Dentists prescribe 10% of all outpatient antibiotics in the United States and are the top specialty prescriber. Data on current antibiotic prescribing trends are scarce. Therefore, we evaluated trends in antibiotic prescribing rates by dentists, and we further assessed whether these trends differed by agent, specialty, and by patient characteristics.

Retrospective study of dental antibiotic prescribing included data from the IQVIA Longitudinal Prescription Data set from January 1, 2012 to December 31, 2019.

The change in the dentist prescribing rate and mean days’ supply were evaluated using linear regression models.

Dentists wrote >216 million antibiotic prescriptions between 2012 and 2019. The annual dental antibiotic prescribing rate remained steady over time (P = .5915). However, the dental prescribing rate (antibiotic prescriptions per 1,000 dentists) increased in the Northeast (by 1,313 antibiotics per 1,000 dentists per year), among oral and maxillofacial surgeons (n = 13,054), prosthodontists (n = 2,381), endodontists (n = 2,255), periodontists (n = 1,961), and for amoxicillin (n = 2,562; P < .04 for all). The mean days’ supply significantly decreased over the study period by 0.023 days per 1,000 dentists per year (P < .001).

From 2012 to 2019, dental prescribing rates for antibiotics remained unchanged, despite decreases in antibiotic prescribing nationally and changes in guidelines during the study period. However, mean days’ supply decreased over time. Dental specialties, such as oral and maxillofacial surgeons, had the highest prescribing rate with increases over time. Antibiotic stewardship efforts to improve unnecessary prescribing by dentists and targeting dental specialists may decrease overall antibiotic prescribing rates by dentists.

To identify characteristics of US health systems and end users that report antimicrobial use and resistance (AUR) data, to determine how NHSN AUR data are used by hospitals and health systems and end users, and to identify barriers to AUR reporting.

An anonymous survey was sent to Society of Infectious Diseases Pharmacists (SIDP) and Society for Healthcare Epidemiology of America (SHEA) Research Network members.

Data were collected via Survey Monkey from January 21 to February 21, 2020. Respondent and hospital data were analyzed using descriptive statistics.

We received responses from 238 individuals across 43 US states. Respondents were primarily pharmacists (84%), from urban areas, (44%), from nonprofit medical centers (81%), and from hospitals with >250 beds (72%). Also, 62% reported data to the AU module and 19% reported data to the AR module. Use of software for local AU or AR tracking was associated with increased reporting to the AU module (19% vs 64%) and the AR module (2% vs 30%) (P < .001 each). Only 36% of those reporting data to the AU module used NHSN AUR data analysis tools regularly and only 9% reported data to the AR module regularly. Technical challenges and time and/or salary support were the most common barriers to AUR participation cited by all respondents. Among those not reporting AUR data, increased local expectations to report and better software solutions were the most commonly identified solutions to increase AUR reporting.

Efforts to increase AUR reporting should focus on software solutions and salary support for data-entry activities. Increasing expectations to report may incentivize local resource allocation to improve AUR reporting rates.

Anxiety disorders are highly prevalent with an early age of onset. Understanding the aetiology of disorder emergence and recovery is important for establishing preventative measures and optimising treatment. Experimental approaches can serve as a useful model for disorder and recovery relevant processes. One such model is fear conditioning. We conducted a remote fear conditioning paradigm in monozygotic and dizygotic twins to determine the degree and extent of overlap between genetic and environmental influences on fear acquisition and extinction.

In total, 1937 twins aged 22–25 years, including 538 complete pairs from the Twins Early Development Study took part in a fear conditioning experiment delivered remotely via the Fear Learning and Anxiety Response (FLARe) smartphone app. In the fear acquisition phase, participants were exposed to two neutral shape stimuli, one of which was repeatedly paired with a loud aversive noise, while the other was never paired with anything aversive. In the extinction phase, the shapes were repeatedly presented again, this time without the aversive noise. Outcomes were participant ratings of how much they expected the aversive noise to occur when they saw either shape, throughout each phase.

Twin analyses indicated a significant contribution of genetic effects to the initial acquisition and consolidation of fear, and the extinction of fear (15, 30 and 15%, respectively) with the remainder of variance due to the non-shared environment. Multivariate analyses revealed that the development of fear and fear extinction show moderate genetic overlap (genetic correlations 0.4–0.5).

Fear acquisition and extinction are heritable, and share some, but not all of the same genetic influences.

To assess general medical residents’ familiarity with antibiograms using a self-administered survey

Cross-sectional, single-center survey

Residents in internal medicine, family medicine, and pediatrics at an academic medical center

Participants were administered an anonymous survey at our institution during regularly scheduled educational conferences between January and May 2012. Questions collected data regarding demographics, professional training; further open-ended questions assessed knowledge and use of antibiograms regarding possible pathogens, antibiotic regimens, and prescribing resources for 2 clinical vignettes; a series of directed, closed-ended questions followed. Bivariate analyses to compare responses between residency programs were performed.

Of 122 surveys distributed, 106 residents (87%) responded; internal medicine residents accounted for 69% of responses. More than 20% of residents could not accurately identify pathogens to target with empiric therapy or select therapy with an appropriate spectrum of activity in response to the clinical vignettes; correct identification of potential pathogens was not associated with selecting appropriate therapy. Only 12% of respondents identified antibiograms as a resource when prescribing empiric antibiotic therapy for scenarios in the vignettes, with most selecting the UpToDate online clinical decision support resource or The Sanford Guide. When directly questioned, 89% reported awareness of institutional antibiograms, but only 70% felt comfortable using them and only 44% knew how to access them.

When selecting empiric antibiotics, many residents are not comfortable using antibiograms as part of treatment decisions. Efforts to improve antibiotic use may benefit from residents being given additional education on both infectious diseases pharmacotherapy and antibiogram utilization.

Infect Control Hosp Epidemiol 2018;39:578–583