Publications by authors named "Patrick Ryan"

345 Publications

Phenotype Concept Set Construction from Concept Pair Likelihoods.

AMIA Annu Symp Proc 2020 25;2020:1080-1089. Epub 2021 Jan 25.

Columbia University, New York, NY.

Phenotyping algorithms are essential tools for conducting clinical research on observational data. Manually devel- oped phenotyping algorithms, such as those curated within the eMERGE (electronic Medical Records and Genomics) Network, represent the gold standard but are time consuming to create. In this work, we propose a framework for learning from the structure of eMERGE phenotype concept sets to assist construction of novel phenotype definitions. We use eMERGE phenotypes as a source of reference concept sets and engineer rich features characterizing the con- cept pairs within each set. We treat these pairwise relationships as edges in a concept graph, train models to perform edge prediction, and identify candidate phenotype concept sets as highly connected subgraphs. Candidate concept sets may then be interrogated and composed to construct novel phenotype definitions.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8075469PMC
January 2021

Characterizing database granularity using SNOMED-CT hierarchy.

AMIA Annu Symp Proc 2020 25;2020:983-992. Epub 2021 Jan 25.

Columbia University, New York, NY, USA.

Multi-center observational studies require recognition and reconciliation of differences in patient representations arising from underlying populations, disparate coding practices and specifics of data capture. This leads to different granularity or detail of concepts representing the clinical facts. For researchers studying certain populations of interest, it is important to ensure that concepts at the right level are used for the definition of these populations. We studied the granularity of concepts within 22 data sources in the OHDSI network and calculated a composite granularity score for each dataset. Three alternative SNOMED-based approaches for such score showed consistency in classifying data sources into three levels of granularity (low, moderate and high), which correlated with the provenance of data and country of origin. However, they performed unsatisfactorily in ordering data sources within these groups and showed inconsistency for small data sources. Further studies on examining approaches to data source granularity are needed.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8075504PMC
January 2021

Drawing Reproducible Conclusions from Observational Clinical Data with OHDSI.

Yearb Med Inform 2021 Apr 21. Epub 2021 Apr 21.

Observational Health Data Sciences and Informatics, New York, New York, USA.

Objective: The current observational research literature shows extensive publication bias and contradiction. The Observational Health Data Sciences and Informatics (OHDSI) initiative seeks to improve research reproducibility through open science.

Methods: OHDSI has created an international federated data source of electronic health records and administrative claims that covers nearly 10% of the world's population. Using a common data model with a practical schema and extensive vocabulary mappings, data from around the world follow the identical format. OHDSI's research methods emphasize reproducibility, with a large-scale approach to addressing confounding using propensity score adjustment with extensive diagnostics; negative and positive control hypotheses to test for residual systematic error; a variety of data sources to assess consistency and generalizability; a completely open approach including protocol, software, models, parameters, and raw results so that studies can be externally verified; and the study of many hypotheses in parallel so that the operating characteristics of the methods can be assessed.

Results: OHDSI has already produced findings in areas like hypertension treatment that are being incorporated into practice, and it has produced rigorous studies of COVID-19 that have aided government agencies in their treatment decisions, that have characterized the disease extensively, that have estimated the comparative effects of treatments, and that the predict likelihood of advancing to serious complications.

Conclusions: OHDSI practices open science and incorporates a series of methods to address reproducibility. It has produced important results in several areas, including hypertension therapy and COVID-19 research.
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http://dx.doi.org/10.1055/s-0041-1726481DOI Listing
April 2021

Identifying sensitive windows of airborne lead exposure associated with behavioral outcomes at age 12.

Environ Epidemiol 2021 Apr 16;5(2):e144. Epub 2021 Mar 16.

Division of Biostatistics and Epidemiology, Cincinnati Children's Hospital Medical Center.

Despite the precipitous decline of airborne lead concentrations following the removal of lead in gasoline, lead is still detectable in ambient air in most urban areas. Few studies, however, have examined the health effects of contemporary airborne lead concentrations in children.

