Literature DB >> 29556770

Applicability and accuracy of pretest probability calculations implemented in the NICE clinical guideline for decision making about imaging in patients with chest pain of recent onset.

Robert Roehle1, Viktoria Wieske1, Georg M Schuetz1, Pascal Gueret2, Daniele Andreini3,4, Willem Bob Meijboom5, Gianluca Pontone3, Mario Garcia6, Hatem Alkadhi7, Lily Honoris8, Jörg Hausleiter9, Nuno Bettencourt10, Elke Zimmermann1, Sebastian Leschka11, Bernhard Gerber12, Carlos Rochitte13, U Joseph Schoepf14, Abbas Arjmand Shabestari15, Bjarne Nørgaard16, Akira Sato17, Juhani Knuuti18, Matthijs F L Meijs19, Harald Brodoefel20, Shona M M Jenkins21, Kristian Altern Øvrehus22,23, Axel Cosmus Pyndt Diederichsen22, Ashraf Hamdan24,25, Bjørn Arild Halvorsen26, Vladimir Mendoza Rodriguez27, Yung Liang Wan28,29, Johannes Rixe30, Mehraj Sheikh31,32, Christoph Langer33,34, Said Ghostine35, Eugenio Martuscelli36, Hiroyuki Niinuma37, Arthur Scholte38, Konstantin Nikolaou39, Geir Ulimoen40, Zhaoqi Zhang41, Hans Mickley22, Koen Nieman42,43, Philipp A Kaufmann44, Ronny Ralf Buechel44, Bernhard A Herzog44, Melvin Clouse45, David A Halon46,47, Jonathan Leipsic48, David Bush49,50, Reda Jakamy51, Kai Sun52, Lin Yang41, Thorsten Johnson53, Jean-Pierre Laissy54, Roy Marcus55, Simone Muraglia56, Jean-Claude Tardif57, Benjamin Chow58, Narinder Paul59,60, David Maintz61, John Hoe62, Albert de Roos63, Robert Haase1, Michael Laule64, Peter Schlattmann65, Marc Dewey66.   

Abstract

OBJECTIVES: To analyse the implementation, applicability and accuracy of the pretest probability calculation provided by NICE clinical guideline 95 for decision making about imaging in patients with chest pain of recent onset.
METHODS: The definitions for pretest probability calculation in the original Duke clinical score and the NICE guideline were compared. We also calculated the agreement and disagreement in pretest probability and the resulting imaging and management groups based on individual patient data from the Collaborative Meta-Analysis of Cardiac CT (CoMe-CCT).
RESULTS: 4,673 individual patient data from the CoMe-CCT Consortium were analysed. Major differences in definitions in the Duke clinical score and NICE guideline were found for the predictors age and number of risk factors. Pretest probability calculation using guideline criteria was only possible for 30.8 % (1,439/4,673) of patients despite availability of all required data due to ambiguity in guideline definitions for risk factors and age groups. Agreement regarding patient management groups was found in only 70 % (366/523) of patients in whom pretest probability calculation was possible according to both models.
CONCLUSIONS: Our results suggest that pretest probability calculation for clinical decision making about cardiac imaging as implemented in the NICE clinical guideline for patients has relevant limitations. KEY POINTS: • Duke clinical score is not implemented correctly in NICE guideline 95. • Pretest probability assessment in NICE guideline 95 is impossible for most patients. • Improved clinical decision making requires accurate pretest probability calculation. • These refinements are essential for appropriate use of cardiac CT.

Entities:  

Keywords:  Coronary artery disease; Duke clinical score; Multidetector computed tomography; NICE clinical guideline; Pretest probability

Mesh:

Year:  2018        PMID: 29556770     DOI: 10.1007/s00330-018-5322-5

Source DB:  PubMed          Journal:  Eur Radiol        ISSN: 0938-7994            Impact factor:   5.315


  24 in total

1.  Percutaneous coronary interventions in Europe in 2006.

Authors:  Aris Moschovitis; Stéphane Cook; Bernhard Meier
Journal:  EuroIntervention       Date:  2010-06       Impact factor: 6.534

2.  Strict application of NICE Clinical Guideline 95 'chest pain of recent onset' leads to over 90% increase in cost of investigation.

