ArticleCardiovascular diagnosis and therapy2021
Nomogram to differentiate between aortic dissection and non-ST segment elevation acute coronary syndrome: a retrospective cohort study.
Article in Cardiovascular diagnosis and therapy, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed, 4 citations in OpenAlex.
- Development and validation of identification models for aortic dissection and non-ST-segment elevation acute coronary syndrome in the emergency department.Scientific reports · 2025Article
- Ventricular fibrillation arrest in aortic dissection presenting as myocardial injury.Radiology case reports · 2024Article
- A model to predict a risk of allergic rhinitis based on mitochondrial DNA copy number.European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery · 2022Article
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAortic dissection (AD) and non-ST segment elevation acute coronary syndrome (ACS) are two of the most life-threatening diseases encountered in the emergency department (ED), but there are no rapid and reliable tools for differentiation. The purpose of this study is to develop and validate a nomogram that incorporates both the clinical characteristics and bedside laboratory tests available to differentiate between AD and non-ST segment elevation ACS (NSTE-ACS).
methodsBetween January 2016 and July 2018, patients with AD and NSTE-ACS were enrolled and divided into training and validation groups. The least absolute shrinkage and selection operator (LASSO) regression model was used to select the factors with significant value of predicting the diagnosis of AD. A nomogram was built on the basis of multivariable logistic regression analysis. Area under the curve (AUC) of receiver operating characteristic (ROC) curve and the calibration curve were used to assess the performance of the nomogram. Decision curve analysis was performed to assess the clinical utility of the nomogram.
resultsA final cohort of 263 patients (94 patients with AD and 169 patients with NSTE-ACS) were enrolled. Six variables were incorporated in the nomogram: pain severity, tearing pain, pulse asymmetry, electrocardiogram (ECG), D-dimer level and troponin I level. The AUC of the nomogram to predict the probability of AD was 0.919 (95% CI, 0.876-0.962) in the training group and 0.938 (95% CI, 0.888-0.989) in the validation group. The calibration curve demonstrated a good consistency between the actual clinical results and the predicted outcomes. The decision curve analysis indicated that the nomogram had higher overall net benefits in predicting AD in both the training group and the validation group.
conclusionsWe developed and validated a predictive nomogram that could be used as a tool to differentiate AD from NSTE-ACS rapidly and accurately.
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