National Data Repository Research Articles

Overview of Finnish national patient data repository for research on medical risk assessment

The Kanta Patient Data Repository (PDR) contains healthcare data from the population of Finland for more than a decade. The repository is a continuously expanding real world dataset produced by many information systems and healthcare service providers. Kanta data has been available for secondary uses such as scientific research since 2019. The data can be requested from the Finnish authority Findata. However, before a request has been accepted, it is difficult to assess if the accumulated data allows answering a specific research question. Publicly available descriptions of data structures in the Kanta PDR do not tell how much they are used in practice. This publication enables future data use cases by providing a view on the overall availability of types of structured health data in the Kanta PDR based on a sample of 96 200 medical histories of over 18-year-old patients. We conclude that the Kanta PDR is a promising source of real world data for development and evaluation of medical risk calculators within the Finnish population. The wide coverage of the Finnish population and timeliness of the data are its strengths as a source of research data also outside of Finnish context. However, the limitations on data availability in variable level need to be considered on a case-by-case basis. Main challenges in the use of data in the Kanta PDR are multiple code systems for laboratory results, short durations of recorded data for specific data types, and missing or very rarely used structured format e.g., in cases of tobacco and alcohol use.

NIAGADS: A Comprehensive National Data Repository for Alzheimer's Disease and Related Dementia Genetics and Genomics Research.

NIAGADS is the National Institute on Aging (NIA) designated national data repository for human genetics research on Alzheimer's Disease and related dementia (ADRD). NIAGADS maintains a high-quality data collection for ADRD genetic/genomic research and supports genetics data production and analysis. NIAGADS hosts whole genome and exome sequence data from the Alzheimer's Disease Sequencing Project (ADSP) and other genotype/phenotype data, encompassing 209,000 samples. NIAGADS shares these data with hundreds of research groups around the world via the Data Sharing Service, a FISMA moderate compliant cloud-based platform that fully supports the NIH Genome Data Sharing Policy. NIAGADS Open Access consists of multiple knowledge bases with genome-wide association summary statistics and rich annotations on the biological significance of genetic variants and genes across the human genome. NIAGADS stands as a keystone in promoting collaborations to advance the understanding and treatment of Alzheimer's disease.

Progress made in digitalizing antimicrobial resistance surveillance in a One Health approach in Kenya.

Antimicrobial resistance (AMR) is a major threat to global public health, affecting human and animal health, agriculture, food safety, and the environment. The control of AMR is often challenging, particularly when data are scanty or siloed in individual sectors. To develop evidence-based control policies for AMR, an electronic information system that integrates AMR data from various sectors, in a One Health approach, is critical. Acknowledging the interconnectedness of AMR in humans, animals, and the environment and the need to assess the AMR burden using a One Health approach, Kenya's National Antimicrobial Stewardship Interagency Committee (NASIC), with support from FIND, integrated human and animal health AMR data at the national AMR data repository and developed the One Health AMR Surveillance System (OHAMRS). The OHAMRS comprises two core digital components: interoperability middleware for integrating data from various sources and a DHIS2 web portal for the analysis and visualization of AMR surveillance data from the human and animal health sectors. These components are scalable for future inclusion of data from other One Health sectors, e.g., the environment, food/feed, and aquaculture sectors. The OHAMRS has 42 dashboards that facilitate the presentation, interpretation, and dissemination of actionable information relating to AMR, including 17 dashboards for human and animal health priority pathogens and 8 for drug-resistance indicators. The priority pathogen dashboards provide visualization of antimicrobial susceptibility patterns, resistance and susceptibility trends, resistance tables, and geospatial susceptibility maps. Other dashboards include surveillance sites and specimen reports, data completeness, data reconciliation, sample testing workload, a One Health intersectoral dashboard, and other reporting tools for diverse stakeholders. Digitalizing AMR surveillance through a One Health lens is pivotal to understand AMR prevalence and patterns across various sectors. The OHAMRS provides comprehensive data analysis and presentation, informing policymaking on AMR control. Digital tools such as the OHAMRS are vital in facilitating the availability of data and actionable information on AMR required to address the AMR crisis in Kenya.

Assessing olaparib efficacy in U.S. Veterans with metastatic prostate cancer utilizing a time-indifferent g-rate method ideal for real-world analyses

We aimed to assess real-world efficacy of the PARP inhibitor, olaparib, in US Veterans with metastatic prostate cancer (mPC) by leveraging the national data repository and evaluate a novel approach to assess treatment efficacy in tumors considered rare or harboring rare mutations. Included Veterans had 1) mPC with somatic or germline alterations/mutations in genes involved in homologous recombination repair (HRR), 2) received olaparib monotherapy as well as a novel hormonal therapy/androgen receptor pathway inhibitors (NHT/ARPI), and/or chemotherapy, and 3) estimable rates of tumor growth (g-rate) using PSA values obtained while receiving treatment. Previous work has shown an excellent inverse correlation of g-rate with survival. Using g-rate, we determined tumor doubling time (DT) and DT ratios (DT on olaparib/DT on prior medication). We postulated that a DT ratio≥ 1 was associated with benefit. We identified 139 Veterans, including 42 Black males with tumors harboring mutations/alterations in HRR genes who received olaparib: BRCA2 (50), ATM (32), BRCA1 (10), other mutations (47). 62/139 (45%) of all and 21/42 (50%) of Black Veterans had DT ratios ≥1, including 31, 10, 2, and 19 with BRCA2, ATM, BRCA1, and other mutations, respectively (p=0.006). Median survival with DT ratios ≥1 was superior, being 24.5 vs. 11.4 months for DT ratio <1 (p=0.01, HR 0.50, 95% CI 0.29-0.85). Benefit from olaparib, defined as DT ratio ≥1, was not observed for germline status, starting PSA value, number of prior therapies, or immediate prior therapy. Compared to matched cohorts, tumors in the olaparib cohort had shorter DTs with enzalutamide in first line (367 vs. 884 days; p=0.0043). Using equations indifferent to timing of assessments ideal for real-world efficacy analyses, we showed DT ratio ≥1 representing slower tumor growth on olaparib relative to the prior therapy correlates with improved survival. Olaparib efficacy in Veterans with mPC harboring mutations/alterations in HRR genes emulates clinical trial results. Black men had comparable results. Compared to matched cohorts, in first line, enzalutamide was less efficacious in tumors harboring mutations/alterations in HRR genes. American Society of Clinical Oncology Conquer Cancer Foundation (ASCO CCF), the Blavatnik Family Foundation and the Prostate Cancer Foundation (PCF).

