Kim et al developed a model for predicting acute kidney injury (AKI) following aortic surgery. This can help to identify a patient who may benefit from more aggressive management. The authors are from Samsung Medical Center in Seoul, Republic of Korea.
Patient selection: aortic surgery
Outcome: acute kidney injury (AKI)
Parameters:
(1) age in years
(2) preoperative GFR in mL per min per 1.73 square meter
(3) preoperative left ventricular ejection fraction (LVEF) in percent
(4) operation time in hours
(5) intraoperative oliguria (< 0.5 mL per kg per hour)
(6) intraoperative furosemide use
Parameter |
Finding |
Beta Coefficient |
Points |
age in years |
<= 60 years |
0 |
0 |
|
> 60 years |
0.60 |
1 |
preoperative GFR |
>= 60 |
0 |
0 |
|
< 60 |
0.86 |
1 |
preoperative LVEF |
>= 55% |
0 |
0 |
|
< 55% |
0.73 |
1 |
operation time |
<= 7 hours |
0 |
0 |
|
> 7 hours |
0.97 |
1 |
intraoperative oliguria |
no |
0 |
0 |
|
yes |
1.03 |
1 |
furosemide use |
no |
0 |
0 |
|
yes |
0.69 |
1 |
X =
= SUM(beta coefficients) - 2.54
probability of AKI =
= 1 / (1 + EXP((-1) * X))
point score =
= SUM(points for all 6 parameters)
Interpretation:
• minimum point score: 0
• maximum point score: 6
Points |
Percent AKI |
0 |
7% |
1 |
14% |
2 |
29% |
3 |
43% |
4 |
66% |
5 |
81% |
6 |
NA |
Performance:
• The area under the ROC curve is 0.74
Specialty: Nephrology, Clinical Laboratory