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Risk factors of chloroquine resistance in Plasmodium falciparum malaria
F I Hess1, A Iannuzzi, J Leafasia
1Department of Tropical Medicine, University of Munich, Germany.
Insights
Young age, high parasite density, normal spleen size, malnutrition, and gametocytes predict chloroquine resistance in Plasmodium falciparum malaria. These easily measurable factors aid early risk identification for effective treatment decisions.
Area of Science:
- Tropical Medicine
- Infectious Diseases
- Malariology
Background:
- Chloroquine resistance in Plasmodium falciparum poses a significant challenge to malaria treatment.
- Identifying patient-related risk factors can improve early diagnosis and management.
Purpose of the Study:
- To identify patient-related risk factors associated with chloroquine resistance in Plasmodium falciparum malaria.
- To provide easily measurable indicators for health workers to assess resistance risk.
Main Methods:
- A case-control study was conducted in North Guadalcanal, Solomon Islands.
- 38 Plasmodium falciparum infected children with chloroquine resistance (cases) were compared to 125 children with chloroquine sensitivity (controls).
- Risk factors were assessed using logistic regression analysis.
Main Results:
- Five independent predictors of chloroquine resistance were identified: young age (< 7 years), high parasite density (> 1000/microliters), normal spleen size, malnutrition, and presence of gametocytes.
- Odds ratios ranged from 3.0 to 7.1 for these factors.
Conclusions:
- The identified risk factors are readily measurable without specialized equipment.
- These indicators can assist health workers in remote areas of the Solomon Islands to identify individuals at high risk for chloroquine resistance.
- Early identification of high-risk patients can inform timely treatment decisions and improve malaria control efforts.
Objective:
To identify patient-related risk factors of chloroquine resistance.
Design:
A case control study.
Subjects:
Plasmodium falciparum infected school children were followed prospectively for 7 days for the detection of chloroquine resistance. Cases were 38 individuals with chloroquine resistant infections. Controls were 125 individuals with chloroquine sensitive infections. Cases were compared with controls with respect to previous or current study factor levels. Subjects were recruited from randomly selected schools which were stratified for area. Study location was in North Guadalcanal, Solomon Islands.
Outcome Measure:
Treatment failure of chloroquine in standard dosage (25 mg/kg). Follow-up period was 7 days.
Results:
Logistic regression resulted in 5 independent significant predictors of chloroquine resistance, obtained simultaneously with the diagnosis of malarial infection: (i) Young age (odds ratio (OR) for age < 7 years: 7.1; 95% confidence interval (CI): 2.5-25.0; OR per year increase after the age of 5 years: 0.8; 95% CI: 0.6-0.9). (ii) High parasite density (OR for > 1000/microliters: 5.0; 95% CI: 2.0-10.6; OR per 500 parasites/microliters increase: 1.3; 95% CI: 1.1-1.7). (iii) Normal spleen size (OR: 4.0, 95% CI; 1.5-10.8). (iv) Malnutrition (OR: 4.9; 95% CI: 1.8-13.2). (v) Presence of gametocytes in the thick smear (OR: 3.0; 95% CI: 1.1-8.0).
Conclusion:
The identified risk factors are easily measurable without special equipment. They may be useful for health workers in the Solomon Islands, even in remote areas, to identify Plasmodium falciparum infected individuals at high risk for chloroquine resistance before a treatment decision is made.