The Society of Thoracic Surgeons Adult Cardiac Surgery Database: 2017 Update on Research

Thourani, Vinod H.; Badhwar, Vinay; Shahian, David M.; Edwards, Fred H.; O’Brien, Sean M.; Habib, Robert H.; Kelly, John; Rankin, J. Scott; Prager, Richard L.; Jacobs, Jeffrey P.

doi:10.1016/j.athoracsur.2017.05.013

Cited by 17 publications

(8 citation statements)

References 20 publications

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“…Summaries of research based on each of the three STS National Databases were published in 2016 [8,10,12] and 2017 [20,21,23]. The STS has three mechanisms by which investigators at institutions participating in the STS National Database may propose and make operational a research project using data from the STS National Database.…”

Section: The Sts National Database: Researchmentioning

confidence: 99%

The Society of Thoracic Surgeons National Database 2017 Annual Report

Jacobs

Shahian

D’Agostino

et al. 2017

The Annals of Thoracic Surgery

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The Society of Thoracic Surgeons (STS) National Database has three major component databases: the STS Adult Cardiac Surgery Database (ACSD), the STS Congenital Heart Surgery Database (CHSD), and the STS General Thoracic Surgery Database (GTSD). Beginning in January 2016, The Annals of Thoracic Surgery began publishing a monthly series of scholarly articles on outcomes analysis, quality improvement, and patient safety. This article summarizes the status of the STS National Database as of October 2017 and summarizes the articles about the STS National Database that appeared in The Annals of Thoracic Surgery 2017 series "Outcomes Analysis, Quality Improvement, and Patient Safety."

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Section: The Sts National Database: Researchmentioning

confidence: 99%

The Society of Thoracic Surgeons National Database 2017 Annual Report

Jacobs

Shahian

D’Agostino

et al. 2017

The Annals of Thoracic Surgery

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“…The most commonly used surgical risk scores for cardiac surgery are the European System for Cardiac Operative Risk Evaluation (EuroSCORE II), from ESC/EACTS, the SYNTAX score, also from ESC/EACTS, and the American STS score. The STS score started to be produced in 1989 and is validated through the analysis of 6,3 millions of cardiac surgical procedures [12] .…”

Section: Guidelines Database and Surgical Riskmentioning

confidence: 99%

Reflections on the Cardiac Surgery Practiced in the1970s when Compared with the Current Practice

Murad¹

2019

Braz J Cardiovasc Surg

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“…The guidelines for the management of valvular heart disease recommend that risk prediction models be developed to assess personalized risk for patients undergoing valvular surgery (4,5). To this aim, several risk prediction models have been developed to assess the risk of death in patients after valve surgery (6)(7)(8). Traditional risk scores have been developed and validated in surgical populations, primarily for patients undergoing coronary artery bypass grafting.…”

Section: Introductionmentioning

confidence: 99%

Machine Learning-Based Personalized Risk Prediction Model for Mortality of Patients Undergoing Mitral Valve Surgery: The PRIME Score

Zhou

et al. 2022

Front. Cardiovasc. Med.

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BackgroundMitral valve surgery (MVS) is an effective treatment for mitral valve diseases. There is a lack of reliable personalized risk prediction models for mortality in patients undergoing mitral valve surgery. Our aim was to develop a risk stratification system to predict all-cause mortality in patients after mitral valve surgery.MethodsDifferent machine learning models for the prediction of all-cause mortality were trained on a derivation cohort of 1,883 patients undergoing mitral valve surgery [split into a training cohort (70%) and internal validation cohort (30%)] to predict all-cause mortality. Forty-five clinical variables routinely evaluated at discharge were used to train the models. The best performance model (PRIME score) was tested in an externally validated cohort of 220 patients undergoing mitral valve surgery. The model performance was evaluated according to the area under the curve (AUC). Net reclassification improvement (NRI) and integrated discrimination improvement (IDI) were compared with existing risk strategies.ResultsAfter a median follow-up of 2 years, there were 133 (7.063%) deaths in the derivation cohort and 17 (7.727%) deaths in the validation cohort. The PRIME score showed an AUC of 0.902 (95% confidence interval [CI], 0.849–0.956) in the internal validation cohort and 0.873 (95% CI: 0.769–0.977) in the external validation cohort. In the external validation cohort, the performance of the PRIME score was significantly improved compared with that of the existing EuroSCORE II (NRI = 0.550, [95% CI 0.001–1.099], P = 0.049, IDI = 0.485, [95% CI 0.230–0.741], P < 0.001).ConclusionMachine learning-based model (the PRIME score) that integrate clinical, demographic, imaging, and laboratory features demonstrated superior performance for the prediction of mortality patients after mitral valve surgery compared with the traditional risk model EuroSCORE II.Clinical Trial Registration[http://www.clinicaltrials.gov], identifier [NCT05141292].

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The Society of Thoracic Surgeons Adult Cardiac Surgery Database: 2017 Update on Research

Cited by 17 publications

References 20 publications

The Society of Thoracic Surgeons National Database 2017 Annual Report

The Society of Thoracic Surgeons National Database 2017 Annual Report

Reflections on the Cardiac Surgery Practiced in the1970s when Compared with the Current Practice

Machine Learning-Based Personalized Risk Prediction Model for Mortality of Patients Undergoing Mitral Valve Surgery: The PRIME Score

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