Multiple Sclerosis, Rituximab, Hypogammaglobulinemia, and Risk of Infections.

BACKGROUND AND OBJECTIVES: B-cell-depleting therapies increase the risk of infections and hypogammaglobulinemia. These relationships are poorly understood. The objectives of these analyses were to estimate how much of this rituximab-associated infection risk is mediated by hypogammaglobulinemia and to identify other modifiable risk factors in persons with multiple sclerosis (pwMS). METHODS: We conducted a retrospective cohort study of rituximab-treated pwMS from January 1, 2008, to December 31, 2020, in Kaiser Permanente Southern California. Cumulative rituximab dose was defined as ≤2, >2 and ≤4, or >4 g. Serious infections were defined as infections requiring or prolonging hospitalizations, and recurrent outpatient infections as seeking care for ≥3 within 12 months. Exposures, outcomes, and covariates were collected from the electronic health record. Adjusted hazard ratios (aHRs) were estimated using Andersen-Gill hazards models, and generalized estimating equations were used to examine correlates of IgG values. Cross-sectional causal mediation analyses of rituximab and hypogammaglobulinemia were conducted. RESULTS: We identified 2,482 pwMS who were treated with rituximab for a median of 2.4 years (interquartile range = 1.3-3.9). The average age at rituximab initiation was 43.0 years, 71.9% were female, 49.7% were White, non-Hispanic patients, and 29.6% had advanced disability (requiring walker or worse). Seven hundred patients (28.2%) developed recurrent outpatient infections, 155 (6.2%) developed serious infections, and only 248 (10.0%) had immunoglobulin G (IgG) < 700 mg/dL. Higher cumulative rituximab dose (>4 g) was correlated with lower IgG levels (Beta = -58.8, p < 0.0001, ref ≤2 g) and, in models mutually adjusted for hypogammaglobulinemia, both were independently associated with an increased risk of serious (>4 g, aHR = 1.56, 95% CI 1.09-2.24; IgG < 500, aHR = 2.98, 95% CI 1.56-5.72) and outpatient infections (>4 g, aHR = 1.73, 95% CI 1.44-2.06; IgG < 500 aHR = 2.06, 95% CI 1.52-2.80; ref = IgG ≥ 700). Hypogammaglobulinemia explained at most 17.9% (95% CI -47.2-119%) of serious infection risk associated with higher cumulative rituximab exposure but was not significant for outpatient infections. Other independent modifiable risk factors were advanced physical disability for serious (aHR = 5.51, 95% CI 3.71-8.18) and outpatient infections (aHR = 1.24, 95% CI 1.06-1.44) and COPD (aHR = 1.68, 95% CI 1.34-2.11) and obesity (aHR = 1.25, 95% CI 1.09-1.45) for outpatient infections. DISCUSSION: Higher cumulative rituximab doses increase the risk of infections even in this population where 90% of patients maintained normal IgG levels. Clinicians should strive to use minimally effective doses of rituximab and other B-cell-depleting therapies and consider important comorbidities to minimize risks of infections.

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.

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.

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.

Factors associated with uptake of bivalent mRNA COVID-19 vaccines in a large US health care system.

BACKGROUND: Bivalent mRNA COVID-19 vaccines were developed to provide protection against the original SARS-CoV-2 strain and Omicron BA.4/BA.5 variants, but uptake in the United States has been low. Sociodemographic disparities in COVID-19 vaccine uptake have been documented, but it is unclear if similar disparities persist among individuals who previously completed a primary series of monovalent COVID-19 vaccine. METHODS: We conducted a retrospective cohort study at Kaiser Permanente Southern California (KPSC) including youth aged 5-17 years and adults aged ≥18 years who were KPSC members and had completed a primary series of monovalent COVID-19 vaccine. Individuals were followed from index date (date of eligibility for bivalent vaccine) to 03/31/2023 to ascertain receipt of any dose of bivalent mRNA COVID-19 vaccine or until disenrollment from KPSC or death. Multivariable robust Poisson regression was conducted to assess the adjusted relative risk and 95 % confidence intervals of factors associated with receipt of bivalent vaccine. RESULTS: The final cohorts included 305,339 youth and 2,534,619 adults, of whom 19.5 % and 30.7 %, respectively, had received bivalent COVID-19 vaccine. Factors associated with being more likely to receive bivalent COVID-19 vaccine included older age, Asian race, more prior year outpatient and virtual visits, Charlson score ≥1, and immunocompromised status. Factors associated with being less likely to receive a bivalent COVID-19 vaccine included age 12-17 vs 5-11 years, Hispanic and non-Hispanic Black race/ethnicity, ≥1 prior year inpatient or emergency department visits, prior history of SARS-CoV-2 infection (adults only), Medicaid insurance, and higher neighborhood deprivation index. CONCLUSION: Even among youth and adults who had previously received a primary series of monovalent COVID-19 vaccine, sociodemographic and clinical disparities were observed in receipt of bivalent COVID-19 vaccine. These findings are critical to inform equitable strategies for the implementation of the updated monovalent COVID-19 vaccine targeting the Omicron XBB strain.

