The Value of Chest Pain during the Exercise Tolerance Test in Predicting Coronary Artery Disease

Cardiology ◽  
1992 ◽  
Vol 81 (2-3) ◽  
pp. 164-171 ◽  
Author(s):  
Mark T. Richardson ◽  
Robert G. Holly ◽  
Ezra A. Amsterdam ◽  
Michael F. Miller
Keyword(s):  
Coronary Artery Disease ◽  
Chest Pain ◽  
Coronary Artery ◽  
Exercise Tolerance ◽  
Tolerance Test ◽  
Exercise Tolerance Test ◽  
Artery Disease

scholarly journals Accuracy of exercise tolerance test in the diagnosis of coronary artery disease in patients with left dominant coronary circulation

2017 ◽  
Vol 69 (5) ◽  
pp. 624-627 ◽  
Author(s):  
Armin Attar ◽  
Arman Mehrzadeh ◽  
Mohsen Foulad ◽  
Davar Aldavood ◽  
Mohammad Amin Fallahzadeh ◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Exercise Tolerance ◽  
Coronary Circulation ◽  
Tolerance Test ◽  
Exercise Tolerance Test ◽  
Artery Disease

scholarly journals Novel Scoring System for Prediction of Cardiac Syndrome X in Women with Typical Angina and a Positive Exercise Tolerance Test

2018 ◽  
Vol 45 (1) ◽  
pp. 5-10 ◽  
Author(s):  
Farzad Masoudkabir ◽  
Ali Vasheghani-Farahani ◽  
Elham Hakki ◽  
Hamidreza Poorhosseini ◽  
Saeed Sadeghian ◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Scoring System ◽  
Degrees Of Freedom ◽  
Obstructive Coronary Artery Disease ◽  
Area Under The Curve ◽  
Tolerance Test ◽  
Exercise Tolerance Test ◽  
Cardiac Syndrome ◽  
Artery Disease

A major diagnostic challenge for cardiologists is to distinguish cardiac syndrome X (CSX) from obstructive coronary artery disease in women with typical angina and a positive exercise tolerance test (ETT). We performed this study to develop a scoring system that more accurately predicts CSX in this patient population. Data on 976 women with typical angina and a positive ETT who underwent coronary angiography at our center were randomly divided into derivation and validation datasets. We developed a backward stepwise logistic regression model that predicted the presence of CSX, and a scoring system was derived from it. The derivation dataset (809 patients) was calibrated by uing a Hosmer-Lemeshow goodness-of-fit test (8 degrees of freedom; χ2=12.9; P=0.115), and the area under the curve was 0.758. The validation dataset (167 patients) was calibrated in the same way (8 degrees of freedom; χ2=9.0; P=0.339), and the area under the curve was 0.782. Independent predictors of CSX were age <55 years; negative histories of smoking, diabetes mellitus, hyperlipidemia, hypertension, or familial premature coronary artery disease; and highly positive ETTs. A total score >9.5 was the optimal cutoff point for differentiating CSX from obstructive coronary artery disease. Our proposed scoring system is a simple, objective, and accurate system for distinguishing CSX from obstructive coronary artery disease in women with typical angina and positive ETTs. It may help determine which of these patients need invasive coronary angiograms or noninvasive tests like computed tomographic coronary angiography.

Effects of Oral Magnesium Therapy on Exercise Tolerance, Exercise-Induced Chest Pain, and Quality of Life in Patients With Coronary Artery Disease

2003 ◽  
Vol 91 (5) ◽  
pp. 517-521 ◽  
Author(s):  
Michael Shechter ◽  
C.Noel Bairey Merz ◽  
Hermann-Georg Stuehlinger ◽  
Joerg Slany ◽  
Otmar Pachinger ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Coronary Artery Disease ◽  
Chest Pain ◽  
Coronary Artery ◽  
Exercise Tolerance ◽  
Artery Disease ◽  
Exercise Induced ◽  
Magnesium Therapy ◽  
Oral Magnesium

scholarly journals Discrimination capability of pretest probability of stable coronary artery disease: a systematic review and meta-analysis suggesting how to improve validation procedures

BMJ Open ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. e047677
Author(s):  
Pierpaolo Mincarone ◽  
Antonella Bodini ◽  
Maria Rosaria Tumolo ◽  
Federico Vozzi ◽  
Silvia Rocchiccioli ◽  
...  
Keyword(s):  
Systematic Review ◽  
Coronary Artery Disease ◽  
Chest Pain ◽  
Coronary Artery ◽  
Quality Assessment ◽  
Meta Analysis ◽  
Stable Coronary Artery Disease ◽  
First Line ◽  
Discrimination Capability ◽  
Artery Disease

ObjectiveExternally validated pretest probability models for risk stratification of subjects with chest pain and suspected stable coronary artery disease (CAD), determined through invasive coronary angiography or coronary CT angiography, are analysed to characterise the best validation procedures in terms of discriminatory ability, predictive variables and method completeness.DesignSystematic review and meta-analysis.Data sourcesGlobal Health (Ovid), Healthstar (Ovid) and MEDLINE (Ovid) searched on 22 April 2020.Eligibility criteriaWe included studies validating pretest models for the first-line assessment of patients with chest pain and suspected stable CAD. Reasons for exclusion: acute coronary syndrome, unstable chest pain, a history of myocardial infarction or previous revascularisation; models referring to diagnostic procedures different from the usual practices of the first-line assessment; univariable models; lack of quantitative discrimination capability.MethodsEligibility screening and review were performed independently by all the authors. Disagreements were resolved by consensus among all the authors. The quality assessment of studies conforms to the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2). A random effects meta-analysis of area under the receiver operating characteristic curve (AUC) values for each validated model was performed.Results27 studies were included for a total of 15 models. Besides age, sex and symptom typicality, other risk factors are smoking, hypertension, diabetes mellitus and dyslipidaemia. Only one model considers genetic profile. AUC values range from 0.51 to 0.81. Significant heterogeneity (p<0.003) was found in all but two cases (p>0.12). Values of I2 >90% for most analyses and not significant meta-regression results undermined relevant interpretations. A detailed discussion of individual results was then carried out.ConclusionsWe recommend a clearer statement of endpoints, their consistent measurement both in the derivation and validation phases, more comprehensive validation analyses and the enhancement of threshold validations to assess the effects of pretest models on clinical management.PROSPERO registration numberCRD42019139388.

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