Bridging information gaps in menopause status classification through natural language processing

Objective

To use natural language processing (NLP) of clinical notes to augment existing structured electronic health record (EHR) data for classification of a patient's menopausal status.

Materials and methods

A rule-based NLP system was designed to capture evidence of a patient's menopause status including dates of a patient's last menstrual period, reproductive surgeries, and postmenopause diagnosis as well as their use of birth control and menstrual interruptions. NLP-derived output was used in combination with structured EHR data to classify a patient's menopausal status. NLP processing and patient classification were performed on a cohort of 307 512 female Veterans receiving healthcare at the US Department of Veterans Affairs (VA).

Results

NLP was validated at 99.6% precision. Including the NLP-derived data into a menopause phenotype increased the number of patients with data relevant to their menopausal status by 118%. Using structured codes alone, 81 173 (27.0%) are able to be classified as postmenopausal or premenopausal. However, with the inclusion of NLP, this number increased 167 804 (54.6%) patients. The premenopausal category grew by 532.7% with the inclusion of NLP data.

Discussion

By employing NLP, it became possible to identify documented data elements that predate VA care, originate outside VA networks, or have no corresponding structured field in the VA EHR that would be otherwise inaccessible for further analysis.

Conclusion

NLP can be used to identify concepts relevant to a patient's menopausal status in clinical notes. Adding NLP-derived data to an algorithm classifying a patient's menopausal status significantly increases the number of patients classified using EHR data, ultimately enabling more detailed assessments of the impact of menopause on health outcomes.

Racial Disparities in Uterine Fibroid Treatment Among Veterans Using VA Health Care

INTRODUCTION

Uterine fibroids are common, nonmalignant tumors that disproportionately impact Black patients. We aimed to examine Black and White differences in receipt of any treatment and type of first treatment in the Department of Veterans Affairs, including effect modification by severity as approximated by anemia.

METHODS

We used Department of Veterans Affairs administrative data to identify 5,041 Black and 3,206 White veterans with symptomatic uterine fibroids, identified by International Classification of Diseases, 9th edition, Clinical Modification, codes, between fiscal year 2010 and fiscal year 2012 and followed in the administrative data through fiscal year 2018 for outcomes. Outcomes included receipt of any treatment, hysterectomy as first treatment, and fertility-sparing treatment as first treatment. We stratified all analyses by age (<45, ≥45 years old), used generalized linear models with a log link and Poisson error distribution, included an interaction term between race and anemia, and used recycled predictions to estimate adjusted percentages for outcomes.

RESULTS

There was evidence of effect modification by anemia for receipt of any treatment but not for any other outcomes. Across age and anemia sub-groups, Black veterans were less likely to receive any treatment than White veterans. Adjusted racial differences were most pronounced among veterans with anemia (<45 years, Black-White difference = -10.3 percentage points; 95% confidence interval, -15.9 to -4.7; ≥45 years, Black-White difference = -20.3 percentage points; 95% confidence interval, -27.8 to -12.7). Across age groups, Black veterans were less likely than White veterans to have hysterectomy and more likely to have a fertility-sparing treatment as their first treatment.

CONCLUSIONS

We identified significant Black-White disparities in receipt of treatment for symptomatic uterine fibroids. Additional research that centers the experiences of Black veterans with uterine fibroids is needed to inform strategies to eliminate racial disparities in uterine fibroid care.

Reproducible variability: assessing investigator discordance across 9 research teams attempting to reproduce the same observational study

OBJECTIVE

Observational studies can impact patient care but must be robust and reproducible. Nonreproducibility is primarily caused by unclear reporting of design choices and analytic procedures. This study aimed to: (1) assess how the study logic described in an observational study could be interpreted by independent researchers and (2) quantify the impact of interpretations' variability on patient characteristics.

MATERIALS AND METHODS

Nine teams of highly qualified researchers reproduced a cohort from a study by Albogami et al. The teams were provided the clinical codes and access to the tools to create cohort definitions such that the only variable part was their logic choices. We executed teams' cohort definitions against the database and compared the number of subjects, patient overlap, and patient characteristics.

RESULTS

On average, the teams' interpretations fully aligned with the master implementation in 4 out of 10 inclusion criteria with at least 4 deviations per team. Cohorts' size varied from one-third of the master cohort size to 10 times the cohort size (2159-63 619 subjects compared to 6196 subjects). Median agreement was 9.4% (interquartile range 15.3-16.2%). The teams' cohorts significantly differed from the master implementation by at least 2 baseline characteristics, and most of the teams differed by at least 5.

CONCLUSIONS

Independent research teams attempting to reproduce the study based on its free-text description alone produce different implementations that vary in the population size and composition. Sharing analytical code supported by a common data model and open-source tools allows reproducing a study unambiguously thereby preserving initial design choices.

Causes of alcohol-attributable death and associated years of potential life lost among LGB and non-LGB veteran men and women in Veterans Health Administration

BACKGROUND

Alcohol use is a significant concern nationally and research now highlights higher rates of alcohol attributable death (AAD) and years of potential life lost (YPLL) among lesbian, gay, and bisexual (LGB) veterans compared to non-LGB veterans. In this study, we examined specific causes of AAD and associated YPLL between LGB and non-LGB veteran men and women to highlight needed outreach, prevention, and treatment strategies.

METHODS

Using data from the nationwide Veterans Health Administration electronic health record and National Death Index from 2014 to 2018, we examined the top ten ranked causes of AAD among LGB (n = 102,085) and non-LGB veteran (n = 5,300,521) men and women, as well as associated YPLL per AAD.

RESULTS

We observed higher rates of AAD among men than women, but higher rates among LGB veterans relative to their same-sex non-LGB counterparts. We noted greater YPLL per AAD among LGB men and all women compared to non-LGB men, even when of similar or same rank in cause of death. Acute-cause AAD death (e.g., alcohol-related suicide, poisonings) was ranked higher among LGB men and all women. YPLL was greater for both acute- and chronic-cause AAD (e.g., liver disease) among LGB men and all women compared to non-LGB men.

CONCLUSIONS

Causes of AAD differ between LGB and non-LGB men and women. The differences observed highlight disparities in acute- and chronic-cause AAD between groups help explain the higher number of YPLL per AAD that disfavor LGB men and women veterans, and essential next steps in primary and secondary prevention of hazardous drinking and mortality risk.

A MUC5B Gene Polymorphism, rs35705950-T, Confers Protective Effects Against COVID-19 Hospitalization but Not Severe Disease or Mortality

Rationale: A common MUC5B gene polymorphism, rs35705950-T, is associated with idiopathic pulmonary fibrosis (IPF), but its role in severe acute respiratory syndrome coronavirus 2 infection and disease severity is unclear. Objectives: To assess whether rs35705950-T confers differential risk for clinical outcomes associated with coronavirus disease (COVID-19) infection among participants in the Million Veteran Program (MVP). Methods: The MUC5B rs35705950-T allele was directly genotyped among MVP participants; clinical events and comorbidities were extracted from the electronic health records. Associations between the incidence or severity of COVID-19 and rs35705950-T were analyzed within each ancestry group in the MVP followed by transancestry meta-analysis. Replication and joint meta-analysis were conducted using summary statistics from the COVID-19 Host Genetics Initiative (HGI). Sensitivity analyses with adjustment for additional covariates (body mass index, Charlson comorbidity index, smoking, asbestosis, rheumatoid arthritis with interstitial lung disease, and IPF) and associations with post-COVID-19 pneumonia were performed in MVP subjects. Measurements and Main Results: The rs35705950-T allele was associated with fewer COVID-19 hospitalizations in transancestry meta-analyses within the MVP (N_cases = 4,325; N_controls = 507,640; OR = 0.89 [0.82-0.97]; P = 6.86 × 10^-3) and joint meta-analyses with the HGI (N_cases = 13,320; N_controls = 1,508,841; OR, 0.90 [0.86-0.95]; P = 8.99 × 10^-5). The rs35705950-T allele was not associated with reduced COVID-19 positivity in transancestry meta-analysis within the MVP (N_cases = 19,168/N_controls = 492,854; OR, 0.98 [0.95-1.01]; P = 0.06) but was nominally significant (P < 0.05) in the joint meta-analysis with the HGI (N_cases = 44,820; N_controls = 1,775,827; OR, 0.97 [0.95-1.00]; P = 0.03). Associations were not observed with severe outcomes or mortality. Among individuals of European ancestry in the MVP, rs35705950-T was associated with fewer post-COVID-19 pneumonia events (OR, 0.82 [0.72-0.93]; P = 0.001). Conclusions: The MUC5B variant rs35705950-T may confer protection in COVID-19 hospitalizations.

Sleep disturbance and suicide risk among sexual and gender minority people

Sleep disturbance has emerged as an independent, mechanistic, and modifiable risk factor for suicide. Sexual and gender minority (SGM) people disproportionately experience sleep disturbance and are at higher risk of death by suicide relative to cisgender and/or heterosexual individuals. The present narrative review evaluates nascent research related to sleep disturbance and suicide-related thoughts and behaviors (STBs) among SGM populations, and discusses how experiences of minority stress may explain heightened risk among SGM people. Although there is a growing understanding of the link between sleep disturbance and STBs, most research has not been conducted in SGM populations or has not examined suicide as an outcome. Research is needed to examine whether and how aspects of sleep disturbances relate to STBs among SGM people in order to better tailor sleep treatments for SGM populations.

Alcohol-attributable deaths and years of potential life lost due to alcohol among veterans: Overall and between persons with minoritized and non-minoritized sexual orientations

BACKGROUND

Unhealthy alcohol use is disproportionally experienced by individuals with minoritized sexual orientations. Unlike the general US population, for whom the burden of alcohol as it relates to mortality is consistently monitored across time with national survey data, the impact of unhealthy alcohol use among veterans with minoritized sexual orientations, for whom addressing substance use is a national priority, is largely unknown.

METHODS

Using Alcohol Use Disorders Identification Test Consumption data from the Department of Veterans Affairs electronic health record and underlying cause of death from National Death Index from 2014 to 2018 we quantified alcohol consumption and related mortality among veterans with (n = 102,085) and without minoritized sexual orientations (n = 5300,521). Age adjusted rates of alcohol attributed deaths (AAD) per 100,000 persons and years of potential life lost (YPLL) were estimated by sexual orientation, sex, and sexual orientation stratified by sex.

RESULTS

Alcohol attributable deaths (n = 21,861) were higher among veterans with minoritized sexual orientations than veterans without after adjustment for age (486.5 deaths/100,000 versus 309.7 deaths/100,000, respectively). Veterans with minoritized sexual orientations also experienced more YPLL (13,772.8 years/100,000 versus 7618.9 years/100,000). Years of potential life lost per AAD was higher in women (33.2 years) than men (18.7 years).

