解读无呼吸的未来:一种新的方法来预测患有吉兰-巴雷综合征的儿童的呼吸衰竭
Zhiwei Yu1, Hanyu Luo2, Yuhang Li2
1Department of Neurology, Children's Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing, China; Chongqing Key Laboratory of Child Neurodevelopment and Cognitive Disorders, Chongqing, China; Big Data Engineering Center, Children's Hospital of Chongqing Medical University, Chongqing, China.
在中国开发了一种针对儿科吉兰-巴雷综合征 (GBS) 呼吸衰竭的新预测模型. 这种模型结合了血小板与淋巴细胞比率 (PLR),有望在年轻GBS患者中改善风险预测.
科学领域:
- 儿科神经学 儿科神经学
- 呼吸系统医学 呼吸系统医学
- 临床预测建模临床预测建模
- 吉兰 - 巴雷综合征 (GBS)
背景情况:
- 现有的临床预测模型用于儿童吉兰-巴雷综合征 (GBS) 的呼吸衰竭在亚洲人群中的适用性有限.
- 需要验证的模型来预测中国儿科GBS患者的呼吸衰竭风险.
研究的目的:
- 开发和验证中国儿科GBS患者呼吸衰竭的临床预测模型.
- 为了评估Erasmus GBS呼吸不足评分 (EGRIS) -儿童评分在这个人群中的有效性.
- 评估免疫生物标志物的有用性,特别是血小板与淋巴细胞的比率 (PLR),用于风险预测.
主要方法:
- 在重庆医科大学儿童医院对175名儿科GBS患者 (2014-2022) 的回顾性研究.
- 后勤回归被用来识别预测因素和构建名ograms (包括基于Web的动态版本).
- 模型性能使用净重新分类指数和综合歧视性改进指数进行了比较,并进行了引导验证.
主要成果:
- 在研究的儿科GBS患者中,23人 (13%) 患有呼吸不全.
- 确定新模型的关键预测因素是年龄,腹筋麻,双侧部曲和血小板与淋巴细胞比率 (PLR).
- 开发的诺米图实现了0.899.9的AUC. EGRIS-Kids得分的AUC为0.849,其中PLR纳入显示增量值 (12.51%,P=0.03).
结论:
- 这项研究为中国儿科GBS患者的EGRIS-Kids评分提供了第一个外部验证.
- 结合PLR的新型预测模型证明了预测呼吸衰竭的有希望的附加价值.
- 建议对新开发的预测模型进行进一步的外部验证.
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