Publications by authors named "Scott DuVall"

111 Publications

Improvements to PTSD quality metrics with natural language processing.

J Eval Clin Pract 2021 May 24. Epub 2021 May 24.

VA Medical Center, San Francisco, California, USA.

Rationale Aims And Objectives: As quality measurement becomes increasingly reliant on the availability of structured electronic medical record (EMR) data, clinicians are asked to perform documentation using tools that facilitate data capture. These tools may not be available, feasible, or acceptable in all clinical scenarios. Alternative methods of assessment, including natural language processing (NLP) of clinical notes, may improve the completeness of quality measurement in real-world practice. Our objective was to measure the quality of care for a set of evidence-based practices using structured EMR data alone, and then supplement those measures with additional data derived from NLP.

Method: As a case example, we studied the quality of care for posttraumatic stress disorder (PTSD) in the United States Department of Veterans Affairs (VA) over a 20-year period. We measured two aspects of PTSD care, including delivery of evidence-based psychotherapy (EBP) and associated use of measurement-based care (MBC), using structured EMR data. We then recalculated these measures using additional data derived from NLP of clinical note text.

Results: There were 2 098 389 VA patients with a diagnosis of PTSD between 2000 and 2019, 72% (n = 1 515 345) of whom had not previously received EBP for PTSD and were treated after a 2015 mandate to document EBP using templates that generate structured EMR data. Using structured EMR data, we determined that 3.2% (n = 48 004) of those patients met our EBP for PTSD quality standard between 2015 and 2019, and 48.1% (n = 23 088) received associated MBC. With the addition of NLP-derived data, estimates increased to 4.1% (n = 62 789) and 58.0% (n = 36 435), respectively.

Conclusion: Healthcare quality data can be significantly improved by supplementing structured EMR data with NLP-derived data. By using NLP, health systems may be able to fill the gaps in documentation when structured tools are not yet available or there are barriers to using them in clinical practice.
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http://dx.doi.org/10.1111/jep.13587DOI Listing
May 2021

Effectiveness and comparative effectiveness of evidence-based psychotherapies for posttraumatic stress disorder in clinical practice.

Psychol Med 2021 May 18:1-10. Epub 2021 May 18.

Mental Health Service, White River Junction VA Medical Center, and National Center for Posttraumatic Stress Disorder, Executive Division, White River Junction, VT.

Background: While evidence-based psychotherapy (EBP) for posttraumatic stress disorder (PTSD) is a first-line treatment, its real-world effectiveness is unknown. We compared cognitive processing therapy (CPT) and prolonged exposure (PE) each to an individual psychotherapy comparator group, and CPT to PE in a large national healthcare system.

Methods: We utilized effectiveness and comparative effectiveness emulated trials using retrospective cohort data from electronic medical records. Participants were veterans with PTSD initiating mental healthcare (N = 265 566). The primary outcome was PTSD symptoms measured by the PTSD Checklist (PCL) at baseline and 24-week follow-up. Emulated trials were comprised of 'person-trials,' representing 112 discrete 24-week periods of care (10/07-6/17) for each patient. Treatment group comparisons were made with generalized linear models, utilizing propensity score matching and inverse probability weights to account for confounding, selection, and non-adherence bias.

Results: There were 636 CPT person-trials matched to 636 non-EBP person-trials. Completing ⩾8 CPT sessions was associated with a 6.4-point greater improvement on the PCL (95% CI 3.1-10.0). There were 272 PE person-trials matched to 272 non-EBP person-trials. Completing ⩾8 PE sessions was associated with a 9.7-point greater improvement on the PCL (95% CI 5.4-13.8). There were 232 PE person-trials matched to 232 CPT person-trials. Those completing ⩾8 PE sessions had slightly greater, but not statistically significant, improvement on the PCL (8.3-points; 95% CI 5.9-10.6) than those completing ⩾8 CPT sessions (7.0-points; 95% CI 5.5-8.5).

Conclusions: PTSD symptom improvement was similar and modest for both EBPs. Although EBPs are helpful, research to further improve PTSD care is critical.
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http://dx.doi.org/10.1017/S0033291721001628DOI Listing
May 2021

Phenome-wide association of 1809 phenotypes and COVID-19 disease progression in the Veterans Health Administration Million Veteran Program.

PLoS One 2021 13;16(5):e0251651. Epub 2021 May 13.

Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, United States of America.

Background: The risk factors associated with the stages of Coronavirus Disease-2019 (COVID-19) disease progression are not well known. We aim to identify risk factors specific to each state of COVID-19 progression from SARS-CoV-2 infection through death.

