Literature DB >> 23152436

Dynamic trends in cardiac surgery: why the logistic EuroSCORE is no longer suitable for contemporary cardiac surgery and implications for future risk models.

Graeme L Hickey1, Stuart W Grant, Gavin J Murphy, Moninder Bhabra, Domenico Pagano, Katherine McAllister, Iain Buchan, Ben Bridgewater.   

Abstract

OBJECTIVES: Progressive loss of calibration of the original EuroSCORE models has necessitated the introduction of the EuroSCORE II model. Poor model calibration has important implications for clinical decision-making and risk adjustment of governance analyses. The objective of this study was to explore the reasons for the calibration drift of the logistic EuroSCORE.
METHODS: Data from the Society for Cardiothoracic Surgery in Great Britain and Ireland database were analysed for procedures performed at all National Health Service and some private hospitals in England and Wales between April 2001 and March 2011. The primary outcome was in-hospital mortality. EuroSCORE risk factors, overall model calibration and discrimination were assessed over time.
RESULTS: A total of 317 292 procedures were included. Over the study period, mean age at surgery increased from 64.6 to 67.2 years. The proportion of procedures that were isolated coronary artery bypass grafts decreased from 67.5 to 51.2%. In-hospital mortality fell from 4.1 to 2.8%, but the mean logistic EuroSCORE increased from 5.6 to 7.6%. The logistic EuroSCORE remained a good discriminant throughout the study period (area under the receiver-operating characteristic curve between 0.79 and 0.85), but calibration (observed-to-expected mortality ratio) fell from 0.76 to 0.37. Inadequate adjustment for decreasing baseline risk affected calibration considerably. DISCUSSIONS: Patient risk factors and case-mix in adult cardiac surgery change dynamically over time. Models like the EuroSCORE that are developed using a 'snapshot' of data in time do not account for this and can subsequently lose calibration. It is therefore important to regularly revalidate clinical prediction models.

Entities:  

Keywords:  Cardiac surgery; EuroSCORE; Model expiry; Patient trends; Risk model

Mesh:

Year:  2012        PMID: 23152436      PMCID: PMC3655624          DOI: 10.1093/ejcts/ezs584

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


  18 in total

1.  The comparative assessment and improvement of quality of surgical care in the Department of Veterans Affairs.

Authors:  Shukri F Khuri; Jennifer Daley; William G Henderson
Journal:  Arch Surg       Date:  2002-01

2.  The logistic EuroSCORE.

Authors:  F Roques; P Michel; A R Goldstone; S A M Nashef
Journal:  Eur Heart J       Date:  2003-05       Impact factor: 29.983

3.  Validation of European System for Cardiac Operative Risk Evaluation (EuroSCORE) in North American cardiac surgery.

Authors:  Samer A M Nashef; Francois Roques; Bradley G Hammill; Eric D Peterson; Philippe Michel; Frederick L Grover; Richard K H Wyse; T Bruce Ferguson
Journal:  Eur J Cardiothorac Surg       Date:  2002-07       Impact factor: 4.191

4.  Sampling time error in EuroSCORE II.

Authors:  Michael Poullis; Brian Fabri; Mark Pullan; John Chalmers
Journal:  Interact Cardiovasc Thorac Surg       Date:  2012-02-20

5.  EuroSCORE II.

Authors:  Samer A M Nashef; François Roques; Linda D Sharples; Johan Nilsson; Christopher Smith; Antony R Goldstone; Ulf Lockowandt
Journal:  Eur J Cardiothorac Surg       Date:  2012-02-29       Impact factor: 4.191

6.  Risk stratification in heart surgery: comparison of six score systems.

Authors:  H J Geissler; P Hölzl; S Marohl; F Kuhn-Régnier; U Mehlhorn; M Südkamp; E R de Vivie
Journal:  Eur J Cardiothorac Surg       Date:  2000-04       Impact factor: 4.191

Review 7.  Performance of the original EuroSCORE.

