Chung-Esaki et al developed a model for predicting endocarditis in a febrile injection drug user. This can help to identify a patient who may require more aggressive management. The authors are from Stanford University, University of California at San Francisco and Alameda County Medical Center in Oakland.
Patient selection: injection drug user > 17 years old with fever >= 38°C
Parameters:
(1) tachycardia (heart rate > 100 bpm at any time during the first 6 hours in the ED)
(2) cardiac murmur
(3) skin infection (abscess or cellulitis)
Parameter |
Finding |
Points |
tachycardia |
absent |
0 |
|
present |
1 |
cardiac murmur |
absent |
0 |
|
present |
1 |
skin infection |
absent |
0 |
|
present |
1 |
X =
= (0.63 * (points for tachycardia)) + (0.61 * (points for murmur)) – (points for skin infection)) – 2.61
probability of endocarditis =
= 1 / (1 + EXP((-1) * X))
Alternatively a point score was developed
score =
= (points for tachycardia) + (points for cardiac murmur) – (points for skin infection
Interpretation:
• minimum score: -1
• maximum score: 2
• The higher the score the greater the risk of endocarditis.
Score |
Endocarditis Risk |
-1 |
3% |
0 |
5-7% |
1 |
9-10% |
2 |
20% |
Specialty: Infectious Diseases, Cardiology
ICD-10: ,