AIMC Topic: Tracheostomy

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Using ML techniques to predict extubation outcomes for patients with central nervous system injuries in the Yun-Gui Plateau.

Scientific reports
No predictive models have been reported for tracheostomy extubation success in plateau region rehabilitation departments. Hence, the primary objective of this retrospective study was to evaluate the predictive capabilities of different models for ext...

Predicting Tracheostomy Need on Admission to the Intensive Care Unit-A Multicenter Machine Learning Analysis.

Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery
OBJECTIVE: It is difficult to predict which mechanically ventilated patients will ultimately require a tracheostomy which further predisposes them to unnecessary spontaneous breathing trials, additional time on the ventilator, increased costs, and fu...

Using artificial intelligence to predict prolonged mechanical ventilation and tracheostomy placement.

The Journal of surgical research
BACKGROUND: Early identification of critically ill patients who will require prolonged mechanical ventilation (PMV) has proven to be difficult. The purpose of this study was to use machine learning to identify patients at risk for PMV and tracheostom...

[The application of a small incision combined with improved percutaneous tracheostomy in difficult tracheostomy].

Zhonghua wei zhong bing ji jiu yi xue
OBJECTIVE: To describe an improved percutaneous tracheostomy combined with conventional tracheostomy technique with result of less trauma and fewer complications, and to explore its application in the patients for whom conventional tracheostomy is di...