Authors:  Sabrina Siregar; Rolf H H Groenwold; Frederiek de Heer; Michiel L Bots; Yolanda van der Graaf; Lex A van Herwerden
Journal:  Eur J Cardiothorac Surg       Date:  2012-01-26       Impact factor: 4.191

8.  How does EuroSCORE II perform in UK cardiac surgery; an analysis of 23 740 patients from the Society for Cardiothoracic Surgery in Great Britain and Ireland National Database.

Authors:  Stuart William Grant; Graeme Lee Hickey; Ioannis Dimarakis; Uday Trivedi; Alan Bryan; Tom Treasure; Graham Cooper; Domenico Pagano; Iain Buchan; Ben Bridgewater
Journal:  Heart       Date:  2012-08-21       Impact factor: 5.994

9.  Does the choice of risk-adjustment model influence the outcome of surgeon-specific mortality analysis? A retrospective analysis of 14,637 patients under 31 surgeons.

Authors:  S W Grant; A D Grayson; M Jackson; J Au; B M Fabri; G Grotte; M Jones; B Bridgewater
Journal:  Heart       Date:  2007-11-01       Impact factor: 5.994

Review 10.  Systematic review: the evidence that publishing patient care performance data improves quality of care.

Authors:  Constance H Fung; Yee-Wei Lim; Soeren Mattke; Cheryl Damberg; Paul G Shekelle
Journal:  Ann Intern Med       Date:  2008-01-15       Impact factor: 25.391

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  36 in total

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Authors:  Glen P Martin; Matthew Sperrin; Mamas A Mamas
Journal:  J Thorac Dis       Date:  2018-11       Impact factor: 2.895

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Authors:  Kieron C Potger; Darryl McMillan; Mark Ambrose
Journal:  J Extra Corpor Technol       Date:  2013-06

3.  A nonparametric updating method to correct clinical prediction model drift.

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Journal:  J Am Med Inform Assoc       Date:  2019-12-01       Impact factor: 4.497

4.  Calibration Drift Among Regression and Machine Learning Models for Hospital Mortality.

Authors:  Sharon E Davis; Thomas A Lasko; Guanhua Chen; Michael E Matheny
Journal:  AMIA Annu Symp Proc       Date:  2018-04-16

5.  Temporal changes in survival after cardiac surgery are associated with the thirty-day mortality benchmark.

Authors:  Bryan G Maxwell; Jim K Wong; D Craig Miller; Robert L Lobato
Journal:  Health Serv Res       Date:  2014-04-09       Impact factor: 3.402

6.  Predicting 30-Day Hospital Readmission Risk in a National Cohort of Patients with Cirrhosis.

Authors:  Jejo D Koola; Sam B Ho; Aize Cao; Guanhua Chen; Amy M Perkins; Sharon E Davis; Michael E Matheny
Journal:  Dig Dis Sci       Date:  2019-09-17       Impact factor: 3.199

7.  Comparison of Prediction Model Performance Updating Protocols: Using a Data-Driven Testing Procedure to Guide Updating.

Authors:  Sharon E Davis; Robert A Greevy; Thomas A Lasko; Colin G Walsh; Michael E Matheny
Journal:  AMIA Annu Symp Proc       Date:  2020-03-04

8.  [ESC/EACTS guidelines on myocardial revascularization : Amendments 2014].

Authors:  H Nef; M Renker; C W Hamm
Journal:  Herz       Date:  2014-12       Impact factor: 1.443

9.  National Veterans Health Administration inpatient risk stratification models for hospital-acquired acute kidney injury.

Authors:  Robert M Cronin; Jacob P VanHouten; Edward D Siew; Svetlana K Eden; Stephan D Fihn; Christopher D Nielson; Josh F Peterson; Clifton R Baker; T Alp Ikizler; Theodore Speroff; Michael E Matheny
Journal:  J Am Med Inform Assoc       Date:  2015-06-23       Impact factor: 4.497

10.  Incidence and outcomes of sepsis after cardiac surgery as defined by the Sepsis-3 guidelines.

Authors:  S H Howitt; M Herring; I Malagon; C N McCollum; S W Grant
Journal:  Br J Anaesth       Date:  2017-11-24       Impact factor: 9.166

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