Prevalence of SARS-COV-2 Vaccination and Factors Impacting Likelihood of Vaccination in a Nationwide Veterans Affairs Cohort of IBD Patients.
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ABSTRACT:
SUBMITTER: Mahmud N
PROVIDER: S-EPMC9383835 | biostudies-literature | 2022 Apr
REPOSITORIES: biostudies-literature
Publications
Prevalence of SARS-COV-2 Vaccination and Factors Impacting Likelihood of Vaccination in a Nationwide Veterans Affairs Cohort of IBD Patients.
Mahmud Nadim N Shah Yash Y Khan Nabeel N
Inflammatory bowel diseases 20221101 11
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Project description:ImportancePatients with cancer are at increased risk for severe COVID-19, but it is unknown whether SARS-CoV-2 vaccination is effective for them.ObjectiveTo determine the association between SARS-CoV-2 vaccination and SARS-CoV-2 infections among a population of Veterans Affairs (VA) patients with cancer.Design, setting, and participantsRetrospective, multicenter, nationwide cohort study of SARS-CoV-2 vaccination and infection among patients in the VA health care system from December 15, 2020, to May 4, 2021. All adults with solid tumors or hematologic cancer who received systemic cancer-directed therapy from August 15, 2010, to May 4, 2021, and were alive and without a documented SARS-CoV-2 positive result as of December 15, 2020, were eligible for inclusion. Each day between December 15, 2020, and May 4, 2021, newly vaccinated patients were matched 1:1 with unvaccinated or not yet vaccinated controls based on age, race and ethnicity, VA facility, rurality of home address, cancer type, and treatment type/timing.ExposuresReceipt of a SARS-CoV-2 vaccine.Main outcomes and measuresThe primary outcome was documented SARS-CoV-2 infection. A proxy for vaccine effectiveness was defined as 1 minus the risk ratio of SARS-CoV-2 infection for vaccinated individuals compared with unvaccinated controls.ResultsA total of 184 485 patients met eligibility criteria, and 113 796 were vaccinated. Of these, 29 152 vaccinated patients (median [IQR] age, 74.1 [70.2-79.3] years; 95% were men; 71% were non-Hispanic White individuals) were matched 1:1 to unvaccinated or not yet vaccinated controls. As of a median 47 days of follow-up, 436 SARS-CoV-2 infections were detected in the matched cohort (161 infections in vaccinated patients vs 275 in unvaccinated patients). There were 17 COVID-19-related deaths in the vaccinated group vs 27 COVID-19-related deaths in the unvaccinated group. Overall vaccine effectiveness in the matched cohort was 58% (95% CI, 39% to 72%) starting 14 days after the second dose. Patients who received chemotherapy within 3 months prior to the first vaccination dose were estimated to have a vaccine effectiveness of 57% (95% CI, -23% to 90%) starting 14 days after the second dose vs 76% (95% CI, 50% to 91%) for those receiving endocrine therapy and 85% (95% CI, 29% to 100%) for those who had not received systemic therapy for at least 6 months prior.Conclusions and relevanceIn this cohort study, COVID-19 vaccination was associated with lower SARS-CoV-2 infection rates in patients with cancer. Some immunosuppressed subgroups may remain at early risk for COVID-19 despite vaccination, and consideration should be given to additional risk reduction strategies, such as serologic testing for vaccine response and a third vaccine dose to optimize outcomes.
