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      The Impact of the Stress Hyperglycemia Ratio on Short-term and Long-term Poor Prognosis in Patients With Acute Coronary Syndrome: Insight From a Large Cohort Study in Asia

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          Abstract

          OBJECTIVE

          In recent years, some studies have indicated that a novel marker described as the stress hyperglycemia ratio (SHR) can reflect true acute hyperglycemic status and is associated with the short-term poor prognosis in patients with acute myocardial infarction. In the current study we evaluated the association of SHR with adverse cardiovascular events among patients with acute coronary syndrome (ACS).

          RESEARCH DESIGN AND METHODS

          We consecutively enrolled 5,562 ACS patients who underwent drug-eluting stent (DES) implantation. All subjects were divided into five groups according to SHR, which was determined by the following formula: ABG / [(28.7 × HbA1c %) − 46.7], where ABG is admission blood glucose level. The primary end point was major adverse cardiovascular and cerebrovascular events (MACCE) at the 2-year follow-up, and the secondary end point included major adverse cardiovascular events (MACE) at 2-year follow-up, cardiac death, and nonfatal myocardial infarction (MI) at 2-year follow-up and in-hospital cardiac death and nonfatal MI.

          RESULTS

          A total of 643 MACCE were recorded during a median follow-up of 28.3 months. Kaplan-Meier survival analysis showed the lowest MACCE incidence in quintile 3 (P < 0.001). Moreover, the outcomes of restricted cubic spline analysis suggested that there was a U-shaped or J-shaped association between the SHR and early and late cardiovascular outcomes even after adjustment for other confounding factors.

          CONCLUSIONS

          There were U-shaped associations of SHR with MACCE rate and MACE rate at 2-year follow-ups and J-shaped associations of SHR with in-hospital cardiac death and MI and that at 2-year follow-up in ACS patients who underwent DES implantation, and the inflection point of SHR for poor prognosis was 0.78.

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          Most cited references40

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          2019 ESC Guidelines for the diagnosis and management of chronic coronary syndromes

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            The lasso method for variable selection in the Cox model.

            I propose a new method for variable selection and shrinkage in Cox's proportional hazards model. My proposal minimizes the log partial likelihood subject to the sum of the absolute values of the parameters being bounded by a constant. Because of the nature of this constraint, it shrinks coefficients and produces some coefficients that are exactly zero. As a result it reduces the estimation variance while providing an interpretable final model. The method is a variation of the 'lasso' proposal of Tibshirani, designed for the linear regression context. Simulations indicate that the lasso can be more accurate than stepwise selection in this setting.
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              OUP accepted manuscript

              (2020)
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                Author and article information

                Contributors
                Journal
                Diabetes Care
                American Diabetes Association
                0149-5992
                April 01 2022
                January 19 2022
                April 01 2022
                January 19 2022
                : 45
                : 4
                : 947-956
                Affiliations
                [1 ]Department of Cardiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
                [2 ]Department of Cardiology and Institute of Vascular Medicine, Peking University Third Hospital, and Key Laboratory of Molecular Cardiovascular Science, Ministry of Education, Beijing, China
                Article
                10.2337/dc21-1526
                35045167
                0e0d5716-7360-4c32-8346-9d9b33eecd96
                © 2022

                https://www.diabetesjournals.org/content/license

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