Methods: We estimated monthly air lead exposure among 263 children (Cincinnati Childhood Allergy and Air Pollution Study; Cincinnati, OH; 2001-2005) using temporally scaled predictions from a validated land use model and assessed neurobehavioral outcomes at age 12 years using the parent-completed Behavioral Assessment System for Children, 2nd edition. We used distributed lag models to estimate the effect of airborne lead exposure on behavioral outcomes while adjusting for potential confounding by maternal education, community-level deprivation, blood lead concentrations, greenspace, and traffic related air pollution.

Results: We identified sensitive windows during mid- and late childhood for increased anxiety and atypicality scores, whereas sensitive windows for increased aggression and attention problems were identified immediately following birth. The strongest effect was at age 12, where a 1 ng/m increase in airborne lead exposure was associated with a 3.1-point (95% confidence interval: 0.4, 5.7) increase in anxiety scores. No sensitive windows were identified for depression, somatization, conduct problems, hyperactivity, or withdrawal behaviors.

Conclusions: We observed associations between exposure to airborne lead concentrations and poor behavioral outcomes at concentrations 10 times lower than the National Ambient Air Quality Standards set by the US Environmental Protection Agency.
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http://dx.doi.org/10.1097/EE9.0000000000000144DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8043737PMC
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

Characterizing the incidence of adverse events of special interest for COVID-19 vaccines across eight countries: a multinational network cohort study.

medRxiv 2021 Mar 28. Epub 2021 Mar 28.

Background: As large-scale immunization programs against COVID-19 proceed around the world, safety signals will emerge that need rapid evaluation. We report population-based, age- and sex- specific background incidence rates of potential adverse events of special interest (AESI) in eight countries using thirteen databases.

Methods: This multi-national network cohort study included eight electronic medical record and five administrative claims databases from Australia, France, Germany, Japan, Netherlands, Spain, the United Kingdom, and the United States, mapped to a common data model. People observed for at least 365 days before 1 January 2017, 2018, or 2019 were included. We based study outcomes on lists published by regulators: acute myocardial infarction, anaphylaxis, appendicitis, Bell's palsy, deep vein thrombosis, disseminated intravascular coagulation, encephalomyelitis, Guillain-Barre syndrome, hemorrhagic and non-hemorrhagic stroke, immune thrombocytopenia, myocarditis/pericarditis, narcolepsy, pulmonary embolism, and transverse myelitis. We calculated incidence rates stratified by age, sex, and database. We pooled rates across databases using random effects meta-analyses. We classified meta-analytic estimates into Council of International Organizations of Medical Sciences categories: very common, common, uncommon, rare, or very rare.

Findings: We analysed 126,661,070 people. Rates varied greatly between databases and by age and sex. Some AESI (e.g., myocardial infarction, Guillain-Barre syndrome) increased with age, while others (e.g., anaphylaxis, appendicitis) were more common in young people. As a result, AESI were classified differently according to age. For example, myocardial infarction was very rare in children, rare in women aged 35-54 years, uncommon in men and women aged 55-84 years, and common in those aged ≥85 years.

Interpretation: We report robust baseline rates of prioritised AESI across 13 databases. Age, sex, and variation between databases should be considered if background AESI rates are compared to event rates observed with COVID-19 vaccines.
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http://dx.doi.org/10.1101/2021.03.25.21254315DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8010764PMC
March 2021

Source-specific contributions of particulate matter to asthma-related pediatric emergency department utilization.

Health Inf Sci Syst 2021 Dec 10;9(1):12. Epub 2021 Mar 10.

Division of Biostatistics and Epidemiology, Cincinnati Children's Hospital Medical Center, 3333 Burnet Ave, Cincinnati, OH 45229 USA.

Ambient particulate matter smaller than 2.5 μm (PM) is associated with different chronic diseases. It is crucial to identify the sources of ambient particulate matter to reduce the impact on health. Still, only a few studies have been linked with specific ambient particulate matter sources. In this study, we estimated the contributions of sources of PM and examined their association with daily asthma hospital utilization in Cincinnati, Ohio, USA. We used a model-based clustering method to group days with similar source-specific contributions into six distinct clusters. Specifically, elevated PM concentrations occurring on days characterized by low coal combustion contributions showed a significantly reduced risk of hospital utilization for asthma (rate ratio: 0.86, 95% CI: [0.77, 0.95]) compared to other clusters. Reducing coal combustion contribution to PM levels could be an effective intervention for lowering asthma-related hospital utilization.