| S-EPMC8640949 | biostudies-literature
Project description:Background/objectivesCOVID-19 has caused significant morbidity and mortality in nursing homes. Vaccination against SARS-COV-2 holds promise for reduction in COVID-19. This operational analysis describes the proportion of SARS-COV-2 positive tests before, during, and after vaccination.DesignRetrospective longitudinal cohort analysis from October 1, 2020 until February 14, 2021.SettingA total of 130 Department of Veterans Affairs (VA) Community Living Centers (CLC), analogous to nursing homes.InterventionVaccination for SARS-CoV-2.MeasurementsThe primary measure is the proportion of SARS-CoV-2 positive tests among CLC residents. In a pooled analysis of weekly testing and vaccine data, the proportion of positive tests was compared for the unvaccinated, first dose, and second dose. For each CLC, we identified the week in which 50% of CLC residents were vaccinated (index week). The analysis aligned the index week for CLCs and examined the proportion of SARS-CoV-2 positive tests at the CLC level before and after. As a reference, we plotted the proportion of positive tests in nursing homes in the same county as the CLC using publicly reported data.ResultsWithin the pooled VA CLCs, the first SARS-CoV-2 vaccine dose was delivered to 50% of CLC residents within 1 week of availability and second dose within 5 weeks. Relative to the index week, the risk ratio of SARS-CoV-2 positive tests in the vaccinated relative to unvaccinated was significantly lower in Week 4 (relative risk 0.37, 95% confidence interval 0.20-0.68). Throughout the study period, the proportion of SARS-CoV-2 positive tests in community nursing homes was higher compared to VA CLC and also declined after vaccine availability.ConclusionThe proportion of SARS-CoV-2 positive tests significantly declined in VA CLCs 4 weeks after vaccine delivery and continued to decline in vaccinated and unvaccinated residents. The results describe the importance of SARS-CoV-2 surveillance and vaccination in VA nursing home residents.
| S-EPMC8250473 | biostudies-literature
Project description:BackgroundAlzheimer's disease and related dementias (ADRD) impact the diagnosis and infection control of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) in nursing homes (NH) by influencing the behavior of residents and their caregivers. Health system data show an association between ADRD and SARS-CoV-2. Whether this association is present in NH populations remains unknown. How increased SARS-CoV-2 risk among residents with ADRD impacts the greater NH population also remains unknown.MethodsThis retrospective cohort study used electronic health record data on Veterans residing in 133 Veterans Affairs Community Living Centers (CLC) and 15 spinal cord injury units from March 1, 2020 to December 13, 2020. We measured ADRD using diagnostic codes 12 months before an index SARS-CoV-2 test date for each resident. We used Poisson regression to determine the relative risk of SARS-CoV-2 for the highest quartile of facility ADRD prevalence versus the lowest, stratifying by individual ADRD status, and adjusting for covariates, with and without a random intercept to account for facility clustering.ResultsAcross the study period, 15,043 residents resided in CLCs, 1952 (13.0%) had SARS-CoV-2, and 8067 (53.6%) had ADRD. There was an estimated 60% increased risk of SARS-CoV-2 in facilities with highest dementia prevalence versus lowest (relative risk, 1.6 [95% confidence interval 0.95, 2.7]).ConclusionsCLC residents had a greater likelihood of SARS-CoV-2 infection in facilities with greater ADRD prevalence. Facility characteristics other than ADRD prevalence may account for this association.
| S-EPMC9349562 | biostudies-literature
Project description: Not available
| S-EPMC7816748 | biostudies-literature
Project description:BackgroundThe US Veterans Affairs (VA) healthcare system began reporting risk-adjusted mortality for intensive care (ICU) admissions in 2005. However, while the VA's mortality model has been updated and adapted for risk-adjustment of all inpatient hospitalizations, recent model performance has not been published. We sought to assess the current performance of VA's 4 standardized mortality models: acute care 30-day mortality (acute care SMR-30); ICU 30-day mortality (ICU SMR-30); acute care in-hospital mortality (acute care SMR); and ICU in-hospital mortality (ICU SMR).MethodsRetrospective cohort study with split derivation and validation samples. Standardized mortality models were fit using derivation data, with coefficients applied to the validation sample. Nationwide VA hospitalizations that met model inclusion criteria during fiscal years 2017-2018(derivation) and 2019 (validation) were included. Model performance was evaluated using c-statistics to assess discrimination and comparison of observed versus predicted deaths to assess calibration.ResultsAmong 1,143,351 hospitalizations eligible for the acute care SMR-30 during 2017-2019, in-hospital mortality was 1.8%, and 30-day mortality was 4.3%. C-statistics for the SMR models in validation data were 0.870 (acute care SMR-30); 0.864 (ICU SMR-30); 0.914 (acute care SMR); and 0.887 (ICU SMR). There were 16,036 deaths (4.29% mortality) in the SMR-30 validation cohort versus 17,458 predicted deaths (4.67%), reflecting 0.38% over-prediction. Across deciles of predicted risk, the absolute difference in observed versus predicted percent mortality was a mean of 0.38%, with a maximum error of 1.81% seen in the highest-risk decile.Conclusions and relevanceThe VA's SMR models, which incorporate patient physiology on presentation, are highly predictive and demonstrate good calibration both overall and across risk deciles. The current SMR models perform similarly to the initial ICU SMR model, indicating appropriate adaption and re-calibration.
