| Title |
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
|
|---|---|
| Published in |
European Radiology, March 2018
|
| DOI | 10.1007/s00330-018-5322-5 |
| Pubmed ID | |
| Authors |
Robert Roehle, Viktoria Wieske, Georg M. Schuetz, Pascal Gueret, Daniele Andreini, Willem Bob Meijboom, Gianluca Pontone, Mario Garcia, Hatem Alkadhi, Lily Honoris, Jörg Hausleiter, Nuno Bettencourt, Elke Zimmermann, Sebastian Leschka, Bernhard Gerber, Carlos Rochitte, U. Joseph Schoepf, Abbas Arjmand Shabestari, Bjarne Nørgaard, Akira Sato, Juhani Knuuti, Matthijs F. L. Meijs, Harald Brodoefel, Shona M. M. Jenkins, Kristian Altern Øvrehus, Axel Cosmus Pyndt Diederichsen, Ashraf Hamdan, Bjørn Arild Halvorsen, Vladimir Mendoza Rodriguez, Yung Liang Wan, Johannes Rixe, Mehraj Sheikh, Christoph Langer, Said Ghostine, Eugenio Martuscelli, Hiroyuki Niinuma, Arthur Scholte, Konstantin Nikolaou, Geir Ulimoen, Zhaoqi Zhang, Hans Mickley, Koen Nieman, Philipp A. Kaufmann, Ronny Ralf Buechel, Bernhard A. Herzog, Melvin Clouse, David A. Halon, Jonathan Leipsic, David Bush, Reda Jakamy, Kai Sun, Lin Yang, Thorsten Johnson, Jean-Pierre Laissy, Roy Marcus, Simone Muraglia, Jean-Claude Tardif, Benjamin Chow, Narinder Paul, David Maintz, John Hoe, Albert de Roos, Robert Haase, Michael Laule, Peter Schlattmann, Marc Dewey |
| Abstract |
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. 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). 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. 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. • 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. |
X Demographics
The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Austria | 1 | 20% |
| Germany | 1 | 20% |
| Unknown | 3 | 60% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 60% |
| Practitioners (doctors, other healthcare professionals) | 1 | 20% |
| Science communicators (journalists, bloggers, editors) | 1 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 41 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 41 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Other | 5 | 12% |
| Professor > Associate Professor | 4 | 10% |
| Student > Bachelor | 4 | 10% |
| Student > Master | 3 | 7% |
| Professor | 3 | 7% |
| Other | 9 | 22% |
| Unknown | 13 | 32% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 13 | 32% |
| Computer Science | 4 | 10% |
| Biochemistry, Genetics and Molecular Biology | 2 | 5% |
| Business, Management and Accounting | 2 | 5% |
| Nursing and Health Professions | 2 | 5% |
| Other | 3 | 7% |
| Unknown | 15 | 37% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 05 January 2023.
All research outputs
#8,348,011
of 25,117,541 outputs
Outputs from European Radiology
#1,326
of 4,869 outputs
Outputs of similar age
#135,243
of 338,047 outputs
Outputs of similar age from European Radiology
#31
of 82 outputs
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