Copyright
©The Author(s) 2017. Published by Baishideng Publishing Group Inc. All rights reserved.
Accuracy of gestalt perception of acute chest pain in predicting coronary artery disease
Cláudio Marcelo Bittencourt das Virgens, Laudenor Lemos Jr, Márcia Noya-Rabelo, Manuela Campelo Carvalhal, Antônio Maurício dos Santos Cerqueira Junior, Fernanda Oliveira de Andrade Lopes, Nicole Cruz de Sá, Jéssica Gonzalez Suerdieck, Thiago Menezes Barbosa de Souza, Vitor Calixto de Almeida Correia, Gabriella Sant'Ana Sodré, André Barcelos da Silva, Felipe Kalil Beirão Alexandre, Felipe Rodrigues Marques Ferreira, Luís Cláudio Lemos Correia
Cláudio Marcelo Bittencourt das Virgens, Márcia Noya-Rabelo, Luís Cláudio Lemos Correia, Department of Cardiology, Hospital São Rafael, Salvador, Bahia 41253-190, Brazil
Laudenor Lemos Jr, Department of Cardiology, Hospital Português, Salvador, Bahia 40140-901, Brazil
Manuela Campelo Carvalhal, Antônio Maurício dos Santos Cerqueira Junior, Fernanda Oliveira de Andrade Lopes, Nicole Cruz de Sá, Jéssica Gonzalez Suerdieck, Thiago Menezes Barbosa de Souza, Vitor Calixto de Almeida Correia, André Barcelos da Silva, Felipe Kalil Beirão Alexandre, Felipe Rodrigues Marques Ferreira, Gabriella Sant’Ana Sodré, Bahiana School of Medicine and Public Health, Salvador, Bahia 40290-000, Brazil
Author contributions: das Virgens CMB, Lemos Jr L, Noya-Rabelo M and Correia LCL designed the research; das Virgens CMB, Lemos Jr L, Carvalhal MC, Cerqueira Junior AMS, Lopes FOA, Suerdieck JG, de Souza TMB, Correia VCA, de Sá NC, Sodré GS, da Silva AB, Alexandre FKB and Ferreira FRM performed the research; Correia LCL analyzed the data; das Virgens CMB and Correia LCL drafted the article; all authors made critical revisions and gave final approval of the version of the article to be published.
Institutional review board statement: The study was reviewed and approved by the Monte Tabor/São Rafael Hospital Institutional Review Board, on 07/25/2011, No. 036/2011.
Informed consent statement: All study participants, or their legal guardian, provided informed written consent prior to study enrollment. All details that might disclose the identity of the subjects under study were omitted or anonymized.
Conflict-of-interest statement: The authors declare that they have no conflict of interest.
Data sharing statement: Technical details and statistical methods are available with the corresponding author at luisclcorreia@gmail.com. Participants gave informed consent for data sharing.
Open-Access: This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Correspondence to: Luís Cláudio Lemos Correia, MD, PhD, Research Coordinator of Hospital São Rafael, Associate Professor of Bahiana School of Medicine and Public Health, Department of Cardiology, Hospital São Rafael, Av. Princesa Leopoldina 19/402, Salvador, Bahia 41253-190, Brazil.
luisclcorreia@gmail.com
Telephone: +55-71-999711032
Received: September 14, 2016
Peer-review started: September 18, 2016
First decision: November 14, 2016
Revised: December 15, 2016
Accepted: January 2, 2017
Article in press: January 3, 2017
Published online: March 26, 2017
Processing time: 193 Days and 8.4 Hours
AIM
To test accuracy and reproducibility of gestalt to predict obstructive coronary artery disease (CAD) in patients with acute chest pain.
METHODS
We studied individuals who were consecutively admitted to our Chest Pain Unit. At admission, investigators performed a standardized interview and recorded 14 chest pain features. Based on these features, a cardiologist who was blind to other clinical characteristics made unstructured judgment of CAD probability, both numerically and categorically. As the reference standard for testing the accuracy of gestalt, angiography was required to rule-in CAD, while either angiography or non-invasive test could be used to rule-out. In order to assess reproducibility, a second cardiologist did the same procedure.
RESULTS
In a sample of 330 patients, the prevalence of obstructive CAD was 48%. Gestalt’s numerical probability was associated with CAD, but the area under the curve of 0.61 (95%CI: 0.55-0.67) indicated low level of accuracy. Accordingly, categorical definition of typical chest pain had a sensitivity of 48% (95%CI: 40%-55%) and specificity of 66% (95%CI: 59%-73%), yielding a negligible positive likelihood ratio of 1.4 (95%CI: 0.65-2.0) and negative likelihood ratio of 0.79 (95%CI: 0.62-1.02). Agreement between the two cardiologists was poor in the numerical classification (95% limits of agreement = -71% to 51%) and categorical definition of typical pain (Kappa = 0.29; 95%CI: 0.21-0.37).
CONCLUSION
Clinical judgment based on a combination of chest pain features is neither accurate nor reproducible in predicting obstructive CAD in the acute setting.
Core tip: In the scenario of acute chest pain, individual features of chest pain presentation are intuitively combined to form physician’s impression, by a process called “gestalt”. Physicians commonly assess probability of disease by unstructured clinical judgment. Although commonly used and presumed to be accurate, diagnostic assessment by gestalt of acute chest pain lacks validation. In the present manuscript, we investigated the accuracy of gestalt in the prediction of coronary artery disease (CAD). Our results indicate that clinical judgment (gestalt) of acute chest pain characteristics has low diagnostic accuracy for obstructive CAD. Thus, physicians should be cautious when relying on chest pain characteristics and investigators should redirect their focus to identify validated predictors.
