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Abstract Background The beta-binomial model is one of the methods that can be used to validly combine event rates from overdispersed binomial data. Our objective is to provide a full description of this method and to update and broaden its applications in clinical and public health research. Methods We describe the statistical theories behind the beta-binomial model and the associated estimation methods. We supply information about statistical software that can provide beta-binomial estimations. Using a published example, we illustrate the application of the beta-binomial model when pooling overdispersed binomial data. Results In an example regarding the safety of oral antifungal treatments, we had 41 treatment arms with event rates varying from 0% to 13.89%. Using the beta-binomial model, we obtained a summary event rate of 3.44% with a standard error of 0.59%. The parameters of the beta-binomial model took the values of 1.24 for alpha and 34.73 for beta. Conclusion The beta-binomial model can provide a robust estimate for the summary event rate by pooling overdispersed binomial data from different studies. The explanation of the method and the demonstration of its applications should help researchers incorporate the beta-binomial method as they aggregate probabilities of events from heterogeneous studies.

In this meta-analysis, the authors evaluated the hepatotoxicity of antifungal agents in the treatment of invasive fungal infections, and examined whether hepatotoxicity was the cause of treatment discontinuation and study withdrawal. The risk of hepatotoxicity was higher in patients with aspergillosis compared with those with candidiasis. Voriconazole, itraconazole, and amphotericin B formulations were the antifungal agents associated with the highest risks of hepatotoxicity. [ABSTRACT FROM AUTHOR]

Background: The beta-binomial model is one of the methods that can be used to validly combine event rates from overdispersed binomial data. Our objective is to provide a full description of this method and to update and broaden its applications in clinical and public health research.Methods: We describe the statistical theories behind the beta-binomial model and the associated estimation methods. We supply information about statistical software that can provide beta-binomial estimations. Using a published example, we illustrate the application of the beta-binomial model when pooling overdispersed binomial data.Results: In an example regarding the safety of oral antifungal treatments, we had 41 treatment arms with event rates varying from 0% to 13.89%. Using the beta-binomial model, we obtained a summary event rate of 3.44% with a standard error of 0.59%. The parameters of the beta-binomial model took the values of 1.24 for alpha and 34.73 for beta.Conclusion: The beta-binomial model can provide a robust estimate for the summary event rate by pooling overdispersed binomial data from different studies. The explanation of the method and the demonstration of its applications should help researchers incorporate the beta-binomial method as they aggregate probabilities of events from heterogeneous studies. [ABSTRACT FROM AUTHOR]

Determines how often patients with cancer received chemotherapy in the months before they die. Study of Medicare patients from Massachusetts and California; Percentage of patients receiving chemotherapy in the last six, three and last months of life; Less use of chemotherapy as patients grow older.

Initial evaluation of an advanced access clinic developed at a VA medical center (VAMC) found decreased Mental Health wait times and improved quality of care for veterans with depression. Subsequently, modified advanced access models were implemented at affiliated community-based outreach clinics (CBOCs). By comparing each site, we sought to determine whether less resource-intensive models could improve care to the same degree. We assessed contributions of the model's components to the improvement of care (i.e., wait times and depression treatment adequacy). The modified advanced access models led to significant improvements, although no such improvements were seen at 2 control sites. Six features related to rapid access, short-term treatment, and barrier-free access to mental health services accounted for most of the observed improvements. CBOCs can implement limited advanced mental health access models and derive similar improvements to those seen in more extensive models at the VAMCs to which they are affiliated. [ABSTRACT FROM AUTHOR]

Background: Influenza may contribute to coronary/cerebrovascular events and exacerbate underlying conditions., Methods: We used self-controlled case series (SCCS) design to analyze data from US Veterans ≥18 years with coronary/cerebrovascular or exacerbation event +/-1 year of lab-confirmed influenza (LCI) during 2010-2018. We estimated the incidence ratio (IR) (95% CI) of the event for risk interval (Days 1-7 post-LCI) versus control interval (all other times +/-1 year of LCI) with fixed-effects conditional Poisson regression. We included biomarker data for mediation analysis., Results: We identified 3439 episodes with coronary/cerebrovascular-related hospitalizations. IRs (95% CI) for LCI risk versus control interval were STEMI 0.6 (0.1, 4.4), NSTEMI 7.3 (5.8, 9.2), ischemic stroke 4.0 (3.0, 5.4), hemorrhagic stroke 6.2 (3.4, 11.5), and coronary spasm 1.3 (0.5, 3.0). IR significantly increased for NSTEMI and ischemic stroke among those ≥ 65 years. IR for NSTEMI and ischemic stroke dropped 26% and 10%, respectively, when white blood cell (WBC) and platelet count were considered. LCI was significantly associated with exacerbation of preexisting asthma, chronic obstructive pulmonary disease, and congestive heart failure., Conclusions: We found significant association between LCI and hospitalization for NSTEMI, ischemic stroke, and hemorrhagic stroke, the latter possibly due to unaccounted time-varying confounding in SCCS design., (© 2024 The Author(s). Influenza and Other Respiratory Viruses published by John Wiley & Sons Ltd. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.)

Design: Retrospective cohort study., Objective: We sought to examine whether disruptions in follow-up intervals contributed to hypertension control., Background: Disruptions in health care were widespread during the coronavirus disease 2019 pandemic., Patients and Methods: We identified a cohort of individuals with hypertension in both prepandemic (March 2019-February 2020) and pandemic periods (March 2020-February 2022) in the Veterans Health Administration. First, we calculated follow-up intervals between the last prepandemic and first pandemic blood pressure measurement during a primary care clinic visit, and between measurements in the prepandemic period. Next, we estimated the association between the maintenance of (or achieving) hypertension control and the period using generalized estimating equations. We assessed associations between follow-up interval and control separately for periods. Finally, we evaluated the interaction between period and follow-up length., Results: A total of 1,648,424 individuals met the study inclusion criteria. Among individuals with controlled hypertension, the likelihood of maintaining control was lower during the pandemic versus the prepandemic (relative risk: 0.93; 95% CI: 0.93, 0.93). Longer follow-up intervals were associated with a decreasing likelihood of maintaining controlled hypertension in both periods. Accounting for follow-up intervals, the likelihood of maintaining control was 2% lower during the pandemic versus the prepandemic. For uncontrolled hypertension, the likelihood of gaining control was modestly higher during the pandemic versus the prepandemic (relative risk: 1.01; 95% CI: 1.01, 1.01). The likelihood of gaining control decreased with follow-up length during the prepandemic but not pandemic., Conclusions: During the pandemic, longer follow-up between measurements contributed to the lower likelihood of maintaining control. Those with uncontrolled hypertension were modestly more likely to gain control in the pandemic., Competing Interests: C.K. has been an investigator on projects with research grants from Pfizer and Sanofi Pasteur for work unrelated to this manuscript. A.J.P. is or has been the principal investigator on research grants from Bayer, Boehringer-Ingelheim, Lundbeck, Reata, and Vascular Dynamics to Yale University for work unrelated to this manuscript; has received honoraria for data safety monitoring activities from Ablative Solutions and KBP Biosciences; and has received consulting fees from BD, CinCor, and Diamedica, all for work unrelated to this manuscript. D.M.W. has received consulting fees for work unrelated to this manuscript from Pfizer, Merck, GSK, Affinivax, and Matrivax, and is the Principal Investigator on research grants from Pfizer and Merck to Yale University for work unrelated to this manuscript. The remaining authors declare no conflict of interest.

