Mehta et al developed a model for predicting mortality for a patient in the intensive care unit (ICU) with acute renal failure. This can help identify a patient who may benefit from more aggressive management. The authors are from the University of California San Diego, University of California San Francisco, Cleveland Clinic, Vanderbilt University and Maine Medical Center in Portland.
Parameters:
(1) age of the patient in years
(2) gender
(3) serum BUN in mg/dL
(4) serum creatinine in mg/dL
(5) hematologic failure (white blood cell count <= 1,000 per µL; platelet count < 20,000 per µL; hematocrit < 20%; require platelet transfusions to keep the platelet count above 20,000 per µL)
(6) liver failure (acute liver failure with serum liver function tests greater than 2 times the upper limit of normal; chronic liver disease with worsening in liver function and the presence of encephalopathy)
(7) respiratory failure (respiratory rate <= 5 breaths per minute or >= 49 breaths per minute; PaCO2 >= 50 mm Hg; AaDO2 >= 350 mm Hg; ventilator dependent after 24 hours of oxygen system failure)
(8) heart rate in beats per minute
(9) urine output in mL per day
Parameter |
Finding |
Points |
gender |
male |
1 |
|
female |
0 |
hematologic failure |
absent |
0 |
|
present |
1 |
liver failure |
absent |
0 |
|
present |
1 |
respiratory failure |
absent |
0 |
|
present |
1 |
X =
= (0.0170 * (age in years)) + (0.8605 * (points for gender)) + (0.0144 * (serum BUN)) – (0.3398 * (serum creatinine)) + (1.2242 * (points for hematologic failure)) + (1.1183 * (points for liver failure)) + (0.9637 * (points for respiratory failure)) + (0.0119 * (heart rate)) – (0.4432 * LOG(urine output)) – 0.7207
where:
• I am assuming that log(urine output) refers to LOG10.
probability of death =
= 1 / (1 + EXP((-1) * X))
Specialty: Nephrology, Clinical Laboratory