Kanako K Kumamaru1, Sachin S Saboo2, Ayaz Aghayev3, Phoebe Cai4, Carlos Gonzalez Quesada5, Elizabeth George3, Zoha Hussain3, Tianrun Cai3, Frank J Rybicki6. 1. Applied Imaging Science Laboratory, Department of Radiology, Brigham and Women's Hospital & Harvard Medical School, Boston, MA, United States; Department of Radiology, Juntendo Univeristy, Tokyo, Japan. Electronic address: k-kumamaru@juntendo.ac.jp. 2. Applied Imaging Science Laboratory, Department of Radiology, Brigham and Women's Hospital & Harvard Medical School, Boston, MA, United States; Department of Radiology, UT Southwestern Medical Center, Dallas, TX, United States. 3. Applied Imaging Science Laboratory, Department of Radiology, Brigham and Women's Hospital & Harvard Medical School, Boston, MA, United States. 4. Massachusetts Institute of Technology, Cambridge, MA, United States. 5. Department of Medicine, Brigham and Women's Hospital & Harvard Medical School, Boston, MA, United States. 6. Applied Imaging Science Laboratory, Department of Radiology, Brigham and Women's Hospital & Harvard Medical School, Boston, MA, United States; Department of Radiology, The University of Ottawa and The Ottawa Hospital Research Institute, Ottawa, Ontario, Canada.
Abstract
BACKGROUND: The purpose is to develop a comprehensive risk-scoring system based on CT findings for predicting 30-day mortality after acute pulmonary embolism (PE), and to compare it with PE Severity Index (PESI). MATERIALS AND METHODS: The study included consecutive 1698 CT pulmonary angiograms (CTPA) positive for acute PE performed at a single institution (2003-2010). Two radiologists independently assessed each study regarding clinically relevant findings and then performed adjudication. These variables plus patient clinical information were included to build a LASSO logistic regression model to predict 30-day mortality. A point score for each significant variable was generated based on the final model. PESI score was calculated in 568 patients who visited the hospital after 2007. RESULTS: Inter-reader agreements of interpretations were >95% except for septal bowing (92%). The final prediction model showed superior ability over PESI (AUC = 0.822 vs 0.745) for predicting all-cause 30-day mortality (12.4%). The scoring system based on the significant variables (age (years), pleural effusion (+20), pericardial effusion (+20), lung/liver/bone lesions suggesting malignancy (+60), chronic interstitial lung disease (+20), enlarged lymph node in thorax (+20), and ascites (+40)) stratified patients into 4 severity categories, with mortality rates of 0.008% in class-I (≤50 pt), 3.8% in class-II (51-100 pt), 17.6% in class-III (101-150 pt), and 40.9% in class-IV (>150 pt). The mortality rate in the CTPA-high risk category (class-IV) was higher than those in the PESI's high risk (27.4%) and very high risk (25.2%) categories. CONCLUSION: The CTPA-based model was superior to PESI in predicting 30-day mortality. Incorporating the CTPA-based scoring system into image interpretation workflows may help physicians to select the most appropriate management approach for individual patients.
BACKGROUND: The purpose is to develop a comprehensive risk-scoring system based on CT findings for predicting 30-day mortality after acute pulmonary embolism (PE), and to compare it with PE Severity Index (PESI). MATERIALS AND METHODS: The study included consecutive 1698 CT pulmonary angiograms (CTPA) positive for acute PE performed at a single institution (2003-2010). Two radiologists independently assessed each study regarding clinically relevant findings and then performed adjudication. These variables plus patient clinical information were included to build a LASSO logistic regression model to predict 30-day mortality. A point score for each significant variable was generated based on the final model. PESI score was calculated in 568 patients who visited the hospital after 2007. RESULTS: Inter-reader agreements of interpretations were >95% except for septal bowing (92%). The final prediction model showed superior ability over PESI (AUC = 0.822 vs 0.745) for predicting all-cause 30-day mortality (12.4%). The scoring system based on the significant variables (age (years), pleural effusion (+20), pericardial effusion (+20), lung/liver/bone lesions suggesting malignancy (+60), chronic interstitial lung disease (+20), enlarged lymph node in thorax (+20), and ascites (+40)) stratified patients into 4 severity categories, with mortality rates of 0.008% in class-I (≤50 pt), 3.8% in class-II (51-100 pt), 17.6% in class-III (101-150 pt), and 40.9% in class-IV (>150 pt). The mortality rate in the CTPA-high risk category (class-IV) was higher than those in the PESI's high risk (27.4%) and very high risk (25.2%) categories. CONCLUSION: The CTPA-based model was superior to PESI in predicting 30-day mortality. Incorporating the CTPA-based scoring system into image interpretation workflows may help physicians to select the most appropriate management approach for individual patients.
Authors: Mads Dam Lyhne; Jacob Gammelgaard Schultz; Peter J MacMahon; Faris Haddad; Mannudeep Kalra; David Mai-King Tso; Alona Muzikansky; Michael H Lev; Christopher Kabrhel Journal: Emerg Radiol Date: 2019-08-02