Infections in children admitted with complicated severe acute malnutrition in Niger.

Page AL de Rekeneire N Sayadi S Aberrane S Janssens AC Rieux C Djibo A Manuguerra JC Ducou-le-Pointe H Grais RF Schaefer M Guerin PJ Baron E
PloS one 2013 ; 8(7); e68699. doi: 10.1371/journal.pone.0068699. Epub 2013 07 17


BACKGROUND: Although malnutrition affects thousands of children throughout the Sahel each year and predisposes them to infections, there is little data on the etiology of infections in these populations. We present a clinical and biological characterization of infections in hospitalized children with complicated severe acute malnutrition (SAM) in Maradi, Niger.

METHODS: Children with complicated SAM hospitalized in the intensive care unit of a therapeutic feeding center, with no antibiotics in the previous 7 days, were included. A clinical examination, blood, urine and stool cultures, and chest radiography were performed systematically on admission.

RESULTS: Among the 311 children included in the study, gastroenteritis was the most frequent clinical diagnosis on admission, followed by respiratory tract infections and malaria. Blood or urine culture was positive in 17% and 16% of cases, respectively, and 36% had abnormal chest radiography. Enterobacteria were sensitive to most antibiotics, except amoxicillin and cotrimoxazole. Twenty-nine (9%) children died, most frequently from sepsis. Clinical signs were poor indicators of infection and initial diagnoses correlated poorly with biologically or radiography-confirmed diagnoses.

CONCLUSIONS: These data confirm the high level of infections and poor correlation with clinical signs in children with complicated SAM, and provide antibiotic resistance profiles from an area with limited microbiological data. These results contribute unique data to the ongoing debate on the use and choice of broad-spectrum antibiotics as first-line treatment in children with complicated SAM and reinforce the call for an update of international guidelines on management of complicated SAM based on more recent data.