Serum fibrinogen-to-albumin ratio predicts new-onset atrial fibrillation risk during hospitalization in patients with acute myocardial infarction after percutaneous coronary intervention: a retrospective study

Bao, Jiaqi; Gao, Zhicheng; Hu, Yilan; Liu, Wenquan; Ye, Lifang; Wang, Lihong

doi:10.1186/s12872-023-03480-9

Cited by 5 publications

(1 citation statement)

References 72 publications

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“…The novel inflammatory marker fibrinogen- to-albumin ratio can also predict NOAF after PCI in patients with AMI. 16 However, to the best of our knowledge, the value of LCR in predicting NOAF in AMI patients after PCI has not yet been studied.…”

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confidence: 99%

A Predictive Model of New-Onset Atrial Fibrillation After Percutaneous Coronary Intervention in Acute Myocardial Infarction Based on the Lymphocyte to C-Reactive Protein Ratio

Gao,

Bao,

et al. 2023

JIR

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Purpose Lymphocyte to C-reactive protein ratio (LCR) is a recognized systemic inflammatory marker and novel prognostic indicator for several cancers. This study investigated the relationship between preoperative LCR and new-onset atrial fibrillation (NOAF) in patients with acute myocardial infarction (AMI) after percutaneous coronary intervention (PCI). Patients and Methods Patients with AMI (n=662) with no history of atrial fibrillation (AF) were enrolled and classified into NOAF and non-NOAF groups based on the occurrence of postoperative NOAF during hospitalization. Logistic regression models were used to analyze NOAF risk factors and to assess the association between preoperative LCR and NOAF incidence. We constructed a new nomogram from the selected NOAF risk factors, and tested its predictive performance, degree of calibration, and clinical utility using receiver operating characteristic and calibration curves, decision curve analysis, and clinical impact curves. Results Overall, 84 (12.7%) patients developed NOAF during hospitalization. The LCR was significantly lower in the NOAF group. Preoperative LCR accurately predicted NOAF after AMI and was correlated with increased NOAF risk. Age, body mass index, diabetes, serum albumin levels, uric acid levels, left atrium (LA) diameter, left ventricular ejection fraction, left circumflex artery stenosis > 50%, and Killip class II status were independent predictors of NOAF after AMI. In addition, a new nomogram combined with LCR was constructed to stratify the risk of NOAF in patients with AMI. The performance of the new nomogram was satisfactory, as shown by the receiver operating characteristic curve, calibration curve, decision curve analysis and clinical impact curve. Conclusion Preoperative LCR was an independent predictor of NOAF in patients with AMI after PCI. The novel nomogram combined with LCR could rapidly and individually identify and treat patients at a high risk of NOAF.

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Section: Introductionmentioning

confidence: 99%

A Predictive Model of New-Onset Atrial Fibrillation After Percutaneous Coronary Intervention in Acute Myocardial Infarction Based on the Lymphocyte to C-Reactive Protein Ratio

Gao,

Bao,

et al. 2023

JIR

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Correlation between triglyceride-glucose index and atrial fibrillation in acute coronary syndrome patients: a retrospective cohort study and the establishment of a LASSO-Logistic regression model

