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1.
Journal of the American Geriatrics Society ; n/a(n/a), 2022.
Article in English | Wiley | ID: covidwho-1807169

ABSTRACT

Background COVID-19 and influenza are important sources of morbidity and mortality among older adults. Understanding how outcomes differ for older adults hospitalized with either infection is important for improving care. We compared outcomes from infection with COVID-19 and influenza among hospitalized older adults. Methods We conducted a retrospective study of 30-day mortality among veterans aged 65+ hospitalized with COVID-19 from March 1, 2020 ? December 31, 2020 or with influenza A/B from September 1, 2017 to August 31, 2019 in Veterans Affairs Health Care System (VAHCS). COVID-19 infection was determined by positive PCR test and influenza by tests used in the VA system. Frailty was defined by the claims-based Veterans Affairs Frailty Index (VA-FI). Logistic regressions of mortality on frailty, age, and infection were adjusted for multiple confounders. Results 15,474 veterans were admitted with COVID-19 and 7,867 with influenza. Mean (SD) ages were 76.1 (7.8) and 75.8 (8.3) years, 97.7% and 97.4% were male, and 66.9% and 76.4% were white in the COVID-19 and influenza cohorts respectively. Crude 30-day mortality (95% CI) was 18.9% (18.3% - 19.5%) for COVID-19 and 4.3% (3.8% - 4.7%) for influenza. Combining cohorts, the odds ratio for 30-day mortality from COVID-19 (versus influenza) was 6.61 (5.74 ? 7.65). There was a statistically significant interaction between infection with COVID-19 and frailty, but there was no significant interaction between COVID-19 and age. Separating cohorts, greater 30-day mortality was significantly associated with older age (p: COVID-19: <0.001, Influenza: <0.001) and for frail compared with robust individuals (p for trend: COVID-19: <0.001, Influenza: <0.001). Conclusion Mortality from COVID-19 exceeded that from influenza among hospitalized older adults. However, odds of mortality were higher at every level of frailty among those admitted with influenza compared to COVID-19. Prevention will remain key to reducing mortality from viral illnesses among older adults.

2.
N Engl J Med ; 386(2): 105-115, 2022 01 13.
Article in English | MEDLINE | ID: covidwho-1557219

ABSTRACT

BACKGROUND: The messenger RNA (mRNA)-based vaccines BNT162b2 and mRNA-1273 are more than 90% effective against coronavirus disease 2019 (Covid-19). However, their comparative effectiveness for a range of outcomes across diverse populations is unknown. METHODS: We emulated a target trial using the electronic health records of U.S. veterans who received a first dose of the BNT162b2 or mRNA-1273 vaccine between January 4 and May 14, 2021, during a period marked by predominance of the SARS-CoV-2 B.1.1.7 (alpha) variant. We matched recipients of each vaccine in a 1:1 ratio according to their risk factors. Outcomes included documented severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, symptomatic Covid-19, hospitalization for Covid-19, admission to an intensive care unit (ICU) for Covid-19, and death from Covid-19. We estimated risks using the Kaplan-Meier estimator. To assess the influence of the B.1.617.2 (delta) variant, we emulated a second target trial that involved veterans vaccinated between July 1 and September 20, 2021. RESULTS: Each vaccine group included 219,842 persons. Over 24 weeks of follow-up in a period marked by alpha-variant predominance, the estimated risk of documented infection was 5.75 events per 1000 persons (95% confidence interval [CI], 5.39 to 6.23) in the BNT162b2 group and 4.52 events per 1000 persons (95% CI, 4.17 to 4.84) in the mRNA-1273 group. The excess number of events per 1000 persons for BNT162b2 as compared with mRNA-1273 was 1.23 (95% CI, 0.72 to 1.81) for documented infection, 0.44 (95% CI, 0.25 to 0.70) for symptomatic Covid-19, 0.55 (95% CI, 0.36 to 0.83) for hospitalization for Covid-19, 0.10 (95% CI, 0.00 to 0.26) for ICU admission for Covid-19, and 0.02 (95% CI, -0.06 to 0.12) for death from Covid-19. The corresponding excess risk (BNT162b2 vs. mRNA-1273) of documented infection over 12 weeks of follow-up in a period marked by delta-variant predominance was 6.54 events per 1000 persons (95% CI, -2.58 to 11.82). CONCLUSIONS: The 24-week risk of Covid-19 outcomes was low after vaccination with mRNA-1273 or BNT162b2, although risks were lower with mRNA-1273 than with BNT162b2. This pattern was consistent across periods marked by alpha- and delta-variant predominance. (Funded by the Department of Veterans Affairs and others.).


