Assessing the association between antibody status and symptoms of long COVID: A multisite study.

The association between SARS-CoV-2 humoral immunity and post-acute sequelae of COVID-19 (long COVID) remains uncertain. The objective of this population-based cohort study was to assess the association between SARS-CoV-2 seropositivity and symptoms consistent with long COVID. English and Spanish-speaking members ≥ 18 years old with SARS-CoV-2 serologic testing conducted prior to August 2021 were recruited from Kaiser Permanente Southern California and Kaiser Permanente Colorado. Between November 2021 and April 2022, participants completed a survey assessing symptoms, physical health, mental health, and cognitive function consistent with long COVID. Survey results were linked to SARS-CoV-2 antibody (Ab) and viral (RNA) lab results in electronic health records. Weighted descriptive analyses were generated for five mutually exclusive patient groups: (1) +Ab/+RNA; (2) +Ab/- or missing RNA; (3) -Ab/+RNA; (4a) -Ab/-RNA reporting no prior infection; and (4b) -Ab/-RNA reporting prior infection. The proportions reporting symptoms between the +Ab/+RNA and -Ab/+RNA groups were compared, adjusted for covariates. Among 3,946 participants, the mean age was 52.1 years old (SD 15.6), 68.3% were female, 28.4% were Hispanic, and the serologic testing occurred a median of 15 months prior (IQR = 12-18). Three quarters (74.5%) reported having had COVID-19. Among people with laboratory-confirmed COVID-19, there was no association between antibody positivity (+Ab/+RNA vs. -Ab/+RNA) and any symptoms, physical health, mental health, or cognitive function. As expected, physical health, cognitive function, and fatigue were worse, and palpitations and headaches limiting the ability to work were more prevalent among people with laboratory-confirmed prior infection and positive serology (+Ab/+RNA) compared to those without reported or confirmed prior infection and negative serology (-Ab/-RNA/no reported COVID-19). Among people with laboratory-confirmed COVID-19, SARS-CoV-2 serology from practice settings were not associated with long COVID symptoms and health status suggesting limited utility of serology testing for long COVID.

COVID-19 Vaccination Coverage and Factors Associated With Vaccine Uptake Among People With HIV.

Importance: People with HIV (PWH) may be at increased risk for severe outcomes with COVID-19 illness compared with people without HIV. Little is known about COVID-19 vaccination coverage and factors associated with primary series completion among PWH. Objectives: To evaluate COVID-19 vaccination coverage among PWH and examine sociodemographic, clinical, and community-level factors associated with completion of the primary series and an additional primary dose. Design, Setting, and Participants: This retrospective cohort study used electronic health record data to assess COVID-19 vaccination information from December 14, 2020, through April 30, 2022, from 8 health care organizations of the Vaccine Safety Datalink project in the US. Participants were adults diagnosed with HIV on or before December 14, 2020, enrolled in a participating site. Main Outcomes and Measures: The percentage of PWH with at least 1 dose of COVID-19 vaccine and PWH who completed the COVID-19 vaccine primary series by December 31, 2021, and an additional primary dose by April 30, 2022. Rate ratios (RR) and 95% CIs were estimated using Poisson regression models for factors associated with completing the COVID-19 vaccine primary series and receiving an additional primary dose. Results: Among 22 058 adult PWH (mean [SD] age, 52.1 [13.3] years; 88.8% male), 90.5% completed the primary series by December 31, 2021. Among 18 374 eligible PWH who completed the primary series by August 12, 2021, 15 982 (87.0%) received an additional primary dose, and 4318 (23.5%) received a booster dose by April 30, 2022. Receipt of influenza vaccines in the last 2 years was associated with completion of the primary series (RR, 1.17; 95% CI, 1.15-1.20) and an additional primary dose (RR, 1.61; 95% CI, 1.54-1.69). PWH with uncontrolled viremia (HIV viral load ≥200 copies/mL) (eg, RR, 0.90 [95% CI, 0.85-0.95] for viral load 200-10 000 copies/mL vs undetected or <200 copies/mL for completing the primary series) and Medicaid insurance (eg, RR, 0.89 [95% CI, 0.87-0.90] for completing the primary series) were less likely to be fully vaccinated. By contrast, greater outpatient utilization (eg, RR, 1.07 [95% CI, 1.05-1.09] for ≥7 vs 0 visits for primary series completion) and residence in counties with higher COVID-19 vaccine coverage (eg, RR, 1.06 [95% CI, 1.03-1.08] for fourth vs first quartiles for primary series completion) were associated with primary series and additional dose completion (RRs ranging from 1.01 to 1.21). Conclusions and Relevance: Findings from this cohort study suggest that, while COVID-19 vaccination coverage was high among PWH, outreach efforts should focus on those who did not complete vaccine series and those who have uncontrolled viremia.

