Literature DB >> 29309570

Risk-adjusted performance evaluation in three academic thoracic surgery units using the Eurolung risk models.

Cecilia Pompili1, Yaron Shargall2, Herbert Decaluwe3, Johnny Moons3, Madhu Chari2, Alessandro Brunelli4.   

Abstract

OBJECTIVES: The objective of this study was to evaluate the performance of 3 thoracic surgery centres using the Eurolung risk models for morbidity and mortality.
METHODS: This was a retrospective analysis performed on data collected from 3 academic centres (2014-2016). Seven hundred and twenty-one patients in Centre 1, 857 patients in Centre 2 and 433 patients in Centre 3 who underwent anatomical lung resections were analysed. The Eurolung1 and Eurolung2 models were used to predict risk-adjusted cardiopulmonary morbidity and 30-day mortality rates. Observed and risk-adjusted outcomes were compared within each centre.
RESULTS: The observed morbidity of Centre 1 was in line with the predicted morbidity (observed 21.1% vs predicted 22.7%, P = 0.31). Centre 2 performed better than expected (observed morbidity 20.2% vs predicted 26.7%, P < 0.001), whereas the observed morbidity of Centre 3 was higher than the predicted morbidity (observed 41.1% vs predicted 24.3%, P < 0.001). Centre 1 had higher observed mortality when compared with the predicted mortality (3.6% vs 2.1%, P = 0.005), whereas Centre 2 had an observed mortality rate significantly lower than the predicted mortality rate (1.2% vs 2.5%, P = 0.013). Centre 3 had an observed mortality rate in line with the predicted mortality rate (observed 1.4% vs predicted 2.4%, P = 0.17). The observed mortality rates in the patients with major complications were 30.8% in Centre 1 (versus predicted mortality rate 3.8%, P < 0.001), 8.2% in Centre 2 (versus predicted mortality rate 4.1%, P = 0.030) and 9.0% in Centre 3 (versus predicted mortality rate 3.5%, P = 0.014).
CONCLUSIONS: The Eurolung models were successfully used as risk-adjusting instruments to internally audit the outcomes of 3 different centres, showing their applicability for future quality improvement initiatives.

Entities:  

Mesh:

Year:  2018        PMID: 29309570     DOI: 10.1093/ejcts/ezx483

Source DB:  PubMed          Journal:  Eur J Cardiothorac Surg        ISSN: 1010-7940            Impact factor:   4.191


  3 in total

1.  A systematic review of risk prediction models for perioperative mortality after thoracic surgery.

Authors:  Marcus Taylor; Syed F Hashmi; Glen P Martin; Michael Shackcloth; Rajesh Shah; Richard Booton; Stuart W Grant
Journal:  Interact Cardiovasc Thorac Surg       Date:  2021-04-08

2.  External validation of five predictive models for postoperative cardiopulmonary morbidity in a Chinese population receiving lung resection.

Authors:  Guanghua Huang; Lei Liu; Luyi Wang; Zhile Wang; Zhaojian Wang; Shanqing Li
Journal:  PeerJ       Date:  2022-02-09       Impact factor: 2.984

3.  Prediction of postoperative cardiopulmonary complications after lung resection in a Chinese population: A machine learning-based study.

Authors:  Guanghua Huang; Lei Liu; Luyi Wang; Shanqing Li
Journal:  Front Oncol       Date:  2022-09-23       Impact factor: 5.738

  3 in total

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