Publications by authors named "Christian G Reich"

Article Synopsis
  • Observational research uses patient data from various global databases, needing consistent drug exposure information for effective analysis.
  • The NLM's RxNorm and WHO's ATC classification provide drug terminology but are not effectively integrated into a unified system.
  • This research introduces a combined ATC-RxNorm drug hierarchy, facilitating drug information retrieval in extensive observational studies, and evaluates its effectiveness using real-world data.
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  • The study emphasizes the importance of real world data (RWD) for understanding and responding to the COVID-19 pandemic using a standardized approach through the CHARYBDIS framework.
  • Researchers conducted a retrospective database study across multiple countries, including the US and parts of Europe and Asia, involving over 4.5 million individuals and focusing on their clinical characteristics and outcomes.
  • Findings reveal higher diagnoses among women but more hospitalizations among men, common comorbidities like diabetes and heart disease, and key symptoms such as cough and fever; this data helps to identify trends in COVID-19 across different populations and time periods.
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  • The study aimed to develop COVID-19 prediction models using influenza data to quickly and accurately assess risks of hospital admission and death in patients diagnosed with COVID-19.
  • The researchers created three COVID-19 Estimated Risk (COVER) scores that quantify risks related to pneumonia and mortality based on historical data and validated them using a large dataset of COVID-19 patients across multiple countries.
  • They found that seven key health predictors, along with age and sex, effectively distinguished which patients were likely to face severe outcomes, achieving strong performance in model validation.
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Many patients with bipolar disorder (BD) are initially misdiagnosed with major depressive disorder (MDD) and are treated with antidepressants, whose potential iatrogenic effects are widely discussed. It is unknown whether MDD is a comorbidity of BD or its earlier stage, and no consensus exists on individual conversion predictors, delaying BD's timely recognition and treatment. We aimed to build a predictive model of MDD to BD conversion and to validate it across a multi-national network of patient databases using the standardization afforded by the Observational Medical Outcomes Partnership (OMOP) common data model.

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  • The study analyzed the demographics, cancer types, comorbidities, and outcomes of patients with a history of cancer who contracted COVID-19, comparing them to those hospitalized with influenza.
  • A total of 366,050 diagnosed patients and 119,597 hospitalized patients with COVID-19 were included, with prostate and breast cancers being the most common among the diagnosed cohort, and many patients over 65 years old having multiple health issues.
  • The findings revealed a significant occurrence of COVID-19-related deaths among cancer patients, with a range of 2% to 26% depending on hospitalization status, highlighting the need for tailored clinical care for this high-risk group.
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  • - The study aimed to compare the demographics, medical conditions, and outcomes of COVID-19 patients with obesity to those without obesity, based on data from Spain, the UK, and the US from early 2020.
  • - A total of over 600,000 diagnosed and over 160,000 hospitalized COVID-19 patients were analyzed, revealing a higher prevalence of obesity among hospitalized patients and noted that women were more frequently represented in the PLWO group.
  • - Results indicated that patients living with obesity (PLWO) had more prior medical conditions, experienced more severe COVID-19 symptoms, and required greater hospital resources compared to those without obesity, highlighting the need for tailored preventive measures.
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Objectives: To characterize the demographics, comorbidities, symptoms, in-hospital treatments, and health outcomes among children and adolescents diagnosed or hospitalized with coronavirus disease 2019 (COVID-19) and to compare them in secondary analyses with patients diagnosed with previous seasonal influenza in 2017-2018.

Methods: International network cohort using real-world data from European primary care records (France, Germany, and Spain), South Korean claims and US claims, and hospital databases. We included children and adolescents diagnosed and/or hospitalized with COVID-19 at age <18 between January and June 2020.

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  • The COVID-19 vulnerability (C-19) index was developed to predict which patients might need hospitalization for pneumonia related to COVID-19 but is at risk of bias and lacks external validation.
  • The study aimed to externally validate the C-19 index using data from various healthcare settings and target populations to determine its predictive capabilities for hospitalization due to pneumonia.
  • Results showed that while the C-19 index performed moderately well in internal validation, its external validation yielded low predictive accuracy across different countries, suggesting that it may underestimate the actual risk of hospitalization.
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Objectives: We incorporated the Korean Electronic Data Interchange (EDI) vocabulary into Observational Medical Outcomes Partnership (OMOP) vocabulary using a semi-automated process. The goal of this study was to improve the Korean EDI as a standard medical ontology in Korea.

Methods: We incorporated the EDI vocabulary into OMOP vocabulary through four main steps.

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Endocannabinoid sex differences are present in the rat hippocampus. Specifically, at perisomatic GABAergic synapses, tonic anandamide (AEA) and estrogenic-AEA signaling are active in females but not males. Furthermore, in males, hippocampal eCB function varies along the CA1 pyramidal somatodendritic axis.

