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.

Long-term Neutralizing Antibody Levels Against Measles and Rubella Viruses Among Adults With 3 Doses of Measles-Mumps-Rubella Vaccine.

Background: A third dose of measles-mumps-rubella vaccine (MMR) may be administered for various reasons, but data on long-term immunity are limited. We assessed neutralizing antibody levels against measles and rubella among adults up to 11 years after receipt of a third MMR dose. Methods: In this longitudinal study, healthy adults who received a third MMR dose as young adults (ages 18-28 years) were recalled around 5 years and 9-11 years after the third dose. Measles and rubella antibody levels were assessed by plaque-reduction and immunocolorimetric neutralization assays, respectively. Antibody concentrations <120 mIU/mL and <10 U/mL were considered potentially susceptible to measles and rubella, respectively. Geometric mean concentrations (GMCs) and 95% confidence intervals (CIs) over time were estimated from generalized estimating equation models. Results: Approximately 5 and 9-11 years after receipt of the third dose, 405 and 304 adults were assessed, respectively. Measles GMC was 428 mIU/mL (95% CI, 392-468 mIU/mL) 5 years postvaccination, declining to 381 mIU/mL (95% CI, 339-428 mIU/mL) 11 years postvaccination. At the last follow-up visit (9-11 years postvaccination), 10% of participants were potentially susceptible to measles infection. Rubella GMCs were stable throughout the follow-up period (63 U/mL to 65 U/mL); none of the participants was susceptible to rubella at the last follow-up visit. Conclusions: Eleven years after receiving a third MMR dose, measles and rubella neutralizing antibody levels remained high in adults. However, on the basis of waning antibody levels, some adults may become susceptible to measles infection over time despite receipt of 3 vaccine doses.

An individual segmented trajectory approach for identifying opioid use patterns using longitudinal dispensing data.

PURPOSE: The aim of this study is to use electronic opioid dispensing data to develop an individual segmented trajectory approach for identifying opioid use patterns. The resulting opioid use patterns can be used for examining the association between opioid use and drug overdose. METHODS: We retrospectively assembled a cohort of members on long-term opioid therapy (LTOT) between January 1, 2006 and June 30, 2019 who were 18 years and older and enrolled in one of three health care systems in the US. We have developed an individual segmented trajectory analysis for identifying various opioid use patterns by scanning over the follow-up and finding distinct opioid use patterns based on variability measured with coefficient of variation and trends of milligram morphine equivalents levels. RESULTS: Among 31, 865 members who were on LTOT between January 1, 2006 and June 30, 2019, 58.3% were female, and the average age was 55.4 years (STD = 15.4). The study population had 152 557 person-years of follow-up, with an average follow-up of 4.4 years per enrollment per person (STD = 3.4). This novel approach identified up to 13 distinct patterns including 88 756 episodes of "stable" pattern (42.1%) with an average follow-up of 11.2 months, 29 140 episodes of "increasing" pattern (13.8%) with an average follow-up of 6.0 months, 13 201 episodes of ≤10% dose reduction (6.3%) with an average follow-up of 10.4 months, 7286 episodes of 11%-20% dose reduction (3.5%) with an average follow-up of 5.3 months, 4457 episodes of 21%-30% dose reduction (2.1%) with an average follow-up of 4.0 months, and 9903 episodes of >30% dose reduction (4.7%) with an average follow-up of 2.6 months. CONCLUSIONS: A novel approach was developed to identify 13 distinct opioid use patterns using each individual's longitudinal dispensing data and these patterns can be used in examining overdose risk during the time that these patterns are ongoing.

Association Between Opioid Dose Reduction Rates and Overdose Among Patients Prescribed Long-Term Opioid Therapy.

BACKGROUND: Tapering long-term opioid therapy is an increasingly common practice, yet rapid opioid dose reductions may increase the risk of overdose. The objective of this study was to compare overdose risk following opioid dose reduction rates of ≤10%, 11% to 20%, 21% to 30%, and >30% per month to stable dosing. METHODS: We conducted a retrospective cohort study in three health systems in Colorado and Wisconsin. Participants were patients ≥18 years of age prescribed long-term opioid therapy between January 1, 2006, and June 30, 2019. Five opioid dosing patterns and drug overdoses (fatal and nonfatal) were identified using electronic health records, pharmacy records, and the National Death Index. Cox proportional hazard regression was conducted on a propensity score-weighted cohort to estimate adjusted hazard ratios (aHRs) for follow-up periods of 1, 3, 6, 9, and 12 months after a dose reduction. RESULTS: In a cohort of 17 540 patients receiving long-term opioid therapy, 42.7% of patients experienced a dose reduction. Relative to stable dosing, a dose reduction rate of >30% was associated with an increased risk of overdose and the aHR estimates decreased as the follow-up increased; the aHRs for the 1-, 6- and 12-month follow-ups were 5.33 (95% CI, 1.98-14.34), 1.81 (95% CI,1.08-3.03), and 1.49 (95% CI, 0.97-2.27), respectively. The slower tapering rates were not associated with overdose risk. CONCLUSIONS: Patients receiving long-term opioid therapy exposed to dose reduction rates of >30% per month had increased overdose risk relative to patients exposed to stable dosing. Results support the use of slow dose reductions to minimize the risk of overdose.

