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使用临床和可穿戴数据预测败血症患者的再入院情况
概括
医院出院前后的活动水平可以在90天内预测败血症再入院风险. 将可穿戴数据与临床信息相结合,可能会提高败血症患者的预测准确度.
科学领域:
- 关键护理医学 关键护理医学
- 数字健康数字健康
- 医疗保健服务研究 医疗服务研究
背景情况:
- 败血症带来了严重的健康负担,医院再入院率很高.
- 身体活动水平与各种条件下的再接收风险有关.
- 了解败血症患者的康复模式对于减少再入院至关重要.
研究的目的:
- 为了研究体育活动水平的预测价值90天的非计划性住院再入院毒症患者.
- 探索将可穿戴设备数据与临床数据相结合的潜力,以提高再接收预测.
主要方法:
- 在医院出院前后分析患者活动水平 (可穿戴数据).
- 统计建模以评估活动模式与90天再录取之间的关联.
- 结合临床和可穿戴数据的探索,以改善预测模型.
主要成果:
- 在出院前和之后的活动水平分布显著预测了败血症患者 (P<1e-3) 的90天计划外再住院情况.
- 初步发现表明,将Fitbit数据与临床测量相结合,可以提高预测模型的性能.
结论:
- 身体活动监测是预测败血症再入院的有希望的工具.
- 可穿戴技术的整合有可能改善败血症护理管理并降低医疗保健成本.
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