A prospective evaluation of a clinical algorithm for the diagnosis of malaria in Gambian children.

Diagnosis of clinical malaria remains difficult, especially in areas where a high proportion of the asymptomatic population have parasitaemia, for the symptoms and signs of malaria overlap with those of other common childhood diseases, such as acute lower respiratory tract infections. However, a study of symptoms and signs in a group of children who presented to Farafenni Health Centre, The Gambia with a history of recent fever identified a group of signs and symptoms which were strong predictors of malaria as opposed to other febrile illnesses. Using these predictors, an algorithm was developed which could be used by fieldworkers and which had a similar sensitivity and specificity for the diagnosis of malaria as that of an experienced paediatrician working without laboratory support. This algorithm has been validated prospectively on 518 children who presented to the Medical Research Council clinic at Basse, The Gambia with fever or a history of recent fever during a 10-month period. A fieldworker obtained a detailed history from the parent or guardian of each child and performed a clinical examination which included measurement of axillary temperature and respiratory rate. Packed cell volume was measured and a thick smear was examined for malaria parasites. A malaria score, based on the presence or absence of malaria-related signs and symptoms, was determined for 382 children who were seen at the clinic during the high transmission season. Using the cut-off score which was optimal during the previous retrospective study, a sensitivity of 70% and a specificity of 77% for a diagnosis of malaria was obtained. The optimal cut-off score for the Basse population was a score of 7; this gave a sensitivity of 88% and a specificity of 62%, figures comparable to those obtained by an experienced paediatrician without laboratory support.