Chrome Extension
WeChat Mini Program
Use on ChatGLM
VIPCreated with Sketch.

    • Ruling out Left Main Stem Stenosis by Clinical and Stress ECG Variables: the MASTER Case-Control Multicenter Study

    CIRCULATION（2024）

    University of Pisa | FTGM Pisa | Fondazione Toscana Gabriele Monasterio | Policlinico Agostino Gemelli | University of Messina | ASL2 Abruzzo | University of Eastern Piedmont | Medstar Health Research Institute | Istituti Clinici Scientifici S. Maugeri | UNIVERSITY OF PISA

    Cited 0|Views3
    Abstract
    Background: The ISCHEMIA trial questioned revascularization in chronic coronary syndrome (CCS) patients, but excluding subjects with left main (LM) coronary artery disease (CAD). A widely available diagnostic method excluding LMCAD would expand the implementation of an initial noninvasive strategy. Objective: Assessing the ability of excluding LMCAD through clinical and ECG stress testing (EST) variables in patients undergoing coronary angiography (CAG) for CCS. Methods: In a multicenter retrospective case-control study we evaluated CCS subjects undergoing CAG after a maximal EST. Cases were patients with angiographic ≥50% LM stenosis or ≥70% stenoses of both proximal left anterior descending and proximal circumflex arteries; we matched them with similar patients without LMCAD ( Controls) in a 1:3 ratio. Models were internally validated through logistic regressions. Results: 219 Cases were matched with 554 Controls . The c-statistic was 0.80 (optimism-adjusted: 0.73). Assuming LMCAD prevalence of 5% and a misclassification cost ratio of 1:100 (ratio of the cost of performing CAG in a subject without LMCAD to the cost of not performing CAG in a patient with LMCAD), the negative predictive value was 98.6%, correctly classifying 84.5% of Cases . CAG could be spared in 57.0% of subjects, missing one LMCAD diagnosis every 70 CAGs spared in patients without LMCAD ( Figure ). Conclusions: Among patients with CCS, LMCAD can be predicted with acceptable diagnostic accuracy and a very high negative predictive value through a model based on clinical and EST parameters, allowing an initial noninvasive management of most patients able to perform an EST, reducing the costs of routine coronary imaging. Such results should enlarge the applicability of the ISCHEMIA results when coronary computed tomography angiography, used in ISCHEMIA, is not available, limiting the referral to invasive CAG.
    More
    Translated text
    Key words
    Drug-Eluting Stents
    求助PDF
    上传PDF
    View via Publisher
    Bibtex
    AI Read Science
    AI Summary
    AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
    Example
    Background
    Key content
    Introduction
    Methods
    Results
    Related work
    Fund
    Key content
    • Pretraining has recently greatly promoted the development of natural language processing (NLP)
    • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
    • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
    • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
    • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
    Upload PDF to Generate Summary
    Must-Reading Tree
    Example
    Generate MRT to find the research sequence of this paper
    Data Disclaimer
    The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
    Chat Paper
    【要点】：研究提出了一种基于临床和心电图压力测试变量排除左主冠状动脉疾病的新方法，具有较高的诊断准确性和阴性预测值，有助于降低冠脉造影的使用，节约医疗成本。
    

    【方法】：通过多中心回顾性病例对照研究，对接受冠脉造影的慢性冠脉综合征患者进行评估，采用逻辑回归模型对临床和心电图压力测试变量进行分析。
    

    【实验】：研究中，219例LMCAD患者与554例非LMCAD患者进行了匹配，使用逻辑回归模型进行内部验证，模型判别力(c-统计量)为0.80，调整后为0.73，在假设LMCAD患病率为5%的情况下，阴性预测值为98.6%，能够正确分类84.5%的病例。通过该模型，可以避免对57.0%的患者进行冠脉造影，每避免70次不必要的冠脉造影可能会漏诊一例LMCAD。