Mitchell Christopher, Keegan Lindsay T, Le Thuy T T, Khader Karim, Beams Alexander, Samore Matthew H, Toth Damon J A
Department of Mathematics, Tarleton State University, Stephenville, Texas, United States of America.
Division of Epidemiology, Department of Internal Medicine, University of Utah, Salt Lake City, Utah, United States of America.
PLoS One. 2024 Aug 8;19(8):e0306622. doi: 10.1371/journal.pone.0306622. eCollection 2024.
Clostridioides difficile infection (CDI) is a significant public health threat, associated with antibiotic-induced disruption of the normally protective gastrointestinal microbiota. CDI is thought to occur in two stages: acquisition of asymptomatic colonization from ingesting C. difficile bacteria followed by progression to symptomatic CDI caused by toxins produced during C. difficile overgrowth. The degree to which disruptive antibiotic exposure increases susceptibility at each stage is uncertain, which might contribute to divergent published projections of the impact of hospital antibiotic stewardship interventions on CDI. Here, we model C. difficile transmission and CDI among hospital inpatients, including exposure to high-CDI-risk antibiotics and their effects on each stage of CDI epidemiology. We derive the mathematical relationship, using a deterministic model, between those parameters and observed equilibrium levels of colonization, CDI, and risk ratio of CDI among certain antibiotic-exposed patients relative to patients with no recent antibiotic exposure. We then quantify the sensitivity of projected antibiotic stewardship intervention impacts to alternate assumptions. We find that two key parameters, the antibiotic effects on susceptibility to colonization and to CDI progression, are not identifiable given the data frequently available. Furthermore, the effects of antibiotic stewardship interventions are sensitive to their assumed values. Thus, discrepancies between different projections of antibiotic stewardship interventions may be largely due to model assumptions. Data supporting improved quantification of mechanistic antibiotic effects on CDI epidemiology are needed to understand stewardship effects better.
艰难梭菌感染（CDI）是一项重大的公共卫生威胁，与抗生素导致的正常保护性胃肠道微生物群破坏有关。CDI被认为分两个阶段发生：通过摄入艰难梭菌细菌获得无症状定植，随后发展为由艰难梭菌过度生长期间产生的毒素引起的有症状CDI。破坏性抗生素暴露在每个阶段增加易感性的程度尚不确定，这可能导致已发表的关于医院抗生素管理干预对CDI影响的预测存在差异。在此，我们对医院住院患者中的艰难梭菌传播和CDI进行建模，包括暴露于高CDI风险抗生素及其对CDI流行病学各阶段的影响。我们使用确定性模型推导这些参数与观察到的定植、CDI平衡水平以及某些抗生素暴露患者相对于近期未接触抗生素患者的CDI风险比之间的数学关系。然后，我们量化了预测的抗生素管理干预影响对替代假设的敏感性。我们发现，鉴于经常可用的数据，无法确定两个关键参数，即抗生素对定植易感性和CDI进展的影响。此外，抗生素管理干预的效果对其假设值很敏感。因此，抗生素管理干预不同预测之间的差异可能很大程度上归因于模型假设。需要支持更好地量化抗生素对CDI流行病学的机制性影响的数据，以更好地理解管理效果。
