在现实世界中为临床肥胖服务开发决策辅助:DACOS全国试点研究
Evan Atlantis1, Nic Kormas2,3, Milan Piya3,4
1School of Health Sciences, Western Sydney University, Campbelltown Campus, Locked Bag 1797, Penrith, NSW, Australia. e.atlantis@westernsydney.edu.au.
Obesity surgery
|March 12, 2024
概括
这项研究开发了DACOS,该工具使用澳大利亚的健康数据预测腹部手术或非手术护理后的体重减轻. 它确定了患者讨论的关键预测因素.
科学领域:
- 肥胖研究的研究.
- 医疗信息学 医疗信息学
- 临床决策支持 临床决策支持
背景情况:
- 肥胖管理需要有效的工具来预测治疗结果.
- 减肥手术和非手术干预是肥胖的主要治疗方法.
- 现实世界的数据可以为减肥的预测模型提供信息.
研究的目的:
- 开发一种帮助决策的工具 (DACOS),用于预测减肥.
- 利用澳大利亚现实世界的健康数据进行模型开发.
- 帮助临床医生与患者讨论减肥预测因素.
主要方法:
- 从2015年至2020年对患者记录 (16岁以上) 的分析.
- 主要结局:6个月和9个月/12个月的百分比总体重减轻 (%TWL).
- 使用统计和临床判断开发的多重线性回归模型用于预测器选择.
主要成果:
- 腹腔外科手术的TWL% (19-22%) 比非手术治疗 (5%) 高.
- 确定的主要预测因素包括减肥手术,BMI,抑郁,焦虑,饮食障碍,2型糖尿病和脂肪肝.
- 模型准确度在55-58%之间,对于目标减肥的灵敏度和特异性各不相同.
结论:
- 该DACOS工具可以帮助临床医生在患者咨询.
- 预测者在手术和非手术减肥途径之间有所不同.
- 现实世界的数据为减肥轨迹提供了宝贵的见解.
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