CONCLUSIONS

Alcohol consumption results in substantial disability and death among veterans, particularly veterans with minoritized sexual orientations. Findings suggest need for increased alcohol-related services for all VA patients, and potential targeted approaches to for veterans with minoritized sexual orientations and women to offset risk for, and years of potential life lost from, alcohol attributable death.

Association of Kidney Comorbidities and Acute Kidney Failure With Unfavorable Outcomes After COVID-19 in Individuals With the Sickle Cell Trait

Importance

Sickle cell trait (SCT), defined as the presence of 1 hemoglobin beta sickle allele (rs334-T) and 1 normal beta allele, is prevalent in millions of people in the US, particularly in individuals of African and Hispanic ancestry. However, the association of SCT with COVID-19 is unclear.

Objective

To assess the association of SCT with the prepandemic health conditions in participants of the Million Veteran Program (MVP) and to assess the severity and sequelae of COVID-19.

Design, Setting, and Participants

COVID-19 clinical data include 2729 persons with SCT, of whom 353 had COVID-19, and 129 848 SCT-negative individuals, of whom 13 488 had COVID-19. Associations between SCT and COVID-19 outcomes were examined using firth regression. Analyses were performed by ancestry and adjusted for sex, age, age squared, and ancestral principal components to account for population stratification. Data for the study were collected between March 2020 and February 2021.

Exposures

The hemoglobin beta S (HbS) allele (rs334-T).

Main Outcomes and Measures

This study evaluated 4 COVID-19 outcomes derived from the World Health Organization severity scale and phenotypes derived from International Classification of Diseases codes in the electronic health records.

Results

Of the 132 577 MVP participants with COVID-19 data, mean (SD) age at the index date was 64.8 (13.1) years. Sickle cell trait was present in 7.8% of individuals of African ancestry and associated with a history of chronic kidney disease, diabetic kidney disease, hypertensive kidney disease, pulmonary embolism, and cerebrovascular disease. Among the 4 clinical outcomes of COVID-19, SCT was associated with an increased COVID-19 mortality in individuals of African ancestry (n = 3749; odds ratio, 1.77; 95% CI, 1.13 to 2.77; P = .01). In the 60 days following COVID-19, SCT was associated with an increased incidence of acute kidney failure. A counterfactual mediation framework estimated that on average, 20.7% (95% CI, -3.8% to 56.0%) of the total effect of SCT on COVID-19 fatalities was due to acute kidney failure.

Conclusions and Relevance

In this genetic association study, SCT was associated with preexisting kidney comorbidities, increased COVID-19 mortality, and kidney morbidity.

Sexual Health Assessment Is Vital to Whole Health Models of Care

Sexual health is the state of well-being regarding sexuality. Sexual health is highly valued and associated with overall health. Overall health and well-being are more than the absence of disease or dysfunction. Health care systems adopting whole health models of care need to incorporate a holistic assessment of sexual health. This includes assessing patients' sexual orientation and gender identity (SOGI). If health systems, including but not limited to the Veterans Health Administration (VHA), incorporate sexual health into whole health they could enhance preventive care, promote healthy sexual functioning, and optimize overall health and well-being. Assessing sexual health can give providers important information about a patient's health, well-being, and health goals. Sexual concerns or dysfunction may also signal undiagnosed health conditions. Additionally, collecting SOGI information as part of a sexual health assessment would allow providers to address problems that drive disparities for lesbian, gay, bisexual, transgender, queer, and similar minority (LGBTQ+) populations. Health care providers do not routinely assess sexual health in clinical practice. One barrier is a gap in communication between patients and providers. Providers cite beliefs that patients will bring up sexual concerns themselves or might be offended by discussing sexual health. Patients often report an expectation that providers will bring up sexual health and being comfortable discussing sexual health with their providers. Within the VHA, the lack of a sexual health template within the electronic health record (EHR) adds an additional barrier. The VHA's transition toward whole health and updates to its EHR provide unique opportunities to integrate sexual health assessment into routine care. We highlight system modifications to address this within the VHA. These examples may be helpful for other health care systems interested in moving toward whole health. It will be vital for health care systems integrating a whole health approach to develop both practical and educational interventions to address the communication gap. These interventions will need to target both providers and patients in health care systems that transition to a whole health model of care, not just the VHA. Both the communication gap between providers and patients, and the lack of support within some EHR systems for sexual health assessment are barriers to assessing sexual health in primary care clinics. Routine sexual health assessment would benefit patient well-being and present an opportunity to address health disparities for LGBTQ+ populations. Health care systems (ie, both the VHA and other systems) can overcome these barriers by implementing educational interventions and updating their EHRs and back-end data structures. VHA's expertise in developing and implementing health education interventions and EHR-based quality improvements may help inform interventions beyond VHA.

International comparisons of laboratory values from the 4CE collaborative to predict COVID-19 mortality

Given the growing number of prediction algorithms developed to predict COVID-19 mortality, we evaluated the transportability of a mortality prediction algorithm using a multi-national network of healthcare systems. We predicted COVID-19 mortality using baseline commonly measured laboratory values and standard demographic and clinical covariates across healthcare systems, countries, and continents. Specifically, we trained a Cox regression model with nine measured laboratory test values, standard demographics at admission, and comorbidity burden pre-admission. These models were compared at site, country, and continent level. Of the 39,969 hospitalized patients with COVID-19 (68.6% male), 5717 (14.3%) died. In the Cox model, age, albumin, AST, creatine, CRP, and white blood cell count are most predictive of mortality. The baseline covariates are more predictive of mortality during the early days of COVID-19 hospitalization. Models trained at healthcare systems with larger cohort size largely retain good transportability performance when porting to different sites. The combination of routine laboratory test values at admission along with basic demographic features can predict mortality in patients hospitalized with COVID-19. Importantly, this potentially deployable model differs from prior work by demonstrating not only consistent performance but also reliable transportability across healthcare systems in the US and Europe, highlighting the generalizability of this model and the overall approach.

Using electronic health records to streamline provider recruitment for implementation science studies

Background

Healthcare providers are often targeted as research participants, especially for implementation science studies evaluating provider- or system-level issues. Frequently, provider eligibility is based on both provider and patient factors. Manual chart review and self-report are common provider screening strategies but require substantial time, effort, and resources. The automated use of electronic health record (EHR) data may streamline provider identification for implementation science research. Here, we describe an approach to provider screening for a Veterans Health Administration (VHA)-funded study focused on implementing risk-aligned surveillance for bladder cancer patients.

Methods

Our goal was to identify providers at 6 pre-specified facilities who performed ≥10 surveillance cystoscopy procedures among bladder cancer patients in the 12 months prior to recruitment start on January 16, 2020, and who were currently practicing at 1 of 6 pre-specified facilities. Using VHA EHR data (using CPT, ICD10 procedure, and ICD10 diagnosis codes), we identified cystoscopy procedures performed after an initial bladder cancer diagnosis (i.e., surveillance procedures). Procedures were linked to VHA staff data to determine the provider of record, the number of cystoscopies they performed, and their current location of practice. To validate this approach, we performed a chart review of 105 procedures performed by a random sample of identified providers. The proportion of correctly identified procedures was calculated (Positive Predictive Value (PPV)), along with binomial 95% confidence intervals (CI).

Findings

We identified 1,917,856 cystoscopies performed on 703,324 patients from October 1, 1999—January 16, 2020, across the nationwide VHA. Of those procedures, 40% were done on patients who had a prior record of bladder cancer and were completed by 15,065 distinct providers. Of those, 61 performed ≥ 10 procedures and were currently practicing at 1 of the 6 facilities of interest in the 1 year prior to study recruitment. The random chart review of 7 providers found 101 of 105 procedures (PPV: 96%; 95% CI: 91% to 99%) were surveillance procedures and were performed by the selected provider on the recorded date.

Implications

These results show that EHR data can be used for accurate identification of healthcare providers as research participants when inclusion criteria consist of both patient- (temporal relationship between diagnosis and procedure) and provider-level (frequency of procedure and location of current practice) factors. As administrative codes and provider identifiers are collected in most, if not all, EHRs for billing purposes this approach can be translated from provider recruitment in VHA to other healthcare systems. Implementation studies should consider this method of screening providers.

Impact of Coronavirus Disease 2019 (COVID-19) Severity on Long-term Events in United States Veterans Using the Veterans Affairs Severity Index for COVID-19 (VASIC)

In this retrospective cohort study of 94 595 severe acute respiratory syndrome coronavirus 2-positive cases, we developed and validated an algorithm to assess the association between coronavirus disease 2019 (COVID-19) severity and long-term complications (stroke, myocardial infarction, pulmonary embolism/deep vein thrombosis, heart failure, and mortality). COVID-19 severity was associated with a greater risk of experiencing a long-term complication 31-120 days postinfection. Most incident events occurred 31-60 days postinfection and diminished after day 91, except heart failure for severe patients and death for moderate patients, which peaked on days 91-120. Understanding the differential impact of COVID-19 severity on long-term events provides insight into possible intervention modalities and critical prevention strategies.

Overall and sex-specific risk factors for subjective cognitive decline: findings from the 2015-2018 Behavioral Risk Factor Surveillance System Survey

BACKGROUND

Prior research indicates that at least 35% of Alzheimer's disease and related dementia risk may be amenable to prevention. Subjective cognitive decline is often the first indication of preclinical dementia, with the risk of subsequent Alzheimer's disease in such individuals being greater in women than men. We wished to understand how modifiable factors are associated with subjective cognitive decline, and whether differences exist by sex.

METHODS

Data were collected from men and women (45 years and older) who completed the U.S. Behavioral Risk Factor Surveillance System Cognitive Decline Module (2015-2018), n = 216,838. We calculated population-attributable fractions for subjective cognitive decline, stratified by sex, of the following factors: limited education, deafness, social isolation, depression, smoking, physical inactivity, obesity, hypertension, and diabetes. Our models were adjusted for age, race, income, employment, marital and Veteran status, and accounted for communality among risk factors.

RESULTS

The final study sample included more women (53.7%) than men, but both had a similar prevalence of subjective cognitive decline (10.6% of women versus 11.2% of men). Women and men had nearly equivalent overall population-attributable fractions to explain subjective cognitive decline (39.7% for women versus 41.3% for men). The top three contributing risk factors were social isolation, depression, and hypertension, which explained three-quarters of the overall population-attributable fraction.

CONCLUSIONS

While we did not identify any differences in modifiable factors between men and women contributing to subjective cognitive decline, other factors including reproductive or endocrinological health history or biological factors that interact with sex to modify risk warrant further research.

Unraveling COVID-19: A Large-Scale Characterization of 4.5 Million COVID-19 Cases Using CHARYBDIS

Purpose

Routinely collected real world data (RWD) have great utility in aiding the novel coronavirus disease (COVID-19) pandemic response. Here we present the international Observational Health Data Sciences and Informatics (OHDSI) Characterizing Health Associated Risks and Your Baseline Disease In SARS-COV-2 (CHARYBDIS) framework for standardisation and analysis of COVID-19 RWD.