Vaccination Timeliness Among US Children Aged 0-19 Months, National Immunization Survey-Child 2011-2021.

Importance: Delays in receiving vaccinations lead to greater vaccine-preventable disease risk. Timeliness of receipt of recommended vaccinations is not routinely tracked in the US, either overall or for populations that have known barriers to accessing routine health care, including lower-income families and children. Objective: To measure vaccination timeliness among US children aged 0 to 19 months, overall and by socioeconomic indicators. Design, Setting, and Participants: This serial, cross-sectional study analyzed nationally representative data from the 2011 to 2021 National Immunization Survey-Child (NIS-Child), an annual survey of parents, with immunization histories collected from clinicians administering vaccines. The 2020 and 2021 surveys largely reflected vaccinations in the US before the COVID-19 pandemic. Study participants included US children surveyed at ages 19 to 35 months. Data were analyzed from January to August 2023. Exposure: Survey year. Main Outcomes and Measures: The primary outcomes were average days undervaccinated (ADU) and percentage of children who received all vaccine doses on time (ie, 0 days undervaccinated) for the combined 7-vaccine series up to age 19 months. The mean adjusted annual change in on-time vaccination by socioeconomic indicators was calculated by use of multivariable log-linked binomial regression models. Results: The surveys included 179 154 children (92 248 boys [51.2%]); 74 479 (31.4%, weighted) lived above the federal poverty level with more than $75 000 in annual family income, 58 961 (32.4%) lived at or above the poverty level with $75 000 or less in annual family income, and 39 564 (30.2%) lived below the poverty level. Overall, the median (IQR) ADU for the combined 7-vaccine series in the US decreased from 22.3 (0.4-71.5) days in the 2011 survey to 11.9 (0.0-55.5) days in the 2021 survey. The prevalence of on-time receipt of the combined 7-vaccine series increased from 22.5% (95% CI, 21.4%-23.6%) to 35.6% (95% CI, 34.2%-37.0%). Although children with more than $75 000 in annual family income had a 4.6% (95% CI, 4.0%-5.2%) mean annual increase in on-time vaccination, the mean annual increase was 2.8% (95% CI, 2.0%-3.6%) for children living at or above the poverty level with $75 000 or less in annual family income and 2.0% (95% CI, 1.0%-3.0%) for children living below the poverty level. Conclusions and Relevance: In this cross-sectional study of NIS-Child data, improvements in vaccination timeliness were observed from the 2011 to the 2021 survey. However, widening disparities by socioeconomic indicators signal that increased efforts to facilitate timely vaccination among children in lower-income families are needed.

Influenza vaccination accuracy among adults: Self-report compared with electronic health record data.

OBJECTIVE: To assess the validity of electronic health record (EHR)-based influenza vaccination data among adults in a multistate network. METHODS: Following the 2018-2019 and 2019-2020 influenza seasons, surveys were conducted among a random sample of adults who did or did not appear influenza-vaccinated (per EHR data) during the influenza season. Participants were asked to report their influenza vaccination status; self-report was treated as the criterion standard. Results were combined across survey years. RESULTS: Survey response rate was 44.7% (777 of 1740) for the 2018-2019 influenza season and 40.5% (505 of 1246) for the 2019-2020 influenza season. The sensitivity of EHR-based influenza vaccination data was 75.0% (95% confidence interval [CI] 68.1, 81.1), specificity 98.4% (95% CI 92.9, 99.9), and negative predictive value 73.9% (95% CI 68.0, 79.3). CONCLUSIONS: In a multistate research network across two recent influenza seasons, there was moderate concordance between EHR-based vaccination data and self-report.

