Mortality risk after COVID-19 vaccination: A self-controlled case series study.

BACKGROUND: Although previous studies found no-increased mortality risk after COVID-19 vaccination, residual confounding bias might have impacted the findings. Using a modified self-controlled case series (SCCS) design, we assessed the risk of non-COVID-19 mortality, all-cause mortality, and four cardiac-related death outcomes after primary series COVID-19 vaccination. METHODS: We analyzed all deaths between December 14, 2020, and August 11, 2021, among individuals from eight Vaccine Safety Datalink sites. Demographic characteristics of deaths in recipients of COVID-19 vaccines and unvaccinated individuals were reported. We conducted SCCS analyses by vaccine type and death outcomes and reported relative incidences (RI). The observation period for death spanned from the dates of emergency use authorization to the end of the study period (August 11, 2021) without censoring the observation period upon death. We pre-specified a primary risk interval of 28-day and a secondary risk interval of 14-day after each vaccination dose. Adjusting for seasonality in mortality analyses is crucial because death rates vary over time. Deaths among unvaccinated individuals were included in SCCS analyses to account for seasonality by incorporating calendar month in the models. RESULTS: For Pfizer-BioNTech (BNT162b2), RIs of non-COVID-19 mortality, all-cause mortality, and four cardiac-related death outcomes were below 1 and 95 % confidence intervals (CIs) excluded 1 across both doses and both risk intervals. For Moderna (mRNA-1273), RI point estimates of all outcomes were below 1, although the 95 % CIs of two RI estimates included 1: cardiac-related (RI = 0.78, 95 % CI, 0.58-1.04) and non-COVID-19 cardiac-related mortality (RI = 0.80, 95 % CI, 0.60-1.08) 14 days after the second dose in individuals without pre-existing cancer and heart disease. For Janssen (Ad26.COV2.S), RIs of four cardiac-related death outcomes ranged from 0.94 to 0.98 for the 14-day risk interval, and 0.68 to 0.72 for the 28-day risk interval and 95 % CIs included 1. CONCLUSION: Using a modified SCCS design and adjusting for temporal trends, no-increased risk was found for non-COVID-19 mortality, all-cause mortality, and four cardiac-related death outcomes among recipients of the three COVID-19 vaccines used in the US.

Validation of ICD-10 hospital discharge diagnosis codes to identify incident and recurrent ischemic stroke from a US integrated healthcare system.

PURPOSE: This study validated incident and recurrent ischemic stroke identified by International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10) hospital discharge diagnosis codes. METHODS: Using electronic health records (EHR) of adults (≥18 years) receiving care from Kaiser Permanente Southern California with ICD-10 hospital discharge diagnosis codes of ischemic stroke (I63.x, G46.3, and G46.4) between October 2015 and September 2020, we identified 75 patients with both incident and recurrent stroke events (total 150 cases). Two neurologists independently evaluated validity of ICD-10 codes through chart reviews. RESULTS: The positive predictive value (PPV, 95% CI) for incident stroke was 93% (95% CI: 88%, 99%) and the PPV for recurrent stroke was 72% (95% CI: 62%, 82%). The PPV for recurrent stroke improved after applying a gap of 20 days (PPV of 75%; 95% CI: 63%, 87%) or removing hospital admissions related to stroke-related procedures (PPV of 78%; 95% CI: 68%, 88%). CONCLUSION: The ICD-10 hospital discharge diagnosis codes for ischemic stroke showed a high PPV for incident cases, while the PPV for recurrent cases were less optimal. Algorithms to improve the accuracy of ICD-10 codes for recurrent ischemic stroke may be necessary.

Association of masking policies with mask adherence and distancing during the SARS-COV-2 pandemic.

BACKGROUND: Quantification of the impact of local masking policies may help guide future policy interventions to reduce SARS-COV-2 disease transmission. This study's objective was to identify factors associated with adherence to masking and social distancing guidelines. METHODS: Faculty from 16 U.S. colleges and universities trained 231 students in systematic direct observation. They assessed correct mask use and distancing in public settings in 126 US cities from September 2020 through August 2021. RESULTS: Of 109,999 individuals observed in 126 US cities, 48% wore masks correctly with highest adherence among females, teens and seniors and lowest among non-Hispanic whites, those in vigorous physical activity, and in larger groups (P < .0001). Having a local mask mandate increased the odds of wearing a mask by nearly 3-fold (OR = 2.99, P = .0003) compared to no recommendation. People observed in non-commercial areas were least likely to wear masks. Correct mask use was greatest in December 2020 and remained high until June 2021 (P < .0001). Masking policy requirements were not associated with distancing. DISCUSSION: The strong association between mask mandates and correct mask use suggests that public policy has a powerful influence on individual behavior. CONCLUSIONS: Mask mandates should be considered in future pandemics to increase adherence.