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1.
Eur J Emerg Med ; 30(1): 40-46, 2023 Feb 01.
Article in English | MEDLINE | ID: mdl-36542336

ABSTRACT

Acute nontraumatic chest pain is a frequent reaso n for consultation in emergency departments and represents a diagnostic challenge. The objective is to estimate the risk of significant coronary artery disease (CAD) in patients with cardiogenic acute chest pain for whom the diagnosis of infarction was ruled out in the emergency department with a nondiagnostic ECG and negative high-sensitivity troponins. We prospectively recruited 1625 patients from emergency departments of seven Spanish hospitals. The outcome was presence of significant CAD determined by presence of ischaemia in functional tests or more than 70% stenosis in imaging tests. In this study, we developed a predictive model and evaluated its performance and clinical utility. The prevalence of significant CAD was 14% [227/1625; 95% confidence interval (CI), 12-16]. MAPAC Cardio-PreTest model included seven predictors: age, sex, smoking, history of hypertension, family history of CAD, history of hyperuricaemia, and type of chest pain. The optimism-adjusted model discrimination was C-statistic 0.654 (95% CI, 0.618-0.693). Calibration plot showed good agreement between the predicted and observed risks, and calibration slope was 0.880 (95% CI, 0.731-1.108) and calibration-in-the-large -0.001 (95% CI, -0.141 to 0.132). The model increased net benefit and improved risk classification over the recommended approach by the European Society of Cardiology [Net Reclassification Index (NRI) of events = 5.3%, NRI of nonevents = 7.0%]. MAPAC Cardio-PreTest model is an online prediction tool to estimate the individualised probability of significant CAD in patients with acute chest pain without a diagnosis of infarction in emergency department. The model was more useful than the current alternatives in helping patients and clinicians make individually tailored choices about the intensity of monitoring or additional coronary tests.


Subject(s)
Coronary Artery Disease , Humans , Coronary Artery Disease/complications , Coronary Artery Disease/diagnosis , Coronary Artery Disease/epidemiology , Risk Assessment/methods , Predictive Value of Tests , Chest Pain/diagnosis , Chest Pain/epidemiology , Chest Pain/etiology , Emergency Service, Hospital , Infarction , Risk Factors
2.
Radiographics ; 40(5): 1318-1338, 2020.
Article in English | MEDLINE | ID: mdl-32795238

ABSTRACT

Ectopic gas is defined as the presence of gas in abnormal locations, that is, outside the aerodigestive tract. It constitutes a common radiologic finding associated with a wide range of disorders. Although it is usually an innocuous and self-limited condition, it should prompt a search for the underlying cause, given that the clinical significance of ectopic gas varies from benign to life threatening, depending on the site involved and the rate of accumulation. To ensure optimal management of each case, the origin of ectopic gas should be determined. The search for its exact location and underlying cause often represents a challenge, as air can be depicted distant from its point of origin because of fascial interconnectivity. Thorough knowledge of anatomic compartments facilitates quick identification of the cause and contributes to a prompt diagnosis. Likewise, radiologists should be familiar with the alarm signs associated with severe conditions. Imaging studies are essential to help the radiologist confirm the diagnosis of ectopic gas, determine its precise location and extension, identify severe cases, exclude associated complications, and monitor evolution. CT is the modality of choice in the imaging assessment of ectopic gas. In this review, the authors discuss the different causes of ectopic gas with an etiopathogenic approach to describe the myriad processes that might give rise to this condition. In addition, alarm signs associated with potentially fatal ectopic gas are described and depicted. ©RSNA, 2020.


Subject(s)
Emphysema/diagnostic imaging , Gases , Tomography, X-Ray Computed , Contrast Media , Diagnosis, Differential , Humans
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