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.

Association between severe acute respiratory syndrome coronavirus 2 antibody status and reinfection: A case-control study nested in a Colorado-based prospective cohort study.

The association between the presence of detectable antibodies to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and SARS-CoV-2 reinfection is not well established. The objective of this study was to determine the association between antibody seronegativity and reinfection. METHODS: Participants in Colorado, USA, were recruited between June 15, 2020, and March 28, 2021, and encouraged to complete SARS-CoV-2 molecular ribonucleic acid (RNA) and serology testing for antibodies every 28 days for 10 months. Participants with reinfections (positive SARS-CoV-2 RNA test ≥ 90 days after the first positive RNA test) were matched to controls without reinfections by age, sex, date of the first positive RNA test, date of the last serology test, and serology test type. Using conditional logistic regression, case patients were compared to control patients on the last serologic test result, with adjustment for demographic and clinical confounders. RESULTS: The cohort (n = 4,235) included 2,033 participants with ≥ 1 positive RNA test, of whom 120 had reinfection. Among the 80 case patients who could be matched, the last serologic test was negative in 12 of the cases (15.0 %) whereas the last serologic test was negative in 77 of 1,034 (7.5 %) controls. Seronegativity (adjusted OR [aOR] 2.24; 95 % CI 1.07, 4.68), Hispanic ethnicity (aOR 1.87; 95 % 1.10, 3.18), and larger household size (aOR 1.15; 95 % 1.01, 1.30 for each additional household member) were associated with reinfection. CONCLUSIONS: Seronegative status, Hispanic ethnicity, and increasing household size were associated with reinfection. Serologic testing could be considered to reduce vaccine hesitancy in higher risk populations.

Impact of the COVID-19 Pandemic on Health Care Utilization in the Vaccine Safety Datalink: Retrospective Cohort Study.

BACKGROUND: Understanding the long-term impact of the COVID-19 pandemic on health care utilization is important to health care organizations and policy makers for strategic planning, as well as to researchers when designing studies that use observational electronic health record data during the pandemic period. OBJECTIVE: This study aimed to evaluate the changes in health care utilization across all care settings among a large, diverse, and insured population in the United States during the COVID-19 pandemic. METHODS: We conducted a retrospective cohort study within 8 health care organizations participating in the Vaccine Safety Datalink Project using electronic health record data from members of all ages from January 1, 2017, to December 31, 2021. The visit rates per person-year were calculated monthly during the study period for 4 health care settings combined as well as by inpatient, emergency department (ED), outpatient, and telehealth settings, both among all members and members without COVID-19. Difference-in-difference analysis and interrupted time series analysis were performed to assess the changes in visit rates from the prepandemic period (January 2017 to February 2020) to the early pandemic period (April-December 2020) and the later pandemic period (July-December 2021), respectively. An exploratory analysis was also conducted to assess trends through June 2023 at one of the largest sites, Kaiser Permanente Southern California. RESULTS: The study included more than 11 million members from 2017 to 2021. Compared with the prepandemic period, we found reductions in visit rates during the early pandemic period for all in-person care settings. During the later pandemic period, overall use reached 8.36 visits per person-year, exceeding the prepandemic level of 7.49 visits per person-year in 2019 (adjusted percent change 5.1%, 95% CI 0.6%-9.9%); inpatient and ED visits returned to prepandemic levels among all members, although they remained low at 0.095 and 0.241 visits per person-year, indicating a 7.5% and 8% decrease compared to pre-pandemic levels among members without COVID-19, respectively. Telehealth visits, which were approximately 42% of the volume of outpatient visits during the later pandemic period, were increased by 97.5% (95% CI 86.0%-109.7%) from 0.865 visits per person-year in 2019 to 2.35 visits per person-year in the later pandemic period. The trends in Kaiser Permanente Southern California were similar to those of the entire study population. Visit rates from January 2022 to June 2023 were stable and appeared to be a continuation of the use levels observed at the end of 2021. CONCLUSIONS: Telehealth services became a mainstay of the health care system during the late COVID-19 pandemic period. Inpatient and ED visits returned to prepandemic levels, although they remained low among members without evidence of COVID-19. Our findings provide valuable information for strategic resource allocation for postpandemic patient care and for designing observational studies involving the pandemic period.

