P890Diamond-Forrester risk model and chest pain typicality in assessment of stable coronary 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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Simple risk models to predict cardiovascular death in patients with stable coronary artery disease

European Heart Journal - Quality of Care and Clinical Outcomes ◽

10.1093/ehjqcco/qcz070 ◽

2020 ◽

Cited By ~ 1

Author(s):

Ian Ford ◽

Michele Robertson ◽

Nicola Greenlaw ◽

Christophe Bauters ◽

Gilles Lemesle ◽

...

Keyword(s):

Coronary Artery Disease ◽

Coronary Artery ◽

Risk Model ◽

Stable Coronary Artery Disease ◽

Cardiovascular Death ◽

Left Ventricular ◽

Cox Proportional Hazards Model ◽

Clinical Variables ◽

Model Based ◽

Artery Disease

Abstract Aims Risk estimation is important to motivate patients to adhere to treatment and to identify those in whom additional treatments may be warranted and expensive treatments might be most cost effective. Our aim was to develop a simple risk model based on readily available risk factors for patients with stable coronary artery disease (CAD). Methods and results Models were developed in the CLARIFY registry of patients with stable CAD, first incorporating only simple clinical variables and then with the inclusion of assessments of left ventricular function, estimated glomerular filtration rate, and haemoglobin levels. The outcome of cardiovascular death over ∼5 years was analysed using a Cox proportional hazards model. Calibration of the models was assessed in an external study, the CORONOR registry of patients with stable coronary disease. We provide formulae for calculation of the risk score and simple integer points-based versions of the scores with associated look-up risk tables. Only the models based on simple clinical variables provided both good c-statistics (0.74 in CLARIFY and 0.80 or over in CORONOR), with no lack of calibration in the external dataset. Conclusion Our preferred model based on 10 readily available variables [age, diabetes, smoking, heart failure (HF) symptom status and histories of atrial fibrillation or flutter, myocardial infarction, peripheral arterial disease, stroke, percutaneous coronary intervention, and hospitalization for HF] had good discriminatory power and fitted well in an external dataset. Study registration The CLARIFY registry is registered in the ISRCTN registry of clinical trials (ISRCTN43070564).

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Myocardial perfusion scintigraphy: clinical value

10.1093/med/9780198759942.003.0010 ◽

2017 ◽

Author(s):

Nikant Sabharwal ◽

Parthiban Arumugam ◽

Andrew Kelion

Keyword(s):

Coronary Artery Disease ◽

Chest Pain ◽

Coronary Artery ◽

Myocardial Perfusion ◽

Myocardial Perfusion Scintigraphy ◽

Coronary Revascularization ◽

Stable Coronary Artery Disease ◽

Hibernating Myocardium ◽

Perfusion Scintigraphy ◽

Artery Disease

Myocardial perfusion scintigraphy (MPS) is most commonly used to diagnose or exclude obstructive coronary disease in patients presenting with chest pain. This chapter covers the value of MPS in this context, as well as providing detail on the guidelines which help the clinician choose what investigations are appropriate for the patient presenting with chest pain. It also details a number of considerations related to the use of MPS, such as its cost-effectiveness and the prognosis value in the diagnosis of coronary artery disease compared to exercise ECG, X-ray computed tomographic coronary angiography, and other imaging investigations. Risk assessment prior to elective non-cardiac surgery is covered, with detailed attention paid to the challenges of assessing coronary artery disease special groups including women and patients with diabetes or renal disease. This chapter also covers assessment in known stable coronary artery disease, predicting the value of coronary revascularization and hibernating myocardium.

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