Authors:  Toby Rogers; Rory Dowd; Hsiu Lye Yap; Simon Claridge; Khaled Al Fakih; Jonathan Byrne
Journal:  Int J Cardiol       Date:  2012-10-13       Impact factor: 4.164

3.  A clinical prediction rule for the diagnosis of coronary artery disease: validation, updating, and extension.

Authors:  Tessa S S Genders; Ewout W Steyerberg; Hatem Alkadhi; Sebastian Leschka; Lotus Desbiolles; Koen Nieman; Tjebbe W Galema; W Bob Meijboom; Nico R Mollet; Pim J de Feyter; Filippo Cademartiri; Erica Maffei; Marc Dewey; Elke Zimmermann; Michael Laule; Francesca Pugliese; Rossella Barbagallo; Valentin Sinitsyn; Jan Bogaert; Kaatje Goetschalckx; U Joseph Schoepf; Garrett W Rowe; Joanne D Schuijf; Jeroen J Bax; Fleur R de Graaf; Juhani Knuuti; Sami Kajander; Carlos A G van Mieghem; Matthijs F L Meijs; Maarten J Cramer; Deepa Gopalan; Gudrun Feuchtner; Guy Friedrich; Gabriel P Krestin; M G Myriam Hunink
Journal:  Eur Heart J       Date:  2011-03-02       Impact factor: 29.983

4.  The effect of applying NICE guidelines for the investigation of stable chest pain on out-patient cardiac services in the UK.

Authors:  C Patterson; E Nicol; L Bryan; T Woodcock; J Collinson; S Padley; D Bell
Journal:  QJM       Date:  2011-02-11

5.  Diagnostic accuracy of 64-slice computed tomography coronary angiography: a prospective, multicenter, multivendor study.

Authors:  W Bob Meijboom; Matthijs F L Meijs; Joanne D Schuijf; Maarten J Cramer; Nico R Mollet; Carlos A G van Mieghem; Koen Nieman; Jacob M van Werkhoven; Gabija Pundziute; Annick C Weustink; Alexander M de Vos; Francesca Pugliese; Benno Rensing; J Wouter Jukema; Jeroen J Bax; Mathias Prokop; Pieter A Doevendans; Myriam G M Hunink; Gabriel P Krestin; Pim J de Feyter
Journal:  J Am Coll Cardiol       Date:  2008-12-16       Impact factor: 24.094

6.  Estimating the likelihood of significant coronary artery disease.

Authors:  D B Pryor; F E Harrell; K L Lee; R M Califf; R A Rosati
Journal:  Am J Med       Date:  1983-11       Impact factor: 4.965

7.  Clinical outcomes when applying NICE guidance for the investigation of recent-onset chest pain to a rapid-access chest pain clinic population.

Authors:  Caroline Marie Patterson; Arjun Nair; Nabeel Ahmed; Leoni Bryan; Derek Bell; Edward David Nicol
Journal:  Heart       Date:  2014-09-12       Impact factor: 5.994

8.  Value of the history and physical in identifying patients at increased risk for coronary artery disease.

Authors:  D B Pryor; L Shaw; C B McCants; K L Lee; D B Mark; F E Harrell; L H Muhlbaier; R M Califf
Journal:  Ann Intern Med       Date:  1993-01-15       Impact factor: 25.391

9.  Prevalence and predictors of nonobstructive coronary artery disease identified with coronary angiography in contemporary clinical practice.

Authors:  Manesh R Patel; David Dai; Adrian F Hernandez; Pamela S Douglas; John Messenger; Kirk N Garratt; Thomas M Maddox; Eric D Peterson; Matthew T Roe
Journal:  Am Heart J       Date:  2014-03-14       Impact factor: 4.749

10.  Individual patient data meta-analysis for the clinical assessment of coronary computed tomography angiography: protocol of the Collaborative Meta-Analysis of Cardiac CT (CoMe-CCT).

Authors:  Georg M Schuetz; Peter Schlattmann; Stephan Achenbach; Matthew Budoff; Mario J Garcia; Robert Roehle; Gianluca Pontone; Willem Bob Meijboom; Daniele Andreini; Hatem Alkadhi; Lily Honoris; Nuno Bettencourt; Jörg Hausleiter; Sebastian Leschka; Bernhard L Gerber; Matthijs Fl Meijs; Abbas Arjmand Shabestari; Akira Sato; Elke Zimmermann; Uwe J Schoepf; Axel Diederichsen; David A Halon; Vladimir Mendoza-Rodriguez; Ashraf Hamdan; Bjarne L Nørgaard; Harald Brodoefel; Kristian A Ovrehus; Shona Mm Jenkins; Bjørn A Halvorsen; Johannes Rixe; Mehraj Sheikh; Christoph Langer; Eugenio Martuscelli; Andrea Romagnoli; Arthur Jha Scholte; Roy P Marcus; Geir R Ulimoen; Koen Nieman; Hans Mickley; Konstantin Nikolaou; Jean-Claude Tardif; Thorsten Rc Johnson; Simone Muraglia; Benjamin Jw Chow; David Maintz; Michael Laule; Marc Dewey
Journal:  Syst Rev       Date:  2013-02-15
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