Mehta et al reported an algorithm for predicting bleeding after percutaneous coronary intervention (PCI). This can help to identify a patient who may benefit from more aggressive management. The authors are from Mid America Heart Institute, Saint Luke's Hospital Kansas City, Duke Clinical Research Institute and the National Cardiovascular Data Registry.
Patient selection: PCI
Outcome: bleeding
Parameters:
(1) acute coronary syndrome (ACS) type
(2) cardiogenic shock
(3) sex
(4) history of previous CHF
(5) history of previous PCI
(6) CHF NYHA class
(7) peripheral vascular disease
(8) age in years
(9) estimated GFR in mL per min per 1.73 square meter
Parameter
Finding
Points
ACS type
ST-segment AMI
10
NSTEMI
3
unstable angina
3
other
0
cardiogenic shock
no
0
yes
8
sex
male
0
female
6
history of previous CHF
no
0
yes
5
history of previous PCI
no
4
yes
0
CHF
none
0
NYHA I to III
0
NYHA IV
4
peripheral arterial disease
no
0
yes
2
age in years
< 66 years
0
66 to 75 years
2
76 to 84.9 years
5
>= 85 years
8
eGFR
>= 90
0
< 90
INT((90-GFR)/10)
total score =
= SUM(points for all 9 parameters)
Interpretation:
• minimum score: 0
• maximum score: 55
• The higher the score the greater the risk of bleeding.
Score
Risk Group
Average Bleeding Risk
<= 7
low
0.63%
8 to 17
intermediate
1.8%
>= 18
high
5.1%
Score
Percent Bleeding
0 or 1
0.3
2 or 3
0.45
4 or 5
0.55
6 or 7
0.82
8 or 9
1.04
10 or 11
1.4
12 or 13
1.8
14 or 15
2.2
16 or 17
2.6
18 or 19
3.4
20 or 21
3.3
22 or 23
4.7
>= 24
8.2
Performance:
• The area under the ROC curve is 0.72.
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