Risk Factors for Not Completing a 2-Dose Primary Series of Messenger RNA COVID-19 Vaccination in a Large Health Care System in Southern California: Retrospective Cohort Study.

BACKGROUND: COVID-19 vaccination is crucial in combating the COVID-19 pandemic. Messenger RNA COVID-19 vaccines were initially authorized as a 2-dose primary series and have been widely used in the United States; completing the 2-dose primary series offers protection against infection, severe illness, and death. Understanding the risk factors for not completing the 2-dose primary series is critical to evaluate COVID-19 vaccination programs and promote completion of the 2-dose primary series. OBJECTIVE: This study examined potential risk factors for not completing a 2-dose primary series of mRNA COVID-19 vaccination. METHODS: We conducted a retrospective cohort study among members aged ≥18 years from a large integrated health care system, Kaiser Permanente Southern California, from December 14, 2020, to June 30, 2022. Noncompletion of the 2-dose primary series was defined as not completing the second dose within 6 months after receipt of the first dose. Crude noncompletion rates were estimated overall and by demographic characteristics, health care use patterns, comorbidity, and community-level socioeconomic factors. A Poisson regression model was fit to examine associations of individual-level and community-level risk factors with noncompletion of the 2-dose primary series. RESULTS: Among 2.5 million recipients of ≥1 dose of mRNA COVID-19 vaccines, 3.3% (n=81,202) did not complete the second dose within 6 months. Members aged 25-44 years, 65-74 years, and ≥75 years were less likely to not complete the 2-dose primary series than those aged 18-24 years, while members aged 45-64 years were more likely to not complete the 2-dose primary series (adjusted risk ratio [aRR] 1.13, 95% CI 1.10-1.15). Male sex was associated with a higher risk of noncompletion (aRR 1.17, 95% CI 1.15-1.19). Hispanic and non-Hispanic Black race/ethnicity were associated with a lower risk of noncompletion (range aRR 0.78-0.91). Having Medicaid and prior influenza vaccination were associated with a higher risk of noncompletion. Having SARS-CoV-2 infection, experiencing an adverse event, or having an inpatient and emergency department visit during the minimum recommended dose intervals were associated with a higher risk of not completing the 2-dose primary series (aRR 1.98, 95% CI 1.85-2.12; 1.99, 95% CI 1.43-2.76; and 1.85, 95% CI 1.77-1.93, respectively). Those who received the first dose after June 30, 2021, were more likely to not complete the 2-dose primary series within 6 months of receipt of the first dose. CONCLUSIONS: Despite limitations such as being a single-site study and the inability to consider social factors such as employment and vaccine attitudes, our study identified several risk factors for not completing a 2-dose primary series of mRNA vaccination, including being male; having Medicaid coverage; and experiencing SARS-CoV-2 infection, adverse events, or inpatient and emergency department visits during the minimum recommended dose intervals. These findings can inform future efforts in developing effective strategies to enhance vaccination coverage and improve the completion rate of necessary doses.

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.

Simultaneous administration of mRNA COVID-19 bivalent booster and influenza vaccines.

The U.S. Food and Drug Administration authorized use of mRNA COVID-19 bivalent booster vaccines on August 31, 2022. Currently, CDC's clinical guidance states that COVID-19 and other vaccines may be administered simultaneously. At time of authorization and recommendations, limited data existed describing simultaneous administration of COVID-19 bivalent booster and other vaccines. We describe simultaneous influenza and mRNA COVID-19 bivalent booster vaccine administration between August 31-December 31, 2022, among persons aged ≥6 months in the Vaccine Safety Datalink (VSD) by COVID-19 bivalent booster vaccine type, influenza vaccine type, age group, sex, and race and ethnicity. Of 2,301,876 persons who received a COVID-19 bivalent booster vaccine, 737,992 (32.1%) received simultaneous influenza vaccine, majority were female (53.1%), aged ≥18 years (91.4%), and non-Hispanic White (55.7%). These findings can inform future VSD studies on simultaneous influenza and COVID-19 bivalent booster vaccine safety and coverage, which may have implications for immunization service delivery.

