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Prediction Models for Dysphagia in Intensive Care Unit after Mechanical Ventilation: A Systematic Review and Meta-analysis
被引:1
作者:
Chen, Juan
[1
]
Lu, Guangyu
[2
]
Wang, Zhiyao
[3
,4
]
Zhang, Jingyue
[1
]
Ding, Jiali
[1
]
Zeng, Qingping
[1
]
Chai, Liying
[1
,2
]
Zhao, Li
[1
,2
]
Yu, Hailong
[3
,4
,5
]
Li, Yuping
[3
,4
,6
]
机构:
[1] Yangzhou Univ, Sch Nursing & Publ Hlth, Yangzhou, Peoples R China
[2] Yangzhou Univ, Med Coll, Inst Publ Hlth, Yangzhou, Peoples R China
[3] Yangzhou Univ, Dept Neurosurg, Clin Med Coll, Yangzhou, Peoples R China
[4] Yangzhou Univ, Dept Neurosurg, Neuro Intens Care Unit, Clin Med Coll, Yangzhou, Peoples R China
[5] Northern Jiangsu Peoples Hosp, Dept Neurol, Yangzhou, Peoples R China
[6] Yangzhou Univ, Clin Med Coll, Dept Neurosurg, Neurointens Care Unit, Yangzhou 225001, Jiangsu, Peoples R China
基金:
中国国家自然科学基金;
关键词:
dysphagia;
intensive care;
invasive mechanical ventilation;
prediction models;
systematic review;
OROPHARYNGEAL DYSPHAGIA;
RISK;
APPLICABILITY;
DIAGNOSIS;
PROBAST;
IMPACT;
BIAS;
TOOL;
D O I:
10.1002/lary.30931
中图分类号:
R-3 [医学研究方法];
R3 [基础医学];
学科分类号:
1001 ;
摘要:
ObjectiveDysphagia is a common condition that can independently lead to death in patients in the intensive care unit (ICU), particularly those who require mechanical ventilation. Despite extensive research on the predictors of dysphagia development, consistency across these studies is lacking. Therefore, this study aimed to identify predictors and summarize existing prediction models for dysphagia in ICU patients undergoing invasive mechanical ventilation. MethodsWe searched five databases: PubMed, EMBASE, Web of Science, Cochrane Library, and the China National Knowledge Infrastructure. Studies that developed a post-extubation dysphagia risk prediction model in ICU were included. A meta-analysis of individual predictor variables was performed with mixed-effects models. The risk of bias was assessed using the prediction model risk of bias assessment tool (PROBAST). ResultsAfter screening 1,923 references, we ultimately included nine studies in our analysis. The most commonly identified risk predictors included in the final risk prediction model were the length of indwelling endotracheal tube & GE;72 h, Acute Physiology and Chronic Health Evaluation (APACHE) II score & GE;15, age & GE;65 years, and duration of gastric tube & GE;72 h. However, PROBAST analysis revealed a high risk of bias in the performance of these prediction models, mainly because of the lack of external validation, inadequate pre-screening of variables, and improper treatment of continuous and categorical predictors. ConclusionsThese models are particularly susceptible to bias because of numerous limitations in their development and inadequate external validation. Future research should focus on externally validating the existing model in ICU patients with varying characteristics. Moreover, assessing the acceptance and effectiveness of the model in clinical practice is needed. Level of EvidenceN/A Laryngoscope, 2023
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页码:517 / 525
页数:9
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