Supplementary Information: The online version contains supplementary material available at 10.1007/s13755-021-00141-z.
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http://dx.doi.org/10.1007/s13755-021-00141-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7947163PMC
December 2021

Comprehensive Comparative Effectiveness and Safety of First-Line β-Blocker Monotherapy in Hypertensive Patients: A Large-Scale Multicenter Observational Study.

Hypertension 2021 May 29;77(5):1528-1538. Epub 2021 Mar 29.

Division of Cardiology, Severance Cardiovascular Hospital and Integrated Research Center for Cerebrovascular and Cardiovascular Diseases (S.P.), Yonsei University College of Medicine, Seoul, Korea.

[Figure: see text].
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http://dx.doi.org/10.1161/HYPERTENSIONAHA.120.16402DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8035236PMC
May 2021

Developing and Implementing a Dedicated Prone Positioning Team for Mechanically Ventilated ARDS Patients During the COVID-19 Crisis.

Jt Comm J Qual Patient Saf 2021 Feb 26. Epub 2021 Feb 26.

Background: The spread of the COVID-19 pandemic in China demonstrated at an early stage the high rate of moderate to severe acute respiratory distress syndrome (ARDS) in the patient population. An intervention that has proved beneficial is the use of prone positioning (PP) for mechanically ventilated patients with ARDS. In one institution, PP was practiced in the medical ICU for this population. However, with the dramatically increasing patient load, staff anticipated that greater capacity to provide this treatment to all qualifying patients would be required.

Methods: A group of physical therapists and occupational therapists (PT/OTs) with ICU experience was redeployed from their regular roles to receive training in PP from an experienced medical ICU (MICU) RN. After intensive training, the team was ready to provide PP to patients. As the workload increased, additional PT/OTs were recruited to the team. A coordinating structure comprising attending pulmonologists screened and advised on appropriate patients. A communication and feedback structure was also implemented.

Results: Over a period of seven weeks, the team provided PP to more than 100 patients, with 577 individual interventions in a total of 14 ICUs and one emergency department. There were no major airway or central venous access complications, and only one anterior pressure injury was recorded.

Conclusion: The rapid implementation of an interdisciplinary PP team in a crisis situation is feasible. It can provide a safe and efficient alternative to adding to the workload of an overloaded nursing staff.
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http://dx.doi.org/10.1016/j.jcjq.2021.02.007DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7907735PMC
February 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

Associations of observed home dampness and mold with the fungal and bacterial dust microbiomes.

Environ Sci Process Impacts 2021 Mar 1;23(3):491-500. Epub 2021 Mar 1.

Department of Environmental Health, University of Cincinnati, P.O. Box 670056, Cincinnati, OH, USA.

The objective of this analysis was to examine and compare quantitative metrics of observed dampness and mold, including visible mold and moisture damage, and fungal and bacterial microbiomes. In-home visits were conducted at age 7 for children enrolled in the Cincinnati Childhood Allergy and Air Pollution Study. Trained study staff evaluated the primary residence and measured total areas of visible moisture and mold damage in the home. Floor dust was collected and archived. Archived dust samples collected from each home (n = 178) were extracted and analyzed using bacterial (16S rRNA gene) and fungal (internal transcribed spacer region) sequencing. Fungi were also divided into moisture requirement categories of xerophiles, mesophiles, and hydrophiles. Data analyses used Spearman's correlation, Kruskal-Wallis, Permanova, DESeq, and negative binomial regression models. Comparing high moisture or mold damage to no damage, five fungal species and two bacterial species had higher concentrations (absolute abundance) and six fungal species and three bacterial species had lower concentrations. Hydrophilic and mesophilic fungi showed significant dose-related increases with increasing moisture damage and mold damage, respectively. When comparing alpha or beta diversity of fungi and bacteria across mold and moisture damage levels, no significant associations or differences were found. Mold and moisture damage did not affect diversity of fungal and bacterial microbiomes. Instead, both kinds of damage were associated with changes in species composition of both bacterial and fungal microbiomes, indicating that fungal and bacterial communities in the home might be influenced by one another as well as by mold or moisture in the home.
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http://dx.doi.org/10.1039/d0em00505cDOI Listing
March 2021

Dynamic histone acetylation in floral volatile synthesis and emission in petunia flowers.

