Miscarriage after SARS-CoV-2 vaccination: A population-based cohort study.

OBJECTIVE: To evaluate the risk of miscarriage following SARS-CoV-2 vaccination, while accounting for the competing risk of induced abortion. DESIGN: Population-based cohort study. SETTING: Ontario, Canada. PARTICIPANTS: Women aged 15-50 years with a confirmed pregnancy at ≤19 completed weeks' gestation. METHODS: Exposure to first SARS-CoV-2 vaccination, handled in a time-varying manner, was defined as (i) unvaccinated, (ii) remotely vaccinated >28 days before the estimated conception date or (iii) recently vaccinated ≤28 days before conception and up to 120 days after conception. MAIN OUTCOME MEASURES: The outcome was miscarriage, occurring between the estimated date of conception and up to 19 completed weeks of pregnancy. Fine-Grey hazard models, accounting for the competing risk of induced abortion, generated hazard ratios (aHR), adjusted for socio-demographic factors, comorbidities, and biweekly periods. RESULTS: Included were 246 259 pregnant women, of whom 34% received a first SARS-CoV-2 vaccination. Miscarriage occurred at a rate of 3.6 per 10 000 person-days among remotely vaccinated women and 3.2 per 10 000 person-days among those recently vaccinated, in contrast to a rate of 1.9 per 10 000 person-days among unvaccinated women, with corresponding aHR of 0.98 (95% confidence interval [CI] 0.91-1.07) and 1.00 (95% CI 0.93-1.08). CONCLUSIONS: SARS-CoV-2 vaccination was not associated with miscarriage while accounting for the competing risk of induced abortion. This study reiterates the importance of including pregnant women in new vaccine clinical trials and registries, and the rapid dissemination of vaccine safety data.

Physician Characteristics Associated With Opioid Prescribing After Same-Day Breast Surgery in Ontario, Canada: A Population-Based Cohort Study.

Background and Objectives: Opioid overprescribing in patients undergoing breast surgery is a concern, as evidence suggests that minimal or no opioid is needed to manage pain. We sought to describe characteristics of opioid prescribers and determine associations between prescriber's characteristics and high opioid prescribing within 7 days of same-day breast surgery. Methods: Patients ≥18 years of age who underwent same-day breast surgery in Ontario, Canada from 2012 to 2020 were identified and linked to prescriber data. The primary outcome was current high opioid prescribing defined as >75th percentile of the mean oral morphine equivalents (OME; milligrams). Prescriber characteristics including age, sex, specialty, years in practice, practice setting, and history of high (>75th percentile) opioid prescribing in the previous year were captured. Associations between prescriber characteristics and the primary outcome were estimated in modified Poisson regression models. Results: The final cohort contained 56,434 patients, 3469 unique prescribers, and 58,656 prescriptions. Over half (1971/3469; 57%) of prescribers wrote ≥1 prescription that was >75th percentile of mean OME of 180 mg, of which 50% were family practice physicians. Adjusted mean OMEs prescribed varied by specialty with family practice specialties prescribing the highest mean OME (614 ± 38 mg) compared to surgical specialties (general surgery [165 ± 9 mg], plastic surgery [198 ± 10 mg], surgical oncology [154 ± 14 mg]). Whereas 73% of first and 31% of second prescriptions were provided by general surgery physicians, family practice physicians provided 2% of first and 51% of second prescriptions. Prescriber characteristics associated with a higher likelihood of high current opioid prescribing were family practice (risk ratio [RR], 1.56; 95% confidence interval [CI], 1.35-1.79 compared to general surgery), larger community practice setting (RR, 1.34; 95% CI, 1.05-1.71 compared to urban), and a previous high opioid prescribing behavior (RR, 2.28; 95% CI, 2.06-2.52). Conclusions: While most studies examine surgeon opioid prescribing, our data suggest that other specialties contribute to opioid overprescribing in surgical patients and identify characteristics of physicians likely to overprescribe.