From: Using machine learning methods to predict in-hospital mortality of sepsis patients in the ICU
Variables | Maximum scores | |
---|---|---|
Acute physiology | Temperature | 3 |
Heart rate | 11 | |
Systolic blood pressure | 13 | |
WBC | 12 | |
Bilirubin | 9 | |
Serum sodium | 5 | |
Serum potassium | 3 | |
Serum bicarbonate | 6 | |
BUN | 10 | |
Urine output | 11 | |
PaO2aor FiO2a | 11 | |
GCS | 26 | |
Chronic health status | AIDSa | 17 |
Haematologic malignancy | 10 | |
Metastatic cancer | 9 | |
Other | Age | 18 |
Type of admission | 8 | |
Overall score | Â | 182 |