Safety signal identification for COVID-19 bivalent booster vaccination using tree-based scan statistics in the Vaccine Safety Datalink.

BACKGROUND: Traditional active vaccine safety monitoring involves pre-specifying health outcomes and biologically plausible outcome-specific time windows of concern, limiting the adverse events that can be evaluated. In this study, we used tree-based scan statistics to look broadly for >60,000 possible adverse events after bivalent COVID-19 vaccination. METHODS: Vaccine Safety Datalink enrollees aged ≥5 years receiving Moderna or Pfizer-BioNTech bivalent COVID-19 vaccine through November 2022 were followed for 56 days post-vaccination. Incident diagnoses in inpatient or emergency department settings were analyzed for clustering within the hierarchical ICD-10-CM diagnosis code "tree" and temporally within post-vaccination follow-up. The conditional self-controlled tree-temporal scan statistic was used, conditioning on total number of cases of each diagnosis and total number of cases of any diagnosis occurring during the scanning risk window across the entire tree. P = 0.01 was the pre-specified cut-off for statistical significance. RESULTS: Analysis included 352,509 doses of Moderna and 979,189 doses of Pfizer-BioNTech bivalent vaccines. After Moderna vaccination, no statistically significant clusters were found. After Pfizer-BioNTech, there were clusters of unspecified adverse events (Days 1-3, p = 0.0001-0.0007), influenza (Days 35-56, p = 0.0001), cough (Days 44-55, p = 0.0002), and COVID-19 (Days 52-56, p = 0.0004). CONCLUSIONS: For Pfizer-BioNTech only, we detected clusters of: (1) unspecified adverse effects, as have been observed in other vaccine studies using this method, and (2) respiratory disease toward the end of follow-up. The respiratory clusters were likely due to overlap of follow-up with the spread of respiratory syncytial virus, influenza, and COVID-19, i.e., confounding by seasonality. The untargeted nature of the method and its inherent adjustment for the many diagnoses and risk intervals evaluated are unique advantages. Limitations include susceptibility to time-varying confounding, lower statistical power for assessing risks of specific outcomes than in traditional studies targeting fewer outcomes, and the possibility of missing adverse events not strongly clustered in time or within the "tree."

Effectiveness of first and second COVID-19 mRNA vaccine monovalent booster doses during a period of circulation of Omicron variant sublineages: December 2021-July 2022.

Background: US recommendations for COVID-19 vaccine boosters have expanded in terms of age groups covered and numbers of doses recommended, whereas evolution of Omicron sublineages raises questions about ongoing vaccine effectiveness. Methods: We estimated effectiveness of monovalent COVID-19 mRNA booster vaccination versus two-dose primary series during a period of Omicron variant virus circulation in a community cohort with active illness surveillance. Hazard ratios comparing SARS-CoV-2 infection between booster versus primary series vaccinated individuals were estimated using Cox proportional hazards models with time-varying booster status. Models were adjusted for age and prior SARS-CoV-2 infection. The effectiveness of a second booster among adults ≥50 years of age was similarly estimated. Results: The analysis included 883 participants ranging in age, from 5 to >90 years. Relative effectiveness was 51% (95% CI: 34%, 64%) favoring the booster compared with primary series vaccination and did not vary by prior infection status. Relative effectiveness was 74% (95% CI: 57%, 84%) at 15 to 90 days after booster receipt, but declined to 42% (95% CI: 16%, 61%) after 91 to 180 days, and to 36% (95% CI: 3%, 58%) after 180 days. The relative effectiveness of a second booster compared to a single booster was 24% (95% CI: -40% to 61%). Conclusions: An mRNA vaccine booster dose added significant protection against SARS-CoV-2 infection, but protection decreased over time. A second booster did not add significant protection for adults ≥50 years of age. Uptake of recommended bivalent boosters should be encouraged to increase protection against Omicron BA.4/BA.5 sublineages.

Association Between Aluminum Exposure From Vaccines Before Age 24 Months and Persistent Asthma at Age 24 to 59 Months.