Methods And Results: We included 648,202 participants from the Veteran Affairs Million Veteran Program (2011-). We identified characteristics and 1,809 ICD code-based phenotypes from the electronic health record. We used logistic regression to examine the association of age, sex, body mass index (BMI), race, and prevalent phenotypes to the stages of COVID-19 disease progression: infection, hospitalization, intensive care unit (ICU) admission, and 30-day mortality (separate models for each). Models were adjusted for age, sex, race, ethnicity, number of visit months and ICD codes, state infection rate and controlled for multiple testing using false discovery rate (≤0.1). As of August 10, 2020, 5,929 individuals were SARS-CoV-2 positive and among those, 1,463 (25%) were hospitalized, 579 (10%) were in ICU, and 398 (7%) died. We observed a lower risk in women vs. men for ICU and mortality (Odds Ratio (95% CI): 0.48 (0.30-0.76) and 0.59 (0.31-1.15), respectively) and a higher risk in Black vs. Other race patients for hospitalization and ICU (OR (95%CI): 1.53 (1.32-1.77) and 1.63 (1.32-2.02), respectively). We observed an increased risk of all COVID-19 disease states with older age and BMI ≥35 vs. 20-24 kg/m2. Renal failure, respiratory failure, morbid obesity, acid-base balance disorder, white blood cell diseases, hydronephrosis and bacterial infections were associated with an increased risk of ICU admissions; sepsis, chronic skin ulcers, acid-base balance disorder and acidosis were associated with mortality.

Conclusions: Older age, higher BMI, males and patients with a history of respiratory, kidney, bacterial or metabolic comorbidities experienced greater COVID-19 severity. Future studies to investigate the underlying mechanisms associated with these phenotype clusters and COVID-19 are warranted.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0251651PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8118298PMC
May 2021

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

Nat Med 2021 04 9;27(4):668-676. Epub 2021 Apr 9.

Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA.

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; IFNAR2, P = 9.8 × 10 and IL-10RB, P = 2.3 × 10) 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.
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http://dx.doi.org/10.1038/s41591-021-01310-zDOI Listing
April 2021

Alpha-1 blockers and susceptibility to COVID-19 in benign prostate hyperplasia patients : an international cohort study.

medRxiv 2021 Mar 24. Epub 2021 Mar 24.

Alpha-1 blockers, often used to treat benign prostate hyperplasia (BPH), have been hypothesized to prevent COVID-19 complications by minimising cytokine storms release. We conducted a prevalent-user active-comparator cohort study to assess association between alpha-1 blocker use and risks of three COVID-19 outcomes: diagnosis, hospitalization, and hospitalization requiring intensive services. Our study included 2.6 and 0.46 million users of alpha-1 blockers and of alternative BPH therapy during the period between November 2019 and January 2020, found in electronic health records from Spain (SIDIAP) and the United States (Department of Veterans Affairs, Columbia University Irving Medical Center, IQVIA OpenClaims, Optum DOD, Optum EHR). We estimated hazard ratios using state-of-the-art techniques to minimize potential confounding, including large-scale propensity score matching/stratification and negative control calibration. We found no differential risk for any of COVID-19 outcome, pointing to the need for further research on potential COVID-19 therapies.
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http://dx.doi.org/10.1101/2021.03.18.21253778DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8010772PMC
March 2021

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

Rheumatology (Oxford) 2021 Mar 16. Epub 2021 Mar 16.

Real-World Evidence, Trial, Barcelona, Spain, Form Support.

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.

Methods: A multinational network cohort study was conducted using electronic health records data from Columbia University Irving Medical Center (CUIMC) (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). 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. Outcomes were death and complications within 30 days of hospitalisation.

Results: We studied 133 589 patients diagnosed and 48 418 hospitalised 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 hospitalised vs diagnosed patients with COVID-19. Compared with 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% vs 6.3% to 24.6%).

Conclusions: Compared with influenza, COVID-19 is a more severe disease, leading to more complications and higher mortality.
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http://dx.doi.org/10.1093/rheumatology/keab250DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7989171PMC
March 2021

Unraveling COVID-19: a large-scale characterization of 4.5 million COVID-19 cases using CHARYBDIS.

Res Sq 2021 Mar 1. Epub 2021 Mar 1.

