Our results showed that the XGBoost model could be a suitable model for predicting RICU mortality with easy-to-collect variables at admission and help intensivists improve clinical decision-making for RICU patients. We found that higher NT-proBNP can be a good indicator of poor prognosis.
Keyphrases
- poor prognosis
- intensive care unit
- machine learning
- end stage renal disease
- long non coding rna
- decision making
- ejection fraction
- emergency department
- newly diagnosed
- chronic kidney disease
- risk factors
- peritoneal dialysis
- prognostic factors
- artificial intelligence
- big data
- extracorporeal membrane oxygenation
- patient reported
- respiratory tract