Background: The real-world clinical effectiveness of sotrovimab in preventing coronavirus disease 2019 (COVID-19)-related hospitalization or mortality among high-risk patients diagnosed with COVID-19, particularly after the emergence of the Omicron variant, needs further research., Method: Using data from the US Department of Veterans Affairs (VA) health care system, we adopted a target trial emulation design in our study. Veterans aged ≥18 years, diagnosed with COVID-19 between December 1, 2021, and April 4, 2022, were included. Patients treated with sotrovimab (n = 2816) as part of routine clinical care were compared with all eligible but untreated patients (n = 11,250). Cox proportional hazards modeling estimated the hazard ratios (HRs) and 95% CIs for the association between receipt of sotrovimab and outcomes., Results: Most (90%) sotrovimab recipients were ≥50 years old, and 64% had ≥2 mRNA vaccine doses or ≥1 dose of Ad26.COV2. During the period that BA.1 was dominant, compared with patients not treated, sotrovimab-treated patients had a 70% lower risk of hospitalization or mortality within 30 days (HR, 0.30; 95% CI, 0.23-0.40). During BA.2 dominance, sotrovimab-treated patients had a 71% (HR, 0.29; 95% CI, 0.08-0.98) lower risk of 30-day COVID-19-related hospitalization, emergency room visits, or urgent care visits (defined as severe COVID-19) compared with patients not treated., Conclusions: Using national real-world data from high-risk and predominantly vaccinated veterans, administration of sotrovimab, compared with contemporary standard treatment regimens, was associated with reduced risk of 30-day COVID-19-related hospitalization or all-cause mortality during the Omicron BA.1 period., Competing Interests: Potential conflicts of interest. V.C.M. reports research grants from the CDC, Gilead Sciences, NIH, Veterans Affairs, and ViiV Healthcare; reports honoraria from Eli Lilly and Company; has served as an advisory board member for Eli Lilly and Company and Novartis; and has participated as a study section chair for the NIH. Y.Y.X., G.Z., and C.K. report receiving grants from the US Food and Drug Administration through an interagency agreement with the Veterans Health Administration and from the US Department of Veterans Affairs Office of Rural Health. Y.Y.X., G.Z., and J.S. also report receiving funding from Vir Biotechnology to the US Department of Veterans Affairs for other research projects outside the submitted work. Y.Y.X. and V.C.M. are supported by VA/BLRD VA SEQCURE (821-SD-ID-42403). V.C.M. received support from the Emory Center for AIDS Research (P30 AI050409). A.A.G. received COVID-19 research project funding from the National Institutes of Health, Department of Defense, Centers for Disease Control and Prevention, AbbVie, and Faron Pharmaceuticals, outside the submitted work. M.M.C., C.R., and S.S. are employees of and shareholders of Vir Biotechnology. M.D. is employee of and shareholder of GSK. All other authors report no potential conflicts., (Published by Oxford University Press on behalf of Infectious Diseases Society of America 2023.)

Background: The US Department of Veterans Affairs (VA) enterprise approach to research (VA Research) has built a data-sharing framework available to all research teams within VA. Combined with robust analytic systems and tools available for investigators, VA Research has produced actionable results during the COVID-19 pandemic. Big data science techniques applied to VA's health care data demonstrate that medical research can be performed quickly and judiciously during nationwide health care emergencies., Observations: We envision a common framework of data collection, management, and surveillance implemented in partnership with other health care agencies that would capture even broader, actionable, and timely observational data on populations, while providing opportunities for enhanced collaborative research across agencies. This model should be continued and expanded through the current COVID-19 and future pandemics., Conclusions: Extending the achievements of VA Research in the COVID-19 pandemic to date, we advocate national goals of open science by working toward a synergistic national framework of anonymized, synchronized, shared health data that would provide researchers with potent tools to combat future public health crises., Competing Interests: Author disclosures: Vincent C. Marconi received investigator-initiated research grants (to Emory University) and consultation fees from Eli Lilly, Bayer, Gilead Sciences and ViiV. The grants and fees were unrelated to the work discussed here., (Copyright © 2023 Frontline Medical Communications Inc., Parsippany, NJ, USA.)

Little is known regarding the effectiveness of tixagevimab/cilgavimab in preventing SARS-CoV-2 infection in vaccinated immunocompromised patients, particularly after the emergence of the Omicron variant. In this retrospective cohort study with exact matching and propensity score adjustment within the U.S. Department of Veterans Affairs (VA) healthcare system, we selected immunocompromised veterans age ≥18 years as of 1 January 2022, receiving VA healthcare. We compared a cohort of 1,878 patients treated with at least one dose of intramuscular tixagevimab/cilgavimab to 7,014 matched controls selected from patients who met study criteria but were not treated. Patients were followed through 15 June 2022, or until death, whichever occurred earlier. The primary outcome was a composite of SARS-CoV-2 infection, COVID-19-related hospitalization, and all-cause mortality. We used Cox proportional hazards modeling to estimate the hazard ratios (HRs) and 95% CI for the association between receipt of tixagevimab/cilgavimab and outcomes. Most (73%) tixagevimab/cilgavimab recipients were ≥65 years old, and 80% had ≥3 mRNA vaccine doses or two doses of Ad26.COV2. Compared to matched controls, recipients had a lower incidence of the composite COVID-19 outcome (49/1,878 [2.6%] versus 312/7,014 [4.4%]; HR 0.35; 95% CI, 0.24-0.52), and individually SARS-CoV-2 infection (HR 0.44; 95% CI, 0.22-0.88), COVID-19 hospitalization (HR 0.24; 95% CI, 0.10-0.59), and all-cause mortality (HR 0.32; 95% CI, 0.19-0.55). In conclusion, tixagevimab/cilgavimab was associated with lower rates of SARS-CoV-2 infection and severe COVID-19 during the Omicron BA.1, BA.2, and BA.2.12.1 surge. IMPORTANCE SARS-CoV-2 remains an ongoing global health crisis that justifies continued efforts to validate and expand, when possible, knowledge on the efficacy of available vaccines and treatments. Clinical trials have been limited due to fast tracking of medications for mitigation of the COVID-19 pandemic for the general population. We present a real-world analysis, using electronic health record data, of the effectiveness of tixagevimab/cilgavimab for the prevention of COVID-19 infection in the unique population of U.S. veterans. Unlike those in the PROVENT clinical trial from which the emergency use authorization for tixagevimab/cilgavimab as a preventative treatment arose, the veterans population is highly immunocompromised and nearly 96% totally vaccinated. These demographics allowed us to analyze the effectiveness of tixagevimab/cilgavimab in preventing COVID-19 under different conditions in a more fragile population than that of the initial clinical trial., Competing Interests: V.C.M. has received investigator-initiated research grants (to the institution) and consultation fees (both unrelated to the current work) from Eli Lilly, Bayer, Gilead Sciences and ViiV. Y.Y.-X., G.Z., C.K., and J.S. reported receiving grants from the U.S. Food and Drug Administration through an interagency agreement with the Veterans Health Administration and from the U.S. Department of Veterans Affairs Office of Rural Health. Y.Y.-X., G.Z., C.K., and J.S. also reported receiving funding from Pfizer to the U.S. Department of Veterans Affairs for other research projects outside the submitted work. R.A.B. is supported by VA/BLRD VA SHIELD (821-SD-null-41942); Y.Y.-X., V.C.M., and R.A.B. are supported by VA/BLRD VA SEQCURE (821-SD-ID-42403). A.A.G. received COVID-19 research project funding from the National Institutes of Health, Department of Defense, Centers for Disease Control and Prevention, AbbVie, and Faron Pharmaceuticals, outside the submitted work.

Objectives: To determine the association between covid-19 vaccination types and doses with adverse outcomes of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection during the periods of delta (B.1.617.2) and omicron (B.1.1.529) variant predominance., Design: Retrospective cohort., Setting: US Veterans Affairs healthcare system., Participants: Adults (≥18 years) who are affiliated to Veterans Affairs with a first documented SARS-CoV-2 infection during the periods of delta (1 July-30 November 2021) or omicron (1 January-30 June 2022) variant predominance. The combined cohorts had a mean age of 59.4 (standard deviation 16.3) and 87% were male., Interventions: Covid-19 vaccination with mRNA vaccines (BNT162b2 (Pfizer-BioNTech) and mRNA-1273 (Moderna)) and adenovirus vector vaccine (Ad26.COV2.S (Janssen/Johnson & Johnson))., Main Outcome Measures: Stay in hospital, intensive care unit admission, use of ventilation, and mortality measured 30 days after a positive test result for SARS-CoV-2., Results: In the delta period, 95 336 patients had infections with 47.6% having at least one vaccine dose, compared with 184 653 patients in the omicron period, with 72.6% vaccinated. After adjustment for patient demographic and clinical characteristics, in the delta period, two doses of the mRNA vaccines were associated with lower odds of hospital admission (adjusted odds ratio 0.41 (95% confidence interval 0.39 to 0.43)), intensive care unit admission (0.33 (0.31 to 0.36)), ventilation (0.27 (0.24 to 0.30)), and death (0.21 (0.19 to 0.23)), compared with no vaccination. In the omicron period, receipt of two mRNA doses were associated with lower odds of hospital admission (0.60 (0.57 to 0.63)), intensive care unit admission (0.57 (0.53 to 0.62)), ventilation (0.59 (0.51 to 0.67)), and death (0.43 (0.39 to 0.48)). Additionally, a third mRNA dose was associated with lower odds of all outcomes compared with two doses: hospital admission (0.65 (0.63 to 0.69)), intensive care unit admission (0.65 (0.59 to 0.70)), ventilation (0.70 (0.61 to 0.80)), and death (0.51 (0.46 to 0.57)). The Ad26.COV2.S vaccination was associated with better outcomes relative to no vaccination, but higher odds of hospital stay and intensive care unit admission than with two mRNA doses. BNT162b2 was generally associated with worse outcomes than mRNA-1273 (adjusted odds ratios between 0.97 and 1.42)., Conclusions: In veterans with recent healthcare use and high occurrence of multimorbidity, vaccination was robustly associated with lower odds of 30 day morbidity and mortality compared with no vaccination among patients infected with covid-19. The vaccination type and number of doses had a significant association with outcomes., Competing Interests: Competing interests: All authors have completed the ICMJE uniform disclosure form at www.icmje.org/disclosure-of-interest/ and declare support from the US Department of Veterans Affairs for the submitted work but no financial relationship with any organisation that might have an interest in the submitted work in the previous three years and no other relationships or activities that could appear to have influenced the submitted work., (© Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Objectives: We explored factors related to testing positive for severe acute respiratory coronavirus 2 (SARS-CoV-2) to identify populations most at risk for this airborne pathogen., Methods: Data were abstracted from the medical record database of the U.S. Department of Veterans Affairs and from public sources. Veterans testing positive were matched in a 1:4 ratio to those at a similar timepoint and local disease burden who remained negative between March 1, 2020, and December 31, 2020. Multivariable logistic regression was used to calculate odds ratios for the association of each potential risk factor with a positive test result., Results: A total of 24,843 veterans who tested positive for SARS-CoV-2 were matched with 99,324 controls. Cases and controls were similar in age, sex, ethnicity, and rurality, but cases were more likely to be Black, reside in low-income counties, and suffer from dementia. Multivariable analysis demonstrated highest risk for Black veterans, those with dementia or diabetes, and those living in nursing homes or high-poverty areas. Veterans living in counties likely to be more adherent to public health guidelines were at the lowest risk., Conclusions: Our results are similar to those from studies of other populations and add to that work by accounting for several important proxies for risk. In particular, this work has implications for the value of infection control measures at the population level in helping to stem widespread outbreaks of this type., (Published by Oxford University Press on behalf of the Association of Military Surgeons of the United States 2021. This work is written by (a) US Government employee(s) and is in the public domain in the US.)

