开发和验证一种预测模型,用于慢性阻塞性肺病患者的急性恶化,并患有并发性失眠症
1Chaohu Hospital Affiliated with Anhui Medical University, Chaohu, China.
Frontiers in medicine
|April 7, 2025
概括
一个新的模型预测慢性阻塞性肺病 (AECOPD) 急性恶化患者的失眠. 关键因素包括PSQI等级,婚姻状况,白细胞计数和氨酸细胞百分比,有助于早期检测.
科学领域:
- 呼吸系统医学 呼吸系统医学
- 睡眠医学 睡眠医学
- 临床预测建模临床预测建模
背景情况:
- 失眠是慢性阻塞性肺病 (AECOPD) 急性恶化患者的常见并发症.
- 在AECOPD患者中早期识别和治疗失眠对于改善结果至关重要.
- 在这个特定人群中,对失眠的现有预测工具是有限的.
研究的目的:
- 开发和验证一个强大的风险预测模型,用于估计AECOPD患者失眠的可能性.
- 确定与AECOPD患者失眠相关的关键临床变量.
- 为临床医生提供一个工具,以帮助早期发现失眠.
主要方法:
- 对253名AECOPD患者的前性研究,随机分配到培训 (70%) 和测试 (30%) 组.
- 最小绝对收缩和选择运算符 (LASSO) 回归用于识别显著预测因素.
- 为可视化开发的诺米图,使用霍斯默-莱梅肖测试,ROC曲线,校准曲线和决策曲线分析 (DCA) 进行验证.
主要成果:
- 确定为显著预测因素的四个变量:PSQI等级,寡妇婚姻状况,白细胞 (WBC) 计数和乙素百分比 (EOS%).
- 诺米图表表现出了出色的预测性能,AUC为0.987 (训练) 和0.933 (测试).
- 校准曲线和Hosmer-Lemeshow测试证实,预测和观察结果之间有很强的一致性;DCA表明了卓越的临床效用.
结论:
- 一个经过验证的风险预测模型,包括PSQI等级,婚姻状况,白细胞计数和EOS%,有效估计了AECOPD患者的失眠概率.
- 开发的诺米图谱具有很高的预测准确性和临床适用性.
- 这种模型可以指导在AECOPD人群中早期识别和管理失眠的策略.
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