Routinely collected real world data (RWD) have great utility in aiding the novel coronavirus disease (COVID-19) pandemic response [1,2]. Here we present the international Observational Health Data Sciences and Informatics (OHDSI) [3] Characterizing Health Associated Risks, and Your Baseline Disease In SARS-COV-2 (CHARYBDIS) framework for standardisation and analysis of COVID-19 RWD. We conducted a descriptive cohort 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 11 June 2020 and are iteratively updated via GitHub [4]. We identified three non-mutually exclusive cohorts of 4,537,153 individuals with a clinical 886,193 , and 113,627 . All comorbidities, symptoms, medications, and outcomes are described by cohort in aggregate counts, and are available in an interactive website: https://data.ohdsi.org/Covid19CharacterizationCharybdis/. CHARYBDIS findings provide benchmarks that contribute to our understanding of COVID-19 progression, management and evolution over time. This can enable timely assessment of real-world outcomes of preventative and therapeutic options as they are introduced in clinical practice.
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http://dx.doi.org/10.21203/rs.3.rs-279400/v1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7941629PMC
March 2021

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

JMIR Med Inform 2021 Apr 5;9(4):e21547. Epub 2021 Apr 5.

Department of Biomedical Informatics, Ajou University School of Medicine, Suwon, Republic of Korea.

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.
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http://dx.doi.org/10.2196/21547DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8023380PMC
April 2021

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

LGBT Health 2021 04 24;8(3):201-208. Epub 2021 Feb 24.

Suzanne Dworak-Peck School of Social Work, University of Southern California, Los Angeles, California, USA.

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). 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. Approximately 1.4% of all VHA Veterans ( = 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. 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.
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http://dx.doi.org/10.1089/lgbt.2020.0333DOI Listing
April 2021

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.

medRxiv 2021 Feb 5. Epub 2021 Feb 5.

BIOMERIS (BIOMedical Research Informatics Solutions).

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.
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http://dx.doi.org/10.1101/2020.12.16.20247684DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7872369PMC
February 2021

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.

medRxiv 2021 Feb 5. Epub 2021 Feb 5.

BIOMERIS (BIOMedical Research Informatics Solutions).

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.
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http://dx.doi.org/10.1101/2020.12.16.20247684DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7872369PMC
February 2021

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.

medRxiv 2021 Feb 5. Epub 2021 Feb 5.

BIOMERIS (BIOMedical Research Informatics Solutions).

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.
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http://dx.doi.org/10.1101/2020.12.16.20247684DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7872369PMC
February 2021

Renin-angiotensin system blockers and susceptibility to COVID-19: an international, open science, cohort analysis.

Lancet Digit Health 2021 02 17;3(2):e98-e114. Epub 2020 Dec 17.

Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK.

Background: Angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs) have been postulated to affect susceptibility to COVID-19. Observational studies so far have lacked rigorous ascertainment adjustment and international generalisability. We aimed to determine whether use of ACEIs or ARBs is associated with an increased susceptibility to COVID-19 in patients with hypertension.

Methods: In this international, open science, cohort analysis, we used electronic health records from Spain (Information Systems for Research in Primary Care [SIDIAP]) and the USA (Columbia University Irving Medical Center data warehouse [CUIMC] and Department of Veterans Affairs Observational Medical Outcomes Partnership [VA-OMOP]) to identify patients aged 18 years or older with at least one prescription for ACEIs and ARBs (target cohort) or calcium channel blockers (CCBs) and thiazide or thiazide-like diuretics (THZs; comparator cohort) between Nov 1, 2019, and Jan 31, 2020. Users were defined separately as receiving either monotherapy with these four drug classes, or monotherapy or combination therapy (combination use) with other antihypertensive medications. We assessed four outcomes: COVID-19 diagnosis; hospital admission with COVID-19; hospital admission with pneumonia; and hospital admission with pneumonia, acute respiratory distress syndrome, acute kidney injury, or sepsis. We built large-scale propensity score methods derived through a data-driven approach and negative control experiments across ten pairwise comparisons, with results meta-analysed to generate 1280 study effects. For each study effect, we did negative control outcome experiments using a possible 123 controls identified through a data-rich algorithm. This process used a set of predefined baseline patient characteristics to provide the most accurate prediction of treatment and balance among patient cohorts across characteristics. The study is registered with the EU Post-Authorisation Studies register, EUPAS35296.

