Background Antibiotic prescribing practices among dentists and dental specialists in the United States (US) remains poorly understood. The purpose of our study is to compare prescribing practices between dental specialties, evaluate the duration of antibiotics prescribed by dentists, and determine variation in antibiotic selection among dentists. Methods We performed a retrospective cross-sectional analysis of dental provider specialties linked to de-identified antibiotic claims data from a large pharmacy benefits manager during the 2015 calendar year. Results As a group, general dentists and dental specialists were responsible for over 2.7 million antibiotic prescriptions, higher than several other medical and allied health provider specialties. Antibiotic treatment duration was generally prolonged and commonly included broad-spectrum agents, such as amoxicillin-clavulanate and clindamycin. Although amoxicillin was the most commonly prescribed antibiotic among all dental specialties, there was significant variation among other antibiotics selected by each specialty. The most common antibiotic treatment durations were for 7 and 10 days. Conclusions This study demonstrates that dentists frequently prescribe antibiotics for prolonged periods of time and often use broad-spectrum antibiotics. Further studies are necessary to evaluate the appropriateness of these antibiotic prescribing patterns. Practical Implications The significant variation in antibiotic selection and treatment duration identified among all dental specialties in this study population implies that further research and guidance into the treatment of dental infections is necessary to improve and standardize antibiotic prescribing practices.

OBJECTIVETo characterize trends in outpatient antibiotic prescriptions in the United StatesDESIGNRetrospective ecological and temporal trend study evaluating outpatient antibiotic prescriptions from 2013 to 2015SETTINGNational administrative claims data from a pharmacy benefits manager PARTICIPANTS. Prescription pharmacy beneficiaries from Express Scripts Holding CompanyMEASUREMENTSAnnual and seasonal percent change in antibiotic prescriptionsRESULTSApproximately 98 million outpatient antibiotic prescriptions were filled by 39 million insurance beneficiaries during the 3-year study period. The most commonly prescribed antibiotics were azithromycin, amoxicillin, amoxicillin/clavulanate, ciprofloxacin, and cephalexin. No significant changes in individual or overall annual antibiotic prescribing rates were found during the study period. Significant seasonal variation was observed, with antibiotics being 42% more likely to be prescribed during February than September (peak-to-trough ratio [PTTR], 1.42; 95% confidence interval [CI], 1.39-1.61). Similar seasonal trends were found for azithromycin (PTTR, 2.46; 95% CI, 2.44-3.47), amoxicillin (PTTR, 1.52; 95% CI, 1.42-1.89), and amoxicillin/clavulanate (PTTR, 1.78; 95% CI, 1.68-2.29).CONCLUSIONSThis study demonstrates that annual national outpatient antibiotic prescribing practices remained unchanged during our study period. Furthermore, seasonal peaks in antibiotics generally used to treat viral upper respiratory tract infections remained unchanged during cold and influenza season. These results suggest that inappropriate prescribing of antibiotics remains widespread, despite the concurrent release of several guideline-based best practices intended to reduce inappropriate antibiotic consumption; however, further research linking national outpatient antibiotic prescriptions to associated medical conditions is needed to confirm these findings.Infect Control Hosp Epidemiol 2018;39:584-589.

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Objective. National estimates of arthritis prevalence rely on a single survey question about doctor-diagnosed arthritis without using survey information on joint symptoms, even though some subjects with only the latter have been shown to have arthritis. The sensitivity of the current surveillance definition is only 53% and 69% in subjects ages 45-64 years and ages ≥65 years, respectively, resulting in misclassification of nearly one-half and one-third of subjects in those age groups. This study was undertaken to estimate arthritis prevalence based on an expansive surveillance definition that is adjusted for the measurement errors in the current definition.Methods. Using the 2015 National Health Interview Survey, we developed a Bayesian multinomial latent class model for arthritis surveillance based on doctordiagnosed arthritis, joint symptoms, and whether symptom duration exceeded 3 months.Results. Of 33,672 participants, 19.3% of men and 16.7% of women ages 18-64 years and 15.7% of men and 13.5% of women ages ≥65 years affirmed joint symptoms without doctor-diagnosed arthritis. The measurement error-adjusted prevalence of arthritis was 29.9% (95% Bayesian probability interval [95% PI] 23.4-42.3) in men ages 18-64 years, 31.2% (95% PI 25.8-44.1) in women ages 18-64 years, 55.8% (95% PI 49.9-70.4) in men ages ≥65 years, and 68.7% (95% PI 62.1-79.9) in women ages ≥65 years. Arthritis affected 91.2 million adults (of 247.7 million; 36.8%) in the US in 2015, which included 61.1 million persons between 18 and 64 years of age (of 199.9 million; 30.6%). Our arthritis prevalence estimate was 68% higher than the previously reported national estimate.Conclusion. Arthritis prevalence in the US population has been substantially underestimated, especially among adults younger than 65 years of age.

ObjectivesAlthough treatment development in osteoarthritis (OA) focuses on chondroprotection, it is unclear how much preventing cartilage loss reduces joint pain. It is also unclear how nociceptive tissues may be involved.MethodsUsing data from the Osteoarthritis Initiative, we quantified the relation between cartilage loss and worsening knee pain after adjusting for bone marrow lesions (BMLs) and synovitis, and examined how much these factors mediated this association. 600 knee MRIs were scored at baseline, 12 months and 24 months for quantitative and semiquantitative measures of OA structural features. We focused on change in medial cartilage thickness using an amount similar to that seen in recent trials. Linear models calculated mean change in Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain score with cartilage loss, adjusted for baseline BMLs, synovitis and covariates. Mediation analysis tested whether change in synovitis or BMLs mediated the cartilage loss–pain association. We carried out a subanalysis for knees with non-zero baseline WOMAC pain scores and another for non-valgus knees.ResultsCartilage thickness loss was significantly associated with a small degree of worsening in pain over 24 months. For example, a loss of 0.1 mm of cartilage thickness over 2 years was associated with a 0.32 increase in WOMAC pain (scale 0–20). The association of cartilage thickness loss with pain was mediated by synovitis change but not by BML change. Subanalysis results were similar.ConclusionsCartilage thickness loss is associated with only a small amount of worsening knee pain, an association mediated in part by worsening synovitis. Demonstrating that chondroprotection reduces knee pain will be extremely challenging and is perhaps unachievable.