Prediction Models for Dysphagia in Intensive Care Unit after Mechanical Ventilation: A Systematic Review and Meta-analysis
Juan Chen MD
School of Nursing and Public Health, Yangzhou University, Yangzhou, China
Search for more papers by this authorGuangyu Lu PhD
Institute of Public Health, Medical College of Yangzhou University, Yangzhou University, Yangzhou, China
Search for more papers by this authorZhiyao Wang MD
Department of Neurosurgery, Clinical Medical College of Yangzhou University, Yangzhou, China
Neuro Intensive Care Unit, Department of Neurosurgery, Clinical Medical College of Yangzhou University, Yangzhou, China
Search for more papers by this authorJingyue Zhang MD
School of Nursing and Public Health, Yangzhou University, Yangzhou, China
Search for more papers by this authorJiali Ding MD
School of Nursing and Public Health, Yangzhou University, Yangzhou, China
Search for more papers by this authorQingping Zeng MD
School of Nursing and Public Health, Yangzhou University, Yangzhou, China
Search for more papers by this authorLiying Chai MD
School of Nursing and Public Health, Yangzhou University, Yangzhou, China
Institute of Public Health, Medical College of Yangzhou University, Yangzhou University, Yangzhou, China
Search for more papers by this authorLi Zhao MD
School of Nursing and Public Health, Yangzhou University, Yangzhou, China
Institute of Public Health, Medical College of Yangzhou University, Yangzhou University, Yangzhou, China
Search for more papers by this authorHailong Yu PhD
Neuro Intensive Care Unit, Department of Neurosurgery, Clinical Medical College of Yangzhou University, Yangzhou, China
Department of Neurology, Northern Jiangsu People's Hospital, Yangzhou, China
Search for more papers by this authorCorresponding Author
Yuping Li PhD
Department of Neurosurgery, Clinical Medical College of Yangzhou University, Yangzhou, China
Neuro Intensive Care Unit, Department of Neurosurgery, Clinical Medical College of Yangzhou University, Yangzhou, China
Send correspondence to Yuping Li, Neuro-Intensive Care Unit, Department of Neurosurgery, Clinical Medical College, Yangzhou University, Jiangsu 225001, China. Email: [email protected]
Search for more papers by this authorJuan Chen MD
School of Nursing and Public Health, Yangzhou University, Yangzhou, China
Search for more papers by this authorGuangyu Lu PhD
Institute of Public Health, Medical College of Yangzhou University, Yangzhou University, Yangzhou, China
Search for more papers by this authorZhiyao Wang MD
Department of Neurosurgery, Clinical Medical College of Yangzhou University, Yangzhou, China
Neuro Intensive Care Unit, Department of Neurosurgery, Clinical Medical College of Yangzhou University, Yangzhou, China
Search for more papers by this authorJingyue Zhang MD
School of Nursing and Public Health, Yangzhou University, Yangzhou, China
Search for more papers by this authorJiali Ding MD
School of Nursing and Public Health, Yangzhou University, Yangzhou, China
Search for more papers by this authorQingping Zeng MD
School of Nursing and Public Health, Yangzhou University, Yangzhou, China
Search for more papers by this authorLiying Chai MD
School of Nursing and Public Health, Yangzhou University, Yangzhou, China
Institute of Public Health, Medical College of Yangzhou University, Yangzhou University, Yangzhou, China
Search for more papers by this authorLi Zhao MD
School of Nursing and Public Health, Yangzhou University, Yangzhou, China
Institute of Public Health, Medical College of Yangzhou University, Yangzhou University, Yangzhou, China
Search for more papers by this authorHailong Yu PhD
Neuro Intensive Care Unit, Department of Neurosurgery, Clinical Medical College of Yangzhou University, Yangzhou, China
Department of Neurology, Northern Jiangsu People's Hospital, Yangzhou, China
Search for more papers by this authorCorresponding Author
Yuping Li PhD
Department of Neurosurgery, Clinical Medical College of Yangzhou University, Yangzhou, China
Neuro Intensive Care Unit, Department of Neurosurgery, Clinical Medical College of Yangzhou University, Yangzhou, China
Send correspondence to Yuping Li, Neuro-Intensive Care Unit, Department of Neurosurgery, Clinical Medical College, Yangzhou University, Jiangsu 225001, China. Email: [email protected]
Search for more papers by this authorJuan Chen, Guangyu Lu contributed equally to this study.
The authors have no other funding, financial relationships, or conflicts of interest to disclose.
Abstract
Objective
Dysphagia 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.
Methods
We 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).
Results
After 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 ≥72 h, Acute Physiology and Chronic Health Evaluation (APACHE) II score ≥15, age ≥65 years, and duration of gastric tube ≥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.
Conclusions
These 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 Evidence
NA Laryngoscope, 134:517–525, 2024
Supporting Information
| Filename | Description |
|---|---|
| lary30931-sup-0001-supinfo.docxWord 2007 document , 878.4 KB | Appendix 1. Search strategy and databases. Appendix 2. The forest plot of PED-related variables. Appendix 3. Quality assessment of included studies using the PROBAST scale for predictive modeling studies. |
Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
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