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1.
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
3.
J Med Internet Res ; 23(10): e31400, 2021 10 11.
Article in English | MEDLINE | ID: covidwho-1463405

ABSTRACT

BACKGROUND: Many countries have experienced 2 predominant waves of COVID-19-related hospitalizations. Comparing the clinical trajectories of patients hospitalized in separate waves of the pandemic enables further understanding of the evolving epidemiology, pathophysiology, and health care dynamics of the COVID-19 pandemic. OBJECTIVE: In this retrospective cohort study, we analyzed electronic health record (EHR) data from patients with SARS-CoV-2 infections hospitalized in participating health care systems representing 315 hospitals across 6 countries. We compared hospitalization rates, severe COVID-19 risk, and mean laboratory values between patients hospitalized during the first and second waves of the pandemic. METHODS: Using a federated approach, each participating health care system extracted patient-level clinical data on their first and second wave cohorts and submitted aggregated data to the central site. Data quality control steps were adopted at the central site to correct for implausible values and harmonize units. Statistical analyses were performed by computing individual health care system effect sizes and synthesizing these using random effect meta-analyses to account for heterogeneity. We focused the laboratory analysis on C-reactive protein (CRP), ferritin, fibrinogen, procalcitonin, D-dimer, and creatinine based on their reported associations with severe COVID-19. RESULTS: Data were available for 79,613 patients, of which 32,467 were hospitalized in the first wave and 47,146 in the second wave. The prevalence of male patients and patients aged 50 to 69 years decreased significantly between the first and second waves. Patients hospitalized in the second wave had a 9.9% reduction in the risk of severe COVID-19 compared to patients hospitalized in the first wave (95% CI 8.5%-11.3%). Demographic subgroup analyses indicated that patients aged 26 to 49 years and 50 to 69 years; male and female patients; and black patients had significantly lower risk for severe disease in the second wave than in the first wave. At admission, the mean values of CRP were significantly lower in the second wave than in the first wave. On the seventh hospital day, the mean values of CRP, ferritin, fibrinogen, and procalcitonin were significantly lower in the second wave than in the first wave. In general, countries exhibited variable changes in laboratory testing rates from the first to the second wave. At admission, there was a significantly higher testing rate for D-dimer in France, Germany, and Spain. CONCLUSIONS: Patients hospitalized in the second wave were at significantly lower risk for severe COVID-19. This corresponded to mean laboratory values in the second wave that were more likely to be in typical physiological ranges on the seventh hospital day compared to the first wave. Our federated approach demonstrated the feasibility and power of harmonizing heterogeneous EHR data from multiple international health care systems to rapidly conduct large-scale studies to characterize how COVID-19 clinical trajectories evolve.


Subject(s)
COVID-19 , Pandemics , Adult , Aged , Female , Hospitalization , Hospitals , Humans , Male , Middle Aged , Retrospective Studies , SARS-CoV-2
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.
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
6.
PLoS One ; 16(3): e0248128, 2021.
Article in English | MEDLINE | ID: covidwho-1138582

ABSTRACT

BACKGROUND: The COVID-19 pandemic remains a significant global threat. However, despite urgent need, there remains uncertainty surrounding best practices for pharmaceutical interventions to treat COVID-19. In particular, conflicting evidence has emerged surrounding the use of hydroxychloroquine and azithromycin, alone or in combination, for COVID-19. The COVID-19 Evidence Accelerator convened by the Reagan-Udall Foundation for the FDA, in collaboration with Friends of Cancer Research, assembled experts from the health systems research, regulatory science, data science, and epidemiology to participate in a large parallel analysis of different data sets to further explore the effectiveness of these treatments. METHODS: Electronic health record (EHR) and claims data were extracted from seven separate databases. Parallel analyses were undertaken on data extracted from each source. Each analysis examined time to mortality in hospitalized patients treated with hydroxychloroquine, azithromycin, and the two in combination as compared to patients not treated with either drug. Cox proportional hazards models were used, and propensity score methods were undertaken to adjust for confounding. Frequencies of adverse events in each treatment group were also examined. RESULTS: Neither hydroxychloroquine nor azithromycin, alone or in combination, were significantly associated with time to mortality among hospitalized COVID-19 patients. No treatment groups appeared to have an elevated risk of adverse events. CONCLUSION: Administration of hydroxychloroquine, azithromycin, and their combination appeared to have no effect on time to mortality in hospitalized COVID-19 patients. Continued research is needed to clarify best practices surrounding treatment of COVID-19.


Subject(s)
Antiviral Agents/therapeutic use , Azithromycin/therapeutic use , COVID-19/drug therapy , Hydroxychloroquine/therapeutic use , Pandemics/prevention & control , Data Management/methods , Drug Therapy, Combination/methods , Female , Hospitalization , Humans , Male , SARS-CoV-2/drug effects
7.
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 , Ethnic Groups , 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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