Frequency and Predictors of Suboptimal Prescribing Among a Cohort of Older Male Residents with Urinary Tract Infections

CLINICAL INFECTIOUS DISEASES(2021)

引用 4|浏览8
暂无评分
摘要
Background. Unnecessary antibiotic treatment of suspected urinary tract infections (UTI) is common in long-term care facilities (LTCFs). However, less is known about the extent of suboptimal treatment, in terms of antibiotic choice, dose, and duration, after the decision to use antibiotics has been made. Methods. We described the frequency of potentially suboptimal treatment among residents with an incident UTI (the first during the study with none in the year prior) in Department of Veterans Affairs (VA) community living centers (CLCs; 2013-2018). Time trends were analyzed using Joinpoint regression. Residents with UTIs receiving potentially suboptimal treatment were compared with those receiving optimal treatment, to identify resident characteristics predictive of suboptimal antibiotic treatment, using multivariable unconditional logistic regression models. Results. We identified 21 938 residents with an incident UTI treated in 120 VA CLCs, of whom 96.0% were male. Potentially suboptimal antibiotic treatment was identified in 65.0% of residents and decreased 1.8% annually (P <.05). Potentially suboptimal initial drug choice was identified in 45.6% of residents, suboptimal dose frequency in 28.6%, and longer than recommended duration in 12.7%. Predictors of suboptimal antibiotic treatment included prior fluoroquinolone exposure (adjusted odds ratio, 1.38), chronic renal disease (1.19), age >= 85 years (1.17), prior skin infection (1.14), recent high white blood cell count (1.08), and genitourinary disorder (1.08). Conclusion. Similar to findings in non-VA facilities, potentially suboptimal treatment was common but improving in CLC residents with an incident UTI. Predictors of suboptimal antibiotic treatment should be targeted with antibiotic stewardship interventions to improve UTI treatment.
更多
查看译文
关键词
urinary tract infection, suboptimal antibiotic treatment, Veterans Affairs, Community Living Center
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要