title: Logistic regression model for identification of right ventricular dysfunction in patients with acute pulmonary embolism by means of computed tomography.
abstract: OBJECTIVE
  Diagnosis of right ventricular dysfunction in patients with acute pulmonary embolism (PE) is known to be associated with increased risk of mortality. The aim of the study was to calculate a logistic regression model for reliable identification of right ventricular dysfunction (RVD) in patients diagnosed with computed tomography pulmonary angiography.
  
  
  METHODS
  Ninety-seven consecutive patients with acute pulmonary embolism were divided into groups with and without RVD basing upon echocardiographic measurement of pulmonary artery systolic pressure (PASP). PE severity was graded with the pulmonary obstruction score. CT measurements of heart chambers and mediastinal vessels were performed; position of interventricular septum and presence of contrast reflux into the inferior vena cava were also recorded. The logistic regression model was prepared by means of stepwise logistic regression.
  
  
  RESULTS
  Among the used parameters, the final model consisted of pulmonary obstruction score, short axis diameter of right ventricle and diameter of inferior vena cava. The calculated model is characterized by 79% sensitivity and 81% specificity, and its performance was significantly better than single CT-based measurements.
  
  
  CONCLUSIONS
  Logistic regression model identifies RVD significantly better, than single CT-based measurements.
authors.affiliation: 1st Department of Radiology, Medical University of Lublin, Lublin, Poland. grzegorz.staskiewicz@gmail.com
authors.forename: Grzegorz
authors.initials: G
authors.lastname: Staskiewicz
authors.forename: Elżbieta
authors.initials: E
authors.lastname: Czekajska-Chehab
authors.forename: Sebastian
authors.initials: S
authors.lastname: Uhlig
authors.forename: Jerzy
authors.initials: J
authors.lastname: Przegalinski
authors.forename: Ryszard
authors.initials: R
authors.lastname: Maciejewski
authors.forename: Andrzej
authors.initials: A
authors.lastname: Drop
mesh_terms: D000208:Acute Disease; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D005260:Female; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D011655:Pulmonary Embolism / Q000150:complications* / Q000000981:diagnostic imaging*; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D012044:Regression Analysis; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014057:Tomography, X-Ray Computed / Q000379:methods*; D018497:Ventricular Dysfunction, Right / Q000000981:diagnostic imaging* / Q000209:etiology*