Background: Depressive disorders are common. Many patients with major depression do not achieve remission with available treatments. Buprenorphine has been raised as a potential treatment for depression as well as suicidal behavior but may pose certain risks., Methods: A meta-analysis comparing the efficacy, tolerability, and safety of buprenorphine (or combinations such as buprenorphine/samidorphan) versus control in improving symptoms in patients with depression. Medline, Cochrane Database, PsycINFO, Excerpta Medica Database and The Cumulative Index to Nursing and Allied Health Literature were searched from inception through January 2, 2022. Depressive symptoms were pooled using Hedge's g with 95% Confidence Intervals (CI). Tolerability, safety, suicide outcomes were summarized qualitatively., Results: 11 studies (N = 1699) met inclusion criteria. Buprenorphine had a small effect on depressive symptoms (Hedges' g 0.17, 95%CI: 0.05-0.29). Results were driven by six trials of buprenorphine/samidorphan (N = 1,343, Hedges's g 0.17, 95%CI: 0.04-0.29). One study reported significant improvement in suicidal thoughts (Least Squares Mean Change: -7.1, 95%CI: -12.0 - 2.3). Most studies found buprenorphine was well-tolerated with no evidence of abuse behavior or dependency., Conclusions: Buprenorphine may have a small benefit for depressive symptoms. Future research should clarify the dose response relationship between buprenorphine and depression., Competing Interests: Declaration of competing interest Natalie Riblet has no conflicts of interest to report. Yinong Young-Xu has no conflicts of interest to report. Brian Shiner has no conflicts of interest to report. Paula P. Schnurr has no conflicts of interest to report. Bradley V. Watts has no conflicts of interest to report., (Published by Elsevier Ltd.)

Importance: During the first year of the COVID-19 pandemic, there was a substantial increase in the rate of death in the United States. It is unclear whether those who had access to comprehensive medical care through the Department of Veterans Affairs (VA) health care system had different death rates compared with the overall US population., Objective: To quantify and compare the increase in death rates during the first year of the COVID-19 pandemic between individuals who received comprehensive medical care through the VA health care system and those in the general US population., Design, Setting, and Participants: This cohort study compared 10.9 million enrollees in the VA, including 6.8 million active users of VA health care (those with a visit in the last 2 years), with the general population of the US, with deaths occurring from January 1, 2014, to December 31, 2020. Statistical analysis was conducted from May 17, 2021, to March 15, 2023., Main Outcomes and Measures: Changes in rates of death from any cause during the COVID-19 pandemic in 2020 compared with previous years. Changes in all-cause death rates by quarter were stratified by age, sex, race and ethnicity, and region, based on individual-level data. Multilevel regression models were fit in a bayesian setting. Standardized rates were used for comparison between populations., Results: There were 10.9 million enrollees in the VA health care system and 6.8 million active users. The demographic characteristics of the VA populations were predominantly male (>85% in the VA health care system vs 49% in the general US population), older (mean [SD], 61.0 [18.2] years in the VA health care system vs 39.0 [23.1] years in the US population), and had a larger proportion of patients who were White (73% in the VA health care system vs 61% in the US population) or Black (17% in the VA health care system vs 13% in the US population). Increases in death rates were apparent across all of the adult age groups (≥25 years) in both the VA populations and the general US population. Across all of 2020, the relative increase in death rates compared with expected values was similar for VA enrollees (risk ratio [RR], 1.20 [95% CI, 1.14-1.29]), VA active users (RR, 1.19 [95% CI, 1.14-1.26]), and the general US population (RR, 1.20 [95% CI, 1.17-1.22]). Because the prepandemic standardized mortality rates were higher in the VA populations prior to the pandemic, the absolute rates of excess mortality were higher in the VA populations., Conclusions and Relevance: In this cohort study, a comparison of excess deaths between populations suggests that active users of the VA health system had similar relative increases in mortality compared with the general US population during the first 10 months of the COVID-19 pandemic.

Introduction: Early identification of patients with coronavirus disease 2019 (COVID-19) who are at risk for hospitalization may help to mitigate disease burden by allowing healthcare systems to conduct sufficient resource and logistical planning in the event of case surges. We sought to develop and validate a clinical risk score that uses readily accessible information at testing to predict individualized 30-day hospitalization risk following COVID-19 diagnosis., Methods: We assembled a retrospective cohort of U.S. Veterans Health Administration patients (age ≥ 18 years) diagnosed with COVID-19 between March 1, 2020, and December 31, 2020. We screened patient characteristics using Least Absolute Shrinkage and Selection Operator logistic regression and constructed the risk score using characteristics identified as most predictive for hospitalization. Patients diagnosed before November 1, 2020, comprised the development cohort, while those diagnosed on or after November 1, 2020, comprised the validation cohort. We assessed risk score discrimination by calculating the area under the receiver operating characteristic (AUROC) curve and calibration using the Hosmer-Lemeshow (HL) goodness-of-fit test. This study was approved by the Veteran's Institutional Review Board of Northern New England at the White River Junction Veterans Affairs Medical Center (Reference no.:1473972-1)., Results: The development and validation cohorts comprised 11,473 and 12,970 patients, of whom 4,465 (38.9%) and 3,669 (28.3%) were hospitalized, respectively. The independent predictors for hospitalization included in the risk score were increasing age, male sex, non-white race, Hispanic ethnicity, homelessness, nursing home/long-term care residence, unemployed or retired status, fever, fatigue, diarrhea, nausea, cough, diabetes, chronic kidney disease, hypertension, and chronic obstructive pulmonary disease. Model discrimination and calibration was good for the development (AUROC = 0.80; HL P-value = .05) and validation (AUROC = 0.80; HL P-value = .31) cohorts., Conclusions: The prediction tool developed in this study demonstrated that it could identify patients with COVID-19 who are at risk for hospitalization. This could potentially inform clinicians and policymakers of patients who may benefit most from early treatment interventions and help healthcare systems anticipate capacity surges., (Published by Oxford University Press on behalf of the Association of Military Surgeons of the United States 2021. This work is written by (a) US Government employee(s) and is in the public domain in the US.)