Patients and Methods

We conducted a descriptive retrospective database study using a federated network of data partners in the United States, Europe (the Netherlands, Spain, the UK, Germany, France and Italy) and Asia (South Korea and China). The study protocol and analytical package were released on 11th June 2020 and are iteratively updated via GitHub. We identified three non-mutually exclusive cohorts of 4,537,153 individuals with a clinical COVID-19 diagnosis or positive test, 886,193 hospitalized with COVID-19, and 113,627 hospitalized with COVID-19 requiring intensive services.

Results

We aggregated over 22,000 unique characteristics describing patients with COVID-19. All comorbidities, symptoms, medications, and outcomes are described by cohort in aggregate counts and are readily available online. Globally, we observed similarities in the USA and Europe: more women diagnosed than men but more men hospitalized than women, most diagnosed cases between 25 and 60 years of age versus most hospitalized cases between 60 and 80 years of age. South Korea differed with more women than men hospitalized. Common comorbidities included type 2 diabetes, hypertension, chronic kidney disease and heart disease. Common presenting symptoms were dyspnea, cough and fever. Symptom data availability was more common in hospitalized cohorts than diagnosed.

Conclusion

We constructed a global, multi-centre view to describe trends in COVID-19 progression, management and evolution over time. By characterising baseline variability in patients and geography, our work provides critical context that may otherwise be misconstrued as data quality issues. This is important as we perform studies on adverse events of special interest in COVID-19 vaccine surveillance.

Seek COVER: using a disease proxy to rapidly develop and validate a personalized risk calculator for COVID-19 outcomes in an international network

Background

We investigated whether we could use influenza data to develop prediction models for COVID-19 to increase the speed at which prediction models can reliably be developed and validated early in a pandemic. We developed COVID-19 Estimated Risk (COVER) scores that quantify a patient’s risk of hospital admission with pneumonia (COVER-H), hospitalization with pneumonia requiring intensive services or death (COVER-I), or fatality (COVER-F) in the 30-days following COVID-19 diagnosis using historical data from patients with influenza or flu-like symptoms and tested this in COVID-19 patients.

Methods

We analyzed a federated network of electronic medical records and administrative claims data from 14 data sources and 6 countries containing data collected on or before 4/27/2020. We used a 2-step process to develop 3 scores using historical data from patients with influenza or flu-like symptoms any time prior to 2020. The first step was to create a data-driven model using LASSO regularized logistic regression, the covariates of which were used to develop aggregate covariates for the second step where the COVER scores were developed using a smaller set of features. These 3 COVER scores were then externally validated on patients with 1) influenza or flu-like symptoms and 2) confirmed or suspected COVID-19 diagnosis across 5 databases from South Korea, Spain, and the United States. Outcomes included i) hospitalization with pneumonia, ii) hospitalization with pneumonia requiring intensive services or death, and iii) death in the 30 days after index date.

Results

Overall, 44,507 COVID-19 patients were included for model validation. We identified 7 predictors (history of cancer, chronic obstructive pulmonary disease, diabetes, heart disease, hypertension, hyperlipidemia, kidney disease) which combined with age and sex discriminated which patients would experience any of our three outcomes. The models achieved good performance in influenza and COVID-19 cohorts. For COVID-19 the AUC ranges were, COVER-H: 0.69–0.81, COVER-I: 0.73–0.91, and COVER-F: 0.72–0.90. Calibration varied across the validations with some of the COVID-19 validations being less well calibrated than the influenza validations.

Conclusions

This research demonstrated the utility of using a proxy disease to develop a prediction model. The 3 COVER models with 9-predictors that were developed using influenza data perform well for COVID-19 patients for predicting hospitalization, intensive services, and fatality. The scores showed good discriminatory performance which transferred well to the COVID-19 population. There was some miscalibration in the COVID-19 validations, which is potentially due to the difference in symptom severity between the two diseases. A possible solution for this is to recalibrate the models in each location before use.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12874-022-01505-z.

Identifying Posttraumatic Stress Disorder and Disparity Among Transgender Veterans Using Nationwide Veterans Health Administration Electronic Health Record Data

Purpose: The prevalence of posttraumatic stress disorder (PTSD) and other psychiatric disorders is high among military veterans and even higher among transgender veterans. Prior prevalence estimates have become outdated, and novel methods of estimation have since been developed but not used to estimate PTSD prevalence among transgender veterans. This study provides updated estimates of PTSD prevalence among transgender and cisgender veterans. Methods: We examined Veterans Health Administration (VHA) medical record data from October 1, 1999 to April 1, 2021 for 9995 transgender veterans and 29,985 cisgender veteran comparisons (1:3). We matched on age group at first VHA health care visit, sex assigned at birth, and year of first VHA visit. We employed both probabilistic and rule-based algorithms to estimate the prevalence of PTSD for transgender and cisgender veterans. Results: The prevalence of PTSD was 1.5-1.8 times higher among transgender veterans. Descriptive data suggest that the prevalence of depression, schizophrenia, bipolar disorder, alcohol and non-alcohol substance use disorders, current/former smoking status, and military sexual trauma was also elevated among transgender veterans. Conclusion: The PTSD and overall psychiatric burden observed among transgender veterans was significantly higher than that of their cisgender peers, especially among recent users of VHA care. These PTSD findings are consistent with prior literature and minority stress theory, and they were robust across probabilistic and two rule-based methods employed in this study. As such, enhanced and careful screening, outreach, and evidence-based practices are recommended to help reduce this disparity among transgender veterans.

Characteristics and outcomes of patients with COVID-19 with and without prevalent hypertension: a multinational cohort study

OBJECTIVE

To characterise patients with and without prevalent hypertension and COVID-19 and to assess adverse outcomes in both inpatients and outpatients.

DESIGN AND SETTING

This is a retrospective cohort study using 15 healthcare databases (primary and secondary electronic healthcare records, insurance and national claims data) from the USA, Europe and South Korea, standardised to the Observational Medical Outcomes Partnership common data model. Data were gathered from 1 March to 31 October 2020.

PARTICIPANTS

Two non-mutually exclusive cohorts were defined: (1) individuals diagnosed with COVID-19 (diagnosed cohort) and (2) individuals hospitalised with COVID-19 (hospitalised cohort), and stratified by hypertension status. Follow-up was from COVID-19 diagnosis/hospitalisation to death, end of the study period or 30 days.

OUTCOMES

Demographics, comorbidities and 30-day outcomes (hospitalisation and death for the 'diagnosed' cohort and adverse events and death for the 'hospitalised' cohort) were reported.

RESULTS

We identified 2 851 035 diagnosed and 563 708 hospitalised patients with COVID-19. Hypertension was more prevalent in the latter (ranging across databases from 17.4% (95% CI 17.2 to 17.6) to 61.4% (95% CI 61.0 to 61.8) and from 25.6% (95% CI 24.6 to 26.6) to 85.9% (95% CI 85.2 to 86.6)). Patients in both cohorts with hypertension were predominantly >50 years old and female. Patients with hypertension were frequently diagnosed with obesity, heart disease, dyslipidaemia and diabetes. Compared with patients without hypertension, patients with hypertension in the COVID-19 diagnosed cohort had more hospitalisations (ranging from 1.3% (95% CI 0.4 to 2.2) to 41.1% (95% CI 39.5 to 42.7) vs from 1.4% (95% CI 0.9 to 1.9) to 15.9% (95% CI 14.9 to 16.9)) and increased mortality (ranging from 0.3% (95% CI 0.1 to 0.5) to 18.5% (95% CI 15.7 to 21.3) vs from 0.2% (95% CI 0.2 to 0.2) to 11.8% (95% CI 10.8 to 12.8)). Patients in the COVID-19 hospitalised cohort with hypertension were more likely to have acute respiratory distress syndrome (ranging from 0.1% (95% CI 0.0 to 0.2) to 65.6% (95% CI 62.5 to 68.7) vs from 0.1% (95% CI 0.0 to 0.2) to 54.7% (95% CI 50.5 to 58.9)), arrhythmia (ranging from 0.5% (95% CI 0.3 to 0.7) to 45.8% (95% CI 42.6 to 49.0) vs from 0.4% (95% CI 0.3 to 0.5) to 36.8% (95% CI 32.7 to 40.9)) and increased mortality (ranging from 1.8% (95% CI 0.4 to 3.2) to 25.1% (95% CI 23.0 to 27.2) vs from 0.7% (95% CI 0.5 to 0.9) to 10.9% (95% CI 10.4 to 11.4)) than patients without hypertension.

CONCLUSIONS

COVID-19 patients with hypertension were more likely to suffer severe outcomes, hospitalisations and deaths compared with those without hypertension.

Predictors of diagnostic transition from major depressive disorder to bipolar disorder: a retrospective observational network study

Many patients with bipolar disorder (BD) are initially misdiagnosed with major depressive disorder (MDD) and are treated with antidepressants, whose potential iatrogenic effects are widely discussed. It is unknown whether MDD is a comorbidity of BD or its earlier stage, and no consensus exists on individual conversion predictors, delaying BD's timely recognition and treatment. We aimed to build a predictive model of MDD to BD conversion and to validate it across a multi-national network of patient databases using the standardization afforded by the Observational Medical Outcomes Partnership (OMOP) common data model. Five "training" US databases were retrospectively analyzed: IBM MarketScan CCAE, MDCR, MDCD, Optum EHR, and Optum Claims. Cyclops regularized logistic regression models were developed on one-year MDD-BD conversion with all standard covariates from the HADES PatientLevelPrediction package. Time-to-conversion Kaplan-Meier analysis was performed up to a decade after MDD, stratified by model-estimated risk. External validation of the final prediction model was performed across 9 patient record databases within the Observational Health Data Sciences and Informatics (OHDSI) network internationally. The model's area under the curve (AUC) varied 0.633-0.745 (µ = 0.689) across the five US training databases. Nine variables predicted one-year MDD-BD transition. Factors that increased risk were: younger age, severe depression, psychosis, anxiety, substance misuse, self-harm thoughts/actions, and prior mental disorder. AUCs of the validation datasets ranged 0.570-0.785 (µ = 0.664). An assessment algorithm was built for MDD to BD conversion that allows distinguishing as much as 100-fold risk differences among patients and validates well across multiple international data sources.

Sexual orientation-related disparities in health conditions that elevate COVID-19 severity

Purpose

The Veterans Health Administration (VA) is the largest single integrated healthcare system in the US and is likely the largest healthcare provider for people with minoritized sexual orientations (e.g., gay, lesbian, bisexual). The purpose of this study was to use electronic health record (EHR) data to replicate self-reported survey findings from the general US population and assess whether sexual orientation is associated with diagnosed physical health conditions that may elevate risk of COVID-19 severity among veterans who utilize the VA.

