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Overview :
Aust et al developed a bedside risk formula for predicting
30-day mortality in surgical patients. This is a simplified version of formulas
based on logistic regression analysis (see previous section). The authors are
from the University of Texas Health Science Center at San Antonio.
Parameters:
(1) serum
albumin in g/dL
(2) ASA
(American Society of Anesthesiologists) patient classification (from 1 to 5, see
above)
(3) age of
the patient
(4) cancer
diagnosis
(5)
emergency surgery
(6)
difficulty or complexity of surgery
|
Parameter |
Finding |
Points |
|
cancer diagnosis |
none |
0 |
|
|
present |
1 |
|
emergency surgery |
no |
0 |
|
|
yes |
1 |
|
surgery difficult or complex |
no |
0 |
|
|
yes |
1 |
risk index =
= ((age of the patient in years) / 40) - (serum albumin in
g/dL) + (ASA classification) + (points for cancer diagnosis) + (points for
emergency surgery) + (points for surgical difficulty) - 5
|
Risk Index |
30-Day
Mortality |
|
-4 |
1% |
|
-3 |
4% |
|
-2 |
12% |
|
-1 |
25% |
|
0 |
50% |
|
+ 1 |
75% |
When this data is analyzed in JMP"
percent mortality (as a whole number from 0 to 100) =
= (3.1786 * ((index)^2)) + (24.4214 * (index)) + 48.0429
Performance:
• The area under the ROC (c index) was 0.82.
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