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."

Association of Direct Oral Anticoagulation Management Strategies With Clinical Outcomes for Adults With Atrial Fibrillation.

Importance: Anticoagulation management services (AMSs; ie, warfarin clinics) have evolved to include patients treated with direct oral anticoagulants (DOACs), but it is unknown whether DOAC therapy management services improve outcomes for patients with atrial fibrillation (AF). Objective: To compare outcomes associated with 3 DOAC care models for preventing adverse anticoagulation-related outcomes among patients with AF. Design, Setting, and Participants: This retrospective cohort study included 44 746 adult patients with a diagnosis of AF who initiated oral anticoagulation (DOAC or warfarin) between August 1, 2016, and December 31, 2019, in 3 Kaiser Permanente (KP) regions. Statistical analysis was conducted from August 2021 through May 2023. Exposures: Each KP region used an AMS to manage warfarin but used distinct approaches to DOAC care: (1) usual care (UC) by the prescribing clinician, (2) UC plus an automated population management tool (PMT), or (3) pharmacist-managed AMS care. Propensity scores and inverse probability of treatment weights (IPTWs) were estimated. Direct oral anticoagulant care models were first indirectly compared using warfarin as a common comparator within each region and then directly compared across regions. Main Outcomes and Measures: Patients were followed up until the first occurrence of an outcome (composite of thromboembolic stroke, intracranial hemorrhage, other major bleeding, or death), discontinuation of KP membership, or December 31, 2020. Results: Overall, 44 746 patients were included: 6182 in the UC care model (3297 DOAC; 2885 warfarin), 33 625 in the UC plus PMT care model (21 891 DOAC; 11 734 warfarin), and 4939 in the AMS care model (2089 DOAC; 2850 warfarin). Baseline characteristics (mean [SD] age, 73.1 [10.6] years, 56.1% male, 67.2% non-Hispanic White, median CHA2DS2-VASc [congestive heart failure, hypertension, age ≥75 years, diabetes, stroke, vascular disease, age 65-74 years, female sex] score of 3 [IQR, 2-5]) were well balanced after IPTW. Over a median follow-up of 2 years, patients who received the UC plus PMT or AMS care model did not have significantly better outcomes than those who received UC. The incidence rate of the composite outcome was 5.4% per year for DOAC and 9.1% per year for warfarin for those in the UC group, 6.1% per year for DOAC and 10.5% per year for those in the UC plus PMT group, and 5.1% per year for DOAC and 8.0% per year for those in the AMS group. The IPTW-adjusted hazard ratios (HRs) for the composite outcome comparing DOAC vs warfarin were 0.91 (95% CI, 0.79-1.05) in the UC group, 0.85 (95% CI, 0.79-0.90) in the UC plus PMT group, and 0.84 (95% CI, 0.72-0.99) in the AMS group (P = .62 for heterogeneity across care models). When directly comparing patients receiving DOAC, the IPTW-adjusted HR was 1.06 (95% CI, 0.85-1.34) for the UC plus PMT group vs the UC group and 0.85 (95% CI, 0.71-1.02) for the AMS group vs the UC group. Conclusions and Relevance: This cohort study did not find appreciably better outcomes for patients receiving DOAC who were managed by either a UC plus PMT or AMS care model compared with UC.

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.

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.

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.

Anakinra or high-dose corticosteroids in COVID-19 pneumonia patients who deteriorate on low-dose dexamethasone: an observational study of comparative effectiveness.

