The Society of Thoracic Surgeons 2018 Adult Cardiac Surgery Risk Models: Part 2 - Statistical Methods and Results.

MedStar author(s):
Citation: Annals of Thoracic Surgery. 105(5):1419-1428, 2018 05.PMID: 29577924Institution: MedStar Heart & Vascular InstituteForm of publication: Journal ArticleMedline article type(s): Journal ArticleSubject headings: *Cardiac Surgical Procedures/ae [Adverse Effects] | *Models, Statistical | *Postoperative Complications/et [Etiology] | *Risk Assessment | Adult | Databases, Factual | Humans | Societies, Medical | Thoracic SurgeryYear: 2018Local holdings: Available online from MWHC library: 1995 - present, Available in print through MWHC library:1999-2007ISSN:
  • 0003-4975
Name of journal: The Annals of thoracic surgeryAbstract: BACKGROUND: The Society of Thoracic Surgeons (STS) uses statistical models to create risk-adjusted performance metrics for Adult Cardiac Surgery Database (ACSD) participants. Because of temporal changes in patient characteristics and outcomes, evolution of surgical practice, and additional risk factors available in recent ACSD versions, completely new risk models have been developed.CONCLUSIONS: New STS ACSD risk models have generally excellent calibration and discrimination and are well suited for risk adjustment of STS performance metrics.Copyright (c) 2018. Published by Elsevier Inc.METHODS: Using July 2011 to June 2014 ACSD data, risk models were developed for operative mortality, stroke, renal failure, prolonged ventilation, mediastinitis /deep sternal wound infection (DSWI), reoperation, major morbidity or mortality composite, and prolonged postoperative length of stay (PLOS) or short PLOS among patients who underwent isolated coronary artery bypass grafting (CABG; n = 439,092), aortic or mitral valve surgery (n = 150,150), or combined valve + CABG (n = 81,588). Separate models were developed for each procedure and endpoint except DSWI, which was analyzed in a combined model because of its infrequency. A surgeon panel selected predictors by assessing model performance and clinical face validity of full and progressively more parsimonious models. ACSD data (July 2014 to December 2016) were used to assess model calibration and to compare discrimination with previous STS risk models.RESULTS: Calibration in the validation sample was excellent for all models except DSWI which slightly under-estimated risk and will be recalibrated in feedback reports. C-indices of new models exceeded those of the last published STS models for all populations and endpoints except stroke in valve patients.All authors: Badhwar V, Cleveland JC Jr., D'Agostino RS, Desai ND, Edgerton JR, Edwards FH, Feng L, Furnary AP, He X, Jacobs JP, Kurlansky PA, Lobdell KW, O'Brien SM, Rankin JS, Shahian DM, Thourani VH, Vassileva C, Wyler von Ballmoos MC, Xian YFiscal year: FY2018Digital Object Identifier: Date added to catalog: 2018-04-20
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Item type Current library Collection Call number Status Date due Barcode
Journal Article MedStar Authors Catalog Article 29577924 Available 29577924

Available online from MWHC library: 1995 - present, Available in print through MWHC library:1999-2007

BACKGROUND: The Society of Thoracic Surgeons (STS) uses statistical models to create risk-adjusted performance metrics for Adult Cardiac Surgery Database (ACSD) participants. Because of temporal changes in patient characteristics and outcomes, evolution of surgical practice, and additional risk factors available in recent ACSD versions, completely new risk models have been developed.

CONCLUSIONS: New STS ACSD risk models have generally excellent calibration and discrimination and are well suited for risk adjustment of STS performance metrics.

Copyright (c) 2018. Published by Elsevier Inc.

METHODS: Using July 2011 to June 2014 ACSD data, risk models were developed for operative mortality, stroke, renal failure, prolonged ventilation, mediastinitis /deep sternal wound infection (DSWI), reoperation, major morbidity or mortality composite, and prolonged postoperative length of stay (PLOS) or short PLOS among patients who underwent isolated coronary artery bypass grafting (CABG; n = 439,092), aortic or mitral valve surgery (n = 150,150), or combined valve + CABG (n = 81,588). Separate models were developed for each procedure and endpoint except DSWI, which was analyzed in a combined model because of its infrequency. A surgeon panel selected predictors by assessing model performance and clinical face validity of full and progressively more parsimonious models. ACSD data (July 2014 to December 2016) were used to assess model calibration and to compare discrimination with previous STS risk models.

RESULTS: Calibration in the validation sample was excellent for all models except DSWI which slightly under-estimated risk and will be recalibrated in feedback reports. C-indices of new models exceeded those of the last published STS models for all populations and endpoints except stroke in valve patients.

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