血清甲状旁腺素水平与急诊PCI慢复流、室性心律失常的相关性与预测价值

    Correlation and predictive value of serum parathyroid hormone levels with slow-reflow and ventricular arrhythmias during primary PCI

      摘要
    • 摘要:
      目的 探讨急性ST段抬高型心肌梗死（STEMI）患者血清甲状旁腺素（PTH）水平与急诊经皮冠状动脉介入治疗（PCI）术中慢复流、围手术期（急诊室至术后72h）室性心律失常（VAs）的相关性与预测价值。
      方法 连续性入选112例因STEMI接受急诊PCI治疗的患者，利用二分类Logistic回归分析模型评估PTH与慢复流及VAs是否独立相关，绘制ROC曲线评价其预测价值。
      结果 PTH是介入术中慢复流（OR=5.768, 95%CI: 1.808-18.402, P<0.01）及围手术期中高危VAs（OR=18.278, 95%CI: 4.881-68.445, P<0.01）的独立预测因子，预测慢血流的ROC曲线下面积（AUC）为0.737 (95%CI: 0.634-0.841, P<0.01)，其截断点为PTH=65.5pg/ml，灵敏度75%，特异度72%；预测VAs时，AUC为0.837 (95%CI: 0.759-0.914, P<0.01)，截断点为PTH=61.9pg/ml，灵敏度82%，特异度73%。
      结论 血清PTH水平与STEMI患者急诊PCI术中慢复流及围手术期VAs有一定相关性，并有较好的预测价值。

       

      Abstract:
      AIM To evaluate the association and predictive value of serum parathyroid hormone (PTH) levels with slow-reflow and peri-operative ventricular arrhythmias (VAs) in patients with acute ST-segment elevation myocardial infarction (STEMI) undergoing primary percutaneous coronary intervention (PCI).
      METHODS A total of 112 consecutive patients with STEMIs treated with primary PCI were enrolled in this study. Binary logistic regression analysis model was used to analyze whether PTH levels were independently related to slow-reflow and VAs, and ROC curve was drawn to evaluate its predictive value.
      RESULTS PTH was a risk factor of slow-reflow (OR=5.768, 95%CI: 1.808-18.402, P<0.01) and medium to high risk VAs (OR=18.278, 95%CI: 4.881-68.445, P<0.01). The area under ROC curve (AUC) for predicting slow-reflow was 0.737 (95%CI: 0.634-0.841, P<0.01), the cut-off point was PTH=65.5pg/ mL, with a sensitivity of 75% and a specificity of 72%. When VAs was predicted, the AUC was 0.837 (95%CI: 0.759-0.914, P<0.01), the cut-off point was PTH=61.9pg/mL, with a sensitivity of 82% and a specificity of 73%.
      CONCLUSION Serum PTH levels are correlated with intra-operative slow-reflow and peri-operative VAs in patients with STEMI undergoing primary PCI, and has certain predictive value.

       

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