Methods

A retrospective analysis of VA EHR data from January 10, 1999–January 07, 2019 analyzed in 2021. Veterans with minoritized sexual orientations were included if they had documentation of a minoritized sexual orientation within clinical notes identified via natural language processing. Veterans without minoritized sexual orientation documentation comprised the comparison group. Adjusted prevalence and prevalence ratios (aPR) were calculated overall and by race/ethnicity while accounting for differences in distributions of sex assigned at birth, age, calendar year of first VA visit, volumes of healthcare utilization, and VA priority group.

Results

Data from 108,401 veterans with minoritized sexual orientation and 6,511,698 controls were analyzed. After adjustment, veterans with minoritized sexual orientations had a statistically significant elevated prevalence of 10 of the 11 conditions. Amongst the highest disparities observed were COPD (aPR:1.24 [95% confidence interval:1.23–1.26]), asthma (1.22 [1.20–1.24]), and stroke (1.26 [1.24–1.28]).

Conclusions

Findings largely corroborated patterns among the general US population. Further research is needed to determine if these disparities translate to poorer COVID-19 outcomes for individuals with minoritized sexual orientation.

Positive Predictive Value of COVID-19 ICD-10 Diagnosis Codes Across Calendar Time and Clinical Setting

Purpose

To estimate the positive predictive value (PPV) of International Classification of Diseases, Tenth Revision (ICD-10) code U07.1, COVID-19 virus identified, in the Department of Veterans of Affairs (VA).

Patients and Methods

Records of ICD-10 code U07.1 from inpatient, outpatient, and emergency/urgent care settings were extracted from VA medical record data from 4/01/2020 to 3/31/2021. A weighted, random sample of 1500 records from each quarter of the one-year observation period was reviewed by study personnel to confirm active COVID-19 infection at the time of diagnosis and classify reasons for false positive records. PPV was estimated overall and compared across clinical setting and quarters.

Results

We identified 664,406 records of U07.1. Among the 1500 reviewed, 237 were false positives (PPV: 84.2%, 95% CI: 82.4–86.0). PPV ranged from 77.7% in outpatient settings to 93.8% in inpatient settings and was 83.3% in quarter 1, 80.5% in quarter 2, 86.1% in quarter 3, and 83.6% in quarter 4. The most common reasons for false positive records were history of COVID-19 (44.3%) and orders for laboratory tests (21.5%).

Conclusion

The PPV of ICD-10 code U07.1 is low, especially in outpatient settings. Directed training may improve accuracy of coding to levels that are deemed adequate for future use in surveillance efforts.

Smoking Status and Factors associated with COVID-19 In-hospital Mortality among U.S. Veterans

Introduction

The role of smoking in risk of death among patients with COVID-19 remains unclear. We examined the association between in-hospital mortality from COVID-19 and smoking status and other factors in the United States Veterans Health Administration (VHA).

Methods

This is an observational, retrospective cohort study using the VHA COVID-19 shared data resources for February 1 to September 11, 2020. Veterans admitted to the hospital who tested positive for SARS-CoV-2 and hospitalized by VHA were grouped into Never (as reference, NS), Former (FS), and Current smokers (CS). The main outcome was in-hospital mortality. Control factors were the most important variables (among all available) determined through a cascade of machine learning. We reported adjusted odds ratios (aOR) and 95% confidence intervals (95%CI) from logistic regression models, imputing missing smoking status in our primary analysis.

Results

Out of 8 667 996 VHA enrollees, 505 143 were tested for SARS-CoV-2 (NS = 191 143; FS = 240 336; CS = 117 706; Unknown = 45 533). The aOR of in-hospital mortality was 1.16 (95%CI 1.01, 1.32) for FS vs. NS and 0.97 (95%CI 0.78, 1.22; p > .05) for CS vs. NS with imputed smoking status. Among other factors, famotidine and nonsteroidal anti-inflammatory drugs (NSAID) use before hospitalization were associated with lower risk while diabetes with complications, kidney disease, obesity, and advanced age were associated with higher risk of in-hospital mortality.

Conclusions

In patients admitted to the hospital with SARS-CoV-2 infection, our data demonstrate that FS are at higher risk of in-hospital mortality than NS. However, this pattern was not seen among CS highlighting the need for more granular analysis with high-quality smoking status data to further clarify our understanding of smoking risk and COVID-19-related mortality. Presence of comorbidities and advanced age were also associated with increased risk of in-hospital mortality.

Implications

Veterans who were former smokers were at higher risk of in-hospital mortality compared to never smokers. Current smokers and never smokers were at similar risk of in-hospital mortality. The use of famotidine and nonsteroidal anti-inflammatory drugs (NSAIDs) before hospitalization were associated with lower risk while uncontrolled diabetes mellitus, advanced age, kidney disease, and obesity were associated with higher risk of in-hospital mortality.

COVID-19 in patients with autoimmune diseases: characteristics and outcomes in a multinational network of cohorts across three countries

OBJECTIVE

Patients with autoimmune diseases were advised to shield to avoid coronavirus disease 2019 (COVID-19), but information on their prognosis is lacking. We characterized 30-day outcomes and mortality after hospitalization with COVID-19 among patients with prevalent autoimmune diseases, and compared outcomes after hospital admissions among similar patients with seasonal influenza.

METHODS

A multinational network cohort study was conducted using electronic health records data from Columbia University Irving Medical Center [USA, Optum (USA), Department of Veterans Affairs (USA), Information System for Research in Primary Care-Hospitalization Linked Data (Spain) and claims data from IQVIA Open Claims (USA) and Health Insurance and Review Assessment (South Korea). All patients with prevalent autoimmune diseases, diagnosed and/or hospitalized between January and June 2020 with COVID-19, and similar patients hospitalized with influenza in 2017-18 were included. Outcomes were death and complications within 30 days of hospitalization.

RESULTS

We studied 133 589 patients diagnosed and 48 418 hospitalized with COVID-19 with prevalent autoimmune diseases. Most patients were female, aged ≥50 years with previous comorbidities. The prevalence of hypertension (45.5-93.2%), chronic kidney disease (14.0-52.7%) and heart disease (29.0-83.8%) was higher in hospitalized vs diagnosed patients with COVID-19. Compared with 70 660 hospitalized with influenza, those admitted with COVID-19 had more respiratory complications including pneumonia and acute respiratory distress syndrome, and higher 30-day mortality (2.2-4.3% vs 6.32-24.6%).

CONCLUSION

Compared with influenza, COVID-19 is a more severe disease, leading to more complications and higher mortality.

Characteristics and Outcomes of Over 300,000 Patients with COVID-19 and History of Cancer in the United States and Spain

BACKGROUND

We described the demographics, cancer subtypes, comorbidities, and outcomes of patients with a history of cancer and coronavirus disease 2019 (COVID-19). Second, we compared patients hospitalized with COVID-19 to patients diagnosed with COVID-19 and patients hospitalized with influenza.

METHODS

We conducted a cohort study using eight routinely collected health care databases from Spain and the United States, standardized to the Observational Medical Outcome Partnership common data model. Three cohorts of patients with a history of cancer were included: (i) diagnosed with COVID-19, (ii) hospitalized with COVID-19, and (iii) hospitalized with influenza in 2017 to 2018. Patients were followed from index date to 30 days or death. We reported demographics, cancer subtypes, comorbidities, and 30-day outcomes.

RESULTS

We included 366,050 and 119,597 patients diagnosed and hospitalized with COVID-19, respectively. Prostate and breast cancers were the most frequent cancers (range: 5%-18% and 1%-14% in the diagnosed cohort, respectively). Hematologic malignancies were also frequent, with non-Hodgkin's lymphoma being among the five most common cancer subtypes in the diagnosed cohort. Overall, patients were aged above 65 years and had multiple comorbidities. Occurrence of death ranged from 2% to 14% and from 6% to 26% in the diagnosed and hospitalized COVID-19 cohorts, respectively. Patients hospitalized with influenza (n = 67,743) had a similar distribution of cancer subtypes, sex, age, and comorbidities but lower occurrence of adverse events.

CONCLUSIONS

Patients with a history of cancer and COVID-19 had multiple comorbidities and a high occurrence of COVID-19-related events. Hematologic malignancies were frequent.

IMPACT

This study provides epidemiologic characteristics that can inform clinical care and etiologic studies.

Military Sexual Trauma and Adverse Mental and Physical Health and Clinical Comorbidity in Women Veterans

INTRODUCTION

Military sexual trauma (MST)-exposure to sexual harassment or assault during military service-is a major health priority for the Veterans Health Administration (VHA). We examined the health correlates of MST in the largest sample of U.S. women veterans studied to date.

METHODS

Using national VHA electronic medical record data, we identified 502,199 women veterans who enrolled in the VHA between January 1, 2000, and December 31, 2017, had at least one VHA visit, and were screened for MST (exclusive of those who declined to answer the screening). We conducted logistic regression analyses to examine associations of a positive MST screen with various mental and physical health conditions-defined by administrative diagnostic codes-and comorbidity of mental and/or physical health conditions. Models were adjusted for demographic and military service characteristics, along with duration in the VHA.

RESULTS

Approximately 26% (n = 130,738) of women veterans screened positive for MST. In fully adjusted models, a positive MST screen was associated with greater risk of having all mental and physical health conditions examined, except cancer-related conditions, ranging from 9% greater odds of rheumatic disease to 5.4 times greater odds of post-traumatic stress disorder. MST was also associated with greater comorbidity, including greater odds of having ≥2 mental health conditions (odds ratio [OR], 3.28; 99% confidence interval [CI], 3.20-3.37), having ≥2 physical health conditions (OR, 1.26; 99% CI, 1.22-1.29), and having ≥1 mental health condition and ≥1 physical health condition (OR, 2.05; 99% CI, 2.00-2.11).

CONCLUSIONS

Findings suggest that MST is common in women veterans and may play a role in the clinical complexity arising from comorbid conditions.

Characteristics and outcomes of 627 044 COVID-19 patients living with and without obesity in the United States, Spain, and the United Kingdom

BACKGROUND

A detailed characterization of patients with COVID-19 living with obesity has not yet been undertaken. We aimed to describe and compare the demographics, medical conditions, and outcomes of COVID-19 patients living with obesity (PLWO) to those of patients living without obesity.

METHODS

We conducted a cohort study based on outpatient/inpatient care and claims data from January to June 2020 from Spain, the UK, and the US. We used six databases standardized to the OMOP common data model. We defined two non-mutually exclusive cohorts of patients diagnosed and/or hospitalized with COVID-19; patients were followed from index date to 30 days or death. We report the frequency of demographics, prior medical conditions, and 30-days outcomes (hospitalization, events, and death) by obesity status.