OBJECTIVE: To assess the association between cumulative aluminum exposure from vaccines before age 24 months and persistent asthma at age 24 to 59 months. METHODS: A retrospective cohort study was conducted in the Vaccine Safety Datalink (VSD). Vaccination histories were used to calculate cumulative vaccine-associated aluminum in milligrams (mg). The persistent asthma definition required one inpatient or 2 outpatient asthma encounters, and ≥2 long-term asthma control medication dispenses. Cox proportional hazard models were used to evaluate the association between aluminum exposure and asthma incidence, stratified by eczema presence/absence. Adjusted hazard ratios (aHR) and 95% confidence intervals (CI) per 1 mg increase in aluminum exposure were calculated, adjusted for birth month/year, sex, race/ethnicity, VSD site, prematurity, medical complexity, food allergy, severe bronchiolitis, and health care utilization. RESULTS: The cohort comprised 326,991 children, among whom 14,337 (4.4%) had eczema. For children with and without eczema, the mean (standard deviation [SD]) vaccine-associated aluminum exposure was 4.07 mg (SD 0.60) and 3.98 mg (SD 0.72), respectively. Among children with and without eczema, 6.0% and 2.1%, respectively, developed persistent asthma. Among children with eczema, vaccine-associated aluminum was positively associated with persistent asthma (aHR 1.26 per 1 mg increase in aluminum, 95% CI 1.07, 1.49); a positive association was also detected among children without eczema (aHR 1.19, 95% CI 1.14, 1.25). CONCLUSION: In a large observational study, a positive association was found between vaccine-related aluminum exposure and persistent asthma. While recognizing the small effect sizes identified and the potential for residual confounding, additional investigation of this hypothesis appears warranted.

Tree-based data mining for safety assessment of first COVID-19 booster doses in the Vaccine Safety Datalink.

BACKGROUND: The Centers for Disease Control and Prevention's Vaccine Safety Datalink (VSD) has been performing safety surveillance for COVID-19 vaccines since their earliest authorization in the United States. Complementing its real-time surveillance for pre-specified health outcomes using pre-specified risk intervals, the VSD conducts tree-based data-mining to look for clustering of a broad range of health outcomes after COVID-19 vaccination. This study's objective was to use this untargeted, hypothesis-generating approach to assess the safety of first booster doses of Pfizer-BioNTech (BNT162b2), Moderna (mRNA-1273), and Janssen (Ad26.COV2.S) COVID-19 vaccines. METHODS: VSD enrollees receiving a first booster of COVID-19 vaccine through April 2, 2022 were followed for 56 days. Incident diagnoses in inpatient or emergency department settings were analyzed for clustering within both the hierarchical ICD-10-CM code structure and the follow-up period. The self-controlled tree-temporal scan statistic was used, conditioning on the total number of cases for each diagnosis. P-values were estimated by Monte Carlo simulation; p = 0.01 was pre-specified as the cut-off for statistical significance of clusters. RESULTS: More than 2.4 and 1.8 million subjects received Pfizer-BioNTech and Moderna boosters after an mRNA primary series, respectively. Clusters of urticaria/allergy/rash were found during Days 10-15 after the Moderna booster (p = 0.0001). Other outcomes that clustered after mRNA boosters, mostly with p = 0.0001, included unspecified adverse effects, common vaccine-associated reactions like fever and myalgia, and COVID-19. COVID-19 clusters were in Days 1-10 after booster receipt, before boosters would have become effective. There were no noteworthy clusters after boosters following primary Janssen vaccination. CONCLUSIONS: In this untargeted data-mining study of COVID-19 booster vaccination, a cluster of delayed-onset urticaria/allergy/rash was detected after the Moderna booster, as has been reported after Moderna vaccination previously. Other clusters after mRNA boosters were of unspecified or common adverse effects and COVID-19, the latter evidently reflecting immunity to COVID-19 after 10 days.

A broad assessment of covid-19 vaccine safety using tree-based data-mining in the vaccine safety datalink.