J Exp Bot 2021 May;72(10):3704-3722

Department of Horticulture and Landscape Architecture, Purdue University, West Lafayette, IN 47907,USA.

Biosynthesis of secondary metabolites relies on primary metabolic pathways to provide precursors, energy, and cofactors, thus requiring coordinated regulation of primary and secondary metabolic networks. However, to date, it remains largely unknown how this coordination is achieved. Using Petunia hybrida flowers, which emit high levels of phenylpropanoid/benzenoid volatile organic compounds (VOCs), we uncovered genome-wide dynamic deposition of histone H3 lysine 9 acetylation (H3K9ac) during anthesis as an underlying mechanism to coordinate primary and secondary metabolic networks. The observed epigenome reprogramming is accompanied by transcriptional activation at gene loci involved in primary metabolic pathways that provide precursor phenylalanine, as well as secondary metabolic pathways to produce volatile compounds. We also observed transcriptional repression among genes involved in alternative phenylpropanoid branches that compete for metabolic precursors. We show that GNAT family histone acetyltransferase(s) (HATs) are required for the expression of genes involved in VOC biosynthesis and emission, by using chemical inhibitors of HATs, and by knocking down a specific HAT gene, ELP3, through transient RNAi. Together, our study supports that regulatory mechanisms at chromatin level may play an essential role in activating primary and secondary metabolic pathways to regulate VOC synthesis in petunia flowers.
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http://dx.doi.org/10.1093/jxb/erab072DOI Listing
May 2021

Comparative Effectiveness of Famotidine in Hospitalized COVID-19 Patients.

Am J Gastroenterol 2021 Jan 28. Epub 2021 Jan 28.

Janssen Research & Development, LLC, Titusville, New Jersey, USA; Johnson & Johnson, Titusville, New Jersey, USA.

Introduction: Famotidine has been posited as a potential treatment for coronavirus disease 2019 (COVID-19). We compared the incidence of COVID-19 outcomes (i.e., death and death or intensive services use) among hospitalized famotidine users vs proton pump inhibitors (PPIs) users, hydroxychloroquine users, or famotidine nonusers separately.

Methods: We constructed a retrospective cohort study using data from COVID-19 Premier Hospital electronic health records. The study population was COVID-19 hospitalized patients aged 18 years or older. Famotidine, PPI, and hydroxychloroquine exposure groups were defined as patients dispensed any medication containing 1 of the 3 drugs on the day of admission. The famotidine nonuser group was derived from the same source population with no history of exposure to any drug with famotidine as an active ingredient before or on the day of admission. Time at risk was defined based on the intention-to-treat principle starting 1 day after admission to 30 days after admission. For each study comparison group, we fit a propensity score model through large-scale regularized logistic regression. The outcome was modeled using a survival model.

Results: We identified 2,193 users of PPI, 5,950 users of the hydroxychloroquine, 1,816 users of famotidine, and 26,820 nonfamotidine users. After propensity score stratification, the hazard ratios (HRs) for death were as follows: famotidine vs no famotidine HR 1.03 (0.89-1.18), vs PPIs: HR 1.14 (0.94-1.39), and vs hydroxychloroquine: 1.03 (0.85-1.24). Similar results were observed for the risk of death or intensive services use.

Discussion: We found no evidence of a reduced risk of COVID-19 outcomes among hospitalized COVID-19 patients who used famotidine compared with those who did not or compared with PPI or hydroxychloroquine users.
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http://dx.doi.org/10.14309/ajg.0000000000001153DOI Listing
January 2021

An empirical analysis of dealing with patients who are lost to follow-up when developing prognostic models using a cohort design.