Subject(s)
COVID-19/prevention & control , /statistics & numerical data , Adult , Aged , Aged, 80 and over , COVID-19/epidemiology , COVID-19/mortality , Female , Hospitalization/statistics & numerical data , Humans , Incidence , Intensive Care Units , Male , Middle Aged , Risk Factors , United States/epidemiology , Veterans
3.
Am J Epidemiol ; 190(11): 2405-2419, 2021 11 02.
Article in English | MEDLINE | ID: covidwho-1493668

ABSTRACT

Hydroxychloroquine (HCQ) was proposed as an early therapy for coronavirus disease 2019 (COVID-19) after in vitro studies indicated possible benefit. Previous in vivo observational studies have presented conflicting results, though recent randomized clinical trials have reported no benefit from HCQ among patients hospitalized with COVID-19. We examined the effects of HCQ alone and in combination with azithromycin in a hospitalized population of US veterans with COVID-19, using a propensity score-adjusted survival analysis with imputation of missing data. According to electronic health record data from the US Department of Veterans Affairs health care system, 64,055 US Veterans were tested for the virus that causes COVID-19 between March 1, 2020 and April 30, 2020. Of the 7,193 veterans who tested positive, 2,809 were hospitalized, and 657 individuals were prescribed HCQ within the first 48-hours of hospitalization for the treatment of COVID-19. There was no apparent benefit associated with HCQ receipt, alone or in combination with azithromycin, and there was an increased risk of intubation when HCQ was used in combination with azithromycin (hazard ratio = 1.55; 95% confidence interval: 1.07, 2.24). In conclusion, we assessed the effectiveness of HCQ with or without azithromycin in treatment of patients hospitalized with COVID-19, using a national sample of the US veteran population. Using rigorous study design and analytic methods to reduce confounding and bias, we found no evidence of a survival benefit from the administration of HCQ.


Subject(s)
Anti-Bacterial Agents/therapeutic use , Azithromycin/therapeutic use , COVID-19/drug therapy , Hospitalization/statistics & numerical data , Hydroxychloroquine/therapeutic use , Veterans/statistics & numerical data , Aged , Aged, 80 and over , Anti-Bacterial Agents/adverse effects , Azithromycin/adverse effects , COVID-19/mortality , Drug Therapy, Combination , Female , Humans , Hydroxychloroquine/adverse effects , Intention to Treat Analysis , Machine Learning , Male , Middle Aged , Pharmacoepidemiology , Retrospective Studies , SARS-CoV-2 , Treatment Outcome , United States/epidemiology
4.
J Infect Dis ; 224(6): 967-975, 2021 09 17.
Article in English | MEDLINE | ID: covidwho-1429245

ABSTRACT

BACKGROUND: Early convalescent plasma transfusion may reduce mortality in patients with nonsevere coronavirus disease 2019 (COVID-19). METHODS: This study emulates a (hypothetical) target trial using observational data from a cohort of US veterans admitted to a Department of Veterans Affairs (VA) facility between 1 May and 17 November 2020 with nonsevere COVID-19. The intervention was convalescent plasma initiated within 2 days of eligibility. Thirty-day mortality was compared using cumulative incidence curves, risk differences, and hazard ratios estimated from pooled logistic models with inverse probability weighting to adjust for confounding. RESULTS: Of 11 269 eligible person-trials contributed by 4755 patients, 402 trials were assigned to the convalescent plasma group. Forty and 671 deaths occurred within the plasma and nonplasma groups, respectively. The estimated 30-day mortality risk was 6.5% (95% confidence interval [CI], 4.0%-9.7%) in the plasma group and 6.2% (95% CI, 5.6%-7.0%) in the nonplasma group. The associated risk difference was 0.30% (95% CI, -2.30% to 3.60%) and the hazard ratio was 1.04 (95% CI, .64-1.62). CONCLUSIONS: Our target trial emulation estimated no meaningful differences in 30-day mortality between nonsevere COVID-19 patients treated and untreated with convalescent plasma. Clinical Trials Registration. NCT04545047.