OBJECTIVES: To assess whether escalating to high-dose corticosteroids or anakinra compared with continuing low-dose corticosteroids reduced mortality in patients with severe COVID-19 whose respiratory function deteriorated while receiving dexamethasone 6 mg daily. METHODS: We conducted a retrospective cohort study between March 1 to December 31, 2020, of hospitalized patients with confirmed COVID-19 pneumonia. In-hospital death was analyzed using logistic regression with inverse probability of treatment weighting of receiving anakinra, high-dose corticosteroid (dexamethasone >10 mg daily), or remaining on low-dose corticosteroids on the day of first respiratory deterioration. RESULTS: We analyzed 6671 patients whose respiratory status deteriorated while receiving dexamethasone 6 mg daily for COVID-19 pneumonia, of whom 6265 stayed on low-dose corticosteroids, 232 were escalated to high-dose corticosteroids, and 174 to anakinra in addition to corticosteroids. The propensity score-adjusted odds of death were higher in the anakinra (odds ratio [OR] 1.76; 95% CI 1.13-2.72) and high-dose corticosteroid groups (OR 1.53; 95% CI 1.14-2.07) compared with those who continued low-dose corticosteroids on the day of respiratory deterioration. The odds of hospital-acquired infections were also higher in the anakinra (OR 2.00; 95% CI 1.28-3.11) and high-dose corticosteroid groups (OR 1.43; 95% CI 1.00-2.04) compared with low-dose corticosteroid group. CONCLUSION: Our findings do not support escalating patients with COVID-19 pneumonia who deteriorate on low-dose corticosteroids to high-dose corticosteroids or anakinra.

The intensity of anticoagulant dosing in hospitalized patients with COVID-19: An observational, comparative effectiveness study.

BACKGROUND: The question of anticoagulant dosing in hospitalized patients with coronavirus disease-2019 (COVID-19) is unresolved, with randomized trials showing mixed results and heterogeneity of treatment effects for in-hospital death. OBJECTIVE: To examine the association between the intensity of anticoagulation and clinical outcomes in hospitalized patients with COVID-19. DESIGN, SETTING AND PARTICIPANTS: Retrospective cohort study of patients with COVID-19 and respiratory impairment who were hospitalized between 3/1/2020-12/31/2020 in two Kaiser Permanente regions. EXPOSURE AND MAIN OUTCOME: We fit propensity score models using categorical regression to estimate the probability of receiving standard prophylactic, intermediate, or full-dose anticoagulation beginning on the day of admission or on the day of first respiratory deterioration. Exposure was defined by the highest dose on the day of admission or within 24 hours after deterioration. The primary outcome was in-hospital death. RESULTS: We included 17,130 patients in the day of admission analysis and 4,924 patients who experienced respiratory deterioration. There were no differences in propensity score-adjusted odds of in-hospital death for patients who received either intermediate (odds ratio [OR]: 1.00, 95% confidence intervals [CI] 0.89-1.12) or full anticoagulation (OR: 1.00, 95% CI: 0.85-1.17) compared with standard prophylaxis beginning on the day of admission. Similarly, there were no differences in in-hospital death for either intermediate (OR: 1.22, 95% CI: 0.82-1.82) or full anticoagulation (OR: 1.50, 95% CI: 0.90-2.51) compared with standard prophylaxis on the day of deterioration. CONCLUSION: Results of this real-world, comparative effectiveness study showed no differences in in-hospital death among newly admitted or deteriorating patients with COVID-19 who received intermediate-dose or full anticoagulation compared with standard prophylaxis.

High-dose corticosteroids in patients hospitalized for COVID-19 pneumonia: an observational study of comparative effectiveness.

OBJECTIVES: To assess whether high- compared with low-dose corticosteroids started upon hospitalization reduce mortality in patients with severe COVID-19 pneumonia or in subgroups stratified by severity of respiratory impairment on admission. METHODS: We conducted a retrospective cohort study of patients with confirmed SARS-CoV-2 infection who required oxygen supplementation upon hospitalization between March 1 and December 31, 2020. In-hospital death was analyzed using logistic regression with inverse probability of treatment weighting of receiving low- or high-dose corticosteroid (dexamethasone 6-10 mg daily or >10-20 mg daily or other corticosteroid equivalents). RESULTS: We analyzed 13,366 patients who received low-dose and 948 who received high-dose corticosteroids, of whom 31.3% and 40.4% had severe respiratory impairment (>15 l/min of oxygen or mechanical ventilation) upon admission, respectively. There were no differences in the propensity score-adjusted odds of death (odds ratio 1.17, 95% CI 0.72-1.90) or infections (odds ratio 0.70, 95% CI 0.44-1.11) for patients who received high-dose compared with low-dose corticosteroids, beginning on the day of admission. No significant differences in subgroups stratified by severity of respiratory impairment were found. CONCLUSION: Initiating high-dose compared with low-dose corticosteroids among newly hospitalized patients with COVID-19 pneumonia did not improve survival. However, benefit of high-dose corticosteroids in specific subgroups cannot be excluded.

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.