Research Unit, Hammel Neurorehabilitation Centre and University Research Clinic, Hammel, Denmark.
Respir Care. 2020 Nov;65(11):1678-1686. doi: 10.4187/respcare.07497. Epub 2020 Apr 7.
Clinicians are often required to provide a qualified guess on the probability of decannulation in estimating patients' rehabilitation potential and relaying information about prognosis to patients and next of kin. The objective of this study was to use routinely gathered clinical data to develop a prognostic model of time to decannulation in subjects with acquired brain injury, for direct implementation in clinical practice.
Data from a large cohort including 574 tracheostomized subjects admitted for neurorehabilitation were analyzed using discrete time-to-event analysis with logit-link. Within this model, a reference hazard function was modeled using restricted cubic splines, and estimates were presented using odds ratios (95% CIs).
A total of 411 subjects (72%) were decannulated within a median of 27 d (interquartile range 16-49) at the rehabilitation hospital. The prognostic model for decannulation included age, diagnosis, days from injury until admission for rehabilitation, swallowing, and overall functional level measured with the Early Functional Abilities score. Among these, the strongest predictors for decannulation were age and a combination of overall functional abilities combined with swallowing ability.
A prognostic model for decannulation was developed using routinely gathered clinical data. Based on the model, an online graphical user interface was applied, in which the probability of decannulation within days is calculated along with the statistical uncertainty of the probability. Furthermore, a layman's interpretation is provided. The online tool was directly implemented in clinical practice at the rehabilitation hospital, and is available through this link: (http://www.hospitalsenhedmidt.dk/regionshospitalet-hammel/research-unit/Prognosissoftware/).
临床医生经常需要在评估患者康复潜力和向患者及其家属传达预后信息时，对拔管的概率做出有根据的猜测。本研究旨在使用常规收集的临床数据，为获得性脑损伤患者建立一个预测拔管时间的预后模型，以便直接在临床实践中实施。
对包括 574 例因神经康复而接受气管切开术的患者的大型队列数据进行离散时间事件分析，采用对数链接。在该模型中，参考风险函数采用限制性立方样条进行建模，并使用优势比（95%置信区间）进行估计。
共有 411 例患者（72%）在康复医院中位 27 天（四分位距 16-49）内拔管。拔管的预后模型包括年龄、诊断、从受伤到康复入院的天数、吞咽能力和使用早期功能能力评分测量的整体功能水平。其中，年龄和整体功能能力与吞咽能力相结合是拔管的最强预测因素。
使用常规收集的临床数据开发了一个用于拔管的预后模型。在此模型的基础上，应用了一个在线图形用户界面，其中计算了在 天内拔管的概率及其概率的统计不确定性。此外，还提供了一个非专业人士的解释。该在线工具已直接在康复医院的临床实践中实施，并可通过以下链接获得：（http://www.hospitalsenhedmidt.dk/regionshospitalet-hammel/research-unit/Prognosissoftware/）。