BMC Med Inform Decis Mak 2021 02 6;21(1):43. Epub 2021 Feb 6.

Janssen Research and Development, Titusville, NJ, USA.

Background: Researchers developing prediction models are faced with numerous design choices that may impact model performance. One key decision is how to include patients who are lost to follow-up. In this paper we perform a large-scale empirical evaluation investigating the impact of this decision. In addition, we aim to provide guidelines for how to deal with loss to follow-up.

Methods: We generate a partially synthetic dataset with complete follow-up and simulate loss to follow-up based either on random selection or on selection based on comorbidity. In addition to our synthetic data study we investigate 21 real-world data prediction problems. We compare four simple strategies for developing models when using a cohort design that encounters loss to follow-up. Three strategies employ a binary classifier with data that: (1) include all patients (including those lost to follow-up), (2) exclude all patients lost to follow-up or (3) only exclude patients lost to follow-up who do not have the outcome before being lost to follow-up. The fourth strategy uses a survival model with data that include all patients. We empirically evaluate the discrimination and calibration performance.

Results: The partially synthetic data study results show that excluding patients who are lost to follow-up can introduce bias when loss to follow-up is common and does not occur at random. However, when loss to follow-up was completely at random, the choice of addressing it had negligible impact on model discrimination performance. Our empirical real-world data results showed that the four design choices investigated to deal with loss to follow-up resulted in comparable performance when the time-at-risk was 1-year but demonstrated differential bias when we looked into 3-year time-at-risk. Removing patients who are lost to follow-up before experiencing the outcome but keeping patients who are lost to follow-up after the outcome can bias a model and should be avoided.

Conclusion: Based on this study we therefore recommend (1) developing models using data that includes patients that are lost to follow-up and (2) evaluate the discrimination and calibration of models twice: on a test set including patients lost to follow-up and a test set excluding patients lost to follow-up.
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http://dx.doi.org/10.1186/s12911-021-01408-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7866757PMC
February 2021

Quantifying bias in epidemiologic studies evaluating the association between acetaminophen use and cancer.

Regul Toxicol Pharmacol 2021 Mar 15;120:104866. Epub 2021 Jan 15.

Department of Epidemiology, Johnson & Johnson, Titusville, NJ, USA.

Many observational studies explore the association between acetaminophen and cancer, but known limitations such as vulnerability to channeling, protopathic bias, and uncontrolled confounding hamper the interpretability of results. To help understand the potential magnitude of bias, we identify key design choices in these observational studies and specify 10 study design variants that represent different combinations of these design choices. We evaluate these variants by applying them to 37 negative controls - outcome presumed not to be caused by acetaminophen - as well as 4 cancer outcomes in the Clinical Practice Research Datalink (CPRD) database. The estimated odds and hazards ratios for the negative controls show substantial bias in the evaluated design variants, with far fewer of the 95% confidence intervals containing 1 than the nominal 95% expected for negative controls. The effect-size estimates for the cancer outcomes are comparable to those observed for the negative controls. A comparison of exposed and unexposed reveals many differences at baseline for which most studies do not correct. We observe that the design choices made in many of the published observational studies can lead to substantial bias. Thus, caution in the interpretation of published studies of acetaminophen and cancer is recommended.
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http://dx.doi.org/10.1016/j.yrtph.2021.104866DOI Listing
March 2021

Quantifying bias in epidemiologic studies evaluating the association between acetaminophen use and cancer.

Regul Toxicol Pharmacol 2021 Mar 15;120:104866. Epub 2021 Jan 15.

Department of Epidemiology, Johnson & Johnson, Titusville, NJ, USA.