BACKGROUND: Except for spontaneous reporting systems, vaccine safety monitoring generally involves pre-specifying health outcomes and post-vaccination risk windows of concern. Instead, we used tree-based data-mining to look more broadly for possible adverse events after Pfizer-BioNTech, Moderna, and Janssen COVID-19 vaccination. METHODS: Vaccine Safety Datalink enrollees receiving ≥1 dose of COVID-19 vaccine in 2020-2021 were followed for 70 days after Pfizer-BioNTech or Moderna and 56 days after Janssen vaccination. Incident diagnoses in inpatient or emergency department settings were analyzed for clustering within both the hierarchical ICD-10-CM code structure and the post-vaccination follow-up period. We used the self-controlled tree-temporal scan statistic and TreeScan software. Monte Carlo simulation was used to estimate p-values; p = 0.01 was the pre-specified cut-off for statistical significance of a cluster. RESULTS: There were 4.1, 2.6, and 0.4 million Pfizer-BioNTech, Moderna, and Janssen vaccinees, respectively. Clusters after Pfizer-BioNTech vaccination included: (1) unspecified adverse effects, (2) common vaccine reactions, such as fever, myalgia, and headache, (3) myocarditis/pericarditis, and (4) less specific cardiac or respiratory symptoms, all with the strongest clusters generally after Dose 2; and (5) COVID-19/viral pneumonia/sepsis/respiratory failure in the first 3 weeks after Dose 1. Moderna results were similar but without a significant myocarditis/pericarditis cluster. Further investigation suggested the fifth signal group was a manifestation of mRNA vaccine effectiveness after the first 3 weeks. Janssen vaccinees had clusters of unspecified or common vaccine reactions, gait/mobility abnormalities, and muscle weakness. The latter two were deemed to have arisen from confounding related to practices at one site. CONCLUSIONS: We detected post-vaccination clusters of unspecified adverse effects, common vaccine reactions, and, for the mRNA vaccines, chest pain and palpitations, as well as myocarditis/pericarditis after Pfizer-BioNTech Dose 2. Unique advantages of this data mining are its untargeted nature and its inherent adjustment for the multiplicity of diagnoses and risk intervals scanned.

A safety study evaluating non-COVID-19 mortality risk following COVID-19 vaccination.

BACKGROUND: The safety of COVID-19 vaccines plays an important role in addressing vaccine hesitancy. We conducted a large cohort study to evaluate the risk of non-COVID-19 mortality after COVID-19 vaccination while adjusting for confounders including individual-level demographics, clinical risk factors, health care utilization, and community-level socioeconomic risk factors. METHODS: The retrospective cohort study consisted of members from seven Vaccine Safety Datalink sites from December 14, 2020 through August 31, 2021. We conducted three separate analyses for each of the three COVID-19 vaccines used in the US. Crude non-COVID-19 mortality rates were reported by vaccine type, age, sex, and race/ethnicity. The counting process model for survival analyses was used to analyze non-COVID-19 mortality where a new observation period began when the vaccination status changed upon receipt of the first dose and the second dose. We used calendar time as the basic time scale in survival analyses to implicitly adjust for season and other temporal trend factors. A propensity score approach was used to adjust for the potential imbalance in confounders between the vaccinated and comparison groups. RESULTS: For each vaccine type and across age, sex, and race/ethnicity groups, crude non-COVID-19 mortality rates among COVID-19 vaccinees were lower than those among comparators. After adjusting for confounders with the propensity score approach, the adjusted hazard ratios (aHRs) were 0.46 (95% confidence interval [CI], 0.44-0.49) after dose 1 and 0.48 (95% CI, 0.46-0.50) after dose 2 of the BNT162b2 vaccine, 0.41 (95% CI, 0.39-0.44) after dose 1 and 0.38 (95% CI, 0.37-0.40) after dose 2 of the mRNA-1273 vaccine, and 0.55 (95% CI, 0.51-0.59) after receipt of Ad26.COV2.S. CONCLUSION: While residual confounding bias remained after adjusting for several individual-level and community-level risk factors, no increased risk was found for non-COVID-19 mortality among recipients of three COVID-19 vaccines used in the US.

Opioid Dose Trajectories and Associations With Mortality, Opioid Use Disorder, Continued Opioid Therapy, and Health Plan Disenrollment.

Importance: Uncertainty remains about the longer-term benefits and harms of different opioid management strategies, such as tapering and dose escalation. For instance, opioid tapering could help patients reduce opioid exposure to prevent opioid use disorder, but patients may also seek care elsewhere and engage in nonprescribed opioid use. Objective: To evaluate the association between opioid dose trajectories observed in practice and patient outcomes. Design, Setting, and Participants: This retrospective cohort study was conducted in 3 health systems in Colorado and Wisconsin. The study population included patients receiving long-term opioid therapy between 50 and 200 morphine milligram equivalents between August 1, 2014, and July 31, 2017. Follow-up ended on December 31, 2019. Data were analyzed from January 2020 to August 2022. Exposures: Group-based trajectory modeling identified 5 dosing trajectories over 1 year: 1 decreasing, 1 high-dose increasing, and 3 stable. Main Outcomes and Measures: Primary outcomes assessed after the trajectory period were 1-year all-cause mortality, incident opioid use disorder, continued opioid therapy at 1 year, and health plan disenrollment. Associations were tested using Cox proportional hazards regression and log-binomial models, adjusting for baseline covariates. Results: A total of 3913 patients (mean [SD] age, 59.2 [14.4] years; 2767 White non-Hispanic [70.7%]; 2237 female patients [57.2%]) were included in the study. Compared with stable trajectories, the decreasing dose trajectory was negatively associated with opioid use disorder (adjusted hazard ratio [aHR], 0.40; 95% CI, 0.29-0.55) and continued opioid therapy (site 1: adjusted relative risk [aRR], 0.39; 95% CI, 0.34-0.44), but was positively associated with health plan disenrollment (aHR, 1.66; 95% CI, 1.24-2.22). The decreasing trajectory was not associated with mortality (aHR, 1.28; 95% CI, 0.87-1.86). In contrast, the high-dose increasing trajectory was positively associated with mortality (aHR, 2.19; 95% CI, 1.44-3.32) and opioid use disorder (aHR, 1.81; 95% CI, 1.39-2.37) but was not associated with disenrollment (aHR, 0.90; 95% CI, 0.56-1.42) or continued opioid therapy (site 1: aRR, 0.98; 95% CI, 0.94-1.03). Conclusions and Relevance: In this cohort study, decreasing opioid dose was associated with reduced risk of opioid use disorder and continued opioid therapy but increased risk of disenrollment compared with stable dosing, whereas the high-dose increasing trajectory was associated with an increased risk of mortality and opioid use disorder. These findings can inform opioid management decision-making.

