Establishment and evaluation of an early warning model for major cardiovascular adverse events in emergency patients with chest pain within 30 days
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摘要: 目的 通过分析急诊胸痛患者一般资料、心电图指标、血清学指标及超声心动图指标筛选影响患者30 d内主要心血管不良事件(MACE)发生的危险因素，建立列线图预测模型并验证预测效果。方法 采用便利抽样法选取2017年1月-2020年10月我院收治的487例急诊胸痛患者作为建模组，另选取2020年11月-2021年12月我院收治的急诊胸痛患者185例作为验证组。收集患者的一般资料及临床检测指标，使用LASSO回归、多因素logistic回归分析筛选变量并绘制列线图预警模型。采用受试者工作特征(ROC)曲线、C-index、校准曲线评价模型的区分度和校准度；决策曲线分析(DCA)评估预测模型的临床有效性。结果 使用LASSO回归分析筛选出7个预测变量，采用多因素logistic回归进一步分析显示，冠状动脉疾病(CAD)危险因素 > 3个、心电图V1导联P波终末电势(PTFV1)异常、CRP≥3.32、NLR≥3.46、E/Em≥4.28是影响急诊胸痛患者30 d内MACE发生的独立危险因素(P < 0.05)；基于预测变量绘制列线图预警模型，模型预测建模组与验证组患者发生MACE的C-index为0.896、0.802，AUC分别为0.900、0.823，且建模组与验证组的校准曲线显示预测发生风险与实际观察的发生风险基本一致；将本研究中列线图模型预测MACE的效果与HEART评分、GRACE评分、TIMI评分模型比较，结果显示列线图模型的AUC与DCA阈概率范围均大于3种评分模型，有更高的预测效能与临床应用价值。结论 基于5个预测变量建立的列线图预测模型在预测急诊胸痛患者30 d MACE发生率具有更准确地预测效果与更高的临床应用价值，有助于临床早期识别出MACE高危人群从而制定针对性的预防干预措施。Abstract: Objective By analyzing the general data, electrocardiographic indexes, serological indexes and echocardiographic indexes of patients with chest pain in emergency department, the risk factors affecting the occurrence of major adverse cardiovascular events(MACE) within 30 days were screened, and a nomogram prediction model was established to verify the prediction effect.Methods Convenience sampling method was used to select 487 emergency chest pain patients admitted to our hospital from January 2017 to October 2020 as the modeling group, and another 185 emergency chest pain patients admitted to our hospital from November 2020 to December 2021 were selected as validation Group. The general information and clinical test indicators of the patients were collected, and LASSO regression and multivariate logistic regression analysis were used to screen variables and draw a nomogram warning model. Receiver operating characteristic(ROC) curve, C-index, and calibration curve were used to evaluate the discrimination and calibration of the model; decision curve analysis(DCA) was used to evaluate the clinical validity of the prediction model.Results Screening out 7 predictors using LASSO regression analysis, further analysis by multivariate logistic regression showed that CAD risk factors > 3, abnormal PTFV1, CRP≥3.32, NLR≥3.46, E/Em≥4.28 were independent risk factors affecting the occurrence of MACE within 30 days of emergency chest pain patients(P < 0.05). Drawing a nomogram warning model based on the predictor variables, the C-index of the model predicting the occurrence of MACE in the modeling group and the validation group was 0.896 and 0.802, and the AUC was 0.900 and 0.823, respectively. And the calibration curves of the modeling group and the validation group show that the predicted occurrence risk was basically consistent with the actual observed occurrence risk. Comparing the effect of the nomogram model in predicting MACE with the HEART score, GRACE score, and TIMI score model in this study, the results showed that the AUC and DCA threshold probability ranges of the nomogram model were both greater than the three scores model, demonstrating higher predictive performance and clinical application value.Conclusion The nomogram prediction model based on five predictors has more accurate prediction effect and higher clinical application value in predicting the incidence of 30 d MACE in emergency chest pain patients, and is helpful to identify the high-risk groups of MACE in the early clinical stage so as to formulate targeted preventive interventions.
