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Determination of Multiple Dosing Parameters: Loading and Maintenance Doses01:25

Determination of Multiple Dosing Parameters: Loading and Maintenance Doses

A loading dose is an essential pharmacological strategy to rapidly achieve the target plasma drug concentration necessary for an immediate therapeutic effect. This approach is especially critical for drugs characterized by slow absorption or extended half-lives, where delaying therapeutic plasma levels could compromise treatment outcomes. By administering a loading dose, clinicians ensure a prompt onset of drug action, even for agents with complex pharmacokinetic profiles.Achieving steady-state...

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Mouse Oocyte Microinjection, Maturation and Ploidy Assessment
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优化卵细胞产量利用机器学习模型进行剂量和触发决定,多中心,前性研究.

Chelsea Canon1, Lily Leibner1, Michael Fanton2

  • 1RMA of New York, 635 Madison Avenue, 10th Floor, New York, NY, 10022, USA.

Scientific reports
|August 20, 2024
PubMed
概括
此摘要是机器生成的。

人工智能 (AI) 协助临床医生优化卵泡刺激激素 (FSH) 剂量和试管婴儿 (IVF) 的触发时间. 虽然在统计学上不显著,但人工智能使用显示出改善结果的趋势,并在试管婴儿周期中减少FSH消耗.

关键词:
人工智能的人工智能是人工智能.临床研究是临床研究.选择胚胎的选择机器学习 机器学习

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科学领域:

  • 生殖医学 生殖医学
  • 临床试验 临床试验
  • 医疗保健中的人工智能

背景情况:

  • 试管婴儿 (IVF) 治疗依赖于精确的荷尔蒙刺激和最佳结果的时间.
  • 确定卵泡刺激激素 (FSH) 的理想起始剂量和触发注射时间可能是复杂的.
  • 人工智能 (AI) 在临床工作流程中为数据驱动的决策支持提供了潜力.

研究的目的:

  • 评估IVF患者的临床结果,当临床医生使用人工智能平台时.
  • 评估AI对确定FSH最佳起始剂量和触发注射时间的影响.
  • 将人工智能辅助和传统试管婴儿治疗方案之间的患者结果进行比较.

主要方法:

  • 进行了一项前性临床试验,使用历史对照组进行.
  • 两个美国生育中心的四名医生参与了这项研究.
  • 治疗组 (N=291) 使用人工智能来测量FSH剂量和触发时间;对照组接受标准护理.
  • 关键结果指标包括使用的FSH总量和检索到的成熟的第II阶段 (MII) 蛋细胞的平均数量.

主要成果:

  • 人工智能辅助组显示出改善结果的趋势,平均12.20 MII卵细胞,对照组为11.24个 (p=0.16).
  • 平均取出的卵细胞为16.01 (AI组) 与14.54 (对照组),表明潜在的益处 (p=0.08).
  • 与对照组 (3846.29IU) 相比,AI组使用的FSH总量 (3671.95IU) 较少,差异为-174.35IU (p=0.13).

结论:

  • 人工智能可以安全地帮助临床医生提炼FSH起始剂量,并在卵巢刺激期间触发注射时间.
  • 医生在试管婴儿中使用人工智能表明,有可能优化获取的MII卵子细胞数量.
  • 进一步的研究可能会证实AI在提高试管婴儿治疗效率和患者结果方面的作用.