Findings: Among 1 355 349 antihypertensive users (363 785 ACEI or ARB monotherapy users, 248 915 CCB or THZ monotherapy users, 711 799 ACEI or ARB combination users, and 473 076 CCB or THZ combination users) included in analyses, no association was observed between COVID-19 diagnosis and exposure to ACEI or ARB monotherapy versus CCB or THZ monotherapy (calibrated hazard ratio [HR] 0·98, 95% CI 0·84-1·14) or combination use exposure (1·01, 0·90-1·15). ACEIs alone similarly showed no relative risk difference when compared with CCB or THZ monotherapy (HR 0·91, 95% CI 0·68-1·21; with heterogeneity of >40%) or combination use (0·95, 0·83-1·07). Directly comparing ACEIs with ARBs demonstrated a moderately lower risk with ACEIs, which was significant with combination use (HR 0·88, 95% CI 0·79-0·99) and non-significant for monotherapy (0·85, 0·69-1·05). We observed no significant difference between drug classes for risk of hospital admission with COVID-19, hospital admission with pneumonia, or hospital admission with pneumonia, acute respiratory distress syndrome, acute kidney injury, or sepsis across all comparisons.

Interpretation: No clinically significant increased risk of COVID-19 diagnosis or hospital admission-related outcomes associated with ACEI or ARB use was observed, suggesting users should not discontinue or change their treatment to decrease their risk of COVID-19.

Funding: Wellcome Trust, UK National Institute for Health Research, US National Institutes of Health, US Department of Veterans Affairs, Janssen Research & Development, IQVIA, South Korean Ministry of Health and Welfare Republic, Australian National Health and Medical Research Council, and European Health Data and Evidence Network.
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http://dx.doi.org/10.1016/S2589-7500(20)30289-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7834915PMC
February 2021

Study design and implementation of the PRecision Medicine In MEntal health Care (PRIME Care) Trial.

Contemp Clin Trials 2021 02 11;101:106247. Epub 2020 Dec 11.

VA Center for Integrated Healthcare, VAWNYHS (116N), Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, 3495 Bailey Avenue, Buffalo, NY 14215, USA. Electronic address:

Genomic testing has the potential to improve patient outcomes and reduce patient care costs by personalizing medication selection. Commercial pharmacogenetic (PGx) testing for psychotropic and other medications is widely available and promoted as a means to implement "precision medicine." Despite evidence that genetic variation affects the metabolism of psychotropic medications, the clinical utility of these test results has not been established. Moreover, implementing such testing in routine clinical care is complex, requiring informatics support and a systematic approach to patient and provider education. The PRIME Care program is designed to bridge this gap, applying both clinical trials and implementation science methods to conduct a program of research. It is centered on a large, pragmatic randomized clinical trial (RCT) in which 2000 Veterans with a major depressive disorder (MDD) and their health care providers are randomized together to receive PGx test results at the beginning of an episode of care or 6 months later. We hypothesize that providers who receive the PGx test results will prescribe an antidepressant guided by the PGx findings and Veterans whose care is guided by PGx testing will experience higher rates of remission from MDD. If the results of the trial replicate those of prior PGx studies, which provided preliminary evidence of the utility of PGx guided prescribing, it would strongly support using a precision medicine approach to treat MDD. This program of research is also evaluating dissemination influencers, other biomarkers (e.g., genetic variation associated with depression response), and the health care cost implications of PGx testing. ClinicalTrials.gov Identifier: NCT03170362.
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http://dx.doi.org/10.1016/j.cct.2020.106247DOI Listing
February 2021

Use of dialysis, tracheostomy, and extracorporeal membrane oxygenation among 240,392 patients hospitalized with COVID-19 in the United States.

medRxiv 2020 Nov 27. Epub 2020 Nov 27.

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: Six databases from the United States containing routinely-collected patient data: HealthVerity, Premier, 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: 240,392 patients hospitalized with COVID-19 were included (22,887 from HealthVerity, 139,971 from IQVIA Open Claims, 29,061 from Optum EHR, 4,336 from OPTUM SES, 36,019 from Premier, and 8,118 from VA-OMOP). Across the six databases, 9,703 (4.04% [95% CI: 3.96% to 4.11%]) patients received dialysis, 1,681 (0.70% [0.67% to 0.73%]) had a tracheostomy, and 398 (0.17% [95% CI: 0.15% to 0.18%]) patients underwent ECMO over the 30 days following hospitalization. Use of ECMO was generally concentrated among patients who were younger, male, and with fewer comorbidities except for obesity. Tracheostomy was used for a similar proportion of patients regardless of age, sex, or comorbidity. While dialysis was 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 and can be expected to continue grow given the continuing spread of the COVID-19.
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http://dx.doi.org/10.1101/2020.11.25.20229088DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7709172PMC
November 2020

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.

medRxiv 2020 Nov 27. Epub 2020 Nov 27.

