Predicting the need of tracheostomy amongst patients admitted to an intensive care unit: A multivariate model

Keyphrases

• Chile 33%
• Chronic Pulmonary Disease 33%
• Early Detection 33%
• Early Predictors 33%
• Early Tracheostomy 66%
• Hypernatremia 33%
• Intensive Care Unit 100%
• Intubated Patients 33%
• Intubation 33%
• Invasive Mechanical Ventilation 100%
• Logistic Regression Analysis 33%
• Multivariate Model 100%
• Old Age 33%
• Patient Identification 33%
• Patient Selection 33%
• Patients at Risk 33%
• Potential Confounders 33%
• Prolonged Intubation 66%
• Regression Model 33%
• Retrospective Cohort Study 33%
• Tracheal Stenosis 33%
• Tracheostomy 100%
• Ventilatory Support 33%

Nursing and Health Professions

• Artificial Respiration 100%
• Chronic Lung Disease 33%
• Cohort Analysis 33%
• Hypernatremia 33%
• Infection 33%
• Intensive Care Unit 100%
• Intubation 100%
• Multivariate Logistic Regression Analysis 33%
• Public Hospital 33%
• Trachea Stenosis 33%
• Tracheostomy 100%

Medicine and Dentistry

• Artificial Respiration 100%
• Chronic Lung Disease 33%
• Hypernatremia 33%
• Infection 33%
• Intensive Care Unit 100%
• Intubation 100%
• Multivariate Logistic Regression Analysis 33%
• Retrospective Cohort Study 33%
• Trachea Stenosis 33%
• Tracheostomy 100%