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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
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Parameter
|
Finding
|
Points
|
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cancer diagnosis
|
none
|
0
|
|
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present
|
1
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emergency surgery
|
no
|
0
|
|
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yes
|
1
|
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surgery difficult or complex
|
no
|
0
|
|
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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%
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-3
|
4%
|
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-2
|
12%
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-1
|
25%
|
|
0
|
50%
|
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+ 1
|
75%
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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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