Abstract This study investigated the clinical and economic impact of anti-obesity medications (AOMs; orlistat, liraglutide, phentermine/topiramate extended-release [ER], naltrexone ER/bupropion ER) among United States Veterans with obesity participating in Motivating Overweight/Obese Veterans Everywhere! (MOVE!), a government-initiated weight management program. The study population was identified from electronic medical records of the Veterans Health Administration (2010-2020). Clinical indices of obesity and health care resource utilization and costs were evaluated at 6, 12, and 24 months after the initial dispensing of an AOM in the AOM+MOVE! cohort ( N  = 3732, mean age 57 years, 79% male) or on the corresponding date of an inpatient or outpatient encounter in the MOVE! cohort ( N  = 7883, mean age 58 years, 81% male). At 6 months postindex, the AOM+MOVE! cohort had better cardiometabolic indices (eg, systolic blood pressure, diastolic blood pressure, total cholesterol, low-density lipoprotein cholesterol, hemoglobin A1c) than the MOVE! cohort, with the trends persisting at 12 and 24 months. The AOM+MOVE! cohort was significantly more likely than the MOVE! cohort to have weight decreases of 5%-10%, 10%-15%, and >15% and lower body mass index at 6, 12, and 24 months. The AOM+MOVE! cohort also had fewer inpatient and emergency department visits than the MOVE! cohort, which was associated with lower mean total medical costs including inpatient costs. These results suggest that combining AOM treatment with the MOVE! program could yield long-term cost savings for the Veterans Affairs network and meaningful clinical improvements for Veterans with obesity.

Controversy exists regarding the efficacy of lithium for suicide prevention. Except for a recent trial that enrolled over 500 patients, available trials of lithium for suicide prevention have involved small samples. It is challenging to measure suicide in a single randomised controlled trial (RCT). Adding a single large study to existing meta-analyses may provide insights into lithium's anti-suicidal effects. We performed a meta-analysis of RCTs comparing lithium with a control condition for suicide prevention. MEDLINE and other databases were searched up to 30 November 2021. Efficacy was assessed by calculating the summary Peto odds ratio (OR) and incidence rate ratio (IRR) with 95% confidence intervals. Among seven RCTs, the odds of suicide were lower among patients receiving lithium versus control (OR = 0.30, 95% CI 0.09-1.02; IRR = 0.22, 95% CI 0.05-1.05), although the findings were still not statistically significant. The role of lithium in suicide prevention remains uncertain.

Objective: There is limited knowledge about the ability of instruments to detect risk of suicide in a range of settings. Prior reviews have not considered whether the utility of instruments depends on prior probability of risk. We performed a systematic review to determine the diagnostic accuracy of instruments to detect risk of suicide in adults using likelihood ratio analysis. This method aids evaluation of prior probabilities of risk., Data Sources: We searched MEDLINE, Cochrane Database of Systematic Reviews, PsycINFO, EMBASE, and Scopus from inception through January 19, 2021., Study Selection: We included clinical trials, observational studies, and quasi-experimental studies assessing the diagnostic accuracy of instruments to detect risk of suicide in adults. There were no language restrictions., Data Extraction: Three reviewers in duplicate assessed full texts to determine eligibility and extracted data from included studies. Positive (LR+) and negative likelihood ratio (LR-) and 95% CIs were calculated for each instrument., Results: Thirty studies met inclusion criteria. Most instruments showed minimal utility to detect or rule out risk of suicide, with LR+ ≤ 2.0 and LR- ≥ 0.5. A few instruments had a high utility for improving risk detection in emergency department, inpatient mental health, and prison settings when patients scored above the cutoff (LR+ > 10). For example, among patients discharged from an emergency department, the Columbia Suicide Severity Rating Scale-Clinical Practice Screener had a LR+ of 10.3 (95% CI, 6.3-16.8) at 3-month follow-up. The clinical utility of the instruments depends on the pretest probability of suicide in the setting. Because studies spanned over 6 decades, the findings are at risk for secular trends., Discussion: We identified several instruments that may hold promise for detecting risk of suicide in emergency department, inpatient mental health, or prison settings. The utility of the instrument hinges, in part, on baseline suicide risk., Registration: PROSPERO: CRD42021285528., (© Copyright 2022 Physicians Postgraduate Press, Inc.)

Background: Seasonal influenza poses a substantial clinical and economic burden in the United States and vulnerable populations, including the elderly and those with comorbidities, are at elevated risk for influenza-related medical complications., Methods: We conducted a retrospective cohort study using the IQVIA PharMetrics® Plus claims database in two stages. In Stage 1, we identified patients with evidence of medically-attended influenza during influenza seasons from October 1, 2014 to May 31, 2018 (latest available data for Stage 1) and used a multivariable logistic regression model to identify patient characteristics that predicted 30-day influenza-related hospitalization. The findings from Stage 1 informed high-risk subgroups of interest for Stage 2, where we selected cohorts of influenza patients during influenza seasons from October 1, 2014 to March 1, 2019 and used 1:1 propensity score matching to patients without influenza with similar high-risk characteristics to compare influenza-attributable rates of all-cause hospital and emergency department (ED) visits during follow-up (30-day and in the index influenza season)., Results: In Stage 1, more than 1.6 million influenza cases were identified, of which 18,509 (1.2%) had a hospitalization. Elderly age was associated with 9 times the odds of hospitalization (≥65 years vs. 5-17 years; OR = 9.4, 95% CI 8.8-10.1) and select comorbidities were associated with 2-3 times the odds of hospitalization. In Stage 2, elderly influenza patients with comorbidities had 3 to 7 times higher 30-day hospitalization rates compared to matched patients without influenza, including patients with congestive heart failure (41.0% vs.7.9%), chronic obstructive pulmonary disease (34.6% vs. 6.1%), coronary artery disease (22.8% vs. 3.8%), and late-stage chronic kidney disease (44.1% vs. 13.1%; all p < 0.05)., Conclusions: The risk of influenza-related complications is elevated in the elderly, especially those with certain underlying comorbidities, leading to excess healthcare resource utilization. Continued efforts, beyond currently available vaccines, are needed to reduce influenza burden in high-risk populations., (© 2022. The Author(s).)

Objective: To estimate relative effectiveness of the booster mRNA Covid-19 vaccination versus the 2-dose primary series for both Delta and Omicron variants with self-controlled study design., Methods: We used the Veterans Health Administration (VHA) Corporate Data Warehouse to identify U.S. Veterans who received the 2-dose primary mRNA Covid-19 vaccine series and a mRNA Covid-19 booster, and who had a positive SARS-CoV-2 test during the Delta (9/23/2021-11/30/2021) or Omicron (1/1/22-3/19/22) predominant period. Among them, we conducted a self-controlled risk interval (SCRI) analysis to compare odds of SARS-CoV-2 infection during a booster exposure interval versus a control interval. Exposures were a control interval (days 4-6 post-booster vaccination, presumably prior to gain of booster immunity), and booster exposure interval (days 14-16 post-booster vaccination, presumably following gain of booster immunity). Cases had a positive PCR or antigen SARS-CoV-2 test. Separately for Delta and Omicron periods, we used conditional logistic regression to calculate odds ratios (OR) of a positive test for the booster versus control interval and calculated relative effectiveness of booster versus 2-dose primary series as (1-OR)*100. The SCRI approach implicitly controlled for time-fixed confounders., Results: We found 42 individuals with a positive SARS-CoV-2 test in the control interval and 14 in the booster exposure interval during the Delta period, and 141 and 70, respectively, in the Omicron period. For the booster versus 2-dose primary series, the odds of infection were 70% (95 %CI: 42%, 84%) lower during the Delta period and 54% (95 %CI: 38%, 66%) lower during Omicron. In sensitivity analyses among those with prior Covid-19 history, and age stratification, ORs were similar to the main analysis., Conclusions: Booster vaccination was more effective relative to a 2-dose primary series during the Delta and Omicron predominant periods, and the relative effectiveness was consistent across age groups., Competing Interests: Declaration of Competing Interest CK, JS, GZ, EP and YY-X acknowledge having received funding form Pfizer for other research projects ohter than this one. HI and KMR report no competing interests., (Copyright © 2022. Published by Elsevier Ltd.)