Many observational studies explore the association between acetaminophen and cancer, but known limitations such as vulnerability to channeling, protopathic bias, and uncontrolled confounding hamper the interpretability of results. To help understand the potential magnitude of bias, we identify key design choices in these observational studies and specify 10 study design variants that represent different combinations of these design choices. We evaluate these variants by applying them to 37 negative controls - outcome presumed not to be caused by acetaminophen - as well as 4 cancer outcomes in the Clinical Practice Research Datalink (CPRD) database. The estimated odds and hazards ratios for the negative controls show substantial bias in the evaluated design variants, with far fewer of the 95% confidence intervals containing 1 than the nominal 95% expected for negative controls. The effect-size estimates for the cancer outcomes are comparable to those observed for the negative controls. A comparison of exposed and unexposed reveals many differences at baseline for which most studies do not correct. We observe that the design choices made in many of the published observational studies can lead to substantial bias. Thus, caution in the interpretation of published studies of acetaminophen and cancer is recommended.
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http://dx.doi.org/10.1016/j.yrtph.2021.104866DOI Listing
March 2021

How Confident Are We about Observational Findings in Healthcare: A Benchmark Study.

Harv Data Sci Rev 2020 31;2(1). Epub 2020 Jan 31.

Observational Health Data Sciences and Informatics.

Healthcare professionals increasingly rely on observational healthcare data, such as administrative claims and electronic health records, to estimate the causal effects of interventions. However, limited prior studies raise concerns about the real-world performance of the statistical and epidemiological methods that are used. We present the "OHDSI Methods Benchmark" that aims to evaluate the performance of effect estimation methods on real data. The benchmark comprises a gold standard, a set of metrics, and a set of open source software tools. The gold standard is a collection of real negative controls (drug-outcome pairs where no causal effect appears to exist) and synthetic positive controls (drug-outcome pairs that augment negative controls with simulated causal effects). We apply the benchmark using four large healthcare databases to evaluate methods commonly used in practice: the new-user cohort, self-controlled cohort, case-control, case-crossover, and self-controlled case series designs. The results confirm the concerns about these methods, showing that for most methods the operating characteristics deviate considerably from nominal levels. For example, in most contexts, only half of the 95% confidence intervals we calculated contain the corresponding true effect size. We previously developed an "empirical calibration" procedure to restore these characteristics and we also evaluate this procedure. While no one method dominates, self-controlled methods such as the empirically calibrated self-controlled case series perform well across a wide range of scenarios.
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http://dx.doi.org/10.1162/99608f92.147cc28eDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7755157PMC
January 2020

Residential surrounding greenness and self-reported symptoms of anxiety and depression in adolescents.

Environ Res 2021 03 17;194:110628. Epub 2020 Dec 17.

University of Cincinnati, College of Medicine, Department of Pediatrics, Cincinnati, OH, USA; Cincinnati Children's Hospital Medical Center, Division of Biostatistics and Epidemiology, Cincinnati, OH, USA; University of Cincinnati, College of Medicine, Department of Environmental and Public Health Sciences, Cincinnati, OH, USA. Electronic address:

Background: Evidence on the relationship between exposure to greenness and adolescent mental health is limited. The purpose of this study was to examine the association between greenness throughout childhood and mental health at age 12 years.

Methods: We assessed greenness using the satellite-based measure of Normalized Difference Vegetation Index (NDVI) within 200m, 400m, and 800m of home address at birth, age 12 years, and across childhood (averaged for each year from birth to age 12) among the Cincinnati Childhood Allergy and Air Pollution Study (CCAAPS) cohort. Self-reported symptoms of anxiety and depression were assessed at age 12 years using the Spence Children's Anxiety Scale (SCAS) and Children's Depression Inventory 2 (CDI 2), respectively. Associations were estimated using linear regression, adjusting for covariates including traffic-related air pollution, neurological hazard exposure, blood lead level, household income, and community deprivation.

Results: In adjusted models, NDVI was largely not associated with self-reported anxiety and depression symptoms, except for the SCAS separation anxiety subscale at 400m and 800m (0.1 unit increase mean NDVI 400m: β = -0.97, 95% CI: -1.86, -0.07; 800m: β = -1.33, 95% CI: -2.32, -0.34).