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.

Racial and ethnic disparities in influenza vaccination coverage among pregnant women in the United States: The contribution of vaccine-related attitudes.

OBJECTIVE: Racial and ethnic disparities in influenza vaccination coverage among pregnant women in the United States have been documented. This study assessed the contribution of vaccine-related attitudes to coverage disparities. METHODS: Surveys were conducted following the 2019-2020 and 2020-2021 influenza seasons in a US research network. Using electronic health record data to identify pregnant women, random samples were selected for surveying; non-Hispanic Black women and influenza-unvaccinated women were oversampled. Regression-based decomposition analyses were used to assess the contribution of vaccine-related attitudes to racial and ethnic differences in influenza vaccination. Data were combined across survey years, and analyses were weighted and accounted for survey design. RESULTS: Survey response rate was 41.2% (721 of 1748) for 2019-2020 and 39.3% (706 of 1798) for 2020-2021. Self-reported influenza vaccination was higher among non-Hispanic White respondents (79.4% coverage, 95% CI 73.1%-85.7%) than Hispanic (66.2% coverage, 95% CI 52.5%-79.9%) and non-Hispanic Black (55.8% coverage, 95% CI 50.2%-61.4%) respondents. For all racial and ethnic groups, a high proportion (generally >80%) reported being seen for care, recommended for influenza vaccination, and offered vaccination. In decomposition analyses, vaccine-related attitudes (e.g., worry about vaccination causing influenza; concern about vaccine safety and effectiveness) explained a statistically significant portion of the observed racial and ethnic disparities in vaccination. Maternal age, education, and health status were not significant contributors after controlling for vaccine-related attitudes. CONCLUSIONS: In a setting with relatively high influenza vaccination coverage among pregnant women, racial and ethnic disparities in coverage were identified. Vaccine-related attitudes were associated with the disparities observed.

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.

Failure to Complete Multidose Vaccine Series in Early Childhood.

BACKGROUND: Most early childhood immunizations require 3 to 4 doses to achieve optimal protection. Our objective was to identify factors associated with starting but not completing multidose vaccine series. METHODS: Using 2019 National Immunization Survey-Child data, US children ages 19 to 35 months were classified in 1 of 3 vaccination patterns: (1) completed the combined 7-vaccine series, (2) did not initiate ≥1 of the 7 vaccine series, or (3) initiated all series, but did not complete ≥1 multidose series. Associations between sociodemographic factors and vaccination pattern were evaluated using multivariable log-linked binomial regression. Analyses accounted for the survey's stratified design and complex weighting. RESULTS: Among 16 365 children, 72.9% completed the combined 7-vaccine series, 9.9% did not initiate ≥1 series, and 17.2% initiated, but did not complete ≥1 multidose series. Approximately 8.4% of children needed only 1 additional vaccine dose from 1 of the 5 multidose series to complete the combined 7-vaccine series. The strongest associations with starting but not completing multidose vaccine series were moving across state lines (adjusted prevalence ratio [aPR] = 1.45, 95% confidence interval [CI]: 1.18-1.79), number of children in the household (2 to 3: aPR = 1.29, 95% CI: 1.05-1.58; 4 or more: aPR = 1.68, 95% CI: 1.30-2.18), and lack of insurance coverage (aPR = 2.03, 95% CI: 1.42-2.91). CONCLUSIONS: More than 1 in 6 US children initiated but did not complete all doses in multidose vaccine series, suggesting children experienced structural barriers to vaccination. Increased focus on strategies to encourage multidose series completion is needed to optimize protection from preventable diseases and achieve vaccination coverage goals.