Real-World Evidence, Trial Form Support, Barcelona, Spain.

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.
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http://dx.doi.org/10.1101/2020.11.24.20236802DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7709171PMC
November 2020

PCSK9 loss of function is protective against extra-coronary atherosclerotic cardiovascular disease in a large multi-ethnic cohort.

PLoS One 2020 9;15(11):e0239752. Epub 2020 Nov 9.

Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, United States of America.

Background: Therapeutic inhibition of PCSK9 protects against coronary artery disease (CAD) and ischemic stroke (IS). The impact on other diseases remains less well characterized.

Methods: We created a genetic risk score (GRS) for PCSK9 using four single nucleotide polymorphisms (SNPs) at or near the PCSK9 locus known to impact lower LDL-Cholesterol (LDL-C): rs11583680, rs11591147, rs2479409, and rs11206510. We then used our GRS to calculate weighted odds ratios reflecting the impact of a genetically determined 10 mg/dL decrease in LDL-C on several pre-specified phenotypes including CAD, IS, peripheral artery disease (PAD), abdominal aortic aneurysm (AAA), type 2 diabetes, dementia, chronic obstructive pulmonary disease, and cancer. Finally, we used our weighted GRS to perform a phenome-wide association study.

Results: Genetic and electronic health record data that passed quality control was available in 312,097 individuals, (227,490 White participants, 58,907 Black participants, and 25,700 Hispanic participants). PCSK9 mediated reduction in LDL-C was associated with a reduced risk of CAD and AAA in trans-ethnic meta-analysis (CAD OR 0.83 [95% CI 0.80-0.87], p = 6.0 x 10-21; AAA OR 0.76 [95% CI 0.68-0.86], p = 2.9 x 10-06). Significant protective effects were noted for PAD in White individuals (OR 0.83 [95% CI 0.71-0.97], p = 2.3 x 10-04) but not in other genetic ancestries. Genetically reduced PCSK9 function associated with a reduced risk of dementia in trans-ethnic meta-analysis (OR 0.86 [95% CI 0.78-0.93], p = 5.0 x 10-04).

Conclusions: Genetically reduced PCSK9 function results in a reduction in risk of several important extra-coronary atherosclerotic phenotypes in addition to known effects on CAD and IS, including PAD and AAA. We also highlight a novel reduction in risk of dementia, supporting a well-recognized vascular component to cognitive impairment and an opportunity for therapeutic repositioning.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0239752PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7652310PMC
January 2021

Determining the median effective dose of prolonged exposure therapy for veterans with posttraumatic stress disorder.

Behav Res Ther 2020 12 20;135:103756. Epub 2020 Oct 20.

San Francisco Veterans Affairs Health Care System, United States; Sierra Pacific Mental Illness Research, Education, and Clinical Center, United States; University of California San Francisco School of Medicine, United States.

Prolonged exposure therapy (PE) is an effective treatment for posttraumatic stress disorder (PTSD). Identifying metrics of treatment response can guide treatment delivery. The median effective dose represents the number of sessions at which there is a 50% probability of clinically meaningful improvement (i.e., 10-point reduction in PTSD checklist). The goal of the current study was to investigate the median effective dose of PE. We identified a cohort of Iraq and Afghanistan war veterans who received psychotherapy for PTSD in the Veterans Health Administration between 2001 and 2017. From this cohort, 10,234 veterans who received PE (as identified using natural language processing) and had ≥2 PTSD symptom measures were included in analyses. To determine how the number of PE sessions and covariates affected clinically meaningful improvement, we utilized a Cox proportional hazards regression, followed by Kaplan-Meier curves to determine the median effective dose. The median effective dose of PE was four sessions. Although some covariates were found to be statistically significant predictors of clinically meaningful improvement (e.g., age, gender, PTSD medications, and depressive disorder comorbidity), these effects were small. Clinicians and patients should consider evaluating treatment response after four sessions to determine preliminary effectiveness of PE.
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http://dx.doi.org/10.1016/j.brat.2020.103756DOI Listing
December 2020

Baseline characteristics, management, and outcomes of 55,270 children and adolescents diagnosed with COVID-19 and 1,952,693 with influenza in France, Germany, Spain, South Korea and the United States: an international network cohort study.

medRxiv 2020 Oct 30. Epub 2020 Oct 30.

