A decision algorithm to promote outpatient antimicrobial stewardship for uncomplicated urinary tract infection

Abstract

Antibiotic resistance is a major cause of treatment failure and leads to increased use of broad-spectrum agents, which begets further resistance. This vicious cycle is epitomized by uncomplicated urinary tract infection (UTI), which affects one in two women during their life and is associated with increasing antibiotic resistance and high rates of prescription for broad-spectrum second-line agents. To address this, we developed machine learning models to predict antibiotic susceptibility using electronic health record data and built a decision algorithm for recommending the narrowest possible antibiotic to which a specimen is susceptible. When applied to a test cohort of 3629 patients presenting between 2014 and 2016, the algorithm achieved a 67% reduction in the use of second-line antibiotics relative to clinicians. At the same time, it reduced inappropriate antibiotic therapy, defined as the choice of a treatment to which a specimen is resistant, by 18% relative to clinicians. For specimens where clinicians chose a second-line drug but the algorithm chose a first-line drug, 92% (1066 of 1157) of decisions ended up being susceptible to the first-line drug. When clinicians chose an inappropriate first-line drug, the algorithm chose an appropriate first-line drug 47% (183 of 392) of the time. Our machine learning decision algorithm provides antibiotic stewardship for a common infectious syndrome by maximizing reductions in broad-spectrum antibiotic use while maintaining optimal treatment outcomes. Further work is necessary to improve generalizability by training models in more diverse populations.

Changes in abdominal subcutaneous adipose tissue phenotype following menopause is associated with increased visceral fat mass

“…Low ESR1 expression in adipose tissue has been related to adiposity in humans 43 and studies in rodents show that AT depletion of ESR1 leads to mitochondrial dysfunction, adipocyte hypertrophy and IR 29 , 43 , 44 . In this study, we found no differences in expression of ESR1 across menopausal status in either SAT or VAT indicating that it is not a differential expression of ESR1 per se that drives the menopausal differences in AT phenotype.…”

Antibiotic stewardship in the era of precision medicine

“…In a cohort of 3629 patients presenting between 2014 and 2016, the algorithm achieved a 67% reduction in the use of second-line antibiotics and reduced inappropriate antibiotic therapy by 18% relative to clinicians. 38 Further randomized trials are necessary to evaluate the utility of machine learning algorithms in antibiotic stewardship, followed by implementation science to disseminate the research findings into clinical practice.…”

Microorganisms Isolated from Urine Cultures and Their Antimicrobial Susceptibility Patterns at a Commercial Laboratory during 2018-2020

“…요로감염은 호흡기 감염 다음으로 사람에게 가장 흔한 감염병 중 하나이며 지역사회에서 흔하게 발생하는 감염질 환이다 [1]. 여성의 경우 40-50%에서 일생 동안 최소 한번 은 요로감염을 경험하는 것으로 알려져 있으며 그 중 상당 수는 반복적으로 감염된다 [2]. 이러한 요로감염은 높은 유 병율과 이환율로 항균제 사용의 빈도가 매우 높은 실정이 며 [3]…”