Conclusion: While we found no direct relationship between greenness and overall symptoms of anxiety and depression in adolescents upon adjustment for relevant covariates at the 200m distance, greenness may lesson symptoms of separation anxiety within 400m and 800m distance from the home address at age 12 years. Future research should examine mechanisms for these relationships at the community- and individual-level.
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http://dx.doi.org/10.1016/j.envres.2020.110628DOI Listing
March 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

The potential of dietary treatment in patients with glycogen storage disease type IV.

J Inherit Metab Dis 2020 Dec 17. Epub 2020 Dec 17.

Glycogen Storage Disease Program, Connecticut Children's Medical Center, Hartford, Connecticut, USA.

There is paucity of literature on dietary treatment in glycogen storage disease (GSD) type IV and formal guidelines are not available. Traditionally, liver transplantation was considered the only treatment option for GSD IV. In light of the success of dietary treatment for the other hepatic forms of GSD, we have initiated this observational study to assess the outcomes of medical diets, which limit the accumulation of glycogen. Clinical, dietary, laboratory, and imaging data for 15 GSD IV patients from three centres are presented. Medical diets may have the potential to delay or prevent liver transplantation, improve growth and normalize serum aminotransferases. Individual care plans aim to avoid both hyperglycaemia, hypoglycaemia and/or hyperketosis, to minimize glycogen accumulation and catabolism, respectively. Multidisciplinary monitoring includes balancing between traditional markers of metabolic control (ie, growth, liver size, serum aminotransferases, glucose homeostasis, lactate, and ketones), liver function (ie, synthesis, bile flow and detoxification of protein), and symptoms and signs of portal hypertension.
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http://dx.doi.org/10.1002/jimd.12339DOI Listing
December 2020

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.

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

Towards clinical data-driven eligibility criteria optimization for interventional COVID-19 clinical trials.

J Am Med Inform Assoc 2021 01;28(1):14-22

Department of Biomedical Informatics, Columbia University, New York, New York, USA.

Objective: This research aims to evaluate the impact of eligibility criteria on recruitment and observable clinical outcomes of COVID-19 clinical trials using electronic health record (EHR) data.

Materials And Methods: On June 18, 2020, we identified frequently used eligibility criteria from all the interventional COVID-19 trials in ClinicalTrials.gov (n = 288), including age, pregnancy, oxygen saturation, alanine/aspartate aminotransferase, platelets, and estimated glomerular filtration rate. We applied the frequently used criteria to the EHR data of COVID-19 patients in Columbia University Irving Medical Center (CUIMC) (March 2020-June 2020) and evaluated their impact on patient accrual and the occurrence of a composite endpoint of mechanical ventilation, tracheostomy, and in-hospital death.

Results: There were 3251 patients diagnosed with COVID-19 from the CUIMC EHR included in the analysis. The median follow-up period was 10 days (interquartile range 4-28 days). The composite events occurred in 18.1% (n = 587) of the COVID-19 cohort during the follow-up. In a hypothetical trial with common eligibility criteria, 33.6% (690/2051) were eligible among patients with evaluable data and 22.2% (153/690) had the composite event.

Discussion: By adjusting the thresholds of common eligibility criteria based on the characteristics of COVID-19 patients, we could observe more composite events from fewer patients.

Conclusions: This research demonstrated the potential of using the EHR data of COVID-19 patients to inform the selection of eligibility criteria and their thresholds, supporting data-driven optimization of participant selection towards improved statistical power of COVID-19 trials.
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http://dx.doi.org/10.1093/jamia/ocaa276DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7798960PMC
January 2021

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

Association of Ticagrelor vs Clopidogrel With Net Adverse Clinical Events in Patients With Acute Coronary Syndrome Undergoing Percutaneous Coronary Intervention.

JAMA 2020 10;324(16):1640-1650

Center for Outcomes Research and Evaluation, Yale New Haven Hospital, New Haven, Connecticut.

Importance: Current guidelines recommend ticagrelor as the preferred P2Y12 platelet inhibitor for patients with acute coronary syndrome (ACS), primarily based on a single large randomized clinical trial. The benefits and risks associated with ticagrelor vs clopidogrel in routine practice merits attention.