Objective: To estimate the effectiveness of messenger RNA (mRNA) booster doses during the period of Delta and Omicron variant dominance., Design: We conducted a matched test-negative case-control study to estimate the vaccine effectiveness (VE) of three and two doses of mRNA vaccines against infection (regardless of symptoms) and against COVID-19-related hospitalisation and death., Setting: Veterans Health Administration., Participants: We used electronic health record data from 114 640 veterans who had a SARS-CoV-2 test during November 2021-January 2022. Patients were largely 65 years or older (52%), male (88%) and non-Hispanic white (59%)., Main Outcome Measures: First positive result for a SARS-CoV-2 PCR or antigen test., Results: Against infection, booster doses had higher estimated VE (64%, 95% CI 63 to 65) than two-dose vaccination (12%, 95% CI 10 to 15) during the Omicron period. For the Delta period, the VE against infection was 90% (95% CI 88 to 92) among boosted vaccinees, higher than the VE among two-dose vaccinees (54%, 95% CI 50 to 57). Against hospitalisation, booster dose VE was 89% (95% CI 88 to 91) during Omicron and 94% (95% CI 90 to 96) during Delta; two-dose VE was 63% (95% CI 58 to 67) during Omicron and 75% (95% CI 69 to 80) during Delta. Against death, the VE with a booster dose was 94% (95% CI 90 to 96) during Omicron and 96% (95% CI 87 to 99) during Delta., Conclusions: Among an older, mostly male, population with comorbidities, we found that an mRNA vaccine booster was highly effective against infection, hospitalisation and death. Although the effectiveness of booster vaccination against infection was moderately higher against Delta than against the Omicron SARS-CoV-2 variant, effectiveness against severe disease and death was similarly high against both variants., Competing Interests: Competing interests: YY-X, EIP, GMZ, JS, AB and CK acknowledge having received funding from Pfizer for other research projects other than this one., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Purpose: Azithromycin is a common first-line antibiotic for respiratory infection; however, there is conflicting evidence regarding risk of cardiovascular death. We assessed cardiovascular and noncardiovascular mortality associated with azithromycin versus amoxicillin-clavulanate among US Veterans treated for nonear-nose-throat respiratory infection ("respiratory") or ear-nose-throat infection indication., Methods: Electronic health record data from the US Veterans Health Administration database were used to identify Veterans (30-74 years) with outpatient dispensings of oral azithromycin versus amoxicillin-clavulanate for respiratory or ear-nose-throat infection (January 01, 2000-December 31, 2014). Outcomes assessed were risk of cardiovascular death and noncardiovascular death within 1-5 and 6-10 days postdispensing. Inverse probability of treatment-weighted proportional hazards models and binomial regression models were used to estimate hazard ratios (HRs) and compute risk differences (RD) per million courses of therapy. Cardiac death (subset of cardiovascular death) was assessed in sensitivity analyses., Results: There were 629 345 azithromycin and 168 429 amoxicillin-clavulanate dispensings for respiratory indications, 143 783 azithromycin, and 203 142 amoxicillin-clavulanate dispensings for ear-nose-throat indications. For respiratory indications, azithromycin was not associated with a significantly different risk of cardiovascular death versus amoxicillin-clavulanate within 1-5 days postdispensing (HR [95% confidence interval (CI)]: 1.12 [0.63, 2.00]; RD [95% CI]: 11 [-43, 64] deaths/million courses of therapy). No elevated risk for azithromycin was found for ear-nose-throat indications. Pooled results for both indications via meta-analysis showed no association between antibiotics and cardiovascular mortality. There was no significant difference in risk of noncardiovascular or cardiac death between antibiotics postdispensing., Conclusion: Azithromycin was not associated with elevated risk of cardiovascular or noncardiovascular death versus amoxicillin-clavulanate among US Veterans., (© 2022 John Wiley & Sons Ltd.)

Objective: To compare treatment patterns of United States (US) veterans stable on innovator infliximab (IFX) who switched to an IFX biosimilar (switchers) or remained on innovator IFX (continuers)., Methods: US Veterans Healthcare Administration data (01/2012-12/2019) were used to identify adults with rheumatoid arthritis (RA), psoriatic arthritis (PsA), plaque psoriasis (PsO), ankylosing spondylitis (AS), or Crohn's disease and ulcerative colitis (i.e. inflammatory bowel disease [IBD]), treated with innovator or biosimilar IFX. Index date was the first IFX biosimilar administration for switchers or a random innovator IFX administration for continuers. Patients were required to have ≥5 innovator IFX administrations during the 12 months pre-index (prevalent population). Patients with ≥12 months of observation prior to the first innovator IFX administration were analyzed as the primary population (incident population), and data were assessed from start of innovator IFX. Inverse probability of treatment weighting was used to balance baseline characteristics between cohorts. Treatment patterns were evaluated post-index; continuers were censored before switching to IFX biosimilar. Discontinuation was defined as switching to another biologic (including innovator IFX) or having ≥120 days between 2 consecutive index treatment records., Results: In the incident population, mean [median] duration of follow-up was 737 [796] days among switchers ( N  = 838) and 479 [337] days among continuers ( N  = 849). Compared to continuers, switchers were 2.88-times more likely to discontinue index therapy (hazard ratio [HR] = 2.88, p  < .001) and 4.99-times more likely to switch to another innovator biologic (HR = 4.99, p  < .001). Of 653 switchers switching to another innovator biologic, 594 (91.0%) switched back to innovator IFX. Results were similar among the prevalent population and RA and IBD subgroups., Conclusion: Patients switching from innovator to biosimilar IFX were more likely to discontinue treatment and switch to another innovator biologic (notably back to innovator IFX) than those remaining on innovator IFX; however, reasons for discontinuation and switching are unknown.

Background: Prior studies have established those elderly patients with chronic obstructive pulmonary disease (COPD) are at elevated risk for developing influenza-associated complications such as hospitalization, intensive-care admission, and death. This study sought to determine whether influenza vaccination could improve survival among elderly patients with COPD., Materials/methods: This study included Veterans (age ≥ 65 years) diagnosed with COPD that received care at the United States Veterans Health Administration (VHA) during four influenza seasons, from 2012-2013 to 2015-2016. We linked VHA electronic medical records and Medicare administrative files to Centers for Disease Control and Prevention National Death Index cause of death records as well as influenza surveillance data. A multivariable time-dependent Cox proportional hazards model was used to compare rates of mortality of recipients of influenza vaccination to those who did not have records of influenza vaccination. We estimated hazard ratios (HRs) adjusted for age, gender, race, socioeconomic status, comorbidities, and healthcare utilization., Results: Over a span of four influenza seasons, we included 1,856,970 person-seasons of observation where 1,199,275 (65%) had a record of influenza vaccination and 657,695 (35%) did not have a record of influenza vaccination. After adjusting for comorbidities, demographic and socioeconomic characteristics, influenza vaccination was associated with reduced risk of death during the most severe periods of influenza seasons: 75% all-cause (HR = 0.25; 95% CI: 0.24-0.26), 76% respiratory causes (HR = 0.24; 95% CI: 0.21-0.26), and 82% pneumonia/influenza cause (HR = 0.18; 95% CI: 0.13-0.26). A significant part of the effect could be attributed to "healthy vaccinee" bias as reduced risk of mortality was also found during the periods when there was no influenza activity and before patients received vaccination: 30% all-cause (HR = 0.70; 95% CI: 0.65-0.75), 32% respiratory causes (HR = 0.68; 95% CI: 0.60-0.78), and 51% pneumonia/influenza cause (HR = 0.49; 95% CI: 0.31-0.78). However, as a falsification study, we found that influenza vaccination had no impact on hospitalization due to urinary tract infection (HR = 0.97; 95% CI: 0.80-1.18)., Conclusions: Among elderly patients with COPD, influenza vaccination was associated with reduced risk for all-cause and cause-specific mortality., Competing Interests: Competing Interests Statement: YYX has received research funding from Sanofi Pasteur, Sanofi, Pfizer, Genentech, Janssen, VIR Biotechnology, and the Office of Rural Health Resource Center-Eastern Region. SMM has received research funding from Assurex, GSK, Merck, Pfizer, Roche and Sanofi, and is/was a member of advisory boards for GSK and Sanofi. JN, RVA, JKL, EWT and AC are employees of Sanofi Pasteur. The remaining authors have nothing to disclose. Affiliation with Sanofi Pasteur could be perceived as a potential conflict of interest because Sanofi Pasteur produces influenza vaccines.

Objectives: Applying high-reliability organization (HRO) principles to health care is complex. No consensus exists as to an effective framework for HRO implementation or the direct impact of adoption., Methods: The Veterans Health Administration (VHA) National Center for Patient Safety established the high-reliability hospital (HRH) model for HRO adoption and piloted HRH in collaboration with the Truman VA Medical Center (Truman) during a 3-year intervention period (January 1, 2016-December 31, 2018). High-reliability hospital components are as follows: annual patient safety (PS) assessment, annual PS culture survey, annual root cause analysis training, daily leadership walk-arounds, monthly PS forum, annual processes standardization review, Just Culture training, unit-based Clinical Team Training, unit-based continuous improvement projects, and annual Clinical Team Training simulation education. The impact of HRH was examined using a PS Culture Survey, PS event reporting, and quality outcomes of standardized mortality rate and complication rate., Results: Truman internally improved PS culture and PS event reporting rates resulting in outcomes better than all VHA facilities (All VHA; P < 0.001 and P < 0.001, respectively). Low-harm PS event reporting increased (P < 0.001); however, serious safety event rate remained unchanged versus All VHA. Significant improvement in Truman standardized mortality rate and complication rate versus All VHA occurred immediately and were sustained through intervention (slopes, P < 0.001 and P < 0.020; respectively)., Conclusions: High-reliability hospital is an effective framework for HRO implementation and will be applied to 18 additional VHA sites. Based on these results, the expected outcome will be improved PS culture and overall PS event reporting. The impact of HRH on serious safety event rate and quality measures requires further study., (Copyright © 2020 Wolters Kluwer Health, Inc. All rights reserved.)

