title: Predictive value of fever and palmar pallor for P. falciparum parasitaemia in children from an endemic area.
abstract: BACKGROUND
  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.
authors.affiliation: Infectious Disease Epidemiology, Bernhard-Nocht-Institute for Tropical Medicine, Hamburg, Germany. vinnemeier@bni-hamburg.de
authors.forename: Christof David
authors.initials: CD
authors.lastname: Vinnemeier
authors.forename: Norbert Georg
authors.initials: NG
authors.lastname: Schwarz
authors.forename: Nimako
authors.initials: N
authors.lastname: Sarpong
authors.forename: Wibke
authors.initials: W
authors.lastname: Loag
authors.forename: Samuel
authors.initials: S
authors.lastname: Acquah
authors.forename: Bernard
authors.initials: B
authors.lastname: Nkrumah
authors.forename: Frank
authors.initials: F
authors.lastname: Huenger
authors.forename: Yaw
authors.initials: Y
authors.lastname: Adu-Sarkodie
authors.forename: Jürgen
authors.initials: J
authors.lastname: May
mesh_terms: D000465:Algorithms; D002675:Child, Preschool; D019353:Endemic Diseases; D005260:Female; D005334:Fever / Q000150:complications*; D006801:Humans; D007223:Infant; D016778:Malaria, Falciparum / Q000150:complications / Q000175:diagnosis* / Q000453:epidemiology; D008297:Male; D010167:Pallor / Q000150:complications*; D018512:Parasitemia / Q000150:complications / Q000175:diagnosis* / Q000453:epidemiology; D010963:Plasmodium falciparum / Q000472:pathogenicity*; D011237:Predictive Value of Tests; D012044:Regression Analysis