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BACKGROUND:The safety and efficacy of using C-reactive protein (CRP) to decide on antibiotic prescription among febrile children at risk of pneumonia has not been tested. METHODS:This was a randomized (1:1) controlled noninferiority trial in 9 primary care centers in Tanzania (substudy of the ePOCT trial evaluating a novel electronic decision algorithm). Children aged 2-59 months with fever and cough and without life-threatening conditions received an antibiotic based on a CRP-informed strategy (combination of CRP ≥80 mg/L plus age/temperature-corrected tachypnea and/or chest indrawing) or current World Health Organization standard (respiratory rate ≥50 breaths/minute). The primary outcome was clinical failure by day (D) 7; the secondary outcomes were antibiotic prescription at D0, secondary hospitalization, or death by D30. RESULTS:A total of 1726 children were included (intervention: 868, control: 858; 0.7% lost to follow-up). The proportion of clinical failure by D7 was 2.9% (25/865) in the intervention arm vs 4.8% (41/854) in the control arm (risk difference, -1.9% [95% confidence interval {CI}, -3.7% to -.1%]; risk ratio [RR], 0.60 [95% CI, .37-.98]). Twenty of 865 (2.3%) children in the intervention arm vs 345 of 854 (40.4%) in the control arm received antibiotics at D0 (RR, 0.06 [95% CI, .04-.09]). There were fewer secondary hospitalizations and deaths in the CRP arm: 0.5% (4/865) vs 1.5% (13/854) (RR, 0.30 [95% CI, .10-.93]). CONCLUSIONS:CRP testing using a cutoff of ≥80 mg/L, integrated into an electronic decision algorithm, was able to improve clinical outcome in children with respiratory infections while substantially reducing antibiotic prescription. CLINICAL TRIALS REGISTRATION:NCT02225769.

Original publication




Journal article


Clinical infectious diseases : an official publication of the Infectious Diseases Society of America

Publication Date





1926 - 1934


Swiss Tropical and Public Health Institute, Basel.


Humans, Respiratory Tract Infections, Fever, Albuterol, C-Reactive Protein, Anti-Bacterial Agents, Logistic Models, Algorithms, Infant, Primary Health Care, Tanzania, Female, Male