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Updated: Feb 7, 2026

Building a Better Mosquito: Identifying the Genes Enabling Malaria and Dengue Fever Resistance in A. gambiae and A. aegypti Mosquitoes
Published on: July 4, 2007
Identifying risk factors for the development of sepsis during adult severe malaria
Tsi Njim1,2, Arjen Dondorp3,4, Mavuto Mukaka3,4
1Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Old Road Campus, Oxford, OX3 7BN, UK. tsinjim@gmail.com.
Background:
Severe falciparum malaria can be compounded by bacterial sepsis, necessitating antibiotics in addition to anti-malarial treatment. The objective of this analysis was to develop a prognostic model to identify patients admitted with severe malaria at higher risk of developing bacterial sepsis.
Methods:
A retrospective data analysis using trial data from the South East Asian Quinine Artesunate Malaria Trial. Variables correlating with development of clinically defined sepsis were identified by univariable analysis, and subsequently included into a multivariable logistic regression model. Internal validation was performed by bootstrapping. Discrimination and goodness-of-fit were assessed using the area under the curve (AUC) and a calibration plot, respectively.
Results:
Of the 1187 adults with severe malaria, 86 (7.3%) developed clinical sepsis during admission. Predictors for developing sepsis were: female sex, high blood urea nitrogen, high plasma anion gap, respiratory distress, shock on admission, high parasitaemia, coma and jaundice. The AUC of the model was 0.789, signifying modest differentiation for identifying patients developing sepsis. The model was well-calibrated (Hosmer-Lemeshow Chi squared = 1.02). The 25th percentile of the distribution of risk scores among those who developed sepsis could identify a high-risk group with a sensitivity and specificity of 70.0 and 69.4%, respectively.
Conclusions:
The proposed model identifies patients with severe malaria at risk of developing clinical sepsis, potentially benefiting from antibiotic treatment in addition to anti-malarials. The model will need further evaluation with more strictly defined bacterial sepsis as outcome measure.
Insights
This study developed a model to predict bacterial sepsis in severe malaria patients, aiding early antibiotic intervention. The model identified key risk factors for sepsis, improving patient management.
Area of Science:
- Infectious Diseases
- Tropical Medicine
- Clinical Prediction Models
Background:
- Severe falciparum malaria poses a significant risk of secondary bacterial sepsis.
- Prompt antibiotic treatment is crucial alongside anti-malarial therapy for severe malaria patients.
Purpose of the Study:
- To develop and validate a prognostic model for identifying severe malaria patients at high risk of developing bacterial sepsis.
- To aid clinicians in initiating timely antibiotic treatment for at-risk individuals.
Main Methods:
- Retrospective analysis of data from the South East Asian Quinine Artesunate Malaria Trial.
- Multivariable logistic regression was used to identify sepsis predictors.
- Internal validation was performed using bootstrapping, with AUC and calibration plots for assessment.
Main Results:
- Of 1187 severe malaria patients, 7.3% developed sepsis.
- Predictors included female sex, high blood urea nitrogen, high plasma anion gap, respiratory distress, shock, high parasitemia, coma, and jaundice.
- The model demonstrated modest discrimination (AUC=0.789) and good calibration.
Conclusions:
- The prognostic model effectively identifies severe malaria patients at risk of bacterial sepsis.
- This tool may guide the use of antibiotics in conjunction with anti-malarial treatment.
- Further validation using strictly defined bacterial sepsis as an outcome is recommended.
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