Health Care Utilization in the 6 Months Following SARS-CoV-2 Infection.

Importance: After SARS-CoV-2 infection, many patients present with persistent symptoms for at least 6 months, collectively termed post-COVID conditions (PCC). However, the impact of PCC on health care utilization has not been well described. Objectives: To estimate COVID-19-associated excess health care utilization following acute SARS-CoV-2 infection and describe utilization for select PCCs among patients who had positive SARS-CoV-2 test results (including reverse transcription-polymerase chain reaction and antigen tests) compared with control patients whose results were negative. Design, Setting, and Participants: This matched retrospective cohort study included patients of all ages from 8 large integrated health care systems across the United States who completed a SARS-CoV-2 diagnostic test during March 1 to November 1, 2020. Patients were matched on age, sex, race and ethnicity, site, and date of SARS-CoV-2 test and were followed-up for 6 months. Data were analyzed from March 18, 2021, to June 8, 2022. Exposure: SARS-CoV-2 infection. Main Outcomes and Measures: Ratios of rate ratios (RRRs) for COVID-19-associated health care utilization were calculated with a difference-in-difference analysis using Poisson regression models. RRRs were estimated overall, by health care setting, by select population characteristics, and by 44 PCCs. COVID-19-associated excess health care utilization was estimated by health care setting. Results: The final matched cohort included 127 859 patients with test results positive for SARS-CoV-2 and 127 859 patients with test results negative for SARS-CoV-2. The mean (SD) age of the study population was 41.2 (18.6) years, 68 696 patients in each group (53.7%) were female, and each group included 66 211 Hispanic patients (51.8%), 9122 non-Hispanic Asian patients (7.1%), 7983 non-Hispanic Black patients (6.2%), and 34 326 non-Hispanic White patients (26.9%). Overall, SARS-CoV-2 infection was associated with a 4% increase in health care utilization over 6 months (RRR, 1.04 [95% CI, 1.03-1.05]), predominantly for virtual encounters (RRR, 1.14 [95% CI, 1.12-1.16]), followed by emergency department visits (RRR, 1.08 [95% CI, 1.04-1.12]). COVID-19-associated utilization for 18 PCCs remained elevated 6 months from the acute stage of infection, with the largest increase in COVID-19-associated utilization observed for infectious disease sequelae (RRR, 86.00 [95% CI, 5.07-1458.33]), COVID-19 (RRR, 19.47 [95% CI, 10.47-36.22]), alopecia (RRR, 2.52 [95% CI, 2.17-2.92]), bronchitis (RRR, 1.85 [95% CI, 1.62-2.12]), pulmonary embolism or deep vein thrombosis (RRR, 1.74 [95% CI, 1.36-2.23]), and dyspnea (RRR, 1.73 [95% CI, 1.61-1.86]). In total, COVID-19-associated excess health care utilization amounted to an estimated 27 217 additional medical encounters over 6 months (212.9 [95% CI, 146.5-278.4] visits per 1000 patients). Conclusions and Relevance: This cohort study documented an excess health care burden of PCC in the 6 months after the acute stage of infection. As health care systems evolve during a highly dynamic and ongoing global pandemic, these data provide valuable evidence to inform long-term strategic resource allocation for patients previously infected with SARS-CoV-2.

Frail patients having vascular surgery during the early COVID-19 pandemic experienced high rates of adverse perioperative events and amputation.