| S-EPMC9640507 | biostudies-literature
Project description: Not available
| S-EPMC8499751 | biostudies-literature
Project description:ImportanceMany veterans enrolled in the Veterans Affairs (VA) health care system have access to non-VA care through insurance and VA-purchased community care. Prior comparisons of VA and non-VA hospital outcomes have been limited to subpopulations.ObjectiveTo compare outcomes for 6 acute conditions in VA and non-VA hospitals for younger and older veterans using VA and all-payer discharge data.Design, setting, and participantsThis cohort study used a repeated cross-sectional analysis of hospitalization records for acute myocardial infarction (AMI), coronary artery bypass graft (CABG), gastrointestinal (GI) hemorrhage, heart failure (HF), pneumonia, and stroke. Participants included VA enrollees from 11 states at VA and non-VA hospitals from 2012 to 2017. Analysis was conducted from July 1, 2022, to October 18, 2023.ExposuresTreatment in VA or non-VA hospital.Main outcome and measuresThirty-day mortality, 30-day readmission, length of stay (LOS), and costs. Average treatment outcomes of VA hospitals were estimated using inverse probability weighted regression adjustment to account for selection into hospitals. Models were stratified by veterans' age (aged less than 65 years and aged 65 years and older).ResultsThere was a total of 593 578 hospitalizations and 414 861 patients with mean (SD) age 75 (12) years, 405 602 males (98%), 442 297 hospitalizations of non-Hispanic White individuals (75%) and 73 155 hospitalizations of non-Hispanic Black individuals (12%) overall. VA hospitalizations had a lower probability of 30-day mortality for HF (age ≥65 years, -0.02 [95% CI, -0.03 to -0.01]) and stroke (age <65 years, -0.03 [95% CI, -0.05 to -0.02]; age ≥65 years, -0.05 [95% CI, -0.07 to -0.03]). VA hospitalizations had a lower probability of 30-day readmission for CABG (age <65 years, -0.04 [95% CI, -0.06 to -0.01]; age ≥65 years, -0.05 [95% CI, -0.07 to -0.02]), GI hemorrhage (age <65 years, -0.04 [95% CI, -0.06 to -0.03]), HF (age <65 years, -0.05 [95% CI, -0.07 to -0.03]), pneumonia (age <65 years, -0.04 [95% CI, -0.06 to -0.03]; age ≥65 years, -0.03 [95% CI, -0.04 to -0.02]), and stroke (age <65 years, -0.11 [95% CI, -0.13 to -0.09]; age ≥65 years, -0.13 [95% CI, -0.16 to -0.10]) but higher probability of readmission for AMI (age <65 years, 0.04 [95% CI, 0.01 to 0.06]). VA hospitalizations had a longer mean LOS and higher costs for all conditions, except AMI and stroke in younger patients.Conclusions and relevanceIn this cohort study of veterans, VA hospitalizations had lower mortality for HF and stroke and lower readmissions, longer LOS, and higher costs for most conditions compared with non-VA hospitalizations with differences by condition and age group. There were tradeoffs between better outcomes and higher resource use in VA hospitals for some conditions.
| S-EPMC10692833 | biostudies-literature
Project description:BackgroundHealth care personnel and patients are at risk to acquire severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in health care settings, including in outpatient clinics and ancillary care areas.MethodsBetween May 1, 2020, and January 31, 2021, we identified clusters of 3 or more coronavirus disease 2019 (COVID-19) cases in which nosocomial transmission was suspected in a Veterans Affairs health care system. Asymptomatic employees and patients were tested for SARS-CoV-2 if they were identified as being at risk through contact tracing investigations; for 7 clusters, all personnel and/or patients in a shared work area were tested regardless of exposure history. Whole-genome sequencing was performed to determine the relatedness of SARS-CoV-2 samples from the clusters and from control employees and patients.ResultsOf 14 clusters investigated, 7 occurred in community-based outpatient clinics, 1 in the emergency department, 3 in ancillary care areas, and 3 on hospital medical/surgical wards that did not provide care for patients with known COVID-19 infection. Eighty-one of 82 (99%) symptomatic COVID-19 cases and 31 of 35 (89%) asymptomatic cases occurred in health care personnel. Sequencing analysis provided support for several transmission events between coworkers and in 2 cases supported transmission from health care personnel to patients. There were no documented transmissions from patients to personnel.ConclusionsClusters of COVID-19 with nosocomial transmission predominantly involved health care personnel and often occurred in outpatient clinics and ancillary care areas. There is a need for improved measures to prevent transmission of SARS-CoV-2 by health care personnel in inpatient and outpatient settings.