RESULTS

We included 627 044 (Spain: 122 058, UK: 2336, and US: 502 650) diagnosed and 160 013 (Spain: 18 197, US: 141 816) hospitalized patients with COVID-19. The prevalence of obesity was higher among patients hospitalized (39.9%, 95%CI: 39.8-40.0) than among those diagnosed with COVID-19 (33.1%; 95%CI: 33.0-33.2). In both cohorts, PLWO were more often female. Hospitalized PLWO were younger than patients without obesity. Overall, COVID-19 PLWO were more likely to have prior medical conditions, present with cardiovascular and respiratory events during hospitalization, or require intensive services compared to COVID-19 patients without obesity.

CONCLUSION

We show that PLWO differ from patients without obesity in a wide range of medical conditions and present with more severe forms of COVID-19, with higher hospitalization rates and intensive services requirements. These findings can help guiding preventive strategies of COVID-19 infection and complications and generating hypotheses for causal inference studies.

Risk of depression, suicide and psychosis with hydroxychloroquine treatment for rheumatoid arthritis: a multinational network cohort study

OBJECTIVES

Concern has been raised in the rheumatology community regarding recent regulatory warnings that HCQ used in the coronavirus disease 2019 pandemic could cause acute psychiatric events. We aimed to study whether there is risk of incident depression, suicidal ideation or psychosis associated with HCQ as used for RA.

METHODS

We performed a new-user cohort study using claims and electronic medical records from 10 sources and 3 countries (Germany, UK and USA). RA patients ≥18 years of age and initiating HCQ were compared with those initiating SSZ (active comparator) and followed up in the short (30 days) and long term (on treatment). Study outcomes included depression, suicide/suicidal ideation and hospitalization for psychosis. Propensity score stratification and calibration using negative control outcomes were used to address confounding. Cox models were fitted to estimate database-specific calibrated hazard ratios (HRs), with estimates pooled where I2 <40%.

RESULTS

A total of 918 144 and 290 383 users of HCQ and SSZ, respectively, were included. No consistent risk of psychiatric events was observed with short-term HCQ (compared with SSZ) use, with meta-analytic HRs of 0.96 (95% CI 0.79, 1.16) for depression, 0.94 (95% CI 0.49, 1.77) for suicide/suicidal ideation and 1.03 (95% CI 0.66, 1.60) for psychosis. No consistent long-term risk was seen, with meta-analytic HRs of 0.94 (95% CI 0.71, 1.26) for depression, 0.77 (95% CI 0.56, 1.07) for suicide/suicidal ideation and 0.99 (95% CI 0.72, 1.35) for psychosis.

CONCLUSION

HCQ as used to treat RA does not appear to increase the risk of depression, suicide/suicidal ideation or psychosis compared with SSZ. No effects were seen in the short or long term. Use at a higher dose or for different indications needs further investigation.

TRIAL REGISTRATION

Registered with EU PAS (reference no. EUPAS34497; http://www.encepp.eu/encepp/viewResource.htm? id=34498). The full study protocol and analysis source code can be found at https://github.com/ohdsi-studies/Covid19EstimationHydroxychloroquine2.

Healthcare service utilization for formerly homeless veterans in permanent supportive housing: Do neighborhoods matter?

Neighborhood characteristics are associated with residents' healthcare use. However, we understand less about these relationships among formerly homeless persons, who often have complex healthcare needs, including mental health and substance use disorders. Among formerly homeless Veterans, we examined: (a) how neighborhood characteristics are associated with Veteran Health Administration (VHA) healthcare use and, (b) if these relationships varied by Veterans' level of healthcare need. We obtained data on our cohort of 711 Veterans housed through VHA's permanent supportive housing program (HUD-VASH) in 2016-2017 from VHA's Homeless Registry, VHA's electronic health records, and the U.S. Census. We studied the relationships between neighborhood characteristics (% Veteran, % in poverty, % unemployed, % using public transportation, and % vacant properties) and VA healthcare use (primary care visits, outpatient mental health visits, and "high use" of emergency departments [> 4 visits]) using mixed-effects logistic and negative binomial regression models, controlling for patient demographics. We further examined moderation by patient healthcare need (calculated from cost and clinical data). We found that veterans in neighborhoods with higher percentages of residents who (a) were Veterans or (b) used public transportation were more likely to have high emergency department use. Those in neighborhoods with higher public transportation use had more primary care visits while those in neighborhoods with more property vacancies had more outpatient mental health visits. Among those with high healthcare needs, residents of areas with more Veterans had higher emergency department use. Promoting public transportation use and social engagement with other Veterans in residential neighborhoods may influence HUD-VASH Veterans' VA healthcare use. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Association of Posttraumatic Stress Disorder and Incident Ischemic Heart Disease in Women Veterans

Importance

Posttraumatic stress disorder (PTSD) is associated with greater risk of ischemic heart disease (IHD) in predominantly male populations or limited community samples. Women veterans represent a growing, yet understudied, population with high levels of trauma exposure and unique cardiovascular risks, but research on PTSD and IHD in this group is lacking.

Objective

To determine whether PTSD is associated with incident IHD in women veterans.

Design, Setting, and Participants

In this retrospective, longitudinal cohort study of the national Veterans Health Administration (VHA) electronic medical records, the a priori hypothesis that PTSD would be associated with greater risk of IHD onset was tested. Women veterans 18 years or older with and without PTSD who were patients in the VHA from January 1, 2000, to December 31, 2017, were assessed for study eligibility. Exclusion criteria consisted of no VHA clinical encounters after the index visit, IHD diagnosis at or before the index visit, and IHD diagnosis within 90 days of the index visit. Propensity score matching on age at index visit, number of prior visits, and presence of traditional and female-specific cardiovascular risk factors and mental and physical health conditions was conducted to identify women veterans ever diagnosed with PTSD, who were matched in a 1:2 ratio to those never diagnosed with PTSD. Data were analyzed from October 1, 2018, to October 30, 2020.

Exposures

PTSD, defined by International Classification of Diseases, Ninth Revision (ICD-9), or International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10), diagnosis codes from inpatient or outpatient encounters.

Main Outcomes and Measures

Incident IHD, defined as new-onset coronary artery disease, angina, or myocardial infarction, based on ICD-9 and ICD-10 diagnosis codes from inpatient or outpatient encounters, and/or coronary interventions based on Current Procedural Terminology codes.

Results

A total of 398 769 women veterans, 132 923 with PTSD and 265 846 never diagnosed with PTSD, were included in the analysis. Baseline mean (SD) age was 40.1 (12.2) years. During median follow-up of 4.9 (interquartile range, 2.1-9.2) years, 4381 women with PTSD (3.3%) and 5559 control individuals (2.1%) developed incident IHD. In a Cox proportional hazards model, PTSD was significantly associated with greater risk of developing IHD (hazard ratio [HR], 1.44; 95% CI, 1.38-1.50). Secondary stratified analyses indicated that younger age identified women veterans with PTSD who were at greater risk of incident IHD. Effect sizes were largest for those younger than 40 years at baseline (HR, 1.72; 95% CI, 1.55-1.93) and decreased monotonically with increasing age (HR for ≥60 years, 1.24; 95% CI, 1.12-1.38).

Conclusions and Relevance

This cohort study found that PTSD was associated with increased risk of IHD in women veterans and may have implications for IHD risk assessment in vulnerable individuals.

Use of repurposed and adjuvant drugs in hospital patients with covid-19: multinational network cohort study

OBJECTIVE

To investigate the use of repurposed and adjuvant drugs in patients admitted to hospital with covid-19 across three continents.

DESIGN

Multinational network cohort study.

SETTING

Hospital electronic health records from the United States, Spain, and China, and nationwide claims data from South Korea.

PARTICIPANTS

303 264 patients admitted to hospital with covid-19 from January 2020 to December 2020.

MAIN OUTCOME MEASURES

Prescriptions or dispensations of any drug on or 30 days after the date of hospital admission for covid-19.

RESULTS

Of the 303 264 patients included, 290 131 were from the US, 7599 from South Korea, 5230 from Spain, and 304 from China. 3455 drugs were identified. Common repurposed drugs were hydroxychloroquine (used in from <5 (<2%) patients in China to 2165 (85.1%) in Spain), azithromycin (from 15 (4.9%) in China to 1473 (57.9%) in Spain), combined lopinavir and ritonavir (from 156 (<2%) in the VA-OMOP US to 2,652 (34.9%) in South Korea and 1285 (50.5%) in Spain), and umifenovir (0% in the US, South Korea, and Spain and 238 (78.3%) in China). Use of adjunctive drugs varied greatly, with the five most used treatments being enoxaparin, fluoroquinolones, ceftriaxone, vitamin D, and corticosteroids. Hydroxychloroquine use increased rapidly from March to April 2020 but declined steeply in May to June and remained low for the rest of the year. The use of dexamethasone and corticosteroids increased steadily during 2020.

CONCLUSIONS

Multiple drugs were used in the first few months of the covid-19 pandemic, with substantial geographical and temporal variation. Hydroxychloroquine, azithromycin, lopinavir-ritonavir, and umifenovir (in China only) were the most prescribed repurposed drugs. Antithrombotics, antibiotics, H2 receptor antagonists, and corticosteroids were often used as adjunctive treatments. Research is needed on the comparative risk and benefit of these treatments in the management of covid-19.

Uptake of KRAS Testing and Anti-EGFR Antibody Use for Colorectal Cancer in the VA

Advances in precision oncology, including RAS testing to predict response to epidermal growth factor receptor monoclonal antibodies (EGFR mAbs) in colorectal cancer (CRC), can extend patients' lives. We evaluated uptake and clinical use of KRAS molecular testing, guideline recommended since 2010, in the Veterans Affairs Healthcare System (VA).

MATERIALS AND METHODS

We conducted a retrospective cohort study of patients with stage IV CRC diagnosed in the VA 2006-2015. We gathered clinical, demographic, molecular, and treatment data from the VA Corporate Data Warehouse and 29 commercial laboratories. We performed multivariable analyses of associations between patient characteristics, KRAS testing, and EGFR mAb treatment.

RESULTS

Among 5,943 patients diagnosed with stage IV CRC, only 1,053 (17.7%) had KRAS testing. Testing rates increased from 2.3% in 2006 to 28.4% in 2013. In multivariable regression, older patients (odds ratio, 0.17; 95% CI, 0.09 to 0.32 for ≥ age 85 v < 45 years) and those treated in the Northeast and South regions were less likely, and those treated at high-volume CRC centers were more likely to have KRAS testing (odds ratio, 2.32; 95% CI, 1.48 to 3.63). Rates of potentially guideline discordant care were high: 64.3% (321/499) of KRAS wild-type (WT) went untreated with EGFR mAb and 8.8% (401/4,570) with no KRAS testing received EGFR mAb. Among KRAS-WT patients, survival was better for patients who received EGFR mAb treatment (29.6 v 18.8 months; P < .001).