Subject(s)
Blood Component Transfusion , COVID-19/mortality , COVID-19/therapy , Immunization, Passive , Plasma , Adult , Aged , Aged, 80 and over , Female , Hospitalization , Humans , Male , Middle Aged , Treatment Outcome , United States/epidemiology , Veterans , Young Adult
5.
Am J Epidemiol ; 190(11): 2405-2419, 2021 11 02.
Article in English | MEDLINE | ID: covidwho-1393147

ABSTRACT

Hydroxychloroquine (HCQ) was proposed as an early therapy for coronavirus disease 2019 (COVID-19) after in vitro studies indicated possible benefit. Previous in vivo observational studies have presented conflicting results, though recent randomized clinical trials have reported no benefit from HCQ among patients hospitalized with COVID-19. We examined the effects of HCQ alone and in combination with azithromycin in a hospitalized population of US veterans with COVID-19, using a propensity score-adjusted survival analysis with imputation of missing data. According to electronic health record data from the US Department of Veterans Affairs health care system, 64,055 US Veterans were tested for the virus that causes COVID-19 between March 1, 2020 and April 30, 2020. Of the 7,193 veterans who tested positive, 2,809 were hospitalized, and 657 individuals were prescribed HCQ within the first 48-hours of hospitalization for the treatment of COVID-19. There was no apparent benefit associated with HCQ receipt, alone or in combination with azithromycin, and there was an increased risk of intubation when HCQ was used in combination with azithromycin (hazard ratio = 1.55; 95% confidence interval: 1.07, 2.24). In conclusion, we assessed the effectiveness of HCQ with or without azithromycin in treatment of patients hospitalized with COVID-19, using a national sample of the US veteran population. Using rigorous study design and analytic methods to reduce confounding and bias, we found no evidence of a survival benefit from the administration of HCQ.


Subject(s)
Anti-Bacterial Agents/therapeutic use , Azithromycin/therapeutic use , COVID-19/drug therapy , Hospitalization/statistics & numerical data , Hydroxychloroquine/therapeutic use , Veterans/statistics & numerical data , Aged , Aged, 80 and over , Anti-Bacterial Agents/adverse effects , Azithromycin/adverse effects , COVID-19/mortality , Drug Therapy, Combination , Female , Humans , Hydroxychloroquine/adverse effects , Intention to Treat Analysis , Machine Learning , Male , Middle Aged , Pharmacoepidemiology , Retrospective Studies , SARS-CoV-2 , Treatment Outcome , United States/epidemiology
6.
PLoS One ; 16(5): e0251651, 2021.
Article in English | MEDLINE | ID: covidwho-1226903

ABSTRACT

BACKGROUND: The risk factors associated with the stages of Coronavirus Disease-2019 (COVID-19) disease progression are not well known. We aim to identify risk factors specific to each state of COVID-19 progression from SARS-CoV-2 infection through death. METHODS AND RESULTS: We included 648,202 participants from the Veteran Affairs Million Veteran Program (2011-). We identified characteristics and 1,809 ICD code-based phenotypes from the electronic health record. We used logistic regression to examine the association of age, sex, body mass index (BMI), race, and prevalent phenotypes to the stages of COVID-19 disease progression: infection, hospitalization, intensive care unit (ICU) admission, and 30-day mortality (separate models for each). Models were adjusted for age, sex, race, ethnicity, number of visit months and ICD codes, state infection rate and controlled for multiple testing using false discovery rate (≤0.1). As of August 10, 2020, 5,929 individuals were SARS-CoV-2 positive and among those, 1,463 (25%) were hospitalized, 579 (10%) were in ICU, and 398 (7%) died. We observed a lower risk in women vs. men for ICU and mortality (Odds Ratio (95% CI): 0.48 (0.30-0.76) and 0.59 (0.31-1.15), respectively) and a higher risk in Black vs. Other race patients for hospitalization and ICU (OR (95%CI): 1.53 (1.32-1.77) and 1.63 (1.32-2.02), respectively). We observed an increased risk of all COVID-19 disease states with older age and BMI ≥35 vs. 20-24 kg/m2. Renal failure, respiratory failure, morbid obesity, acid-base balance disorder, white blood cell diseases, hydronephrosis and bacterial infections were associated with an increased risk of ICU admissions; sepsis, chronic skin ulcers, acid-base balance disorder and acidosis were associated with mortality. CONCLUSIONS: Older age, higher BMI, males and patients with a history of respiratory, kidney, bacterial or metabolic comorbidities experienced greater COVID-19 severity. Future studies to investigate the underlying mechanisms associated with these phenotype clusters and COVID-19 are warranted.


Subject(s)
COVID-19/epidemiology , Veterans Health , Age Factors , Aged , Aged, 80 and over , Body Mass Index , COVID-19/mortality , Disease Progression , Female , Hospitalization , Humans , Intensive Care Units , Longitudinal Studies , Male , Middle Aged , Risk Factors , SARS-CoV-2/isolation & purification , Sex Factors , United States/epidemiology , Veterans
7.
Nat Med ; 27(4): 668-676, 2021 04.
Article in English | MEDLINE | ID: covidwho-1174686