Objective: To determine the association of ticagrelor vs clopidogrel with ischemic and hemorrhagic events in patients undergoing percutaneous coronary intervention (PCI) for ACS in clinical practice.

Design, Setting, And Participants: A retrospective cohort study of patients with ACS who underwent PCI and received ticagrelor or clopidogrel was conducted using 2 United States electronic health record-based databases and 1 nationwide South Korean database from November 2011 to March 2019. Patients were matched using a large-scale propensity score algorithm, and the date of final follow-up was March 2019.

Exposures: Ticagrelor vs clopidogrel.

Main Outcomes And Measures: The primary end point was net adverse clinical events (NACE) at 12 months, composed of ischemic events (recurrent myocardial infarction, revascularization, or ischemic stroke) and hemorrhagic events (hemorrhagic stroke or gastrointestinal bleeding). Secondary outcomes included NACE or mortality, all-cause mortality, ischemic events, hemorrhagic events, individual components of the primary outcome, and dyspnea at 12 months. The database-level hazard ratios (HRs) were pooled to calculate summary HRs by random-effects meta-analysis.

Results: After propensity score matching among 31 290 propensity-matched pairs (median age group, 60-64 years; 29.3% women), 95.5% of patients took aspirin together with ticagrelor or clopidogrel. The 1-year risk of NACE was not significantly different between ticagrelor and clopidogrel (15.1% [3484/23 116 person-years] vs 14.6% [3290/22 587 person-years]; summary HR, 1.05 [95% CI, 1.00-1.10]; P = .06). There was also no significant difference in the risk of all-cause mortality (2.0% for ticagrelor vs 2.1% for clopidogrel; summary HR, 0.97 [95% CI, 0.81-1.16]; P = .74) or ischemic events (13.5% for ticagrelor vs 13.4% for clopidogrel; summary HR, 1.03 [95% CI, 0.98-1.08]; P = .32). The risks of hemorrhagic events (2.1% for ticagrelor vs 1.6% for clopidogrel; summary HR, 1.35 [95% CI, 1.13-1.61]; P = .001) and dyspnea (27.3% for ticagrelor vs 22.6% for clopidogrel; summary HR, 1.21 [95% CI, 1.17-1.26]; P < .001) were significantly higher in the ticagrelor group.

Conclusions And Relevance: Among patients with ACS who underwent PCI in routine clinical practice, ticagrelor, compared with clopidogrel, was not associated with significant difference in the risk of NACE at 12 months. Because the possibility of unmeasured confounders cannot be excluded, further research is needed to determine whether ticagrelor is more effective than clopidogrel in this setting.
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http://dx.doi.org/10.1001/jama.2020.16167DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7592033PMC
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 mycobiomes and bacteriomes of sputum, saliva, and home dust.

Indoor Air 2021 Mar 7;31(2):357-368. Epub 2020 Oct 7.

Department of Environmental Health, University of Cincinnati, Cincinnati, OH, USA.

Respiratory microbiome is an understudied area of research compared to other microbiomes of the human body. The respiratory tract is exposed to an array of environmental pollutants, including microbes. Yet, we know very little about the relationship between environmental and respiratory microbiome. The primary aim of our study was to compare the mycobiomes and bacteriomes between three sample types from the same participants, including home dust, saliva, and sputum. Samples were collected from 40 adolescents in a longitudinal cohort. We analyzed the samples using 16s bacterial rDNA and ITS fungal rDNA gene sequencing, as well as quantitative PCR with universal fungal and bacterial primers. Results showed that home dust had the greatest alpha diversity between the three sample types for both bacteria and fungi. Dust had the highest total fungal load and the lowest total bacterial load. Sputum had greater bacterial diversity than saliva, but saliva had greater fungal diversity than sputum. The distribution of major bacterial phyla differed between all sample types. However, the distribution of major fungal classes differed only between sputum and saliva. Future research should examine the biological significance of the taxa found in each sample type based on microbial ecology and associations with health effects.
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http://dx.doi.org/10.1111/ina.12750DOI Listing
March 2021