BACKGROUND: Frailty predicts adverse perioperative outcomes and increased mortality in patients having vascular surgery. Frailty assessment is a potential tool to inform resource allocation, and shared decision-making about vascular surgery in the resource constrained COVID-19 pandemic environment. This cohort study describes the prevalence of frailty in patients having vascular surgery and the association between frailty, mortality and perioperative outcomes. METHODS: The COVID-19 Vascular Service in Australia (COVER-AU) prospective cohort study evaluates 30-day and six-month outcomes for consecutive patients having vascular surgery in 11 Australian vascular units, March-July 2020. The primary outcome was mortality, with secondary outcomes procedure-related outcomes and hospital utilization. Frailty was assessed using the nine-point visual Clinical Frailty Score, scores of 5 or more considered frail. RESULTS: Of the 917 patients enrolled, 203 were frail (22.1%). The 30 day and 6 month mortality was 2.0% (n = 20) and 5.9% (n = 35) respectively with no significant difference between frail and non-frail patients (OR 1.68, 95%CI 0.79-3.54). However, frail patients stayed longer in hospital, had more perioperative complications, and were more likely to be readmitted or have a reoperation when compared to non-frail patients. At 6 months, frail patients had twice the odds of major amputation compared to non-frail patients, after adjustment (OR 2.01; 95% CI 1.17-3.78), driven by a high rate of amputation during the period of reduced surgical activity. CONCLUSION: Our findings highlight that older, frail patients, experience potentially preventable adverse outcomes and there is a need for targeted interventions to optimize care, especially in times of healthcare stress.

mRNA COVID-19 vaccine effectiveness against SARS-CoV-2 infection in a prospective community cohort, rural Wisconsin, November 2020 to December 2021.

Reduced COVID-19 vaccine effectiveness (VE) has been observed with increasing predominance of SARS-CoV-2 Delta (B.1.617.2) variant. Two-dose VE against laboratory-confirmed SARS-CoV-2 infection (symptomatic and asymptomatic) was estimated using Cox proportional hazards models with time-varying vaccination status in a prospective rural community cohort of 1266 participants aged ≥12 years. Between November 3, 2020 and December 7, 2021, VE was 56% for mRNA COVID-19 vaccines overall, 65% for Moderna, and 50% for Pfizer-BioNTech. VE when Delta predominated (June to December 2021) was 54% for mRNA COVID-19 vaccines overall, 59% for Moderna, and 52% for Pfizer-BioNTech.

The Childhood Vaccination Schedule and the Lack of Association With Type 1 Diabetes.

OBJECTIVES: Safety studies assessing the association between the entire recommended childhood immunization schedule and autoimmune diseases, such as type 1 diabetes mellitus (T1DM), are lacking. To examine the association between the recommended immunization schedule and T1DM, we conducted a retrospective cohort study of children born between 2004 and 2014 in 8 US health care organizations that participate in the Vaccine Safety Datalink. METHODS: Three measures of the immunization schedule were assessed: average days undervaccinated (ADU), cumulative antigen exposure, and cumulative aluminum exposure. T1DM incidence was identified by International Classification of Disease codes. Cox proportional hazards models were used to analyze associations between the 3 exposure measures and T1DM incidence. Adjusted hazard ratios (aHRs) and 95% confidence intervals (CIs) were calculated. Models were adjusted for sex, race and ethnicity, birth year, mother's age, birth weight, gestational age, number of well-child visits, and study site. RESULTS: In a cohort of 584 171 children, the mean ADU was 38 days, the mean cumulative antigen exposure was 263 antigens (SD = 54), and the mean cumulative aluminum exposure was 4.11 mg (SD = 0.73). There were 1132 incident cases of T1DM. ADU (aHR = 1.01; 95% CI, 0.99-1.02) and cumulative antigen exposure (aHR = 0.98; 95% CI, 0.97-1.00) were not associated with T1DM. Cumulative aluminum exposure >3.00 mg was inversely associated with T1DM (aHR = 0.77; 95% CI, 0.60-0.99). CONCLUSIONS: The recommended schedule is not positively associated with the incidence of T1DM in children. These results support the safety of the recommended childhood immunization schedule.

COVID-19 Vaccination and Non-COVID-19 Mortality Risk - Seven Integrated Health Care Organizations, United States, December 14, 2020-July 31, 2021.

