Marcus Taylor1, Syed F Hashmi1, Glen P Martin2, Michael Shackcloth3, Rajesh Shah1, Richard Booton4, Stuart W Grant5. 1. Department of Cardiothoracic Surgery, Wythenshawe Hospital, Manchester University Hospital Foundation Trust, Manchester, UK. 2. Division of Informatics, Imaging and Data Science, Faculty of Biology, Medicine and Health, Manchester Academic Heath Science Centre, University of Manchester, Manchester, UK. 3. Department of Cardiothoracic Surgery, Liverpool Heart and Chest Hospital, Liverpool, UK. 4. Department of Respiratory Medicine, Wythenshawe Hospital, Manchester University Hospital Foundation Trust, Manchester, UK. 5. Division of Cardiovascular Sciences, University of Manchester, ERC, Manchester University Hospitals Foundation Trust, Manchester, UK.
Abstract
OBJECTIVES: Guidelines advocate that patients being considered for thoracic surgery should undergo a comprehensive preoperative risk assessment. Multiple risk prediction models to estimate the risk of mortality after thoracic surgery have been developed, but their quality and performance has not been reviewed in a systematic way. The objective was to systematically review these models and critically appraise their performance. METHODS: The Cochrane Library and the MEDLINE database were searched for articles published between 1990 and 2019. Studies that developed or validated a model predicting perioperative mortality after thoracic surgery were included. Data were extracted based on the checklist for critical appraisal and data extraction for systematic reviews of prediction modelling studies. RESULTS: A total of 31 studies describing 22 different risk prediction models were identified. There were 20 models developed specifically for thoracic surgery with two developed in other surgical specialties. A total of 57 different predictors were included across the identified models. Age, sex and pneumonectomy were the most frequently included predictors in 19, 13 and 11 models, respectively. Model performance based on either discrimination or calibration was inadequate for all externally validated models. The most recent data included in validation studies were from 2018. Risk of bias (assessed using Prediction model Risk Of Bias ASsessment Tool) was high for all except two models. CONCLUSIONS: Despite multiple risk prediction models being developed to predict perioperative mortality after thoracic surgery, none could be described as appropriate for contemporary thoracic surgery. Contemporary validation of available models or new model development is required to ensure that appropriate estimates of operative risk are available for contemporary thoracic surgical practice.
OBJECTIVES: Guidelines advocate that patients being considered for thoracic surgery should undergo a comprehensive preoperative risk assessment. Multiple risk prediction models to estimate the risk of mortality after thoracic surgery have been developed, but their quality and performance has not been reviewed in a systematic way. The objective was to systematically review these models and critically appraise their performance. METHODS: The Cochrane Library and the MEDLINE database were searched for articles published between 1990 and 2019. Studies that developed or validated a model predicting perioperative mortality after thoracic surgery were included. Data were extracted based on the checklist for critical appraisal and data extraction for systematic reviews of prediction modelling studies. RESULTS: A total of 31 studies describing 22 different risk prediction models were identified. There were 20 models developed specifically for thoracic surgery with two developed in other surgical specialties. A total of 57 different predictors were included across the identified models. Age, sex and pneumonectomy were the most frequently included predictors in 19, 13 and 11 models, respectively. Model performance based on either discrimination or calibration was inadequate for all externally validated models. The most recent data included in validation studies were from 2018. Risk of bias (assessed using Prediction model Risk Of Bias ASsessment Tool) was high for all except two models. CONCLUSIONS: Despite multiple risk prediction models being developed to predict perioperative mortality after thoracic surgery, none could be described as appropriate for contemporary thoracic surgery. Contemporary validation of available models or new model development is required to ensure that appropriate estimates of operative risk are available for contemporary thoracic surgical practice.
Authors: Eric Lim; David Baldwin; Michael Beckles; John Duffy; James Entwisle; Corinne Faivre-Finn; Keith Kerr; Alistair Macfie; Jim McGuigan; Simon Padley; Sanjay Popat; Nicholas Screaton; Michael Snee; David Waller; Chris Warburton; Thida Win Journal: Thorax Date: 2010-10 Impact factor: 9.139
Authors: Syed S A Qadri; Martin Jarvis; Priyadharshanan Ariyaratnam; Mubarak A Chaudhry; Alex R J Cale; Steven Griffin; Michael E Cowen; Mahmoud Loubani Journal: Eur J Cardiothorac Surg Date: 2013-11-07 Impact factor: 4.191
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