Haematological parameters, haemozoin-containing leukocytes in Sudanese children with severe Plasmodium falciparum

Magdi M Salih1, Hatim G Eltahir2, Tajeldin M Abdallah3

  • 1University of Khartoum, Khartoum, Sudan. magdi-206@hotmail.com.

Insights

Haemozoin-containing leucocytes (HCL) and specific blood parameters like RDW and PDW can help predict severe malaria in children. This finding aids in early diagnosis and management of severe Plasmodium falciparum malaria.

Area of Science:

  • Malariology
  • Hematology
  • Parasitology

Background:

  • Haemozoin-containing leucocytes (HCL) are potential biomarkers for predicting severe malaria.
  • Early identification of severe malaria cases is crucial for timely intervention.

Purpose of the Study:

  • To investigate haematological values and HCL in children with severe Plasmodium falciparum malaria.
  • To assess the predictive value of HCL and blood parameters for severe malaria.

Main Methods:

  • A case-control study was conducted in Sudan involving children with severe malaria, uncomplicated malaria, and healthy controls.
  • Haematological parameters including haemoglobin, platelet counts, lymphocyte counts, red cell distribution width (RDW), and platelet distribution width (PDW) were analyzed.
  • The presence of haemozoin in monocytes (HCL) was quantified, and Receiver Operating Characteristic (ROC) curves were used to evaluate predictive values.

Main Results:

  • Children with severe malaria exhibited significantly lower haemoglobin and platelet counts, and higher lymphocyte counts, RDW, and PDW compared to those with uncomplicated malaria.
  • A high percentage of children with severe malaria (91.0%) and uncomplicated malaria (84.6%) tested positive for HCL.
  • ROC curve analysis indicated fair predictability for severe malaria using haemoglobin, lymphocytes, PDW, and HCL.

Conclusions:

  • Red cell distribution width (RDW), platelet distribution width (PDW), and haemozoin-containing leucocytes (HCL) show potential as predictors of severe malaria.
  • These parameters can aid in the clinical assessment and prediction of severe malaria in endemic settings.
Abstract