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A study on multi-organ dysfunction syndrome in malaria using sequential organ failure assessment score
Amish Bhutani1, Rajeev Mohan Kaushik1, Reshma Kaushik1
1Department of Medicine, Himalayan Institute of Medical Sciences, Swami Rama Himalayan University, Dehradun, Uttarakhand, India.
Tropical Parasitology
|March 22, 2021
Summary
Multi-organ dysfunction syndrome (MODS) is common in malaria patients, regardless of malaria type. The severity of MODS, assessed by the Sequential Organ Failure Assessment (SOFA) score, impacts patient outcomes and recovery time.
Area of Science:
- Infectious Diseases
- Critical Care Medicine
- Pathophysiology
Background:
- Malaria remains a significant global health challenge, particularly in tropical regions.
- Multi-organ dysfunction syndrome (MODS) is a severe complication associated with various critical illnesses.
- Understanding MODS in malaria is crucial for improving patient management and outcomes.
Purpose of the Study:
- To investigate the prevalence and clinical spectrum of MODS in malaria patients.
- To identify prognostic factors associated with MODS in malaria.
- To evaluate the outcome of MODS in malaria patients.
Main Methods:
- A study involving 124 malaria patients diagnosed via peripheral blood film and rapid tests.
- Sequential Organ Failure Assessment (SOFA) score was used to assess MODS.
- World Health Organization (WHO) criteria were employed to evaluate malaria severity.
Main Results:
- MODS was prevalent in 87.09% of malaria patients, irrespective of Plasmodium species (P. falciparum, P. vivax, or mixed).
- Mortality in malaria patients with MODS was 5.55%, with higher rates in P. falciparum malaria.
- SOFA score at admission significantly correlated with MODS outcome and hospitalization duration.
Conclusions:
- MODS is a frequent complication of malaria, not influenced by the type of Plasmodium parasite.
- The severity of MODS, as indicated by the SOFA score, is a key determinant of patient prognosis and recovery.
- The SOFA score is a valuable tool for diagnosing MODS and predicting its severity and outcome in malaria.