By September 21, 2021, an estimated 182 million persons in the United States were fully vaccinated against COVID-19.* Clinical trials indicate that Pfizer-BioNTech (BNT162b2), Moderna (mRNA-1273), and Janssen (Johnson & Johnson; Ad.26.COV2.S) vaccines are effective and generally well tolerated (1-3). However, daily vaccination rates have declined approximately 78% since April 13, 2021†; vaccine safety concerns have contributed to vaccine hesitancy (4). A cohort study of 19,625 nursing home residents found that those who received an mRNA vaccine (Pfizer-BioNTech or Moderna) had lower all-cause mortality than did unvaccinated residents (5), but no studies comparing mortality rates within the general population of vaccinated and unvaccinated persons have been conducted. To assess mortality not associated with COVID-19 (non-COVID-19 mortality) after COVID-19 vaccination in a general population setting, a cohort study was conducted during December 2020-July 2021 among approximately 11 million persons enrolled in seven Vaccine Safety Datalink (VSD) sites.§ After standardizing mortality rates by age and sex, this study found that COVID-19 vaccine recipients had lower non-COVID-19 mortality than did unvaccinated persons. After adjusting for demographic characteristics and VSD site, this study found that adjusted relative risk (aRR) of non-COVID-19 mortality for the Pfizer-BioNTech vaccine was 0.41 (95% confidence interval [CI] = 0.38-0.44) after dose 1 and 0.34 (95% CI = 0.33-0.36) after dose 2. The aRRs of non-COVID-19 mortality for the Moderna vaccine were 0.34 (95% CI = 0.32-0.37) after dose 1 and 0.31 (95% CI = 0.30-0.33) after dose 2. The aRR after receipt of the Janssen vaccine was 0.54 (95% CI = 0.49-0.59). There is no increased risk for mortality among COVID-19 vaccine recipients. This finding reinforces the safety profile of currently approved COVID-19 vaccines in the United States.

Trends in Mortality at a Level II Rural Trauma Center.

BACKGROUND: Most studies of deaths from traumatic injury are from urban trauma centers. In contrast, rural areas have higher incidence of traumatic fatal injuries than urban areas. The objective of this research was to describe trends of injuries and mortality from a trauma center serving a largely rural population and compare results with reports from the National Trauma Data Bank (NTDB). METHODS: We conducted a retrospective study of patients admitted to a rural Wisconsin level II trauma center from 2000 through 2018. Details on injuries and deaths prior to discharge were obtained from the trauma registry. Event counts and fatality ratios were described by year, sex, age, mechanism of injury, and injury severity score (ISS). Trends were analyzed across 2000-2005, 2006-2011, and 2012-2018 calendar year eras. RESULTS: During 2000-2018, there were 17,334 injury events among 16,495 patients included in the trauma registry. Across the 3 eras, the proportion of injuries related to falls increased (35.6%, 40.6%, and 51.5%, respectively), and the proportion from on-road motor vehicle events decreased (37.0 %, 32.8, and 22.5%, respectively), similar to the trends from 3 corresponding NTDB reports for 2004, 2010, and 2016. There was a statistically significant decreasing trend (P < 0.001) in overall fatality ratios across the 3 eras, 5.3% (95% CI, 4.7%-6.0%), 4.1% (95% CI, 3.7%-4.6%), and 3.9 (95% CI, 3.4%-4.4%), respectively. The fatality ratios point estimates were similar to overall fatality ratios from the NTDB reports (4.7%, 4.0%, 4.3%, respectively). The median patient age increased significantly from 42, 45, and 55 years across the 3 eras (test for trend P < 0.0001). CONCLUSION: Long-term trends of traumatic injuries and mortality were generally similar to national trends, particularly in the shift to older patients and in the increasing proportion of injury events due to falls. Further research on traumatic injuries and deaths in rural populations is needed, particularly regarding immediate deaths at the scene and longer-term deaths after discharge.

Vaccine Safety Datalink infrastructure enhancements for evaluating the safety of maternal vaccination.

