Literature DB >> 24560063

Usefulness of the SYNTAX score to predict acute kidney injury after percutaneous coronary intervention (from the Acute Catheterization and Urgent Intervention Triage Strategy Trial).

Mahesh V Madhavan1, Philippe Généreux2, Jonah Rubin1, Tullio Palmerini3, Adriano Caixeta4, Ke Xu5, Giora Weisz6, Roxana Mehran7, Gregg W Stone6.   

Abstract

The synergy between percutaneous coronary intervention (PCI) with Taxus and cardiac surgery (SYNTAX) score (SS) has prognostic utility for ischemic outcomes in patients undergoing PCI. Acute kidney injury (AKI) after PCI has been demonstrated to be associated with adverse outcomes. However, the relation between the SS and AKI after PCI has yet to be fully investigated. We therefore sought to study this relation in the formal angiographic substudy of the large Acute Catheterization and Urgent Intervention Triage Strategy trial. We stratified 2,268 patients who underwent PCI for non-ST-segment elevation acute coronary syndromes by postprocedural AKI status and by SS tertiles (SS<7, 7 to 12, and >12). We also assessed rates of in-hospital, 30-day, and 1-year adverse outcomes. A total of 226 patients (10%) developed AKI, and rates in the highest Acute Catheterization and Urgent Intervention Triage Strategy SS tertile (>12) were significantly greater than those in the intermediate (7 to 12) and lowest tertiles (<7; 13% vs 8.9% vs 7.7%, respectively, p=0.002). By multivariable analysis, the SS was independently associated with AKI (odds ratio per 10 SS points 1.22, 95% confidence interval 1.04 to 1.43, p=0.02. Rates of major adverse cardiovascular events and net adverse clinical events increased significantly by SS tertile and were more common in patients who developed AKI. Patients who developed AKI experienced higher in-hospital, 30-day, and 1-year rates of mortality. In this large study, the SS was independently associated with AKI after PCI for non-ST-segment elevation acute coronary syndromes, and patients who developed AKI experienced worse short-term and long-term outcomes.
Copyright © 2014 Elsevier Inc. All rights reserved.

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Year:  2014        PMID: 24560063     DOI: 10.1016/j.amjcard.2013.12.041

Source DB:  PubMed          Journal:  Am J Cardiol        ISSN: 0002-9149            Impact factor:   2.778


  6 in total

1.  The Association of Fractional Pulse Pressure with Acute Kidney Injury in Patients Undergoing Coronary Intervention due to ST-Segment Elevated Myocardial Infarction.

Authors:  Cengiz Burak; Muhammed Süleymanoğlu; Mahmut Yesin; Murat Cap; İbrahim Yıldız; İbrahim Rencüzoğulları; Metin Çağdaş; Yavuz Karabağ; Şerif Hamideyin; Doğan İliş; Erkan Baysal
Journal:  Med Princ Pract       Date:  2020-04-28       Impact factor: 1.927

2.  SYNTAX Score of Infarct-Related Artery Other Than the Number of Coronary Balloon Inflations and Deflations as an Independent Predictor of Contrast-Induced Acute Kidney Injury in Patients with ST-Segment Elevation Myocardial Infarction.

Authors:  Cheng-Wei Liu; Pen-Chih Liao; Kuo-Chin Chen; Jung-Cheng Hsu; Chung-Ming Tu; Yen-Wen Wu; Ai-Hsien Li; Shin-Rong Ke; Jiunn-Lee Lin
Journal:  Acta Cardiol Sin       Date:  2017-07       Impact factor: 2.672

3.  Clinical SYNTAX Score Can Predict Acute Kidney Injury following On-Pump but Not Off-Pump Coronary Artery Bypass Surgery.

Authors:  Mete Gursoy; Abdulkadir Faruk Hokenek; Egemen Duygu; Mehmet Atay; Asuman Yavuz
Journal:  Cardiorenal Med       Date:  2015-08-21       Impact factor: 2.041

4.  Age modifies the risk factor profiles for acute kidney injury among recently diagnosed type 2 diabetic patients: a population-based study.

Authors:  Chia-Ter Chao; Jui Wang; Hon-Yen Wu; Jenq-Wen Huang; Kuo-Liong Chien
Journal:  Geroscience       Date:  2018-02-27       Impact factor: 7.713

5.  Relationship between ST-Segment Shifts in Lead aVR and Coronary Complexity in Patients with Acute Coronary Syndrome.

Authors:  Adem Adar; Orhan Onalan; Fahri Cakan
Journal:  Acta Cardiol Sin       Date:  2019-01       Impact factor: 2.672

6.  Prediction models for acute kidney injury in patients with gastrointestinal cancers: a real-world study based on Bayesian networks.

Authors:  Yang Li; Xiaohong Chen; Ziyan Shen; Yimei Wang; Jiachang Hu; Yunlu Zhang; Jiarui Xu; Xiaoqiang Ding
Journal:  Ren Fail       Date:  2020-11       Impact factor: 2.606

  6 in total

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