José M Porcel1,2, Marina Pardina2,3, Carmen Alemán4, Esther Pallisa5, Richard W Light6, Silvia Bielsa1,2. 1. Pleural Medicine Unit, Department of Internal Medicine, Arnau de Vilanova University Hospital, Lleida, Spain. 2. Institute for Biomedical Research in Lleida Dr Pifarré Foundation, IRBLLEIDA, Lleida, Spain. 3. Department of Radiology, Arnau de Vilanova University Hospital, Lleida, Spain. 4. Department of Internal Medicine, Vall d'Hebron University Hospital, Barcelona, Spain. 5. Department of Radiology, Vall d'Hebron University Hospital, Barcelona, Spain. 6. Division of Allergy, Pulmonary and Critical Care, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Abstract
BACKGROUND AND OBJECTIVE: Due to limited data, we aimed to develop and validate a computed tomography (CT)-based scoring system for identifying those parapneumonic effusions (PPEs) requiring drainage. METHODS: A retrospective review of all patients with PPE who underwent thoracentesis and a chest CT scan before any attempt to place a tube thoracostomy, if applicable, over an 8-year period was conducted. Eleven chest CT characteristics were compared between 90 patients with complicated PPEs (CPPEs), defined as those which eventually required chest drainage, and 60 with non-complicated effusions (derivation sample). A scoring system was devised with those CT findings identified as independent predictors of CPPE in a logistic regression analysis, and further validated in an independent population of 59 PPE patients. RESULTS: CT scores predicting CPPE were pleural contrast enhancement (3 points), pleural microbubbles, increased extrapleural fat attenuation and fluid volume ≥400 mL (1 point each). A sum score of ≥4 yielded 84% sensitivity (95% CI: 62-85%), 75% specificity (95% CI: 62-85%), 81% diagnostic accuracy (95% CI: 73-86%), likelihood ratio (LR) positive of 3.4 (95% CI: 2.1-5.4), LR negative of 0.22 (95% CI: 0.13-0.36) and area under the receiver operating characteristic curve (AUC) of 0.829 (95% CI: 0.754-0.904) for labelling CPPE in the derivation set. These results were reproduced in the validation sample. The CT grading scale also exhibited a fair ability to identify patients who needed surgery or would die from the pleural infection (AUC: 0.76, 95% CI: 0.61-0.9). CONCLUSION: A novel CT scoring system for adults with PPE may allow clinicians to predict the need for chest tube drainage with good accuracy.
BACKGROUND AND OBJECTIVE: Due to limited data, we aimed to develop and validate a computed tomography (CT)-based scoring system for identifying those parapneumonic effusions (PPEs) requiring drainage. METHODS: A retrospective review of all patients with PPE who underwent thoracentesis and a chest CT scan before any attempt to place a tube thoracostomy, if applicable, over an 8-year period was conducted. Eleven chest CT characteristics were compared between 90 patients with complicated PPEs (CPPEs), defined as those which eventually required chest drainage, and 60 with non-complicated effusions (derivation sample). A scoring system was devised with those CT findings identified as independent predictors of CPPE in a logistic regression analysis, and further validated in an independent population of 59 PPEpatients. RESULTS: CT scores predicting CPPE were pleural contrast enhancement (3 points), pleural microbubbles, increased extrapleural fat attenuation and fluid volume ≥400 mL (1 point each). A sum score of ≥4 yielded 84% sensitivity (95% CI: 62-85%), 75% specificity (95% CI: 62-85%), 81% diagnostic accuracy (95% CI: 73-86%), likelihood ratio (LR) positive of 3.4 (95% CI: 2.1-5.4), LR negative of 0.22 (95% CI: 0.13-0.36) and area under the receiver operating characteristic curve (AUC) of 0.829 (95% CI: 0.754-0.904) for labelling CPPE in the derivation set. These results were reproduced in the validation sample. The CT grading scale also exhibited a fair ability to identify patients who needed surgery or would die from the pleural infection (AUC: 0.76, 95% CI: 0.61-0.9). CONCLUSION: A novel CT scoring system for adults with PPE may allow clinicians to predict the need for chest tube drainage with good accuracy.
Authors: Tamsin N Cargill; Maged Hassan; John P Corcoran; Elinor Harriss; Rachelle Asciak; Rachel M Mercer; David J McCracken; Eihab O Bedawi; Najib M Rahman Journal: Eur Respir J Date: 2019-10-01 Impact factor: 16.671