BACKGROUND: Identifying pregnancy episodes and accurately estimating their beginning and end dates are imperative for observational maternal vaccine safety studies using electronic health record (EHR) data. METHODS: We modified the Vaccine Safety Datalink (VSD) Pregnancy Episode Algorithm (PEA) to include both the International Classification of Disease, ninth revision (ICD-9 system) and ICD-10 diagnosis codes, incorporated additional gestational age data, and validated this enhanced algorithm with manual medical record review. We also developed the new Dynamic Pregnancy Algorithm (DPA) to identify pregnancy episodes in real time. RESULTS: Around 75% of the pregnancy episodes identified by the enhanced VSD PEA were live births, 12% were spontaneous abortions (SABs), 10% were induced abortions (IABs), and 0.4% were stillbirths (SBs). Gestational age was identified for 99% of live births, 89% of SBs, 69% of SABs, and 42% of IABs. Agreement between the PEA-assigned and abstractor-identified pregnancy outcome and outcome date was 100% for live births, but was lower for pregnancy losses. When gestational age was available in the medical record, the agreement was higher for live births (97%), but lower for pregnancy losses (75%). The DPA demonstrated strong concordance with the PEA and identified pregnancy episodes ⩾6 months prior to the outcome date for 89% of live births. CONCLUSION: The enhanced VSD PEA is a useful tool for identifying pregnancy episodes in EHR databases. The DPA improves the timeliness of pregnancy identification and can be used for near real-time maternal vaccine safety studies. PLAIN LANGUAGE SUMMARY: Improving identification of pregnancies in the Vaccine Safety Datalink electronic medical record databases to allow for better and faster monitoring of vaccination safety during pregnancy Introduction: It is important to monitor of the safety of vaccines after they have been approved and licensed by the Food and Drug Administration, especially among women vaccinated during pregnancy. The Vaccine Safety Datalink (VSD) monitors vaccine safety through observational studies within large databases of electronic medical records. Since 2012, VSD researchers have used an algorithm called the Pregnancy Episode Algorithm (PEA) to identify the medical records of women who have been pregnant. Researchers then use these medical records to study whether receiving a particular vaccine is linked to any negative outcomes for the woman or her child.Methods: The goal of this study was to update and enhance the PEA to include the full set of medical record diagnostic codes [both from the older International Classification of Disease, ninth revision (ICD-9 system) and the newer ICD-10 system] and to incorporate additional sources of data about gestational age. To ensure the validity of the PEA following these enhancements, we manually reviewed medical records and compared the results with the algorithm. We also developed a new algorithm, the Dynamic Pregnancy Algorithm (DPA), to identify women earlier in pregnancy, allowing us to conduct more timely vaccine safety assessments.Results: The new version of the PEA identified 2,485,410 pregnancies in the VSD database. The enhanced algorithm more precisely estimated the beginning of pregnancies, especially those that did not result in live births, due to the new sources of gestational age data.Conclusion: Our new algorithm, the DPA, was successful at identifying pregnancies earlier in gestation than the PEA. The enhanced PEA and the new DPA will allow us to better evaluate the safety of current and future vaccinations administered during or around the time of pregnancy.

Evaluating the Association of Stillbirths After Maternal Vaccination in the Vaccine Safety Datalink.

OBJECTIVE: To evaluate whether the Centers for Disease Control and Prevention's Advisory Committee on Immunization Practices recommended influenza and tetanus toxoid, reduced diphtheria toxoid, and acellular pertussis (Tdap) vaccinations in pregnancy are associated with increased risk of stillbirth. METHODS: We performed a case-control study in the Vaccine Safety Datalink that was matched 1:4 on site, month, and year of last menstrual period, comparing the odds of vaccination in pregnancies that ended in stillbirth (defined as fetal loss at or after 20 weeks of gestation) compared with those that ended in live birth from January 1, 2012, to September 30, 2015. We included patients with singleton pregnancies that ended in stillbirth or live birth who had at least one prenatal care visit, pregnancy dating information, and continuous health plan enrollment for the duration of pregnancy. Medical records for all stillbirths were reviewed. We were statistically powered to detect an odds ratio (OR) of 1.37 when evaluating the association between influenza or Tdap vaccination and stillbirth. We also examined stillbirth rates in pregnant patients aged 14-49 years in the Vaccine Safety Datalink between 2007 and 2015. RESULTS: In our matched analysis of 795 confirmed stillbirths in the case group and 3,180 live births in the control group, there was no significant association between influenza vaccination during pregnancy and stillbirth (343/795 [43.1%] stillbirths in the case group vs 1,407/3,180 [44.3%] live births in the control group, OR 0.94, adjusted OR 0.95, 95% CI 0.79-1.14, P=.54) and no significant association between Tdap vaccination during pregnancy and stillbirth (184/795 [23.1%] stillbirths in the case group vs 746/3,180 [23.5%] live births in the control group, OR 0.97, aOR 0.96, 95% CI 0.76-1.28, P=.91). From 2007 to 2015, the stillbirth rate in the Vaccine Safety Datalink was 5.2 per 1,000 live births and stillbirths. CONCLUSION: No association was found between vaccination during pregnancy and the odds of stillbirth. These findings support the safety of ACIP recommendations for vaccination during pregnancy.

Prediction of serious RSV-related outcomes in older adults with outpatient RSV respiratory illness during 12 consecutive seasons.

We developed and evaluated a model to predict serious outcomes among 243 adults ≥60 years old with medically attended respiratory illness and laboratory-confirmed respiratory syncytial virus (RSV); 47 patients had a serious outcome defined as hospital admission, emergency department (ED) visit, or pneumonia diagnosis. The model used logistic regression with penalized maximum likelihood estimation. The reduced penalized model included age ≥ 75 years, ≥1 ED visit in prior year, crackles/rales, tachypnea, wheezing, new/increased sputum, and new/increased dyspnea. The optimal score cutoff yielded sensitivity and specificity of 66.0% and 81.6%. This prediction model provided moderate utility for identifying older adults with elevated risk of complicated RSV illness.