Safety of simultaneous vaccination with COVID-19 vaccines in the Vaccine Safety Datalink.

INTRODUCTION: Safety data on simultaneous vaccination (SV) with primary series monovalent COVID-19 vaccines and other vaccines are limited. We describe SV with primary series COVID-19 vaccines and assess 23 pre-specified health outcomes following SV among persons aged ≥5 years in the Vaccine Safety Datalink (VSD). METHODS: We utilized VSD's COVID-19 vaccine surveillance data from December 11, 2020-May 21, 2022. Analyses assessed frequency of SV. Rate ratios (RRs) were estimated by Poisson regression when the number of outcomes was ≥5 across both doses, comparing outcome rates between COVID-19 vaccinees receiving SV and COVID-19 vaccinees receiving no SV in the 1-21 days following COVID-19 vaccine dose 1 and 1-42 days following dose 2 by SV type received ("All SV", "Influenza SV", "Non-influenza SV"). RESULTS: SV with COVID-19 vaccines was not common practice (dose 1: 0.7 % of 8,455,037 persons, dose 2: 0.3 % of 7,787,013 persons). The most frequent simultaneous vaccines were influenza, HPV, Tdap, and meningococcal. Outcomes following SV with COVID-19 vaccines were rare (total of 56 outcomes observed after dose 1 and dose 2). Overall rate of outcomes among COVID-19 vaccinees who received SV was not statistically significantly different than the rate among those who did not receive SV (6.5 vs. 6.8 per 10,000 persons). Statistically significant elevated RRs were observed for appendicitis (2.09; 95 % CI, 1.06-4.13) and convulsions/seizures (2.78; 95 % CI, 1.10-7.06) in the "All SV" group following dose 1, and for Bell's palsy (2.82; 95 % CI, 1.14-6.97) in the "Influenza SV" group following dose 2. CONCLUSION: Combined pre-specified health outcomes observed among persons who received SV with COVID-19 vaccine were rare and not statistically significantly different compared to persons who did not receive SV with COVID-19 vaccine. Statistically significant adjusted rate ratios were observed for some individual outcomes, but the number of outcomes was small and there was no adjustment for multiple testing.

Update of a Multivariable Opioid Overdose Risk Prediction Model to Enhance Clinical Care for Long-term Opioid Therapy Patients.

BACKGROUND: Clinical opioid overdose risk prediction models can be useful tools to reduce the risk of overdose in patients prescribed long-term opioid therapy (LTOT). However, evolving overdose risk environments and clinical practices in addition to potential harmful model misapplications require careful assessment prior to widespread implementation into clinical care. Models may need to be tailored to meet local clinical operational needs and intended applications in practice. OBJECTIVE: To update and validate an existing opioid overdose risk model, the Kaiser Permanente Colorado Opioid Overdose (KPCOOR) Model, in patients prescribed LTOT for implementation in clinical care. DESIGN, SETTING, AND PARTICIPANTS: The retrospective cohort study consisted of 33, 625 patients prescribed LTOT between January 2015 and June 2019 at Kaiser Permanente Colorado, with follow-up through June 2021. MAIN MEASURES: The outcome consisted of fatal opioid overdoses identified from vital records and non-fatal opioid overdoses from emergency department and inpatient settings. Predictors included demographics, medication dispensings, substance use disorder history, mental health history, and medical diagnoses. Cox proportional hazards regressions were used to model 2-year overdose risk. KEY RESULTS: During follow-up, 65 incident opioid overdoses were observed (111.4 overdoses per 100,000 person-years) in the study cohort, of which 11 were fatal. The optimal risk model needed to risk-stratify patients and to be easily interpreted by clinicians. The original 5-variable model re-validated on the new study cohort had a bootstrap-corrected C-statistic of 0.73 (95% CI, 0.64-0.85) compared to a C-statistic of 0.80 (95% CI, 0.70-0.88) in the updated model and 0.77 (95% CI, 0.66-0.87) in the final adapted 7-variable model, which was also well-calibrated. CONCLUSIONS: Updating and adapting predictors for opioid overdose in the KPCOOR Model with input from clinical partners resulted in a parsimonious and clinically relevant model that was poised for integration in clinical care.

