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相关概念视频

Regression Toward the Mean01:52

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Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when...
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相关实验视频

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A New Hybrid Quantitative Evaluation Model for Axillary Junctional Hemorrhage in Swine
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预测产后出血风险与第二个三个月的数据.

Mark A Clapp1, Siguo Li1, Kaitlyn E James1

  • 1Department of Obstetrics and Gynecology and the Department of Psychiatry, Massachusetts General Hospital, and Harvard Medical School, Boston, Massachusetts; and the Department of Obstetrics and Gynecology, University of South Florida, Tampa, Florida.

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|September 26, 2025
PubMed
概括
此摘要是机器生成的。

使用电子健康记录数据的新工具可以在怀孕24周之前识别患产后出血 (PPH) 高风险的患者. 这种产前风险分层有助于早期规划高风险怀孕.

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科学领域:

  • 产科和妇科 产科和妇科
  • 医疗信息学 医疗信息学
  • 预测分析在医疗保健中的应用

背景情况:

  • 产后出血 (PPH) 仍然是孕产妇发病率和死亡率的主要原因.
  • 准确,早期风险分层对于及时干预和改善患者结果至关重要.
  • 现有的工具往往缺乏使用随时可用的数据在产前分层风险的能力.

研究的目的:

  • 开发和验证产后出血 (PPH) 的风险分层工具.
  • 使用电子健康记录 (EHR) 的结构化数据,可在第三个三个月之前使用.
  • 为了使高风险怀孕能够进行积极的分娩前规划和健康优化.

主要方法:

  • 对2017年至2023年间分娩的17201名患者进行了回顾性队列研究.
  • 在培训数据 (2017-2022) 上使用后勤回归与逐步向后选择的开发.
  • 在独立测试 (2017-2022) 和时间验证 (2023) 队列中的验证,使用已知妊娠24周的数据.

主要成果:

  • 最终的模型表现出良好的区分,曲线下的面积为0.689 (测试) 和0.659 (验证).
  • 该工具成功识别了高风险患者,查阳性率约为20%,积极预测值超过20%.
  • 模型性能在测试和时间验证数据集中一致,证实了稳定性.

结论:

  • 一个可靠的产前风险分层模型PPH可以开发使用结构化的EHR数据可用到24周怀孕.
  • 该工具可为PPH高风险人群提供预交付规划和有针对性的管理.
  • 该模型在接受后的工具上提供了优势,因为它允许更早的干预策略.