Empiric Antibiotic Treatment Thresholds for Serious Bacterial Infections: A Scenario-Based Survey Study.

Link to article at PubMed

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Empiric Antibiotic Treatment Thresholds for Serious Bacterial Infections: A Scenario-Based Survey Study.

Clin Infect Dis. 2018 Dec 07;:

Authors: Cressman AM, MacFadden DR, Verma AA, Razak F, Daneman N

Background: Physicians face competing demands of maximizing pathogen coverage, while minimizing unnecessary use of broad-spectrum antibiotics when managing sepsis. We sought to identify physicians' perceived likelihood of coverage achieved by their usual empiric antibiotic regimen, along with minimum thresholds of coverage they would be willing to accept when managing these patients.
Methods: We conducted a scenario-based survey of internal medicine physicians from across Canada using a 2 x 2 factorial design, varied by infection source (undifferentiated vs. genitourinary) and severity (mild vs. severe) denoted by the Quick Sepsis Related Organ Failure Assessment (qSOFA) score. For each scenario, participants selected their preferred empiric antibiotic regimen, estimated the likelihood of coverage achieved by that regimen and considered their minimum threshold of coverage.
Results: We had 238 respondents including 87 (36.6%) residents and 151 attending physicians (63.4%). The perceived likelihood of antibiotic coverage and minimum thresholds of coverage for each scenario were: 1) severe undifferentiated 90% [interquartile range (IQR) 89.5-95.0] and 90% [IQR 80-95], 2) mild undifferentiated 89% [IQR 80-95] and 80% [IQR 70-89.5], 3) severe GU 91% [IQR 87.3-95.0] and 90% [IQR 80.0-90.0], and 4) mild GU 90% [IQR 81.8-91.3%] and 80% [IQR 71.8-90]. Illness severity and infectious diseases specialty predicted higher thresholds of coverage whereas less clinical experience and lower self-reported prescribing intensity predicted lower thresholds of coverage.
Conclusion: Pathogen coverage of 80% and 90% are physician-acceptable thresholds for managing patients with mild and severe sepsis from bacterial infections. These data may inform clinical guidelines and decision-support tools to improve empiric antibiotic prescribing.

PMID: 30535310 [PubMed - as supplied by publisher]

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