Opioid Overdose Risk Following Hospital Discharge Among Individuals Prescribed Long-Term Opioid Therapy: a Risk Interval Analysis.

BACKGROUND: Individuals prescribed long-term opioid therapy (LTOT) have increased risk of readmission and death after hospital discharge. The risk of opioid overdose during the immediate post-discharge time period is unknown. OBJECTIVE: To examine the association between time since hospital discharge and opioid overdose among individuals prescribed LTOT. DESIGN: Self-controlled risk interval analysis. PARTICIPANTS: Adults prescribed LTOT with at least one hospital discharge at a safety-net health system and a non-profit healthcare organization in Colorado. MAIN MEASURES: We identified individuals prescribed LTOT who were discharged from January 2006 through June 2019. The outcome was a composite of fatal and non-fatal opioid overdoses during a 90-day post-discharge observation period, identified using electronic health record (EHR) and vital statistics data. Risk intervals included days 0-6 after index and subsequent hospital discharges. Control intervals ranged from days 7 to 89 after index discharge and included all other time during the observation period that did not fall within a risk interval or time readmitted during a subsequent hospitalization, which was excluded. Poisson regression was used to estimate incidence rate ratios (IRR) and 95% confidence intervals (CI) for overdose events during risk in comparison to control intervals. KEY RESULTS: We identified 7695 adults (63.3% over 55 years, 59.4% female, 20.3% Hispanic) who experienced 9499 total discharges during the study period. Twenty-one overdoses occurred during their observation periods (1174 per 100,000 person-years [9 in risk, 12 in control]). Overdose risk was significantly higher during the risk interval in comparison to the control interval (IRR 6.92; 95% CI 2.92-16.43). CONCLUSION: During the first 7 days after hospital discharge, individuals prescribed LTOT appear to be at elevated risk for opioid overdose. Clarifying mechanisms of overdose risk may help inform in-hospital and post-discharge prevention strategies.

The association between buprenorphine treatment duration and mortality: a multi-site cohort study of people who discontinued treatment.

BACKGROUND AND AIMS: Buprenorphine is an effective medication for opioid use disorder that reduces mortality; however, many patients are not retained in buprenorphine treatment, and an optimal length of treatment after which patients can safely discontinue treatment has not been identified. This study measured the association between buprenorphine treatment duration and all-cause mortality among patients who discontinued treatment. Secondary objectives were to measure the association between treatment duration and drug overdose and opioid-related overdoses. DESIGN: Multi-site cohort study. SETTING: Eight US health systems. PARTICIPANTS: Patients who initiated and discontinued buprenorphine treatment between 1 January 2012 and 31 December 2018 (n = 6550). Outcomes occurring after patients discontinued buprenorphine treatment were compared between patients who initiated and discontinued treatment after 8-30, 31-90, 91-180, 181-365 and > 365 days. MEASUREMENTS: Covariate data were obtained from electronic health records (EHRs). Mortality outcomes were derived from EHRs and state vital statistics. Non-fatal opioid and drug overdoses were obtained from diagnostic codes. Four sites provided cause-of-death data to identify fatal drug and opioid-related overdoses. Adjusted frailty regression was conducted on a propensity-weighted cohort to assess associations between duration of the final treatment episode and outcomes. FINDINGS: The mortality rate after buprenorphine treatment was 1.82 per 100 person-years (n = 191 deaths). In regression analyses with > 365 days as the reference group, treatment duration was not associated with all-cause mortality and drug overdose (P > 0.05 for both). However, compared with > 365 days of treatment, 91-180 days of treatment was associated with increased opioid overdose risk (hazard ratio = 2.94, 95% confidence interval = 1.11-7.79). CONCLUSIONS: Among patients who discontinue buprenorphine treatment, there appears to be no treatment duration period associated with a reduced risk for all-cause mortality. Patients who discontinue buprenorphine treatment after 91-180 days appear to be at heightened risk for opioid overdose compared with patients who discontinue after > 365 days of treatment.

