Development and validation of a nomogram for tracheotomy decannulation in individuals in a persistent vegetative state: A multicentre study.

Decannulation Intermittent oro-esophageal tube feeding Persistent vegetative state Rehabilitation Tracheostomy

Journal

Annals of physical and rehabilitation medicine
ISSN: 1877-0665
Titre abrégé: Ann Phys Rehabil Med
Pays: Netherlands
ID NLM: 101502773

Informations de publication

Date de publication:
02 Jun 2024
Historique:
received: 27 11 2023
revised: 12 03 2024
accepted: 20 03 2024
medline: 4 6 2024
pubmed: 4 6 2024
entrez: 3 6 2024
Statut: aheadofprint

Résumé

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.

Sections du résumé

BACKGROUND BACKGROUND
Decannulation for people in a persistent vegetative state (PVS) is challenging and relevant predictors of successful decannulation have yet to be identified.
OBJECTIVE OBJECTIVE
This study aimed to explore the predictors of tracheostomy decannulation outcomes in individuals in PVS and to develop a nomogram.
METHOD METHODS
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.
RESULT RESULTS
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.
CONCLUSION CONCLUSIONS
The nomogram can help adjust the treatment and reduce decannulation failure.
REGISTRATION BACKGROUND
Clinical registration is not mandatory for retrospective studies.

Identifiants

pubmed: 38830320
pii: S1877-0657(24)00033-2
doi: 10.1016/j.rehab.2024.101849
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

101849

Informations de copyright

Copyright © 2024 Elsevier Masson SAS. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of competing interest None.

Auteurs

Hongji Zeng (H)

School of Public Health, Zhengzhou University, No. 100 Science Avenue, Zhengzhou City, Henan Province 450000, China.

Xi Zeng (X)

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. Electronic address: bestzhj@gs.zzu.edu.cn.

Nanxi Liu (N)

Sanquan College, No. 688, East Section of Shixiangyang Road, Xinxiang City, Henan Province 453000, China.

Yu Ding (Y)

Department of Neurology, The Second Medical Center, PLA General Hospital, No. 28 Fuxing Road, Beijing City 100000, China.

Junfa Wu (J)

Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, No. 433 Huashan Road, Shanghai City 200000, China.

Fangquan Zhang (F)

Department of Rehabilitation Medicine, Xinyang Central Hospital, No.1 Siyi Road, Xinyang City, Henan Province 464000, China.

Nana Xiong (N)

Peking University Sixth Hospital, No. 51 Huayuan North Road, Beijing City 101499, China.

Classifications MeSH