School of Public Health, Zhengzhou University, No. 100 Science Avenue, Zhengzhou City, Henan Province 450000, China.
Department of Rehabilitation Medicine III, The First Affiliated Hospital of Zhengzhou University, No.169-10 Nanyang Road, Zhengzhou City, Henan Province 450000, China; The NHC Key Laboratory of Prevention and Treatment of Cerebrovascular Disease, No.1 Jianshe East Road, Zhengzhou City, Henan Province 450000, China.
Ann Phys Rehabil Med. 2024 Sep;67(6):101849. doi: 10.1016/j.rehab.2024.101849. Epub 2024 Jun 2.
Decannulation for people in a persistent vegetative state (PVS) is challenging and relevant predictors of successful decannulation have yet to be identified.
This study aimed to explore the predictors of tracheostomy decannulation outcomes in individuals in PVS and to develop a nomogram.
In 2022, 872 people with tracheostomy in PVS were retrospectively enrolled and their data was randomly divided into a training set and a validation set in a 7:3 ratio. Univariate and multivariate regression analyses were performed on the training set to explore the influencing factors for decannulation and nomogram development. Internal validation was performed using 5-fold cross-validation. External validation was performed using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA) on both the training and validation sets.
Data from 610 to 262 individuals were used for the training and validation sets, respectively. The multivariate regression analysis found that duration of tracheostomy tube placement≥30 days (Odds Ratio [OR] 0.216, 95 % CI 0.151-0.310), pulmonary infection (OR 0.528, 95 %CI 0.366-0.761), hypoproteinemia (OR 0.669, 95 % CI 0.463-0.967), no passive standing training (OR 0.372, 95 % CI 0.253-0.547), abnormal swallowing reflex (OR 0.276, 95 % CI 0.116-0.656), mechanical ventilation (OR 0.658, 95 % CI 0.461-0.940), intensive care unit (ICU) duration>4 weeks (OR 0.517, 95 % CI 0.332-0.805), duration of endotracheal tube (OR 0.855, 95 % CI 0.803-0.907), older age (OR 0.981, 95 % CI 0.966-0.996) were risk factors for decannulation failure. Conversely, peroral feeding (OR 1.684, 95 % CI 1.178-2.406), passive standing training≥60 min (OR 1.687, 95 % CI 1.072-2.656), private caregiver (OR 1.944, 95 % CI 1.350-2.799) and ICU duration<2 weeks (OR 1.758, 95 % CI 1.173-2.634) were protective factors conducive to successful decannulation. The 5-fold cross-validation revealed a mean area under the curve of 0.744. The ROC curve C-indexes for the training and validation sets were 0.784 and 0.768, respectively, and the model exhibited good stability and accuracy. The DCA revealed a net benefit when the risk threshold was between 0 and 0.4.
The nomogram can help adjust the treatment and reduce decannulation failure.
Clinical registration is not mandatory for retrospective studies.
对于持续性植物状态（PVS）患者的拔管具有挑战性，尚未确定成功拔管的相关预测因素。
本研究旨在探讨 PVS 患者气管切开拔管结局的预测因素，并制定列线图。
2022 年，回顾性纳入了 872 例 PVS 气管切开患者，其数据按 7:3 的比例随机分为训练集和验证集。对训练集进行单因素和多因素回归分析，以探讨影响拔管的因素并进行列线图开发。采用 5 折交叉验证进行内部验证。在训练集和验证集上分别使用接受者操作特征（ROC）曲线、校准曲线和决策曲线分析（DCA）进行外部验证。
分别使用 610 例和 262 例患者的数据进行训练集和验证集分析。多因素回归分析发现，气管切开管放置时间≥30 天（优势比[OR]0.216，95%置信区间[CI]0.151-0.310）、肺部感染（OR 0.528，95%CI 0.366-0.761）、低蛋白血症（OR 0.669，95%CI 0.463-0.967）、无被动站立训练（OR 0.372，95%CI 0.253-0.547）、吞咽反射异常（OR 0.276，95%CI 0.116-0.656）、机械通气（OR 0.658，95%CI 0.461-0.940）、重症监护病房（ICU）时间>4 周（OR 0.517，95%CI 0.332-0.805）、气管内导管放置时间（OR 0.855，95%CI 0.803-0.907）、年龄较大（OR 0.981，95%CI 0.966-0.996）是拔管失败的危险因素。相反，经口喂养（OR 1.684，95%CI 1.178-2.406）、被动站立训练≥60 分钟（OR 1.687，95%CI 1.072-2.656）、私人护理人员（OR 1.944，95%CI 1.350-2.799）和 ICU 时间<2 周（OR 1.758，95%CI 1.173-2.634）是有助于成功拔管的保护因素。5 折交叉验证显示平均曲线下面积为 0.744。训练集和验证集的 ROC 曲线 C 指数分别为 0.784 和 0.768，模型显示出良好的稳定性和准确性。DCA 显示当风险阈值在 0 到 0.4 之间时，净收益较高。
该列线图有助于调整治疗并降低拔管失败的风险。
回顾性研究不需要进行临床注册。