Influenza Vaccination Among Pregnant Women: Self-report Compared With Vaccination Data From Electronic Health Records, 2018-2020 Influenza Seasons.

OBJECTIVES: Having accurate influenza vaccination coverage estimates can guide public health activities. The objectives of this study were to (1) validate the accuracy of electronic health record (EHR)-based influenza vaccination data among pregnant women compared with survey self-report and (2) assess whether survey respondents differed from survey nonrespondents by demographic characteristics and EHR-based vaccination status. METHODS: This study was conducted in the Vaccine Safety Datalink, a network of 8 large medical care organizations in the United States. Using EHR data, we identified all women pregnant during the 2018-2019 or 2019-2020 influenza seasons. Surveys were conducted among samples of women who did and did not appear vaccinated for influenza according to EHR data. Separate surveys were conducted after each influenza season, and respondents reported their influenza vaccination status. Analyses accounted for the stratified design, sampling probability, and response probability. RESULTS: The survey response rate was 50.5% (630 of 1247) for 2018-2019 and 41.2% (721 of 1748) for 2019-2020. In multivariable analyses combining both survey years, non-Hispanic Black pregnant women had 3.80 (95% CI, 2.13-6.74) times the adjusted odds of survey nonresponse; odds of nonresponse were also higher for Hispanic pregnant women and women who had not received (per EHR data) influenza vaccine during current or prior influenza seasons. The sensitivity, specificity, and positive predictive value of EHR documentation of influenza vaccination compared with self-report were ≥92% for both survey years combined. The negative predictive value of EHR-based influenza vaccine status was 80.5% (95% CI, 76.7%-84.0%). CONCLUSIONS: EHR-based influenza vaccination data among pregnant women were generally concordant with self-report. New data sources and novel approaches to mitigating nonresponse bias may be needed to enhance influenza vaccination surveillance efforts.

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.

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.

Beyond Vaccination Coverage: Population-Based Measurement of Early Childhood Immunization Schedule Adherence.

The immunization schedule recommended by the U.S. Advisory Committee on Immunization Practices (ACIP) provides a structure for how 10 different vaccine series should be administered to children in the first 18 months of life. Progress toward US early childhood immunization goals has largely focused on measuring vaccination coverage at age 24 months. However, standard vaccination coverage measures do not reflect whether children received vaccine doses by recommended ages, or whether vaccines were given concomitantly, per the schedule. In this paper, we describe innovations in population-level measurement of immunization schedule adherence through quantifying vaccination timeliness and undervaccination patterns. Measuring vaccination timeliness involves comparing when children received vaccine doses relative to ACIP age recommendations. To assess undervaccination patterns, children's vaccination histories are analyzed to determine whether they were vaccinated consistent with the ACIP schedule. Some patterns, such as spreading out vaccines across visits, are indicative of parental hesitancy. Other patterns, such as starting all recommended series but missing doses, are largely indicative of other immunization services delivery challenges. Since 2003, at least 12 studies have used National Immunization Survey-Child, immunization information system, or integrated health plan data to measure vaccination timeliness or undervaccination patterns at national or state levels. Moving forward, these novel measures can be leveraged for population-based surveillance of vaccine confidence, and for distinguishing undervaccination due to parental vaccine hesitancy from undervaccination due to other causes. Broader adoption of these measures can facilitate identification of targeted strategies for improving timely and routine early childhood vaccination uptake across the United States.