Literature DB >> 20105074

A simple score to predict the outcome of severe malaria in adults.

Josh Hanson1, Sue J Lee, Sanjib Mohanty, M A Faiz, Nicholas M Anstey, Prakaykaew Charunwatthana, Emran Bin Yunus, Saroj K Mishra, Emiliana Tjitra, Ric N Price, Ridwanur Rahman, Francois Nosten, Ye Htut, Gofranul Hoque, Tran Thi Hong Chau, Nguyen Hoan Phu, Tran Tinh Hien, Nicholas J White, Nicholas P J Day, Arjen M Dondorp.   

Abstract

BACKGROUND: World Health Organization treatment guidelines recommend that adults with severe malaria be admitted to an intensive care unit (ICU). However, ICU facilities are limited in the resource-poor settings where most malaria occurs. Identification of patients at greater risk of complications may facilitate their triage and resource allocation.
METHODS: With use of data from a trial conducted in Southeast Asia (n=868), a logistic regression model was built to identify independent predictors of mortality among adults with severe malaria. A scoring system based on this model was tested in the original dataset and then validated in 2 series from Bangladesh (n=188) and Vietnam (n=292).
RESULTS: Acidosis (base deficit) and cerebral malaria (measured as Glasgow Coma Score) were the main independent predictors of outcome. The 5-point Coma Acidosis Malaria (CAM) score was simply derived from these 2 variables. Mortality increased steadily with increasing score. A CAM score <2 predicted survival with a positive predictive value (PPV) of 95.8% (95% confidence interval [CI], 93%- 97.7%). Of the 14 of 331 patients who died with a CAM score <2, 11 (79%) had renal failure and death occurred late after hospital admission (median, 108 h; range, 40-360 h). Substitution of plasma bicarbonate as the measure of acidosis only slightly reduced the prognostic value of the model. Use of respiratory rate was inferior, but a score <2 still predicted survival with a PPV of 92.2% (95% CI, 89.1%-94.7%).
CONCLUSIONS: Patients with a CAM score <2 at hospital admission may be safely treated in a general ward, provided that renal function can be monitored.

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Year:  2010        PMID: 20105074      PMCID: PMC4313369          DOI: 10.1086/649928

Source DB:  PubMed          Journal:  Clin Infect Dis        ISSN: 1058-4838            Impact factor:   9.079


  32 in total

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