Home Print this page Email this page Small font sizeDefault font sizeIncrease font size
Users Online: 24077

 

Home About us Editorial board Search Ahead of print Current issue Archives Submit article Instructions Subscribe Advertise Contacts Login 
     
ORIGINAL ARTICLE
Year : 2014  |  Volume : 55  |  Issue : 6  |  Page : 480-485

Predictors of malaria in febrile children in Sokoto, Nigeria


1 Department of Family Medicine, Usmanu Danfodiyo University Teaching Hospital, Sokoto, Nigeria
2 Department of Family Medicine, Jos University Teaching Hospital, Jos, Nigeria
3 Department of Paediatrics, Usmanu Danfodiyo University Teaching Hospital, Sokoto, Nigeria
4 Department of Biological Sciences, Kebbi State University of Science and Technology, Aliero, Nigeria
5 Department of Family Medicine, Mayo Clinic, Rochester, Minnesota, USA

Correspondence Address:
Sanjay Singh
Department of Family Medicine, Usmanu Danfodiyo University Teaching Hospital, P.M.B. 2370, Sokoto
Nigeria
Login to access the Email id

Source of Support: None, Conflict of Interest: None


DOI: 10.4103/0300-1652.144701

Rights and Permissions

Background: Presumptive diagnosis of malaria is widespread, even where microscopy is available. As fever is very nonspecific, this often leads to over diagnosis, drug wastage and loss of opportunity to consider alternative causes of fever, hence the need to improve on the clinical diagnosis of malaria. Materials and Methods: In a prospective cross-sectional comparative study, we examined 45 potential predictors of uncomplicated malaria in 800 febrile children (0-12 years) in Sokoto, Nigeria. We developed a clinical algorithm for malaria diagnosis and compared it with a validated algorithm, Olaleye's model. Results: Malaria was confirmed in 445 (56%). In univariate analysis, 13 clinical variables were associated with malaria. In multivariate analysis, vomiting (odds ratio, OR 2.6), temperature ≥ 38.5°C (OR 2.2), myalgia (OR 1.8), weakness (OR 1.9), throat pain (OR 1.8) and absence of lung crepitations (OR 5.6) were independently associated with malaria. In children over age 3 years, any 3 predictors had a sensitivity of 82% and specificity of 47% for malaria. An Olaleye score ≥ 5 had a sensitivity of 62% and a specificity of 51%. Conclusion: In hyperendemic areas, the sensitivity of our algorithm may permit presumptive diagnosis of malaria in children. Algorithm positive cases can be presumptively treated, and negative cases can undergo parasitological testing to determine need for treatment.


[FULL TEXT] [PDF]*
Print this article     Email this article
 Next article
 Previous article
 Table of Contents

 Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
 Citation Manager
 Access Statistics
 Reader Comments
 Email Alert *
 Add to My List *
 * Requires registration (Free)
 

 Article Access Statistics
    Viewed4851    
    Printed190    
    Emailed0    
    PDF Downloaded101    
    Comments [Add]    
    Cited by others 3    

Recommend this journal