| S-EPMC8344547 | biostudies-literature
Project description:BackgroundTo study patient physiology throughout a period of acute hospitalization, we sought to create accessible, standardized nationwide data at the level of the individual patient-facility-day. This methodology paper summarizes the development, organization, and characteristics of the Veterans Affairs Patient Database 2014-2017 (VAPD 2014-2017). The VAPD 2014-2017 contains acute hospitalizations from all parts of the nationwide VA healthcare system with daily physiology including clinical data (labs, vitals, medications, risk scores, etc.), intensive care unit (ICU) indicators, facility, patient, and hospitalization characteristics.MethodsThe VA data structure and database organization represents a complex multi-hospital system. We define a single-site hospitalization as one or more consecutive stays with an acute treating specialty at a single facility. The VAPD 2014-2017 is structured at the patient-facility-day level, where every patient-day in a hospital is a row with separate identification variables for facility, patient, and hospitalization. The VAPD 2014-2017 includes daily laboratory, vital signs, and inpatient medication. Such data were validated and verified through lab value range and comparison with patient charts. Sepsis, risk scores, and organ dysfunction definitions were standardized and calculated.ResultsWe identified 565,242 single-site hospitalizations (SSHs) in 2014; 558,060 SSHs in 2015; 553,961 SSHs in 2016; and 550,236 SSHs in 2017 at 141 VA hospitals. The average length of stay was four days for all study years. In-hospital mortality decreased from 2014 to 2017 (1.7 to 1.4%), 30-day readmission rates increased from 15.3% in 2014 to 15.6% in 2017; 30-day mortality also decreased from 4.4% in 2014 to 4.1% in 2017. From 2014 to 2017, there were 107,512 (4.8%) of SSHs that met the Center for Disease Control and Prevention's Electronic Health Record-based retrospective definition of sepsis.ConclusionThe VAPD 2014-2017 represents a large, standardized collection of granular data from a heterogeneous nationwide healthcare system. It is also a direct resource for studying the evolution of inpatient physiology during both acute and critical illness.
| S-EPMC6505066 | biostudies-literature
Project description:BackgroundThe SARS-CoV-2 pandemic has disproportionately affected racial and ethnic minority communities across the United States. We sought to disentangle individual and census tract-level sociodemographic and economic factors associated with these disparities.Methods and findingsAll adults tested for SARS-CoV-2 between February 1 and June 21, 2020 were geocoded to a census tract based on their address; hospital employees and individuals with invalid addresses were excluded. Individual (age, sex, race/ethnicity, preferred language, insurance) and census tract-level (demographics, insurance, income, education, employment, occupation, household crowding and occupancy, built home environment, and transportation) variables were analyzed using linear mixed models predicting infection, hospitalization, and death from SARS-CoV-2.Among 57,865 individuals, per capita testing rates, individual (older age, male sex, non-White race, non-English preferred language, and non-private insurance), and census tract-level (increased population density, higher household occupancy, and lower education) measures were associated with likelihood of infection. Among those infected, individual age, sex, race, language, and insurance, and census tract-level measures of lower education, more multi-family homes, and extreme household crowding were associated with increased likelihood of hospitalization, while higher per capita testing rates were associated with decreased likelihood. Only individual-level variables (older age, male sex, Medicare insurance) were associated with increased mortality among those hospitalized.ConclusionsThis study of the first wave of the SARS-CoV-2 pandemic in a major U.S. city presents the cascade of outcomes following SARS-CoV-2 infection within a large, multi-ethnic cohort. SARS-CoV-2 infection and hospitalization rates, but not death rates among those hospitalized, are related to census tract-level socioeconomic characteristics including lower educational attainment and higher household crowding and occupancy, but not neighborhood measures of race, independent of individual factors.
| S-EPMC7536884 | biostudies-literature