Importance: Effectiveness of mRNA vaccinations in a diverse older population with high comorbidity is unknown., Objectives: To describe the scope of the COVID-19 vaccination rollout among US veterans, and to estimate mRNA COVID-19 vaccine effectiveness (VE) as measured by rates of SARS-CoV-2 infection., Design, Setting, and Participants: This matched test-negative case-control study was conducted using SARS-CoV-2 test results at Veterans Health Administration sites from December 14, 2020, to March 14, 2021. Vaccine coverage was estimated for all veterans. VE against SARS-CoV-2 infection and COVID-19-related hospitalization and death were estimated using electronic health records from veterans who routinely sought care at a VHA facility and had a test result positive for SARS-CoV-2 (cases) or negative for SARS-CoV-2 (controls). Cases and controls were matched on time of test and geographic region. Data were analyzed from May to July 2021., Exposures: Vaccination status, defined as unvaccinated, partially vaccinated (≥14 days after first dose until second dose), or fully vaccinated (≥14 days after second dose), at time of test., Main Outcomes and Measures: The main outcome of interest was a positive result for SARS-CoV-2 on a polymerase chain reaction or antigen test. Secondary outcomes included COVID-19-related hospitalization and death, defined by discharge data and proximity of event to positive test result. VE was estimated from odds ratios for SARS-CoV-2 infection with 95% CIs., Results: Among 6 647 733 veterans included (3 350 373 veterans [50%] aged ≥65 years; 6 014 798 [90%] men and 632 935 [10%] women; 461 645 Hispanic veterans of any race [7%], 1 102 471 non-Hispanic Black veterans [17%], and 4 361 621 non-Hispanic White veterans [66%]), 1 363 180 (21%) received at least 1 COVID-19 vaccination by March 7, 2021. In this period, during which the share of SARS-CoV-2 variants Alpha, Epsilon, and Iota had started to increase in the US, estimates of COVID-19 VE against infection, regardless of symptoms, was 95% (95% CI, 93%-96%) for full vaccination and 64% (95% CI, 59%-68%) for partial vaccination. Estimated VE against COVID-19-related hospitalization for full vaccination was 91% (95% CI 83%-95%); there were no deaths among veterans who were fully vaccinated. VE against infection was similar across subpopulations (non-Hispanic Black, 94% [95% CI, 88%-97%]; Hispanic [any race], 83% [95% CI, 45%-95%]; non-Hispanic White, 92% [95% CI 88%-94%]; rural, 94% [95% CI, 89%-96%]; urban, 93% 95% CI, 89%-95%])., Conclusions and Relevance: For veterans of all racial and ethnic subgroups living in urban or rural areas, mRNA vaccination was associated with substantially decreased risk of COVID-19 infection and hospitalization, with no deaths among fully vaccinated veterans.

A Taiwanese cohort study found that symptomatic herpes simplex virus (HSV) infection was associated with a threefold increased risk of developing dementia; however, antiherpetic medication reduced the risk by 90%. Our aim was to verify and further investigate this finding in the US Veteran population using comprehensive electronic medical records from the Veterans Health Administration (VHA). Eighty-seven thousand six hundred eighty-seven Veterans aged 50 or older with symptomatic HSV-1/HSV-2 infection and 217,895 matched controls were identified in VHA data between January 1, 2001, and December 31, 2014, and followed until December 31, 2019. International Classification of Diseases (ICD) codes, ninth and tenth revisions, were used to define dementia. To define HSV infection, we utilized VHA data on antiherpetic medications and laboratory tests in addition to ICD codes. Cox proportional hazards models were used to analyze the effects of HSV infection and antiherpetic medication on the risk of developing dementia. The analysis revealed an adjusted HR of 0.80 (95% CI, 0.78-0.83) for the development of dementia among those with symptomatic HSV relative to those without. Among the 61,776 HSV-1/HSV-2 patients who were treated with antiherpetic medication, 4836 patients (7.8%) developed dementia (adjusted HR = 0.75; 95% CI, 0.72-0.78); this translated to a population average of one additional year of being dementia free in those who were taking antiherpetic medication. In contrast to Tzeng et al. we did not find that HSV infection was associated with an increased risk of dementia. Like their findings, we found that antiherpetic medication was associated with a protective effect against dementia. Future prospective studies are needed to further investigate this effect., (© 2021. This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply.)

Objective: We explored longitudinal trends in sociodemographic characteristics, reported symptoms, laboratory findings, pharmacological and non-pharmacological treatment, comorbidities, and 30-day in-hospital mortality among hospitalized patients with coronavirus disease 2019 (COVID-19)., Methods: This retrospective cohort study included patients diagnosed with COVID-19 in the United States Veterans Health Administration between 03/01/20 and 08/31/20 and followed until 09/30/20. We focused our analysis on patients that were subsequently hospitalized, and categorized them into groups based on the month of hospitalization. We summarized our findings through descriptive statistics. We used Cuzick's Trend Test to examine any differences in the distribution of our study variables across the six months., Results: During our study period, we identified 43,267 patients with COVID-19. A total of 8,240 patients were hospitalized, and 13.1% (N = 1,081) died within 30 days of admission. Hospitalizations increased over time, but the proportion of patients that died consistently declined from 24.8% (N = 221/890) in March to 8.0% (N = 111/1,396) in August. Patients hospitalized in March compared to August were younger on average, mostly black, urban-dwelling, febrile and dyspneic. They also had a higher frequency of baseline comorbidities, including hypertension and diabetes, and were more likely to present with abnormal laboratory findings including low lymphocyte counts and elevated creatinine. Lastly, there was a decline from March to August in receipt of mechanical ventilation (31.4% to 13.1%) and hydroxychloroquine (55.3% to <1.0%), while treatment with dexamethasone (3.7% to 52.4%) and remdesivir (1.1% to 38.9%) increased., Conclusion: Among hospitalized patients with COVID-19, we observed a trend towards decreased disease severity and mortality over time., Competing Interests: The authors have declared that no competing interests exist.

Background: Pressure injury prevention is a persistent concern in nursing. The Veterans Health Administration implemented a creative approach with successful outcomes across the United States., Problem: Pressure injury prevention is a measure of nursing quality of care and a high priority in the Veterans Health Administration., Methods: A 12-month Virtual Breakthrough Series Collaborative utilizing coaching and group calls was conducted to assist long-term and acute care teams with preventing pressure injuries., Interventions: Interventions from the Veterans Health Administration Skin Bundle were implemented, including pressure-relieving surfaces, novel turning techniques, specialized dressings, and emollients to prevent skin breakdown., Results: The aggregated pressure injury rate for all teams decreased from Prework to the Action phase from 1.0 to 0.8 per 1000 bed days of care (P = .01). The aggregated pressure injury rates for long-term care units decreased from Prework to Continuous Improvement from 0.8 to 0.4 per 1000 bed days of care (P = .021)., Conclusion: The Virtual Breakthrough Series helped reduce pressure injuries., Competing Interests: The authors declare no conflicts of interest., (Copyright © 2020 Wolters Kluwer Health, Inc. All rights reserved.)

Objective: To evaluate the effect of a preexisting posttraumatic stress disorder (PTSD) diagnosis on suicide and non-suicide mortalities among men with newly diagnosed prostate cancer, and examine potential mediating factors for the relationship between PTSD and suicide., Methods: We used patient-level data from Veterans Health Administration electronic medical records to identify men (age ≥40 years) diagnosed with prostate cancer between 2004 and 2014. We used Fine and Gray regression model to estimate the risk for competing mortality outcomes (suicide, non-suicide, and alive). We used structural equation models to evaluate the mediating factors., Results: Our cohort comprised 214,649 men with prostate cancer, of whom 12,208 (5.7%) had a preexisting PTSD diagnosis. Patients with PTSD compared to those without utilized more healthcare services and had lower risk cancer at diagnosis. Additionally, they experienced more suicide deaths (N = 26, 0.21% vs. N = 269, 0.13%) and fewer non-suicide deaths (N = 1399, 11.5% vs. N = 45,625, 22.5%). On multivariable analysis, PTSD was an independent suicide risk factor (HR = 2.35; 95% CI: 1.16, 4.78). Depression, substance use disorder, and any definitive prostate cancer treatment were partial mediators. However, PTSD was associated with lower non-suicide mortality risk (HR = 0.86; 95% CI: 0.77, 0.96)., Conclusion: Patients with PTSD experienced greater suicide risk even after adjusting for important mediators. They may have experienced lower non-suicide mortality risk due to favorable physical health resulting from greater healthcare service use and early diagnosis of lower risk cancer. Our findings highlight the importance of considering psychiatric illnesses when treating patients with prostate cancer and the need for interventions to ameliorate suicide risk., (Published 2020. This article is a U.S. Government work and is in the public domain in the USA.)