Yao,

Qin,

Yan

et al. 2024

BMC Cardiovasc Disord

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Background Insulin resistance (IR) is an independent predictor of atrial fibrillation (AF), but the specific utility of the triglyceride-glucose (TyG) index as a predictive marker for the incidence of AF in the acute coronary syndrome (ACS) population has not yet been explored. Objective To explore the correlation between TyG index and the risk of AF in ACS patients and to establish a predictive model. Methods A retrospective study was conducted on 613 ACS patients admitted to the Department of Cardiovascular Medicine at the First Teaching Hospital of Tianjin University of Traditional Chinese Medicine from January 2022 to September 2024. Patients were divided into four groups based on quartiles of TyG index. Patients were further divided into two groups based on the occurrence of AF: the AF group and the non-AF group. Patient information was collected through the hospital's HIS system. Variable selection was completed using LASSO regression algorithms. Multivariate logistic bidirectional stepwise regression analysis was used to explore the correlation between the TyG index and the risk of AF in ACS patients and to construct a regression model. Three different models were constructed by adjusting for confounding factors and restricted cubic spline plots were drawn to validate the significance of the TyG index combined with AF further. The predictive value of the LASSO-multivariate logistic bidirectional stepwise regression model and the TyG index alone for predicting AF in ACS patients was analyzed using the receiver operating characteristic curve. Results The LASSO-multivariate logistic bidirectional stepwise regression algorithm showed that coronary heart disease (CHD), valvular heart disease (VHD), TyG, age (AGE), and diastolic blood pressure (DBP) were risk factors for AF in ACS. The restricted cubic spline model demonstrated a significant linear relationship between a higher TyG index and an increased risk of AF in the ACS patient population. The area under the curve (AUC) for predicting AF in ACS patients using the TyG index and the LASSO-multivariate logistic bidirectional stepwise regression model was 0.65(95%CI = 0.58 ~ 0.73) and 0.71(95%CI = 0.65 ~ 0.77) respectively. Additionally, the correlation between the TyG index and AF was consistent across different subgroups. Conclusion In ACS patients, the TyG index is a stable and independent predictor of AF, with specific clinical value in identifying the occurrence of AF in this population.

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Biomarkers of risk and prognosis in atrial fibrillation

Stepanenko,

Mirzoyan,

Ruban

et al. 2024

Medicinskij sovet

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Atrial fibrillation is one of the most common forms of arrhythmia and is associated with an increased risk of stroke, thromboembolism, and increased mortality among patients with cardiovascular disease. Identifying patients at high risk of developing atrial fibrillation and predicting the likelihood of acute cerebrovascular accidents of cardioembolic origin, as well as other thromboembolic complications, is key to optimizing treatment strategies and preventing complications. This article provides a comprehensive review of existing and new biomarkers used to assess the risk of onset and recurrence of atrial fibrillation, as well as to assess the safety of anticoagulation therapy for this arrhythmia. Genetic, inflammatory and metabolic markers are discussed in detail, as well as the role of oxidative stress in the context of pathophysiological processes, clinical manifestations of the disease and its complications. Particular attention is paid to the evaluation of markers that can be used to predict adverse outcomes and improve diagnostic accuracy. Limitations in the ability to routinely and widely use both existing and promising biomarkers are discussed. Their clinical significance, cost-effectiveness and possibilities for integration into everyday clinical practice are considered. The need for standardization of approaches to the comprehensive assessment of biomarkers, the importance of interdisciplinary collaboration and the development of individualized approaches to the treatment of patients with atrial fibrillation, including the use of biomarker data, are emphasized. Optimizing approaches to assessing patients with atrial fibrillation using current and promising biomarkers can help overcome existing limitations and facilitate their implementation in clinical practice, which in turn will improve diagnosis, treatment and prognosis of patients.

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Serum fibrinogen-to-albumin ratio predicts new-onset atrial fibrillation risk during hospitalization in patients with acute myocardial infarction after percutaneous coronary intervention: a retrospective study

Cited by 5 publications

References 72 publications

A Predictive Model of New-Onset Atrial Fibrillation After Percutaneous Coronary Intervention in Acute Myocardial Infarction Based on the Lymphocyte to C-Reactive Protein Ratio

A Predictive Model of New-Onset Atrial Fibrillation After Percutaneous Coronary Intervention in Acute Myocardial Infarction Based on the Lymphocyte to C-Reactive Protein Ratio

Correlation between triglyceride-glucose index and atrial fibrillation in acute coronary syndrome patients: a retrospective cohort study and the establishment of a LASSO-Logistic regression model

Biomarkers of risk and prognosis in atrial fibrillation

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