Clinical diagnosis of Plasmodium falciparum among children with history of fever, Sindh, Pakistan.
OBJECTIVE
To identify clinical predictors for malaria and develop a clinical algorithm to more accurately identify malaria from non-malaria cases.


METHODS
Four hundred thirty eight children aged 6-120 months attending the rural health center between August 15 and October 5, 1997, in Jhangara town of district Dadu, Sindh were recruited. A standard questionnaire was used to record symptoms and duration of child's illness. Each child was physically examined, had their axillary temperature measured, and blood samples were collected from which Giemsa stained thick and thin blood films were prepared and examined for presence of Plasmodium parasites. The sensitivity and specificity of several candidate algorithms for parasitemia were evaluated using various combinations of identified predictors.


RESULTS
Twenty-six of 438 children (6%) were slide positive for malaria. An algorithm comprised of fever 3 days duration and (absence of cough or having rigors) had 100% sensitivity and 63% specificity for detecting P. falciparum.


CONCLUSIONS
In this low malaria prevalence region, restricting the diagnosis of malaria to persons who had >3 days of fever and absence of cough or rigors, remained highly sensitive but was more specific than current practice. If validated prospectively, this algorithm could reduce misdiagnosis and mis-treatment.
Hozhabri
Siroos
S
Department of Community Health Sciences, The Aga Khan University, Karachi, Pakistan. siroos.hozhabri@aku.edu
Luby
Stephen P
SP
Rahbar
Mohammad H
MH
Akhtar
Saeed
S
D000465:Algorithms; D000818:Animals; D002648:Child; D002675:Child, Preschool; D005334:Fever / Q000469:parasitology*; D006801:Humans; D007223:Infant; D016778:Malaria, Falciparum / Q000175:diagnosis* / Q000469:parasitology / Q000503:physiopathology*; D010154:Pakistan; D018512:Parasitemia / Q000175:diagnosis / Q000469:parasitology / Q000503:physiopathology; D010963:Plasmodium falciparum / Q000302:isolation & purification; D011237:Predictive Value of Tests; D012423:Rural Health; D012680:Sensitivity and Specificity