Perisse and Strickland developed an algorithm to screen a patient for malaria in a low-to-moderate transmission area. This may be particularly useful in a country with limited health-related resources. The authors are from the University of Maryland in Baltimore, Escola Nacional de Saude Publica in Rio de Janeiro, and the International Centre for Medical Research & Training in Lahore, Pakistan.
Parameters:
(1) history of fever
(2) headache
(3) myalgia
(4) back pain
(5) rigors
(6) cough
(7) nausea or vomiting
(8) splenomegaly (spleen palpated below the left costal margin on inspiration)
|
Parameter |
Finding |
Points |
|
history of fever |
absent |
0 |
|
|
present |
1 |
|
headache |
absent |
0 |
|
|
present |
0.5 |
|
myalgia |
absent |
0.5 |
|
|
present |
0 |
|
back pain |
absent |
0.5 |
|
|
present |
0 |
|
rigors |
absent |
0 |
|
|
present |
1 |
|
cough |
absent |
0.5 |
|
|
present |
0 |
|
nausea or vomiting |
absent |
0 |
|
|
present |
0.5 |
|
splenomegaly |
not palpable |
0 |
|
|
palpable |
1.5 |
total score =
= SUM(points for all 8 parameters)
Interpretation:
• minimum score: 0
• maximum score: 6
• The higher the score the greater the likelihood of malaria.
Performance:
• A patient with a score >= 2 had a moderate sensitivity and specificity (varied with different times of the year and risk groups; sensitivity ranged from 40 to 70% and specificity ranged from 60 to 80%).
• A higher cutoff was more specific but less sensitive.
• Performance is impacted by the prevalence of malaria at the time.
Specialty: Infectious Diseases
