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Patients with hypertrophic cardiomyopathy (HCM) and left ventricular outflow tract (LVOT) obstruction who remain symptomatic despite optimal medical therapy may undergo a septal myectomy (Morrow procedure). This procedure involves excising a portion of the hypertrophied septum below the aortic valve using a heart-lung machine to improve blood flow through the LVOT. Effective preoperative and postoperative nursing management ensures successful patient outcomes, minimizes complications, and...
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相关实验视频

Updated: Jan 16, 2026

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肺切除手术前进行心肺运动测试:仍然适用吗? 使用机器学习评估预测效用.

Ákos Filakovszky1, Kristian Brat2,3, Thomas Tschoellitsch1

  • 1Department of Anesthesiology and Critical Care Medicine, Johannes Kepler University and Kepler University Hospital, Linz, Austria.

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|October 3, 2025
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概括

心肺运动测试 (CPET) 不能改善肺切除候选人的术后并发症预测. 根据这些发现,CPET对肺部外科手术风险分层的当前指导方针可能需要重新评估.

关键词:
运动运动运动.肺癌 肺癌 是 一种 肺癌.

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科学领域:

  • 肺部医学 肺部医学
  • 胸部外科手术 胸部外科手术
  • 心脏病学 心脏病学

背景情况:

  • 肺切除风险分层的心肺运动测试 (CPET) 标准已经有十多年的历史了.
  • 患者护理的进步需要更新的风险评估工具.
  • 假设:CPET对术后并发症没有额外的预测价值.

研究的目的:

  • 评估CPET在肺切除风险分层中的附加预测价值.
  • 评估CPET是否能提高机器学习模型在预测术后并发症方面的性能.

主要方法:

  • 两项前性多中心研究的二次分析.
  • 包括通过CPET,肺功能测试 (PFT) 和动脉血液气体分析评估的肺切除候选人.
  • 使用嵌套交叉验证,训练机器学习模型来预测肺部和心血管并发症.

主要成果:

  • 包括497名患者;14%的人患有肺部并发症 (PPC) 和18%的人患有心血管并发症 (PCC).
  • CPET参数没有提高机器学习模型对未被选择或指南选择的子组的PPC或PCC的预测准确度.
  • 接收器运行特征曲线 (AUC-ROC) 下的面积在CPET纳入后没有显著改善.

结论:

  • 在当代外科实践中,CPET并没有提高PPC或PCC的机器学习模型的预测性能.
  • 在肺切除术前风险分层中CPET的实用性需要重新评估.
  • 目前关于CPET在肺切除中的使用指南可能需要更新.