CONCLUSION

We found underuse of KRAS testing in advanced CRC, especially among older patients and those treated at lower-volume CRC centers. We found high rates of potentially guideline discordant underuse of EGFR mAb in patients with KRAS-WT tumors. Efforts to understand barriers to precision oncology are needed to maximize patient benefit.

Implementation of the COVID-19 Vulnerability Index Across an International Network of Health Care Data Sets: Collaborative External Validation Study

Background

SARS-CoV-2 is straining health care systems globally. The burden on hospitals during the pandemic could be reduced by implementing prediction models that can discriminate patients who require hospitalization from those who do not. The COVID-19 vulnerability (C-19) index, a model that predicts which patients will be admitted to hospital for treatment of pneumonia or pneumonia proxies, has been developed and proposed as a valuable tool for decision-making during the pandemic. However, the model is at high risk of bias according to the “prediction model risk of bias assessment” criteria, and it has not been externally validated.

Objective

The aim of this study was to externally validate the C-19 index across a range of health care settings to determine how well it broadly predicts hospitalization due to pneumonia in COVID-19 cases.

Methods

We followed the Observational Health Data Sciences and Informatics (OHDSI) framework for external validation to assess the reliability of the C-19 index. We evaluated the model on two different target populations, 41,381 patients who presented with SARS-CoV-2 at an outpatient or emergency department visit and 9,429,285 patients who presented with influenza or related symptoms during an outpatient or emergency department visit, to predict their risk of hospitalization with pneumonia during the following 0-30 days. In total, we validated the model across a network of 14 databases spanning the United States, Europe, Australia, and Asia.

Results

The internal validation performance of the C-19 index had a C statistic of 0.73, and the calibration was not reported by the authors. When we externally validated it by transporting it to SARS-CoV-2 data, the model obtained C statistics of 0.36, 0.53 (0.473-0.584) and 0.56 (0.488-0.636) on Spanish, US, and South Korean data sets, respectively. The calibration was poor, with the model underestimating risk. When validated on 12 data sets containing influenza patients across the OHDSI network, the C statistics ranged between 0.40 and 0.68.

Conclusions

Our results show that the discriminative performance of the C-19 index model is low for influenza cohorts and even worse among patients with COVID-19 in the United States, Spain, and South Korea. These results suggest that C-19 should not be used to aid decision-making during the COVID-19 pandemic. Our findings highlight the importance of performing external validation across a range of settings, especially when a prediction model is being extrapolated to a different population. In the field of prediction, extensive validation is required to create appropriate trust in a model.

Actionable druggable genome-wide Mendelian randomization identifies repurposing opportunities for COVID-19

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.

Variation in Sexual Orientation Documentation in a National Electronic Health Record System

Purpose: The purpose of this study was to determine variation in sexual minority (SM) sexual orientation documentation within the electronic medical records of the Veterans Health Administration (VHA). Methods: Documentation of SM sexual orientation was retrospectively extracted from clinical notes and administrative data in the VHA from October 1, 1999 to July 1, 2019. The rate of documentation overall and by calendar year was calculated, and differences across patient, provider, and clinic characteristics were evaluated. Results: Approximately 1.4% of all VHA Veterans (n = 115,911) had at least one documentation of SM sexual orientation, including 79,455 men and 36,456 women. The rate of documentation increased from 81.01/100,000 in 2000 to 568.84/100,000 in 2018. The majority of documentations (58.7%) occurred in mental health settings by non-MD mental health/social work counselors, whereas only 9.6% occurred in primary care settings. Although 99% of these Veterans had a primary care visit, only 19% had SM status recorded in that setting. Conclusion: Documentation patterns of SM sexual orientation varied considerably in the VHA with notable gaps in primary care. Diverse approaches to culturally competent training for primary care clinicians and patient-facing collection strategies could facilitate documentation of sexual orientation.

Partial Versus Complete Bacillus Calmette-Guérin Intravesical Therapy and Bladder Cancer Outcomes in High-risk Non-muscle-invasive Bladder Cancer: Is NIMBUS the Full Story?

Background

It is important to understand the implications of reduced bacillus Calmette-Guérin (BCG) treatment intensity, given global shortages and early termination of the NIMBUS trial.

Objective

To assess the association of partial versus complete BCG induction with outcomes.

Design, setting, and participants

This is a retrospective cohort study of veterans diagnosed with high-risk non–muscle-invasive bladder cancer (NMIBC; high grade [HG] Ta, T1, or carcinoma in situ) between 2005 and 2011 with follow-up through 2014.

Intervention

Patients were categorized into partial versus complete BCG induction (one to five vs five or more instillations). Partial BCG induction subgroups were defined for comparison with the NIMBUS trial.

Outcome measurements and statistical analysis

Propensity score–adjusted regression models were used to assess the association of partial BCG induction with risk of recurrence and bladder cancer death.

Results and limitations

Among 540 patients, 114 (21.1%) underwent partial BCG induction. Partial versus complete BCG induction was not significantly associated with the risk of recurrence in HG Ta (cumulative incidence [CIn] 46.6% vs 53.9% at 5 yr, p =  0.38) or T1 (CIn 47.1% vs 56.7 at 5 yr, p = 0.19) disease. Similarly, we found no increased risk of bladder cancer death (HG Ta: CIn 4.7%7vs 5.4% at 5 yr, p = 0.87; T1: CIn 10.0% vs 11.4% at 5 yr, p =  0.77). NIMBUS-like induction was associated with an increased risk of recurrence in patients with HG Ta disease, although not statistically significant. Unmeasured confounding is a limitation.

Conclusions

Cancer outcomes were similar among high-risk NMIBC patients who underwent partial versus complete BCG induction, suggesting that future research is needed to determine how to optimize BCG delivery for the greatest number of patients, especially during global shortages.

Patient summary

Outcomes were similar between patients receiving partial and complete courses of bacillus Calmette-Guérin (BCG) therapy. Future research is needed to determine how to best deliver BCG to the greatest number of patients, particularly during medication shortages.

Use of dialysis, tracheostomy, and extracorporeal membrane oxygenation among 842,928 patients hospitalized with COVID-19 in the United States

Objective

To estimate the proportion of patients hospitalized with COVID-19 who undergo dialysis, tracheostomy, and extracorporeal membrane oxygenation (ECMO).

Design

A network cohort study.

Setting

Seven databases from the United States containing routinely-collected patient data: HealthVerity, Premier, IQVIA Hospital CDM, IQVIA Open Claims, Optum EHR, Optum SES, and VA-OMOP.

Patients

Patients hospitalized with a clinical diagnosis or a positive test result for COVID-19.

Interventions

Dialysis, tracheostomy, and ECMO.

Measurements and Main Results

842,928 patients hospitalized with COVID-19 were included (22,887 from HealthVerity, 77,853 from IQVIA Hospital CDM, 533,997 from IQVIA Open Claims, 36,717 from Optum EHR, 4,336 from OPTUM SES, 156,187 from Premier, and 10,951 from VA-OMOP). Across the six databases, 35,192 (4.17% [95% CI: 4.13% to 4.22%]) patients received dialysis, 6,950 (0.82% [0.81% to 0.84%]) had a tracheostomy, and 1,568 (0.19% [95% CI: 0.18% to 0.20%]) patients underwent ECMO over the 30 days following hospitalization. Use of ECMO was more common among patients who were younger, male, and with fewer comorbidities. Tracheostomy was broadly used for a similar proportion of patients regardless of age, sex, or comorbidity. While dialysis was generally used for a similar proportion among younger and older patients, it was more frequent among male patients and among those with chronic kidney disease.

Conclusion

Use of dialysis among those hospitalized with COVID-19 is high at around 4%. Although less than one percent of patients undergo tracheostomy and ECMO, the absolute numbers of patients who have undergone these interventions is substantial.

International Comparisons of Harmonized Laboratory Value Trajectories to Predict Severe COVID-19: Leveraging the 4CE Collaborative Across 342 Hospitals and 6 Countries: A Retrospective Cohort Study

Objectives

To perform an international comparison of the trajectory of laboratory values among hospitalized patients with COVID-19 who develop severe disease and identify optimal timing of laboratory value collection to predict severity across hospitals and regions.

Design

Retrospective cohort study.

Setting

The Consortium for Clinical Characterization of COVID-19 by EHR (4CE), an international multi-site data-sharing collaborative of 342 hospitals in the US and in Europe.

Participants

Patients hospitalized with COVID-19, admitted before or after PCR-confirmed result for SARS-CoV-2.

Primary and secondary outcome measures

Patients were categorized as "ever-severe" or "never-severe" using the validated 4CE severity criteria. Eighteen laboratory tests associated with poor COVID-19-related outcomes were evaluated for predictive accuracy by area under the curve (AUC), compared between the severity categories. Subgroup analysis was performed to validate a subset of laboratory values as predictive of severity against a published algorithm. A subset of laboratory values (CRP, albumin, LDH, neutrophil count, D-dimer, and procalcitonin) was compared between North American and European sites for severity prediction.

Results

Of 36,447 patients with COVID-19, 19,953 (43.7%) were categorized as ever-severe. Most patients (78.7%) were 50 years of age or older and male (60.5%). Longitudinal trajectories of CRP, albumin, LDH, neutrophil count, D-dimer, and procalcitonin showed association with disease severity. Significant differences of laboratory values at admission were found between the two groups. With the exception of D-dimer, predictive discrimination of laboratory values did not improve after admission. Sub-group analysis using age, D-dimer, CRP, and lymphocyte count as predictive of severity at admission showed similar discrimination to a published algorithm (AUC=0.88 and 0.91, respectively). Both models deteriorated in predictive accuracy as the disease progressed. On average, no difference in severity prediction was found between North American and European sites.

Conclusions

Laboratory test values at admission can be used to predict severity in patients with COVID-19. Prediction models show consistency across international sites highlighting the potential generalizability of these models.

Evaluation of Suicide Mortality Among Sexual Minority US Veterans From 2000 to 2017

IMPORTANCE

Identification of subgroups at greatest risk for suicide mortality is essential for prevention efforts and targeting interventions. Sexual minority individuals may have an increased risk for suicide compared with heterosexual individuals, but a lack of sufficiently powered studies with rigorous methods for determining sexual orientation has limited the knowledge on this potential health disparity.

OBJECTIVE

To investigate suicide mortality among sexual minority veterans using Veterans Health Administration (VHA) electronic health record data.

DESIGN, SETTING, AND PARTICIPANTS

This retrospective population-based cohort study used data on 8.1 million US veterans enrolled in the VHA after fiscal year 1999 that were obtained from VHA electronic health records from October 1, 1999 to September 30, 2017. Data analysis was carried out from March 1, 2020 to October 31, 2020.

EXPOSURE

Veterans with documentation of a minority sexual orientation. Documentation of sexual minority status was obtained through natural language processing of clinical notes and extraction of structured administrative data for sexual orientation in VHA electronic health records.

