To determine the association between after-hours consultations and the likelihood of antibiotic prescribing for self-limiting upper respiratory tract infections (URTIs) in primary care practices.

A cross-sectional analysis using Australian national primary-care practice data (MedicineInsight) between February 1, 2016 and January 31, 2019.

Nationwide primary-care practices across Australia.

Adult and pediatric patients who visited primary care practices for first-time URTIs.

We estimated the proportion of first-time URTI episodes for which antibiotic prescribing occurred on the same day (immediate prescribing) using diagnoses and prescription records in the electronic primary-care database. Adjusted odds ratios (ORs) and 95% confidence intervals (CIs) for the likelihood of antibiotic prescribing by the time of primary care visits were calculated using generalized estimating equations.

Among 357,287 URTI episodes, antibiotics were prescribed in 172,605 episodes (48.3%). After adjusting for patients’ demographics, practice characteristics, and seasons, we detected a higher likelihood of antibiotic prescribing on weekends compared to weekdays (OR, 1.42; 95% CI, 1.39–1.45) and on national public holidays compared to nonholidays (OR, 1.23; 95% CI, 1.17–1.29). When we controlled for patient presentation and diagnosis, the association between antibiotic prescribing and after-hours consultations remained significant: weekend versus weekdays (OR, 1.37; 95% CI, 1.33–1.41) and holidays versus nonholidays (OR, 1.10; 95% CI, 1.03–1.18).

Primary-care consultations on weekends and public holidays were associated with a higher likelihood of immediate antibiotic prescribing for self-limiting URTIs in primary care. This finding might be attributed to lower resourcing in after-hours health care.

To evaluate the impact of early infectious diseases (ID) antimicrobial stewardship (AMS) intervention on inpatient sepsis antibiotic management.

Interventional, nonrandomized, controlled study.

Tertiary-care referral hospital, Sydney, Australia.

Consecutive, adult, non–intensive care unit (non-ICU) inpatients triggering an institutional clinical sepsis pathway from May to August 2015.

All patients reviewed by an ID Fellow within 24 hours of sepsis pathway trigger underwent case review and clinic file documentation of recommendations. Those not reviewed by an ID Fellow were considered controls and received standard sepsis pathway care. The primary outcome was antibiotic appropriateness 48 hours after sepsis trigger.

In total, 164 patients triggered the sepsis pathway: 6 patients were excluded (previous sepsis trigger); 158 patients were eligible; 106 had ID intervention; and 52 were control cases. Of these 158 patients, 91 (58%) had sepsis, and 15 of these 158 (9.5%) had severe sepsis. Initial antibiotic appropriateness, assessable in 152 of 158 patients, was appropriate in 80 (53%) of these 152 patients and inappropriate in 72 (47%) of these patients. In the intervention arm, 93% of ID Fellow recommendations were followed or partially followed, including 53% of cases in which antibiotics were de-escalated. ID Fellow intervention improved antibiotic appropriateness at 48 hours by 24% (adjusted risk ratio, 1.24; 95% confidence interval, 1.04–1.47; P=.035). The appropriateness agreement among 3 blinded ID staff opinions was 95%. Differences in intervention and control group mortality (13% vs 17%) and median length of stay (13 vs 17.5 days) were not statistically significant.

Sepsis overdiagnosis and delayed antibiotic optimization may reduce sepsis pathway effectiveness. Early ID AMS improved antibiotic management of non-ICU inpatients with suspected sepsis, predominantly by de-escalation. Further studies are needed to evaluate clinical outcomes.

Infect Control Hosp Epidemiol 2017;38:1032–1038

To examine statistical models that have been used to predict the cessation of breast–feeding.

In nutritional epidemiology, a knowledge of risk factors that lead to breast-feeding cessation is essential to promote optimal infant health by increasing or sustaining breast–feeding rates. However, a number of methodological issues complicate the measurement of such risk factors. It is important when building multivariate models that variables entered into the model are not intervening variables, factors on the causal pathway or surrogate outcomes. Inclusion of these types of variable can lead to inaccurate models and biased results. A factor often cited to predict breast–feeding is ‘intention to breast–feed’ prior to the birth of the infant, although this factor is directly on the causal decision–making pathway. Another factor often cited is the age of introduction of formula feeding, which is actually part of the outcome variable because formula feeding defines the difference between full, complementary and no breast-feeding. Rather than include these as risk factors in multivariate models, factors removed from the causal pathway such as influences of educational practices, including advice to complementary feed, and beliefs and attitudes of families and health-care practitioners should be measured.

The accurate quantification of modifiable risk factors is essential for designing public health education campaigns that are effective in sustaining or increasing breast–feeding duration.