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Article Synopsis
  • The study aimed to analyze the demographics, comorbidities, symptoms, treatments, and outcomes of children and adolescents diagnosed or hospitalized with COVID-19, comparing these to those diagnosed with seasonal influenza.
  • Utilizing real-world data from multiple countries including France, Germany, Spain, South Korea, and the US, the research included over 55,000 children with COVID-19 and nearly 2 million with influenza between specified periods.
  • Key findings indicate that comorbidities were more prevalent in hospitalized COVID-19 cases, fever was the most common symptom, and while hospitalization rates were low, complications like pneumonia and multi-system inflammatory syndrome were significantly more common in COVID-19 cases compared to influenza.
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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.

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Purpose: Patients with cancer are predisposed to developing chronic, comorbid conditions that affect prognosis, quality of life, and mortality. While treatment guidelines and care variations for these comorbidities have been described for the general noncancer population, less is known about real-world treatment patterns in patients with cancer. We sought to characterize the prevalence and distribution of initial treatment patterns across a large-scale data network for depression, hypertension, and type II diabetes mellitus (T2DM) among patients with cancer.

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Background: Uncertainty remains about the optimal monotherapy for hypertension, with current guidelines recommending any primary agent among the first-line drug classes thiazide or thiazide-like diuretics, angiotensin-converting enzyme inhibitors, angiotensin receptor blockers, dihydropyridine calcium channel blockers, and non-dihydropyridine calcium channel blockers, in the absence of comorbid indications. Randomised trials have not further refined this choice.

Methods: We developed a comprehensive framework for real-world evidence that enables comparative effectiveness and safety evaluation across many drugs and outcomes from observational data encompassing millions of patients, while minimising inherent bias.

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Systematic application of observational data to the understanding of impacts of cancer treatments requires detailed information models allowing meaningful comparisons between treatment regimens. Unfortunately, details of systemic therapies are scarce in registries and data warehouses, primarily due to the complex nature of the protocols and a lack of standardization. Since 2011, we have been creating a curated and semi-structured website of chemotherapy regimens, HemOnc.

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Background: Clinical sequencing data should be shared in order to achieve the sufficient scale and diversity required to provide strong evidence for improving patient care. A distributed research network allows researchers to share this evidence rather than the patient-level data across centers, thereby avoiding privacy issues. The Observational Medical Outcomes Partnership (OMOP) common data model (CDM) used in distributed research networks has low coverage of sequencing data and does not reflect the latest trends of precision medicine.

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Importance: Consensus around an efficient second-line treatment option for type 2 diabetes (T2D) remains ambiguous. The availability of electronic medical records and insurance claims data, which capture routine medical practice, accessed via the Observational Health Data Sciences and Informatics network presents an opportunity to generate evidence for the effectiveness of second-line treatments.

Objective: To identify which drug classes among sulfonylureas, dipeptidyl peptidase 4 (DPP-4) inhibitors, and thiazolidinediones are associated with reduced hemoglobin A1c (HbA1c) levels and lower risk of myocardial infarction, kidney disorders, and eye disorders in patients with T2D treated with metformin as a first-line therapy.

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Psychosocial stress is linked to the etiology of several neuropsychiatric disorders, including Major Depressive Disorder and Post-Traumatic-Stress-Disorder. Adolescence is a critical neurobehavioral developmental period wherein the maturing nervous system is sensitive to stress-related psychosocial events. The effects of social defeat stress, an animal model of psychosocial stress, on adolescent neurobehavioral phenomena are not well explored.

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Background: We reviewed the results of the Observational Medical Outcomes Research Partnership (OMOP) 2010 Experiment in hopes of finding examples where apparently well-designed drug studies repeatedly produce anomalous findings. OMOP had applied thousands of designs and design parameters to 53 drug-outcome pairs across 10 electronic data resources. Our intent was to use this repository to elucidate some sources of error in observational studies.

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Observational research promises to complement experimental research by providing large, diverse populations that would be infeasible for an experiment. Observational research can test its own clinical hypotheses, and observational studies also can contribute to the design of experiments and inform the generalizability of experimental research. Understanding the diversity of populations and the variance in care is one component.

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Rats avoid intake of a taste cue when paired with a drug of abuse or with the illness-inducing agent, lithium chloride (LiCl). Although progress has been made, it is difficult to compare the suppressive effects of abused agents and LiCl on intake of a gustatory conditioned stimulus (CS) because of the cross-laboratory use of different CSs, different unconditioned stimuli (USs), and different doses of the drugs, different conditioning regimens, and different restriction states. Here we have attempted to unify these variables by comparing the suppressive effects of a range of doses of morphine, cocaine, and LiCl on intake of a saccharin CS using a common regimen in non-restricted, food restricted, or water restricted male Sprague-Dawley rats.

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The vision of creating accessible, reliable clinical evidence by accessing the clincial experience of hundreds of millions of patients across the globe is a reality. Observational Health Data Sciences and Informatics (OHDSI) has built on learnings from the Observational Medical Outcomes Partnership to turn methods research and insights into a suite of applications and exploration tools that move the field closer to the ultimate goal of generating evidence about all aspects of healthcare to serve the needs of patients, clinicians and all other decision-makers around the world.

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