MAIN OUTCOMES AND MEASURES

Suicide mortality rate using data on the underlying cause of death obtained from the National Death Index. Crude and age-adjusted mortality rates were calculated for all-cause death and death from suicide among sexual minority veterans compared with the general US population and the general population of veterans.

RESULTS

Among the 96 893 veterans with at least 1 sexual minority documentation in the electronic health record, the mean (SD) age was 46 (16) years, 68% were male, and 70% were White. Of the 12 591 total deaths, 3.5% were from suicide. Veterans had a significantly higher rate of mortality from suicide (standardized mortality ratio, 4.50; 95% CI, 4.13-4.99) compared with the general US population. Suicide was the fifth leading cause of death in 2017 among sexual minority veterans (3.8% of deaths) and the tenth leading cause of death in the general US population (1.7% of deaths). The crude suicide rate among sexual minority veterans (82.5 per 100 000 person-years) was higher than the rate in the general veteran population (37.7 per 100 000 person-years).

CONCLUSIONS AND RELEVANCE

The results of this population-based cohort study suggest that sexual minority veterans have a greater risk for suicide than the general US population and the general veteran population. Further research is needed to determine whether and how suicide prevention efforts reach sexual minority veterans.

Characteristics, outcomes, and mortality amongst 133,589 patients with prevalent autoimmune diseases diagnosed with, and 48,418 hospitalised for COVID-19: a multinational distributed network cohort analysis

OBJECTIVE

Patients with autoimmune diseases were advised to shield to avoid COVID-19, but information on their prognosis is lacking. We characterised 30-day outcomes and mortality after hospitalisation with COVID-19 among patients with prevalent autoimmune diseases, and compared outcomes after hospital admissions among similar patients with seasonal influenza.

DESIGN

Multinational network cohort study.

SETTING

Electronic health records data from Columbia University Irving Medical Center (CUIMC) (NYC, United States [US]), Optum [US], Department of Veterans Affairs (VA) (US), Information System for Research in Primary Care-Hospitalisation Linked Data (SIDIAP-H) (Spain), and claims data from IQVIA Open Claims (US) and Health Insurance and Review Assessment (HIRA) (South Korea).

PARTICIPANTS

All patients with prevalent autoimmune diseases, diagnosed and/or hospitalised between January and June 2020 with COVID-19, and similar patients hospitalised with influenza in 2017-2018 were included.

MAIN OUTCOME MEASURES

30-day complications during hospitalisation and death.

RESULTS

We studied 133,589 patients diagnosed and 48,418 hospitalised with COVID-19 with prevalent autoimmune diseases. The majority of participants were female (60.5% to 65.9%) and aged ≥50 years. The most prevalent autoimmune conditions were psoriasis (3.5 to 32.5%), rheumatoid arthritis (3.9 to 18.9%), and vasculitis (3.3 to 17.6%). Amongst hospitalised patients, Type 1 diabetes was the most common autoimmune condition (4.8% to 7.5%) in US databases, rheumatoid arthritis in HIRA (18.9%), and psoriasis in SIDIAP-H (26.4%).Compared to 70,660 hospitalised with influenza, those admitted with COVID-19 had more respiratory complications including pneumonia and acute respiratory distress syndrome, and higher 30-day mortality (2.2% to 4.3% versus 6.3% to 24.6%).

CONCLUSIONS

Patients with autoimmune diseases had high rates of respiratory complications and 30-day mortality following a hospitalization with COVID-19. Compared to influenza, COVID-19 is a more severe disease, leading to more complications and higher mortality. Future studies should investigate predictors of poor outcomes in COVID-19 patients with autoimmune diseases.

WHAT IS ALREADY KNOWN ABOUT THIS TOPIC

Patients with autoimmune conditions may be at increased risk of COVID-19 infection andcomplications.There is a paucity of evidence characterising the outcomes of hospitalised COVID-19 patients with prevalent autoimmune conditions.

WHAT THIS STUDY ADDS

Most people with autoimmune diseases who required hospitalisation for COVID-19 were women, aged 50 years or older, and had substantial previous comorbidities.Patients who were hospitalised with COVID-19 and had prevalent autoimmune diseases had higher prevalence of hypertension, chronic kidney disease, heart disease, and Type 2 diabetes as compared to those with prevalent autoimmune diseases who were diagnosed with COVID-19.A variable proportion of 6% to 25% across data sources died within one month of hospitalisation with COVID-19 and prevalent autoimmune diseases.For people with autoimmune diseases, COVID-19 hospitalisation was associated with worse outcomes and 30-day mortality compared to admission with influenza in the 2017-2018 season.

The Utility of Clinical Notes for Sexual Minority Health Research

INTRODUCTION

Despite improvements in electronic medical record capability to collect data on sexual orientation, not all healthcare systems have adopted this practice. This can limit the usability of systemwide electronic medical record data for sexual minority research. One viable resource might be the documentation of sexual orientation within clinical notes. The authors developed an approach to identify sexual orientation documentation and subsequently derived a cohort of sexual minority patients using clinical notes from the Veterans Health Administration electronic medical record.

METHODS

A hybrid natural language processing approach was developed and used to identify and categorize instances of terms and phrases related to sexual orientation in Veterans Health Administration clinical notes from 2000 to 2019. System performance was assessed with positive predictive value and sensitivity. Data were analyzed in 2019.

RESULTS

A total of 2,413,584 sexual minority terms/phrases were found within clinical notes, of which 439,039 (18%) were found to be related to patient sexual orientation with a positive predictive value of 85.9%. Documentation of sexual orientation was found for 115,312 patients. When compared with 2,262 patients with a record of administrative coding for homosexuality, the system found mentions of sexual orientation for 1,808 patients (79.9% sensitivity).

CONCLUSIONS

When systemwide structured data are unavailable or inconsistent, deriving a cohort of sexual minority patients in electronic medical records for research is possible and permits longitudinal analysis across multiple clinical domains. Although limitations and challenges to the approach were identified, this study makes an important step forward for the Veterans Health Administration sexual minority research, and the methodology can be applied in other healthcare organizations.

Baseline phenotype and 30-day outcomes of people tested for COVID-19: an international network cohort including >3.32 million people tested with real-time PCR and >219,000 tested positive for SARS-CoV-2 in South Korea, Spain and the United States

Early identification of symptoms and comorbidities most predictive of COVID-19 is critical to identify infection, guide policies to effectively contain the pandemic, and improve health systems' response. Here, we characterised socio-demographics and comorbidity in 3,316,107persons tested and 219,072 persons tested positive for SARS-CoV-2 since January 2020, and their key health outcomes in the month following the first positive test. Routine care data from primary care electronic health records (EHR) from Spain, hospital EHR from the United States (US), and claims data from South Korea and the US were used. The majority of study participants were women aged 18-65 years old. Positive/tested ratio varied greatly geographically (2.2:100 to 31.2:100) and over time (from 50:100 in February-April to 6.8:100 in May-June). Fever, cough and dyspnoea were the most common symptoms at presentation. Between 4%-38% required admission and 1-10.5% died within a month from their first positive test. Observed disparity in testing practices led to variable baseline characteristics and outcomes, both nationally (US) and internationally. Our findings highlight the importance of large scale characterization of COVID-19 international cohorts to inform planning and resource allocation including testing as countries face a second wave.

Deep phenotyping of 34,128 adult patients hospitalised with COVID-19 in an international network study

Comorbid conditions appear to be common among individuals hospitalised with coronavirus disease 2019 (COVID-19) but estimates of prevalence vary and little is known about the prior medication use of patients. Here, we describe the characteristics of adults hospitalised with COVID-19 and compare them with influenza patients. We include 34,128 (US: 8362, South Korea: 7341, Spain: 18,425) COVID-19 patients, summarising between 4811 and 11,643 unique aggregate characteristics. COVID-19 patients have been majority male in the US and Spain, but predominantly female in South Korea. Age profiles vary across data sources. Compared to 84,585 individuals hospitalised with influenza in 2014-19, COVID-19 patients have more typically been male, younger, and with fewer comorbidities and lower medication use. While protecting groups vulnerable to influenza is likely a useful starting point in the response to COVID-19, strategies will likely need to be broadened to reflect the particular characteristics of individuals being hospitalised with COVID-19.

COVID-19 TestNorm: A tool to normalize COVID-19 testing names to LOINC codes

Large observational data networks that leverage routine clinical practice data in electronic health records (EHRs) are critical resources for research on coronavirus disease 2019 (COVID-19). Data normalization is a key challenge for the secondary use of EHRs for COVID-19 research across institutions. In this study, we addressed the challenge of automating the normalization of COVID-19 diagnostic tests, which are critical data elements, but for which controlled terminology terms were published after clinical implementation. We developed a simple but effective rule-based tool called COVID-19 TestNorm to automatically normalize local COVID-19 testing names to standard LOINC (Logical Observation Identifiers Names and Codes) codes. COVID-19 TestNorm was developed and evaluated using 568 test names collected from 8 healthcare systems. Our results show that it could achieve an accuracy of 97.4% on an independent test set. COVID-19 TestNorm is available as an open-source package for developers and as an online Web application for end users (https://clamp.uth.edu/covid/loinc.php). We believe that it will be a useful tool to support secondary use of EHRs for research on COVID-19.

Risk of hydroxychloroquine alone and in combination with azithromycin in the treatment of rheumatoid arthritis: a multinational, retrospective study

Background

Hydroxychloroquine, a drug commonly used in the treatment of rheumatoid arthritis, has received much negative publicity for adverse events associated with its authorisation for emergency use to treat patients with COVID-19 pneumonia. We studied the safety of hydroxychloroquine, alone and in combination with azithromycin, to determine the risk associated with its use in routine care in patients with rheumatoid arthritis.

Methods

In this multinational, retrospective study, new user cohort studies in patients with rheumatoid arthritis aged 18 years or older and initiating hydroxychloroquine were compared with those initiating sulfasalazine and followed up over 30 days, with 16 severe adverse events studied. Self-controlled case series were done to further establish safety in wider populations, and included all users of hydroxychloroquine regardless of rheumatoid arthritis status or indication. Separately, severe adverse events associated with hydroxychloroquine plus azithromycin (compared with hydroxychloroquine plus amoxicillin) were studied. Data comprised 14 sources of claims data or electronic medical records from Germany, Japan, the Netherlands, Spain, the UK, and the USA. Propensity score stratification and calibration using negative control outcomes were used to address confounding. Cox models were fitted to estimate calibrated hazard ratios (HRs) according to drug use. Estimates were pooled where the I ² value was less than 0·4.