Objectives: To quantify the association between dose reductions of abiraterone acetate plus prednisone (AAP) or enzalutamide and prostate-specific antigen (PSA) progression in patients with metastatic castration-resistant prostate cancer (mCRPC). Changes in medication-taking patterns of AAP or enzalutamide may arise due to clinical (e.g. toxicity) and non-clinical (e.g. patient compliance) reasons in men with mCRPC. However, it is unclear how this affects PSA progression., Methods: Veterans Health Administration electronic health record database was used to identify Veterans diagnosed with prostate cancer who initiated AAP or enzalutamide (index) from April 2010 to December 2016. PSA progression was defined as the first rise in PSA of ≥2 ng/mL and ≥25% above nadir. The relative dose intensity (RDI) was defined as the ratio of the total dispensed dose over the last two months to the standard recommended dose and was updated monthly. Dose reduction was assessed using a threshold of RDI < 80%., Results: The cohort included 6069 Veterans aged 74.6 years on average. Mean follow-up was 12.3 months. PSA progression occurred in 62.7% of patients. About 63.6% of AAP- and 67.2% of enzalutamide-treated patients had ≥1 occurrence of RDI <80%. RDI <80% was associated with an 8.8% higher risk of PSA progression (hazard ratio [HR] = 1.088; p  = .019; 95% confidence interval [CI] [1.014; 1.166])., Conclusions: Dose reduction was observed in most patients and was associated with significantly higher risk of PSA progression in men with mCRPC. These results suggest future efforts to minimize dose reductions for non-clinical reasons are warranted and that patient adherence should be encouraged to limit the risk of PSA progression.

Objectives: Cost savings associated with high-dose (HD) as compared to standard-dose (SD) influenza vaccination in the United States (US) Veteran's Health Administration (VHA) population have been attributed to better protection against hospitalization for cardiac and respiratory diseases. The relative contribution of each of these disease categories to the reported savings remains to be explored., Methods: During a recently completed study of HD versus SD vaccine effectiveness (conducted in the VHA over five respiratory seasons from 2010/11 through 2014/15), we collected cost data for all healthcare services provided at both VHA and Medicare-funded facilities. In that analysis, we compared the costs of vaccination and hospital care for patients admitted with either cardiovascular or respiratory disease. Treatment selection bias and other confounding factors were adjusted using an instrumental variable (IV) method. In this brief report we use the same study cohort and methods to stratify the results by patients admitted for cardiovascular disease (CVD) and those admitted for respiratory disease., Results: We analyzed 3.5 million SD and 0.16 million HD person-seasons. The IV-adjusted rVEs were 14% (7-20%) against hospitalizations for CVD and 15% (5-25%) against respiratory hospitalizations. Net cost savings per HD recipient were $138 ($66-$200) for CVD related hospitalizations and $62 ($10-$107) for respiratory disease related hospitalizations., Conclusions: In the US VHA population, the reduction in hospitalizations for CVD over five respiratory seasons contributed twice the cost savings (per HD recipient) of the reduction in hospitalizations for respiratory disease., Competing Interests: Declaration of Competing Interest This study was funded by Sanofi Pasteur RVA, SS and AC are employees of Sanofi Pasteur. YYX and ER report grants from Sanofi Pasteur during the conduct of the study. SMM has received unrestricted research grants from Merck, GlaxoSmithKline, Sanofi Pasteur, Pfizer and Roche-Assurex for unrelated studies. SMM has received fees as an advisory board member for Sanofi Pasteur. MP received grants and honoraria from various pharmaceutical companies, inclusive those developing, producing and marketing influenza vaccines (in particular GSK, Astra Zeneca, Seqirus and Sanofi Pasteur) NN and JW report no conflict of interest., (Copyright © 2020. Published by Elsevier Ltd.)

Background: Clostridioides difficile infection (CDI) is an important cause of diarrheal disease associated with increasing morbidity and mortality. Efforts to develop a preventive vaccine are ongoing. The goal of this study was to develop an algorithm to identify patients at high risk of CDI for enrollment in a vaccine efficacy trial., Methods: We conducted a 2-stage retrospective study of patients aged ≥ 50 within the US Department of Veterans Affairs Health system between January 1, 2009 and December 31, 2013. Included patients had at least 1 visit in each of the 2 years prior to the study, with no CDI in the past year. We used multivariable logistic regression with elastic net regularization to identify predictors of CDI in months 2-12 (i.e., days 31 - 365) to allow time for antibodies to develop. Performance was measured using the positive predictive value (PPV) and the area under the curve (AUC)., Results: Elements of the predictive algorithm included age, baseline comorbidity score, acute renal failure, recent infections or high-risk antibiotic use, hemodialysis in the last month, race, and measures of recent healthcare utilization. The final algorithm resulted in an AUC of 0.69 and a PPV of 3.4%., Conclusions: We developed a predictive algorithm to identify a patient population with increased risk of CDI over the next 2-12 months. Our algorithm can be used prospectively with clinical and administrative data to facilitate the feasibility of conducting efficacy studies in a timely manner in an appropriate population., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: DNG is an advisory board member or consultant for Ferring, Rebiotix, Merck, DaVolterra, Summit, Actelion, Pfizer, MGB Pharma, Sanofi Pasteur, and Medpace and holds patents for the Treatment and Prevention of CDI. JL, HY, ENG, and BC are employees of Pfizer, Inc. All other authors: no conflicts to report., (Copyright © 2020. Published by Elsevier Ltd.)

Background: Previous studies established an association between laboratory-confirmed influenza infection (LCI) and hospitalization for acute myocardial infarction (AMI) but not causality. We aimed to explore the underlying mechanisms by adding biological mediators to an established study design used by earlier studies., Methods: With data on biomarkers, we used a self-controlled case-series design to evaluate the effect of LCI on hospitalization for AMI among Veterans Health Administration (VHA) patients. We included senior Veterans (age 65 years and older) with LCI between 2010 through 2015. Patient-level data from VHA electronic medical records were used to capture laboratory results, hospitalizations, and baseline patient characteristics. We defined the "risk interval" as the first 7 days after specimen collection and the "control interval" as 1 year before and 1 year after the risk interval. More importantly, using mediation analysis, we examined the role of abnormal white blood cell (WBC) and platelet count in the relationship between LCI and AMI to explore the thrombogenic nature of this association, thus potential causality., Results: We identified 391 hospitalizations for AMI that occurred within +/-1 year of a positive influenza test, of which 31 (31.1 admissions/week) occurred during the risk interval and 360 (3.5/per week) during the control interval, resulting in an incidence ratio (IR) for AMI admission of 8.89 (95% confidence interval [CI]: 6.16-12.84). In stratified analyses, AMI risk was significantly elevated among patients with high WBC count (IR, 12.43; 95% CI: 6.99-22.10) and high platelet count (IR, 15.89; 95% CI: 3.59-70.41)., Conclusion: We confirmed a significant association between LCI and AMI. The risk was elevated among those with high WBC or platelet count, suggesting a potential role for inflammation and platelet activation in the underlying mechanism., Competing Interests: YYX has received research funding from Sanofi Pasteur, Sanofi, Pfizer, Genentech, Janssen, VIR Biotechnology, and the Office of Rural Health Resource Center- Eastern Region. SMM has received research funding from Assurex, GSK, Merck, Pfizer, Roche and Sanofi, and is/was a member of advisory boards for GSK and Sanofi. RVA, JKL, EWT and AC are employees of Sanofi Pasteur. The remaining authors have nothing to disclose. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