To characterize the demographics, comorbidities, symptoms, in-hospital treatments, and health outcomes among children/adolescents diagnosed or hospitalized with COVID-19. Secondly, to describe health outcomes amongst children/adolescents diagnosed with previous seasonal influenza. International network cohort. Real-world data from European primary care records (France/Germany/Spain), South Korean claims and US claims and hospital databases. Diagnosed and/or hospitalized children/adolescents with COVID-19 at age <18 between January and June 2020; diagnosed with influenza in 2017-2018. Baseline demographics and comorbidities, symptoms, 30-day in-hospital treatments and outcomes including hospitalization, pneumonia, acute respiratory distress syndrome (ARDS), multi-system inflammatory syndrome (MIS-C), and death. A total of 55,270 children/adolescents diagnosed and 3,693 hospitalized with COVID-19 and 1,952,693 diagnosed with influenza were studied. Comorbidities including neurodevelopmental disorders, heart disease, and cancer were all more common among those hospitalized vs diagnosed with COVID-19. The most common COVID-19 symptom was fever. Dyspnea, bronchiolitis, anosmia and gastrointestinal symptoms were more common in COVID-19 than influenza. In-hospital treatments for COVID-19 included repurposed medications (<10%), and adjunctive therapies: systemic corticosteroids (6.8% to 37.6%), famotidine (9.0% to 28.1%), and antithrombotics such as aspirin (2.0% to 21.4%), heparin (2.2% to 18.1%), and enoxaparin (2.8% to 14.8%). Hospitalization was observed in 0.3% to 1.3% of the COVID-19 diagnosed cohort, with undetectable (N<5 per database) 30-day fatality. Thirty-day outcomes including pneumonia, ARDS, and MIS-C were more frequent in COVID-19 than influenza. Despite negligible fatality, complications including pneumonia, ARDS and MIS-C were more frequent in children/adolescents with COVID-19 than with influenza. Dyspnea, anosmia and gastrointestinal symptoms could help differential diagnosis. A wide range of medications were used for the inpatient management of pediatric COVID-19.
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http://dx.doi.org/10.1101/2020.10.29.20222083DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7605587PMC
October 2020

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.

medRxiv 2020 Oct 27. Epub 2020 Oct 27.

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.
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http://dx.doi.org/10.1101/2020.10.25.20218875DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7605581PMC
October 2020

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

Nat Commun 2020 10 6;11(1):5009. Epub 2020 Oct 6.

Clinical Pharmacology Unit, Zealand University Hospital, Køge, Denmark.

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.
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http://dx.doi.org/10.1038/s41467-020-18849-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7538555PMC
October 2020

The Utility of Clinical Notes for Sexual Minority Health Research.

Am J Prev Med 2020 11 1;59(5):755-763. Epub 2020 Oct 1.

VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, Utah; Division of Epidemiology, Department of Internal Medicine, University of Utah, Salt Lake City, Utah.

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.
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http://dx.doi.org/10.1016/j.amepre.2020.05.026DOI Listing
November 2020

Genetic Architecture of Abdominal Aortic Aneurysm in the Million Veteran Program.

Circulation 2020 Oct 28;142(17):1633-1646. Epub 2020 Sep 28.

Faculty of Medicine and Health Sciences (A.H.S., L.T., M.E.G., K.H., J.B.N.), Norwegian University of Science and Technology, Trondheim, Norway.

Background: Abdominal aortic aneurysm (AAA) is an important cause of cardiovascular mortality; however, its genetic determinants remain incompletely defined. In total, 10 previously identified risk loci explain a small fraction of AAA heritability.

Methods: We performed a genome-wide association study in the Million Veteran Program testing ≈18 million DNA sequence variants with AAA (7642 cases and 172 172 controls) in veterans of European ancestry with independent replication in up to 4972 cases and 99 858 controls. We then used mendelian randomization to examine the causal effects of blood pressure on AAA. We examined the association of AAA risk variants with aneurysms in the lower extremity, cerebral, and iliac arterial beds, and derived a genome-wide polygenic risk score (PRS) to identify a subset of the population at greater risk for disease.

Results: Through a genome-wide association study, we identified 14 novel loci, bringing the total number of known significant AAA loci to 24. In our mendelian randomization analysis, we demonstrate that a genetic increase of 10 mm Hg in diastolic blood pressure (odds ratio, 1.43 [95% CI, 1.24-1.66]; =1.6×10), as opposed to systolic blood pressure (odds ratio, 1.06 [95% CI, 0.97-1.15]; =0.2), likely has a causal relationship with AAA development. We observed that 19 of 24 AAA risk variants associate with aneurysms in at least 1 other vascular territory. A 29-variant PRS was strongly associated with AAA (odds ratio, 1.26 [95% CI, 1.18-1.36]; =2.7×10 per SD increase in PRS), independent of family history and smoking risk factors (odds ratio, 1.24 [95% CI, 1.14-1.35]; =1.27×10). Using this PRS, we identified a subset of the population with AAA prevalence greater than that observed in screening trials informing current guidelines.

