Construction and validation of a tracheostomy prediction model in mechanically ventilated stroke patients and the impact of early versus late tracheostomy on clinical outcomes: an IPTW-based analysis - Report - MDSpire
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Development and assessment of a predictive model for tracheostomy in stroke patients on mechanical ventilation, along with the effects of early versus delayed tracheostomy on clinical outcomes: an IPTW-based evaluation
Clinical Report: Predictive Model for Tracheostomy in Stroke Patients
Overview
This study developed a predictive model for tracheostomy in mechanically ventilated stroke patients and assessed the impact of early versus delayed tracheostomy on clinical outcomes. The model demonstrated good performance in predicting tracheostomy risk.
Background
Stroke is a leading cause of death and disability globally, with a significant number of patients requiring prolonged mechanical ventilation. Tracheostomy is a common intervention in these cases, associated with both benefits and risks. Understanding the optimal timing for tracheostomy is crucial for improving patient outcomes.
Data Highlights
Predictor
p-value
Midline shift
< 0.05
Hypoalbuminemia
< 0.05
Admission GCS score
< 0.05
CRP
< 0.05
PNI
< 0.05
Key Findings
Independent predictors for tracheostomy included midline shift, hypoalbuminemia, admission GCS score, CRP, and PNI.
The predictive model achieved an AUC of 0.855 in the training set and 0.849 in the validation set.
No significant effect was observed on post-tracheostomy ventilation duration, antibiotic use duration, total hospital stay, or hospitalization costs.
Clinical Implications
The developed nomogram allows for individualized risk assessment for tracheostomy in stroke patients on mechanical ventilation.
Conclusion
The predictive model for tracheostomy in stroke patients shows potential for clinical application. Further validation is warranted.
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