracy compared with clinical, physical exam, lab, and electrocardiographic findings and an average of 22 hours before the results of formal echocardiography were available.
Authors: Michael W Cullen; Lori A Blauwet; Ori M Vatury; Sharon L Mulvagh; Thomas R Behrenbeck; Christopher G Scott; Patricia A Pellikka Journal: Mayo Clin Proc Date: 2014-03-29 Impact factor: 7.616
Authors: Surekha Mullangi; Stephen M Sozio; Paul Segal; Steven Menez; Carol Martire; Tariq Shafi Journal: Semin Dial Date: 2018-01-03 Impact factor: 3.455
Authors: Jason C Ojeda; James A Colbert; Xinyi Lin; Graham T McMahon; Peter M Doubilet; Carol B Benson; Justina Wu; Joel T Katz; Maria A Yialamas Journal: J Gen Intern Med Date: 2014-11-12 Impact factor: 5.128