Procalcitonin Algorithms for Antibiotic Therapy Decisions
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abstract
Previous randomized controlled trials suggest that using clinical algorithms based on procalcitonin levels, a marker of bacterial infections, results in reduced antibiotic use without a deleterious effect on clinical outcomes. However, algorithms differed among trials and were embedded primarily within the European health care setting. Herein, we summarize the design, efficacy, and safety of previous randomized controlled trials and propose adapted algorithms for US settings. We performed a systematic search and included all 14 randomized controlled trials (N = 4467 patients) that investigated procalcitonin algorithms for antibiotic treatment decisions in adult patients with respiratory tract infections and sepsis from primary care, emergency department (ED), and intensive care unit settings. We found no significant difference in mortality between procalcitonin-treated and control patients overall (odds ratio, 0.91; 95% confidence interval, 0.73-1.14) or in primary care (0.13; 0-6.64), ED (0.95; 0.67-1.36), and intensive care unit (0.89; 0.66-1.20) settings individually. A consistent reduction was observed in antibiotic prescription and/or duration of therapy, mainly owing to lower prescribing rates in low-acuity primary care and ED patients, and shorter duration of therapy in moderate- and high-acuity ED and intensive care unit patients. Measurement of procalcitonin levels for antibiotic decisions in patients with respiratory tract infections and sepsis appears to reduce antibiotic exposure without worsening the mortality rate. We propose specific procalcitonin algorithms for low-, moderate-, and high-acuity patients as a basis for future trials aiming at reducing antibiotic overconsumption.