Conclusions: We identify novel AAA genetic associations with therapeutic implications and identify a subset of the population at significantly increased genetic risk of AAA independent of family history. Our data suggest that extending current screening guidelines to include testing to identify those with high polygenic AAA risk, once the cost of genotyping becomes comparable with that of screening ultrasound, would significantly increase the yield of current screening at reasonable cost.
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http://dx.doi.org/10.1161/CIRCULATIONAHA.120.047544DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7580856PMC
October 2020

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

Lancet Rheumatol 2020 Nov 21;2(11):e698-e711. Epub 2020 Aug 21.

Janssen Research and Development, Titusville, NJ, USA.

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 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.
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http://dx.doi.org/10.1016/S2665-9913(20)30276-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7442425PMC
November 2020

Validating a non-invasive, ALT-based non-alcoholic fatty liver phenotype in the million veteran program.

PLoS One 2020 25;15(8):e0237430. Epub 2020 Aug 25.

Corporal Michael J. Crescenz VA Medical Center, Philadelphia, Pennsylvania, United States of America.

Background & Aims: Given ongoing challenges in non-invasive non-alcoholic liver disease (NAFLD) diagnosis, we sought to validate an ALT-based NAFLD phenotype using measures readily available in electronic health records (EHRs) and population-based studies by leveraging the clinical and genetic data in the Million Veteran Program (MVP), a multi-ethnic mega-biobank of US Veterans.

Methods: MVP participants with alanine aminotransferases (ALT) >40 units/L for men and >30 units/L for women without other causes of liver disease were compared to controls with normal ALT. Genetic variants spanning eight NAFLD risk or ALT-associated loci (LYPLAL1, GCKR, HSD17B13, TRIB1, PPP1R3B, ERLIN1, TM6SF2, PNPLA3) were tested for NAFLD associations with sensitivity analyses adjusting for metabolic risk factors and alcohol consumption. A manual EHR review assessed performance characteristics of the NAFLD phenotype with imaging and biopsy data as gold standards. Genetic associations with advanced fibrosis were explored using FIB4, NAFLD Fibrosis Score and platelet counts.

Results: Among 322,259 MVP participants, 19% met non-invasive criteria for NAFLD. Trans-ethnic meta-analysis replicated associations with previously reported genetic variants in all but LYPLAL1 and GCKR loci (P<6x10-3), without attenuation when adjusted for metabolic risk factors and alcohol consumption. At the previously reported LYPLAL1 locus, the established genetic variant did not appear to be associated with NAFLD, however the regional association plot showed a significant association with NAFLD 279kb downstream. In the EHR validation, the ALT-based NAFLD phenotype yielded a positive predictive value 0.89 and 0.84 for liver biopsy and abdominal imaging, respectively (inter-rater reliability (Cohen's kappa = 0.98)). HSD17B13 and PNPLA3 loci were associated with advanced fibrosis.

Conclusions: We validate a simple, non-invasive ALT-based NAFLD phenotype using EHR data by leveraging previously established NAFLD risk-associated genetic polymorphisms.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0237430PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7447043PMC
October 2020

Renin-angiotensin system blockers and susceptibility to COVID-19: a multinational open science cohort study.

medRxiv 2020 Jun 12. Epub 2020 Jun 12.

Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, Oxford University, Oxford, UK.

Introduction: Angiotensin converting enzyme inhibitors (ACEs) and angiotensin receptor blockers (ARBs) could influence infection risk of coronavirus disease (COVID-19). Observational studies to date lack pre-specification, transparency, rigorous ascertainment adjustment and international generalizability, with contradictory results.

Methods: Using electronic health records from Spain (SIDIAP) and the United States (Columbia University Irving Medical Center and Department of Veterans Affairs), we conducted a systematic cohort study with prevalent ACE, ARB, calcium channel blocker (CCB) and thiazide diuretic (THZ) use to determine relative risk of COVID-19 diagnosis and related hospitalization outcomes. The study addressed confounding through large-scale propensity score adjustment and negative control experiments.