Findings

The study included 956 374 users of hydroxychloroquine, 310 350 users of sulfasalazine, 323 122 users of hydroxychloroquine plus azithromycin, and 351 956 users of hydroxychloroquine plus amoxicillin. No excess risk of severe adverse events was identified when 30-day hydroxychloroquine and sulfasalazine use were compared. Self-controlled case series confirmed these findings. However, long-term use of hydroxychloroquine appeared to be associated with increased cardiovascular mortality (calibrated HR 1·65 [95% CI 1·12-2·44]). Addition of azithromycin appeared to be associated with an increased risk of 30-day cardiovascular mortality (calibrated HR 2·19 [95% CI 1·22-3·95]), chest pain or angina (1·15 [1·05-1·26]), and heart failure (1·22 [1·02-1·45]).

Interpretation

Hydroxychloroquine treatment appears to have no increased risk in the short term among patients with rheumatoid arthritis, but in the long term it appears to be associated with excess cardiovascular mortality. The addition of azithromycin increases the risk of heart failure and cardiovascular mortality even in the short term. We call for careful consideration of the benefit-risk trade-off when counselling those on hydroxychloroquine treatment.

Funding

National Institute for Health Research (NIHR) Oxford Biomedical Research Centre, NIHR Senior Research Fellowship programme, US National Institutes of Health, US Department of Veterans Affairs, Janssen Research and Development, IQVIA, Korea Health Industry Development Institute through the Ministry of Health and Welfare Republic of Korea, Versus Arthritis, UK Medical Research Council Doctoral Training Partnership, Foundation Alfonso Martin Escudero, Innovation Fund Denmark, Novo Nordisk Foundation, Singapore Ministry of Health's National Medical Research Council Open Fund Large Collaborative Grant, VINCI, Innovative Medicines Initiative 2 Joint Undertaking, EU's Horizon 2020 research and innovation programme, and European Federation of Pharmaceutical Industries and Associations.

Deep phenotyping of 34,128 patients hospitalised with COVID-19 and a comparison with 81,596 influenza patients in America, Europe and Asia: an international network study

Background In this study we phenotyped individuals hospitalised with coronavirus disease 2019 (COVID-19) in depth, summarising entire medical histories, including medications, as captured in routinely collected data drawn from databases across three continents. We then compared individuals hospitalised with COVID-19 to those previously hospitalised with influenza. Methods We report demographics, previously recorded conditions and medication use of patients hospitalised with COVID-19 in the US (Columbia University Irving Medical Center [CUIMC], Premier Healthcare Database [PHD], UCHealth System Health Data Compass Database [UC HDC], and the Department of Veterans Affairs [VA OMOP]), in South Korea (Health Insurance Review & Assessment [HIRA]), and Spain (The Information System for Research in Primary Care [SIDIAP] and HM Hospitales [HM]). These patients were then compared with patients hospitalised with influenza in 2014-19. Results 34,128 (US: 8,362, South Korea: 7,341, Spain: 18,425) individuals hospitalised with COVID-19 were included. Between 4,811 (HM) and 11,643 (CUIMC) unique aggregate characteristics were extracted per patient, with all summarised in an accompanying interactive website (http://evidence.ohdsi.org/Covid19CharacterizationHospitalization/). Patients were majority male in the US (CUIMC: 52%, PHD: 52%, UC HDC: 54%, VA OMOP: 94%,) and Spain (SIDIAP: 54%, HM: 60%), but were predominantly female in South Korea (HIRA: 60%). Age profiles varied across data sources. Prevalence of asthma ranged from 4% to 15%, diabetes from 13% to 43%, and hypertensive disorder from 24% to 70% across data sources. Between 14% and 33% were taking drugs acting on the renin-angiotensin system in the 30 days prior to hospitalisation. Compared to 81,596 individuals hospitalised with influenza in 2014-19, patients admitted with COVID-19 were more typically male, younger, and healthier, with fewer comorbidities and lower medication use. Conclusions We provide a detailed characterisation of patients hospitalised with COVID-19. Protecting groups known to be vulnerable to influenza is a useful starting point to minimize the number of hospital admissions needed for COVID-19. However, such strategies will also likely need to be broadened so as to reflect the particular characteristics of individuals hospitalised with COVID-19.

The impact of low- versus high-intensity surveillance cystoscopy on surgical care and cancer outcomes in patients with high-risk non-muscle-invasive bladder cancer (NMIBC)

Purpose

To assess the association of low- vs. guideline-recommended high-intensity cystoscopic surveillance with outcomes among patients with high-risk non-muscle invasive bladder cancer (NMIBC).

Materials & methods

A retrospective cohort study of Veterans Affairs patients diagnosed with high-risk NMIBC between 2005 and 2011 with follow-up through 2014. Patients were categorized by number of surveillance cystoscopies over two years following diagnosis: low- (1–5) vs. high-intensity (6 or more) surveillance. Propensity score adjusted regression models were used to assess the association of low-intensity cystoscopic surveillance with frequency of transurethral resections, and risk of progression to invasive disease and bladder cancer death.

Results

Among 1,542 patients, 520 (33.7%) underwent low-intensity cystoscopic surveillance. Patients undergoing low-intensity surveillance had fewer transurethral resections (37 vs. 99 per 100 person-years; p<0.001). Risk of death from bladder cancer did not differ significantly by low (cumulative incidence [CIn] 8.4% [95% CI 6.5–10.9) at 5 years) vs. high-intensity surveillance (CIn 9.1% [95% CI 7.4–11.2) at 5 years, p = 0.61). Low vs. high-intensity surveillance was not associated with increased risk of bladder cancer death among patients with Ta (CIn 5.7% vs. 8.2% at 5 years p = 0.24) or T1 disease at diagnosis (CIn 10.2% vs. 9.1% at 5 years, p = 0.58). Among patients with Ta disease, low-intensity surveillance was associated with decreased risk of progression to invasive disease (T1 or T2) or bladder cancer death (CIn 19.3% vs. 31.3% at 5 years, p = 0.002).

Conclusions

Patients with high-risk NMIBC undergoing low- vs. high-intensity cystoscopic surveillance underwent fewer transurethral resections, but did not experience an increased risk of progression or bladder cancer death. These findings provide a strong rationale for a clinical trial to determine whether low-intensity surveillance is comparable to high-intensity surveillance for cancer control in high-risk NMIBC.

Sex and the Diagnostic Pathway to Bladder Cancer among Veterans: No Evidence of Disparity

BACKGROUND

Longer time intervals from presentation with hematuria to bladder cancer diagnosis have been reported among women compared with men. Despite women being the fastest growing cohort within the Department of Veterans Affairs, little is known about women veterans with bladder cancer. Our objectives were to quantify the time from hematuria to bladder cancer diagnosis in Department of Veterans Affairs and assess differences between sexes.

METHODS

This was a retrospective cohort study of patients diagnosed with bladder cancer from 2001 to 2016. Included were patients with hematuria for fewer than 365 days before a bladder cancer diagnosis and who had a record of diagnostic cystoscopy after hematuria but before diagnosis. We evaluated the number of days from hematuria to diagnostic cystoscopy (clinical appraisal), cystoscopy to bladder cancer diagnosis (surgical appraisal), and hematuria to bladder cancer diagnosis (total diagnostic appraisal). We used quantile regression models to separately evaluate the effect of sex on the three appraisal intervals.

RESULTS

Data from 213 women and 24,295 men were analyzed. The median clinical appraisal time was 78 days for women and 72 for men (p = .49). The median surgical appraisal time was 32 days for women and 33 for men (p = .74). The median total diagnostic appraisal time was 135 days for women and 130 for men (p = .71). Multivariable analyses showed no differences between men and women for any of the three appraisal intervals.

CONCLUSIONS

The majority of time from hematuria to bladder cancer diagnosis is spent in clinical appraisal, but little difference was observed between men and women in Department of Veterans Affairs.

Contributors to Racial Disparities in Minimally Invasive Hysterectomy in the US Department of Veterans Affairs

BACKGROUND

Minimally invasive hysterectomy for fibroids decreases recovery time and risk of postoperative complications compared with abdominal hysterectomy. Within Veterans Affair (VA), black women with uterine fibroids are less likely to receive a minimally invasive hysterectomy than white women.

OBJECTIVE

To quantify the contributions of patient, facility, temporal and geographic factors to VA black-white disparity in minimally invasive hysterectomy.

RESEARCH DESIGN

A cross-sectional study.

SUBJECTS

Veterans with fibroids and hysterectomy performed in VA between October 1, 2012 and September 30, 2015.

MEASURES

Hysterectomy mode was defined using ICD-9 codes as minimally invasive (laparoscopic, vaginal, or robotic-assisted) versus abdominal. The authors estimated a logistic regression model with minimally invasive hysterectomy modeled as a function of 4 sets of factors: sociodemographic characteristics other than race, health risk factors, facility, and temporal and geographic factors. Using decomposition techniques, systematically substituting each white woman's characteristics for each black woman's characteristics, then recalculating the predicted probability of minimally invasive hysterectomy for black women for each possible combination of factors, we quantified the contribution of each set of factors to observed disparities in minimally invasive hysterectomy.

RESULTS

Among 1255 veterans with fibroids who had a hysterectomy at a VA, 61% of black women and 39% of white women had an abdominal hysterectomy. Our models indicated there were 99 excess abdominal hysterectomies among black women. The majority (n=77) of excess abdominal hysterectomies were unexplained by measured sociodemographic factors beyond race, health risk factors, facility, and temporal or geographic trends.

CONCLUSION

Closer examination of the equity of VA gynecology care and ways in which the VA can work to ensure equitable care for all women veterans is necessary.

Incrementally Transforming Electronic Medical Records into the Observational Medical Outcomes Partnership Common Data Model: A Multidimensional Quality Assurance Approach

BACKGROUND

The development and adoption of health care common data models (CDMs) has addressed some of the logistical challenges of performing research on data generated from disparate health care systems by standardizing data representations and leveraging standardized terminology to express clinical information consistently. However, transforming a data system into a CDM is not a trivial task, and maintaining an operational, enterprise capable CDM that is incrementally updated within a data warehouse is challenging.

OBJECTIVES

To develop a quality assurance (QA) process and code base to accompany our incremental transformation of the Department of Veterans Affairs Corporate Data Warehouse health care database into the Observational Medical Outcomes Partnership (OMOP) CDM to prevent incremental load errors.

METHODS

We designed and implemented a multistage QA) approach centered on completeness, value conformance, and relational conformance data-quality elements. For each element we describe key incremental load challenges, our extract, transform, and load (ETL) solution of data to overcome those challenges, and potential impacts of incremental load failure.

RESULTS

Completeness and value conformance data-quality elements are most affected by incremental changes to the CDW, while updates to source identifiers impact relational conformance. ETL failures surrounding these elements lead to incomplete and inaccurate capture of clinical concepts as well as data fragmentation across patients, providers, and locations.

CONCLUSION

Development of robust QA processes supporting accurate transformation of OMOP and other CDMs from source data is still in evolution, and opportunities exist to extend the existing QA framework and tools used for incremental ETL QA processes.