Introduction: Although the incidence of Plasmodium falciparum malaria in some parts of sub-Saharan Africa is reported to decline and other conditions, causing similar symptoms as clinical malaria are gaining in relevance, presumptive anti-malarial treatment is still common. This study traced for age-dependent signs and symptoms predictive for P. falciparum parasitaemia.

Methods: In total, 5447 visits of 3641 patients between 2-60 months of age who attended an outpatient department (OPD) of a rural hospital in the Ashanti Region, Ghana, were analysed. All Children were examined by a paediatrician and a full blood count and thick smear were done. A Classification and Regression Tree (CART) model was used to generate a clinical decision tree to predict malarial parasitaemia a7nd predictive values of all symptoms were calculated.

Results: Malarial parasitaemia was detected in children between 2-12 months and between 12-60 months of age with a prevalence of 13.8% and 30.6%, respectively. The CART-model revealed age-dependent differences in the ability of the variables to predict parasitaemia. While palmar pallor was the most important symptom in children between 2-12 months, a report of fever and an elevated body temperature of ≥37.5°C gained in relevance in children between 12-60 months. The variable palmar pallor was significantly (p<0.001) associated with lower haemoglobin levels in children of all ages. Compared to the Integrated Management of Childhood Illness (IMCI) algorithm the CART-model had much lower sensitivities, but higher specificities and positive predictive values for a malarial parasitaemia.

Conclusions: Use of age-derived algorithms increases the specificity of the prediction for P. falciparum parasitaemia. The predictive value of palmar pallor should be underlined in health worker training. Due to a lack of sensitivity neither the best algorithm nor palmar pallor as a single sign are eligible for decision-making and cannot replace presumptive treatment or laboratory diagnosis.