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Key words:
- emergency chest pain /
- adverse cardiovascular events /
- prognosis /
- early warning model
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表 1 建模组与验证组患者一般特征、心电图指标、血清学指标及心动图指标比较
例(%) 指标 建模组(487例) 验证组(185例) 统计值 P 年龄/岁 68.74±10.53 67.45±9.26 1.465 0.143 性别 0.947 0.331 男 256(52.57) 105(56.76) 女 231(47.43) 80(43.24) CAD危险因素 高血压 112(23.00) 32(17.30) 2.588 0.108 高脂血症 302(62.01) 110(59.46) 0.368 0.544 糖尿病 108(22.18) 35(18.92) 0.849 0.357 冠心病家族史 73(14.99) 33(17.84) 0.819 0.366 吸烟 79(16.22) 35(18.92) 0.692 0.405 大量饮酒史 210(43.12) 89(48.11) 1.350 0.245 肥胖 199(40.86) 83(44.86) 0.882 0.348 CAD危险因素/个 1.516 0.218 ≤3 345(70.84) 122(65.95) > 3 142(29.16) 63(34.05) 既往脑卒中史 0.539 0.463 无 456(93.63) 176(95.14) 有 31(6.37) 9(4.86) 既往心肌梗死史 1.754 0.185 无 379(77.82) 135(72.97) 有 108(22.18) 50(27.03) 收缩压/mmHg 138.72±27.65 135.57±29.40 1.296 0.195 舒张压/mmHg 77.56±12.33 78.24±14.86 0.602 0.547 心率/(次·min-1) 82.44±16.28 81.06±14.52 1.010 0.313 VPB 2.961 0.085 否 376(77.21) 131(70.81) 是 111(22.79) 54(29.19) PTFV1 1.376 0.241 正常 403(82.75) 160(86.49) 异常 84(17.25) 25(13.51) QTc 0.402 0.526 正常 415(85.22) 154(83.24) 延长 72(14.78) 31(16.76) CTnT/(ng·mL-1) 1.66±0.24 1.62±0.20 1.016 0.044 CK-MB/(U·L-1) 86.47±11.39 88.34±12.47 1.851 0.065 NT-proBNP/(ng·L-1) 94(73，122) 91(71，113) 1.925 0.054 白蛋白/(g·L-1) 41.84±7.35 42.03±8.61 0.285 0.776 血红蛋白/(g·L-1) 139.10±16.43 140.35±14.18 0.914 0.361 CRP/(mg·L-1) 2.26(1.75，3.67) 2.31(1.69，3.56) 1.324 0.103 NLR 2.58(1.88，3.39) 2.47(180，3.47) 1.106 0.144 Scr/(μmol·L-1) 80.68±15.38 78.49±16.73 1.609 0.108 空腹血糖/(mmol·L-1) 6.22±1.51 5.90±1.24 2.571 0.010 LAD/mm 34.76±3.89 33.92±4.10 2.463 0.014 LVESD/mm 34.07±3.72 33.86±4.38 0.622 0.534 LVEDD/mm 51.21±5.38 50.48±4.85 1.613 0.107 LVEF/% 60.74±4.28 61.35±3.69 1.712 0.087 LVH 0.253 0.615 否 344(70.64) 127(68.65) 是 143(29.36) 58(31.35) E/A 1.25(1.12，1.41) 1.20(1.09，1.37) 1.547 0.104 E/Em 4.32(3.55，5.37) 4.43(3.64，5.44) 1.143 0.096 注：1 mmHg=0.133 kPa。 
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表 2 变量赋值
变量 赋值 年龄 原值输入 CAD危险因素 ≤3个=0，>3个=1 PTFV1 正常=0，异常=1 cTnT 原值输入 CRP CRP < 3.32=0，CRP≥3.32=1 NLR NLR < 3.46=0，NLR≥3.46=1 E/Em E/Em < 4.28=0，E/Em≥4.28=1
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表 3 影响急诊胸痛患者30d内MACE发生的多因素分析
因素 β SE Wald P OR 95%CI 下限 上限 年龄 0.029 0.020 2.209 0.137 1.030 0.991 1.070 CAD危险因素>3个 1.887 0.397 22.653 0.000 6.602 3.035 14.361 PTFV1 1.547 0.426 13.180 0.000 4.697 2.038 10.826 CTnT -0.128 0.847 0.023 0.880 0.880 0.167 4.632 CRP 1.675 0.516 10.553 0.001 5.340 1.943 14.671 NLR 1.235 0.388 10.102 0.001 3.438 1.605 7.361 E/Em 1.368 0.551 6.167 0.013 3.929 1.334 11.571 常量 -6.254 1.986 9.919 0.002 0.002
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