ABSTRACT

Drug repurposing provides a rapid approach to meet the urgent need for therapeutics to address COVID-19. To identify therapeutic targets relevant to COVID-19, we conducted Mendelian randomization analyses, deriving genetic instruments based on transcriptomic and proteomic data for 1,263 actionable proteins that are targeted by approved drugs or in clinical phase of drug development. Using summary statistics from the Host Genetics Initiative and the Million Veteran Program, we studied 7,554 patients hospitalized with COVID-19 and >1 million controls. We found significant Mendelian randomization results for three proteins (ACE2, P = 1.6 × 10-6; IFNAR2, P = 9.8 × 10-11 and IL-10RB, P = 2.3 × 10-14) using cis-expression quantitative trait loci genetic instruments that also had strong evidence for colocalization with COVID-19 hospitalization. To disentangle the shared expression quantitative trait loci signal for IL10RB and IFNAR2, we conducted phenome-wide association scans and pathway enrichment analysis, which suggested that IFNAR2 is more likely to play a role in COVID-19 hospitalization. Our findings prioritize trials of drugs targeting IFNAR2 and ACE2 for early management of COVID-19.


Subject(s)
COVID-19/genetics , Drug Repositioning , Mendelian Randomization Analysis/methods , SARS-CoV-2 , Angiotensin-Converting Enzyme 2/genetics , Angiotensin-Converting Enzyme 2/physiology , COVID-19/drug therapy , Genome-Wide Association Study , Humans , Interleukin-10 Receptor beta Subunit/genetics , Interleukin-10 Receptor beta Subunit/physiology , Quantitative Trait Loci , Receptor, Interferon alpha-beta/genetics , Receptor, Interferon alpha-beta/physiology
9.
PLoS One ; 15(11): e0241825, 2020.
Article in English | MEDLINE | ID: covidwho-919031

ABSTRACT

BACKGROUND: Available COVID-19 mortality indices are limited to acute inpatient data. Using nationwide medical administrative data available prior to SARS-CoV-2 infection from the US Veterans Health Administration (VA), we developed the VA COVID-19 (VACO) 30-day mortality index and validated the index in two independent, prospective samples. METHODS AND FINDINGS: We reviewed SARS-CoV-2 testing results within the VA between February 8 and August 18, 2020. The sample was split into a development cohort (test positive between March 2 and April 15, 2020), an early validation cohort (test positive between April 16 and May 18, 2020), and a late validation cohort (test positive between May 19 and July 19, 2020). Our logistic regression model in the development cohort considered demographics (age, sex, race/ethnicity), and pre-existing medical conditions and the Charlson Comorbidity Index (CCI) derived from ICD-10 diagnosis codes. Weights were fixed to create the VACO Index that was then validated by comparing area under receiver operating characteristic curves (AUC) in the early and late validation cohorts and among important validation cohort subgroups defined by sex, race/ethnicity, and geographic region. We also evaluated calibration curves and the range of predictions generated within age categories. 13,323 individuals tested positive for SARS-CoV-2 (median age: 63 years; 91% male; 42% non-Hispanic Black). We observed 480/3,681 (13%) deaths in development, 253/2,151 (12%) deaths in the early validation cohort, and 403/7,491 (5%) deaths in the late validation cohort. Age, multimorbidity described with CCI, and a history of myocardial infarction or peripheral vascular disease were independently associated with mortality-no other individual comorbid diagnosis provided additional information. The VACO Index discriminated mortality in development (AUC = 0.79, 95% CI: 0.77-0.81), and in early (AUC = 0.81 95% CI: 0.78-0.83) and late (AUC = 0.84, 95% CI: 0.78-0.86) validation. The VACO Index allows personalized estimates of 30-day mortality after COVID-19 infection. For example, among those aged 60-64 years, overall mortality was estimated at 9% (95% CI: 6-11%). The Index further discriminated risk in this age stratum from 4% (95% CI: 3-7%) to 21% (95% CI: 12-31%), depending on sex and comorbid disease. CONCLUSION: Prior to infection, demographics and comorbid conditions can discriminate COVID-19 mortality risk overall and within age strata. The VACO Index reproducibly identified individuals at substantial risk of COVID-19 mortality who might consider continuing social distancing, despite relaxed state and local guidelines.


Subject(s)
Coronavirus Infections/mortality , Pneumonia, Viral/mortality , Adult , Age Factors , Aged , Aged, 80 and over , Area Under Curve , Betacoronavirus/isolation & purification , COVID-19 , Comorbidity , Coronavirus Infections/pathology , Coronavirus Infections/virology , Databases, Factual , Female , Humans , Logistic Models , Male , Middle Aged , Pandemics , Pneumonia, Viral/pathology , Pneumonia, Viral/virology , ROC Curve , Risk Factors , SARS-CoV-2 , Veterans Health , Young Adult
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