Results: Following over 1.1 million antihypertensive users identified between November 2019 and January 2020, we observed no significant difference in relative COVID-19 diagnosis risk comparing ACE/ARB vs CCB/THZ monotherapy (hazard ratio: 0.98; 95% CI 0.84 - 1.14), nor any difference for mono/combination use (1.01; 0.90 - 1.15). ACE alone and ARB alone similarly showed no relative risk difference when compared to CCB/THZ monotherapy or mono/combination use. Directly comparing ACE vs. ARB demonstrated a moderately lower risk with ACE, non-significant for monotherapy (0.85; 0.69 - 1.05) and marginally significant for mono/combination users (0.88; 0.79 - 0.99). We observed, however, no significant difference between drug- classes for COVID-19 hospitalization or pneumonia risk across all comparisons.

Conclusion: There is no clinically significant increased risk of COVID-19 diagnosis or hospitalization with ACE or ARB use. Users should not discontinue or change their treatment to avoid COVID-19.
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http://dx.doi.org/10.1101/2020.06.11.20125849DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7310640PMC
June 2020

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

J Am Med Inform Assoc 2020 07;27(9):1437-1442

School of Biomedical Informatics, University of Texas, Houston, Texas, USA.

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.
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http://dx.doi.org/10.1093/jamia/ocaa145DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7337837PMC
July 2020

Cognitive Processing Therapy for Veterans with Posttraumatic Stress Disorder: What is the Median Effective Dose?

J Affect Disord 2020 08 22;273:425-433. Epub 2020 May 22.

San Francisco Veterans Affairs Health Care System; Sierra Pacific Mental Illness Research, Education, and Clinical Center; University of California San Francisco School of Medicine.

Objective: Cognitive Processing Therapy (CPT) has been disseminated in the Veterans Health Administration (VHA) to treat posttraumatic stress disorder (PTSD). Identifying the median effective dose (MED) of CPT, the number of sessions at which the probability of experiencing clinically meaningful improvement (CMI) is 50%, can assist with treatment.

Method: From a cohort of Iraq and Afghanistan war veterans who received PTSD psychotherapy in VHA between 2001-2017, veterans who received CPT with available PTSD symptom outcomes (PTSD Checklist; PCL) were identified using natural language processing (n=26,189). Cox proportional hazards regression was used to examine how number of CPT sessions, together with covariates, influenced CMI (10-point PCL reduction). Kaplan-Meier curves were plotted to determine MED.

Results: At eight sessions, there was a 50% probability of experiencing CMI. The Cox proportional hazard regression indicated a greater likelihood of CMI in fewer sessions for veterans who received individual-only CPT versus any group CPT (HR:1.31, 95%CI:1.23-1.39). Kaplan-Meier curves indicated a 50% probability of experiencing CMI at seven sessions for veterans who received individual-only CPT versus ten sessions for veterans receiving any group CPT.

Limitations: PCL data was not available for all veterans who received CPT or at each potential assessment point. Not all veterans continued in CPT until CMI was observed.

Conclusions: The MED of CPT was eight sessions. Fewer sessions were needed to reach MED for veterans who received individual versus group CPT. These results may help those who treat, research, and are recovering from PTSD through accurately anchoring treatment expectations and providing a marker of initial treatment response.
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http://dx.doi.org/10.1016/j.jad.2020.04.030DOI Listing
August 2020

Discovery of 318 new risk loci for type 2 diabetes and related vascular outcomes among 1.4 million participants in a multi-ancestry meta-analysis.

Nat Genet 2020 07 15;52(7):680-691. Epub 2020 Jun 15.

Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.

We investigated type 2 diabetes (T2D) genetic susceptibility via multi-ancestry meta-analysis of 228,499 cases and 1,178,783 controls in the Million Veteran Program (MVP), DIAMANTE, Biobank Japan and other studies. We report 568 associations, including 286 autosomal, 7 X-chromosomal and 25 identified in ancestry-specific analyses that were previously unreported. Transcriptome-wide association analysis detected 3,568 T2D associations with genetically predicted gene expression in 687 novel genes; of these, 54 are known to interact with FDA-approved drugs. A polygenic risk score (PRS) was strongly associated with increased risk of T2D-related retinopathy and modestly associated with chronic kidney disease (CKD), peripheral artery disease (PAD) and neuropathy. We investigated the genetic etiology of T2D-related vascular outcomes in the MVP and observed statistical SNP-T2D interactions at 13 variants, including coronary heart disease (CHD), CKD, PAD and neuropathy. These findings may help to identify potential therapeutic targets for T2D and genomic pathways that link T2D to vascular outcomes.
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http://dx.doi.org/10.1038/s41588-020-0637-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7343592PMC
July 2020