Literature DB >> 29425674

Predictive Variables for Failure in Administration of Intrapleural Tissue Plasminogen Activator/Deoxyribonuclease in Patients With Complicated Parapneumonic Effusions/Empyema.

Danai Khemasuwan1, Jeffrey Sorensen2, David C Griffin3.   

Abstract

BACKGROUND: Combined intrapleural therapy with tissue plasminogen activator (tPA) and deoxyribonuclease (DNase) has been shown to reduce the need for surgical intervention for complicated pleural effusion/empyema (CPE/empyema). For patients in whom tPA/DNase is likely to fail, however, receipt of this therapy may simply delay the inevitable. The goal of this study was to identify risk factors for failure of combined intrapleural therapy.
METHODS: We performed a retrospective chart review of patients who received intrapleural tPA/DNase for the treatment of CPE/empyema. Clinical variables included demographic data, radiographic parameters at time of diagnosis, and results from pleural fluid analysis. We used gradient boosted trees-an ensemble machine learning technique, with hyperparameter tuning to mitigate overfitting-to rank the importance of 19 candidate clinical variables with respect to their ability to predict failure of tPA/DNase therapy.
RESULTS: We identified 84 patients who received intrapleural tPA/DNase for the treatment of complicated pleural effusions/empyema over a 5-year period. Resolution of CPE/empyema with intrapleural tPA/DNase was achieved in two-thirds of the patients (n = 57). Of the 19 candidate predictors of tPA/DNase failure, the presence of pleural thickening was found to be the most important (48% relative importance), followed by the presence of an abscess or necrotizing pneumonia (24%), the pleural protein level (6%), and the presence of loculated effusion (4%).
CONCLUSIONS: Our analysis found that the presence of pleural thickening and the presence of an abscess/necrotizing pneumonia helps to triage patients in whom combined intrapleural therapy is likely to fail. The results warrant further study and validation in a prospective multicenter study.
Copyright © 2018 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  combined intrapleural therapy; complicated pleural effusion; predictive model

Mesh:

Substances:

Year:  2018        PMID: 29425674     DOI: 10.1016/j.chest.2018.01.037

Source DB:  PubMed          Journal:  Chest        ISSN: 0012-3692            Impact factor:   9.410


  6 in total

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Review 6.  Artificial intelligence in pulmonary medicine: computer vision, predictive model and COVID-19.

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