Objectives: The objective of this study was to evaluate the association of prostate-specific antigen doubling time (PSADT) with metastasis-free survival (MFS) and overall survival (OS), and to describe healthcare resource utilization (HRU) and costs among patients with non-metastatic castrate-resistant prostate cancer (nmCRPC) in the Veterans Health Administration setting., Methods and Materials: Patients with nmCRPC were identified from the Veterans Health Administration electronic health record database (1/2007-8/2017). PSADT was categorized as <3 months, 3 to 9 months, 9 to 15 months, ≥15 months, and unknown. MFS and OS were assessed using multivariable Cox proportional hazards regression, including PSADT as a predictor. HRU and costs were described per-patient-per-year (PPPY)., Results: Among 12,083 patients in the study, shorter PSADT was associated with shorter MFS and OS (PSADT <3 months vs. PSADT ≥15 months hazard ratio [HR] [95% confidence interval (CI)] = 0.307 [0.281, 0.335] and 0.371 [0.335, 0.410], respectively). Patients who developed metastasis had a 3-fold higher risk of death compared to those without metastasis (HR [95% CI] = 2.933 [2.763, 3.113]). Mean HRU increased following the onset of nmCRPC and metastatic castrate-resistant prostate cancer (mCRPC); mean inpatient stays more than doubled (0.2 vs. 0.5 and 0.6 vs. 2.8 PPPY, respectively). Similar increases in healthcare costs were observed; pharmacy costs more than tripled following nmCRPC ($2,074 vs. $6,839 PPPY). From nmCRPC to mCRPC, large increases were observed for inpatient costs ($7,257-$61,691), emergency room costs ($844-$1,958), and pharmacy costs ($4,115-$26,279) PPPY., Conclusions: In Veterans with nmCRPC, shorter PSADT was significantly associated with shorter MFS and OS. Onset of nmCRPC and mCRPC was associated with substantial HRU and cost increases., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Objective: Fluoxetine, paroxetine, sertraline, topiramate, and venlafaxine have previously shown efficacy for posttraumatic stress disorder (PTSD). One prior study using US Department of Veterans Affairs (VA) medical records data to compare these agents found no differences in symptom reduction in clinical practice. The current study addresses several weaknesses in that study, including limited standardization of treatment duration, inability to account for prior treatment receipt, use of an outdated symptomatic assessment for PTSD, and lack of functional outcome., Methods: A total of 834 VA outpatients were identified with DSM-5 clinical diagnoses of PTSD between October 2016 and March 2018 who initiated one of the medications and met prespecified criteria for treatment duration and dose, combined with baseline and endpoint DSM-5 PTSD Checklist (PCL-5) measurements. Twelve-week acute-phase changes in PCL-5 score and remission of PTSD symptoms were compared among patients receiving the different medications, as was use of acute psychiatric services in the subsequent 6-month continuation phase., Results: In the acute phase, patients improved by a mean of 6.8-10.1 points on the PCL-5 and 0.0%-10.9% achieved remission of PTSD symptoms. Those taking venlafaxine were significantly more likely to achieve remission (P = .008 vs fluoxetine and P < .0001 vs paroxetine, sertraline, and topiramate). In the continuation phase, there were no differences in acute psychiatric care use between medications. Those who continued their medication were less likely to use acute psychiatric services (HR = 0.55; P = .03)., Conclusions: There may be an advantage to venlafaxine over other agents in achieving acute-phase remission for DSM-5 PTSD in routine clinical practice, but this finding requires further study. Regardless of the agent chosen, medication cessation during the continuation phase is associated with a higher risk of acute psychiatric care use., (© Copyright 2020 Physicians Postgraduate Press, Inc.)

IntroductionIt is unclear whether high-dose influenza vaccine (HD) is more effective at reducing mortality among seniors.AimThis study aimed to evaluate the relative vaccine effectiveness (rVE) of HD. MethodsWe linked electronic medical record databases in the Veterans Health Administration (VHA) and Medicare administrative files to examine the rVE of HD vs standard-dose influenza vaccines (SD) in preventing influenza/pneumonia-associated and cardiorespiratory mortality among VHA-enrolled veterans 65 years or older during the 2012/13, 2013/14 and 2014/15 influenza seasons. A multivariable Cox proportional hazards model was performed on matched recipients of HD vs SD, based on vaccination time, location, age, sex, ethnicity and VHA priority level. ResultsAmong 569,552 person-seasons of observation, 207,574 (36%) were HD recipients and 361,978 (64%) were SD recipients, predominantly male (99%) and white (82%). Pooling findings from all three seasons, the adjusted rVE estimate of HD vs SD during the high influenza periods was 42% (95% confidence interval (CI): 24-59) against influenza/pneumonia-associated mortality and 27% (95% CI: 23-32) against cardiorespiratory mortality. Residual confounding was evident in both early and late influenza periods despite matching and multivariable adjustment. Excluding individuals with high 1-year predicted mortality at baseline reduced the residual confounding and yielded rVE of 36% (95% CI: 10-62) and 25% (95% CI: 12-38) against influenza/pneumonia-associated and cardiorespiratory mortality, respectively. These were confirmed by results from two-stage residual inclusion estimations.DiscussionThe HD was associated with a lower risk of influenza/pneumonia-associated and cardiorespiratory death in men during the high influenza period.

Introduction: To provide up-to-date data on fall prevalence and trends in Veterans Health Administration (VHA) hospitals., Methods: Data were collected by the VHA Inpatient Evaluation Center (IPEC) between 2011 and 2017, to establish prevalence and trends of falls and major injuries occurring in acute care/intensive care units (AC/ICU), behavior health (BH), and community living center (CLC)/long-term care, using bed days of care (BDOC) as denominators., Results: A total of 204,681 falls were reported (rate = 4.8 falls/1,000 BDOC) during the study period, of which 2,549 (1.2%) resulted in a major injury (rate = 6.0/100,000 BDOC). Fall rates decreased over the 6-year study period for all unit types: 10% decrease for BH (p < .0001), 9% decrease for AC/ICU (p < .0001), and 3% decrease for CLC (p = .0043). Major injury rates remained consistent., Conclusions: In this large descriptive study, fall and major injury rates varied by nursing unit type in VHA hospitals. Over the 6-year study period, a clinically and statistically significant decrease in fall rates for BH and AC/ICU units was observed as well as a small but statistically significant decrease in fall rates for CLC units. No trend was observed for major injury rates.

Background: Unmeasured confounders are commonplace in observational studies conducted using real-world data. Prior event rate ratio (PERR) adjustment is a technique shown to perform well in addressing such confounding. However, it has been demonstrated that, in some circumstances, the PERR method actually increases rather than decreases bias. In this work, we seek to better understand the robustness of PERR adjustment., Methods: We begin with a Bayesian network representation of a generalized observational study, which is subject to unmeasured confounding. Previous work evaluating PERR performance used Monte Carlo simulation to calculate joint probabilities of interest within the study population. Here, we instead use a Bayesian networks framework., Results: Using this streamlined analytic approach, we are able to conduct probabilistic bias analysis (PBA) using large numbers of combinations of parameters and thus obtain a comprehensive picture of PERR performance. We apply our methodology to a recent study that used the PERR in evaluating elderly-specific high-dose (HD) influenza vaccine in the US Veterans Affairs population. That study obtained an HD relative effectiveness of 25% (95% CI: 2%-43%) against influenza- and pneumonia-associated hospitalization, relative to standard-dose influenza vaccine. In this instance, we find that the PERR-adjusted result is more like to underestimate rather than to overestimate the relative effectiveness of the intervention., Conclusions: Although the PERR is a powerful tool for mitigating the effects of unmeasured confounders, it is not infallible. Here, we develop some general guidance for when a PERR approach is appropriate and when PBA is a safer option., (© 2019 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.)

Objective: Clostridioides difficile infection (CDI) remains a significant public health concern, resulting in excess morbidity, mortality, and costs. Additional insight into the burden of CDI in adults aged &lt;65 years is needed., Design/setting: A 6-year retrospective cohort study was conducted using data extracted from United States Veterans Health Administration electronic medical records., Patients/methods: Patients aged 18-64 years on January 1, 2011, were followed until incident CDI, death, loss-to-follow-up, or December 31, 2016. CDI was identified by a diagnosis code accompanied by metronidazole, vancomycin, or fidaxomicin therapy, or positive laboratory test. The clinical setting of CDI onset was defined according to 2017 SHEA-IDSA guidelines., Results: Of 1,073,900 patients, 10,534 had a CDI during follow-up. The overall incidence rate was 177 CDIs per 100,000 person years, rising steadily from 164 per 100,000 person years in 2011 to 189 per 100,000 person years in 2016. Those with a CDI were slightly older (55 vs 51 years) and sicker, with a higher baseline Charlson comorbidity index score (1.4 vs 0.5) than those without an infection. Nearly half (48%) of all incident CDIs were community associated, and this proportion rose from 41% in 2011 to 56% in 2016., Conclusions: The findings from this large retrospective study indicate that CDI incidence, driven primarily by increasing community-associated infection, is rising among young and middle-aged adult Veterans with high service-related disability. The increasing burden of community associated CDI in this vulnerable population warrants attention. Future studies quantifying the economic and societal burden of CDI will inform decisions surrounding prevention strategies.