Analysis of Influencing Factors of Prognosis in Patients with Acute Myocardial Infarction Complicated with Malignant Ventricular Arrhythmia and Construction of Nomogram Model
YANG Sa, WEN Fangfang, ZHANG Wen, et al
The Second Affiliated Hospital of Air Force Military Medical University, Shaanxi Xi'an 710038, China
Abstract：Objective: To analyze the influencing factors of prognosis in patients with acute myocardial infarction (AMI) complicated with malignant ventricular arrhythmia (MVA), and to construct a nomogram model and verify it. Methods: A total of 286 patients with AMI complicated with MVA in our hospital from June 2020 to July 2024 were chosen and split into modeling group and verification group. The patients were followed up for the recovery within 72 hours after admission and divided into poor prognosis group and good prognosis group. The nomogram model was developed using single-factor and binary logistic regression analysis, and its prediction accuracy was evaluated using the ROC, calibration, and DCA curves. Results: Among the 286 patients, 58 patients had a poor prognosis (20.28%). Compared with the good prognosis group, the levels of systolic blood pressure (SBP), diastolic blood pressure (DBP) and left ventricular ejection fraction (LVEF) in the poor prognosis group were decreased, the levels of serum magnesium, urea, galectin-3 (Gal-3), growth differentiation factor-15 (GDF-15) and Creatine kinase isoenzyme (CK-MB) were increased, and the proportion of QRS-T angle>90° was increased (all P<0.05). SBP, QRS-T angle, LVEF, serum magnesium, urea and CK-MB were independent influencing factors of poor prognosis in patients with AMI complicated with MVA. ROC curve analysis showed that the AUC of the nomogram model for predicting poor prognosis in the modeling group was 0.914 (95%CI: 0.877-0.952), and the AUC of the validation group was 0.949 (95%CI: 0.875-1.000). The calibration curve fits well with the ideal curve. The net income of each range of the threshold probability value of the DCA curve analysis is greater than 0. Conclusion: The nomogram model constructed in this study has good efficacy and can provide reference for medical staff to evaluate the prognosis of patients with AMI complicated with MVA.
杨飒, 问芳芳, 张雯, 陆荣, 张媛姝. 急性心肌梗死合并恶性室性心律失常患者预后的影响因素分析及列线图模型构建[J]. 河北医学, 2025, 31(8): 1315-1322.
YANG Sa, WEN Fangfang, ZHANG Wen, et al. Analysis of Influencing Factors of Prognosis in Patients with Acute Myocardial Infarction Complicated with Malignant Ventricular Arrhythmia and Construction of Nomogram Model. HeBei Med, 2025, 31(8): 1315-1322.
[1] Galli M,Niccoli G,De Maria G,et al.Coronary microvascular obstruction and dysfunction in patients with acute myocardial infarction[J].Nature Reviews Cardiology,2024,21(5):283-298. [2] Wang X,Wei L,Wu Y,et al.ST-segment elevation predicts the occurrence of malignant ventricular arrhythmia events in patients with acute ST-segment elevation myocardial infarction[J].BMC Cardiovascular Disorders,2023,23(1):61. [3] Trongtorsak A,Kewcharoen J,Thangjui S,et al.Admission hyperglycemia in acute myocardial infarction is associated with an increased risk of arrhythmias:a systematic review and meta-analysis[J].Journal of Arrhythmia,2022,38(3):307-315. [4] Zhu D,Zhang X,Fang Y,et al.Identification of a lactylation-related gene signature as the novel biomarkers for early diagnosis of acute myocardial infarction[J].International Journal of Biological Macromolecules,2024,282(Pt 6):137431. [5] Zeppenfeld D K,Tfelt-Hansen J,De Riva M,et al.2022 ESC Guidelines for the management of patients with ventricular arrhythmias and the prevention of sudden cardiac death[J].European Heart Journal,2022,43(40):3997-4126. [6] 陈强,陈应忠,崔彩艳,等.血尿酸水平与急性心肌梗死患者远期预后的关系研究[J].中国全科医学,2022,25(5):561-567. [7] Zhou Z,Liu C,Xu S,et al.Metabolism regulator adiponectin prevents cardiac remodeling and ventricular arrhythmias via sympathetic modulation in a myocardial infarction model[J].Basic Research in Cardiology,2022,117(1):34. [8] Zhang J L,Hou H T,Song Y,et al.Proteomics study and protein biomarkers of malignant ventricular arrhythmia in acute myocardial infarction patients[J].Clinical and Translational Medicine,2023,13(11):1435. [9] Fang C,Chen Z,Zhang J,et al.Construction and evaluation of nomogram model for individualized prediction of risk of major adverse cardiovascular events during hospitalization after percutaneous coronary intervention in patients with acute ST-segment elevation myocardial infarction[J].Frontiers in Cardiovascular Medicine,2022,9(1):1050785. [10] 瞿小龙,虞旭东,戈睿陀,等.经皮冠状动脉介入治疗术后发生主要不良心血管事件的预测因素分析[J].中华老年心脑血管病杂志,2024,26(12):1405-1408. [11] Wang W,Chen M,Guo J,et al.Construction and validation of nomogram model for predicting the risk of ventricular arrhythmia after emergency PCI in patients with acute myocardial infarction[J].Aging,2024,16(9):8246-8259. [12] Zhuang J,Zhang Q,Wang H,et al.Association between short-term changes in serum magnesium and in-hospital mortality following acute myocardial infarction:a cohort study based on the MIMIC database[J].Magnesium Research,2024,37(1):45-59. [13] Wang L,Yang L,Li T,et al.Development and validation of nomogram for the prediction of malignant ventricular arrhythmia including circulating inflammatory cells in patients with acute ST-segment elevation myocardial infarction[J].Journal of Inflammation Research,2023,16(1):3185-3196. [14] 陈嘉莹,何利伟,庄英渠.β1-肾上腺素能受体基因多态性对STEMI患者室性心律失常和短期预后的影响[J].中国病理生理杂志,2024,40(9):1645-1651.
2025, Vol. 31 
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