Examination of Idiopathic Intracranial Hypertension in the All of Us National Data Repository: A Prospective Genetic Investigation (P1-12.009)

Examination of Idiopathic Intracranial Hypertension in the All of Us National Data Repository: A Prospective Genetic Investigation (P1-12.009)

Dissemination and implementation of evidence-based programs for people with chronic disease: the impact of the COVID-19 pandemic.

Using the RE-AIM (Reach, Effectiveness, Adoption, Implementation, and Maintenance) framework, we describe the implementation of evidence-based chronic disease self-management education (CDSME) programs by the Administration for Community Living CDSME Grantees during 2016-2022 and we also explore the impact of the COVID-19 pandemic on implementation. Grantees collected data before and after the implementation of the CDSME programs and contributed to the national data repository. Data components included workshop information, participant information, and organizational data. The cohort consisted of 175,973 individuals who participated in 34 CDSME programs across 45 states. Participants had a mean ± SD age of 66.1 ± 14.8 years, were primarily female (65.9%) and had a mean ± SD of 2.6 ± 2.3 chronic conditions. Compared to the pre-COVID-19 strata, those who participated during COVID-19 were on average 1.5 years younger and had slightly less comorbidities. For individuals who had pre and post program self-reported health, 65.3% stayed the same, 24.4% improved, and 10.3% worsened (p < 0.001) after participating in CDSME programs. CDSME offers a variety of programs across a broad geographic area to a diverse set of older adults in the US, underscoring the expansive reach of this public health initiative. COVID-19 appears to have shifted participant reach toward a slightly younger and healthier population. Finally, these programs appear to be effective in improving participants' self-rated health. However, these results should be interpreted with caution, given limitations due to missing data and the observational nature of this study design.

ADULT DAY SERVICES DATA COLLECTION AND OUTCOMES: A NATIONAL STRATEGY REALIZED

Abstract The National Adult Day Services Association (NADSA), in its commitment to advance the development and recognition of adult day services across the United States, has defined a comprehensive set of data points and uniform outcome measures to be utilized throughout the Adult Day Services (ADS) industry. NADSA represents more than 500 unique Adult Day Service Centers (ADSCs) across the country. This project has culminated in the opening of a single national secure data entry portal and repository for the collection of this data free to use for adult day service providers across the country. Prior to its full release in January 2023, the beta testing phase allowed for the utilization of this platform across nearly a dozen states, more than 20 ADSCs and more than 500 ADS participants in a variety of settings. As of January 2023, the system is now available to more than 500 ADSCs serving more than 12,000 participants. This session will describe the data points and outcome measures as well as the uniform tools to be utilized for collection and introduce the data portal to the greater academic community. This longitudinal data will be available to NADSA academic partners to provide greater avenues of research into the benefits of adult day services use to participants, caregivers, payors, and the community.

Methamphetamine-associated pulmonary arterial hypertension: data from the national biological sample and data repository for pulmonary arterial hypertension (PAH Biobank)

ObjectiveThis study compares the clinical and haemodynamic severity of methamphetamine-associated pulmonary arterial hypertension (MA-PAH) with idiopathic pulmonary arterial hypertension (IPAH) and connective tissue-associated pulmonary arterial hypertension (CTD-PAH). It also examines...

Ability of Caprini and Padua risk-assessment models to predict venous thromboembolism in a nationwide Veterans Affairs study

ObjectiveVenous thromboembolism (VTE) is a preventable complication of hospitalization. Risk-stratification is the cornerstone of prevention. The Caprini and Padua are two of the most commonly used risk-assessment models (RAMs) to quantify VTE risk. Both models perform well in select, high-risk cohorts. Although VTE RAMs were designed for use in all hospital admissions, they are mostly tested in select, high-risk cohorts. We aim to evaluate the two RAMs in a large, unselected cohort of patients. MethodsWe analyzed consecutive first hospital admissions of 1,252,460 unique surgical and non-surgical patients to 1298 Veterans Affairs facilities nationwide between January 2016 and December 2021. Caprini and Padua scores were generated using the Veterans Affairs’ national data repository. We determined the ability of the two RAMs to predict VTE within 90 days of admission. In secondary analyses, we evaluated prediction at 30 and 60 days, in surgical vs non-surgical patients, after excluding patients with upper extremity deep vein thrombosis, in patients hospitalized ≥72 hours, after including all-cause mortality in a composite outcome, and after accounting for prophylaxis in the predictive model. We used area under the receiver operating characteristic curves (AUCs) as the metric of prediction. ResultsA total of 330,388 (26.4%) surgical and 922,072 (73.6%) non-surgical consecutively hospitalized patients (total N = 1,252,460) were analyzed. Caprini scores ranged from 0 to 28 (median, 4; interquartile range [IQR], 3-6); Padua scores ranged from 0-13 (median, 1; IQR, 1-3). The RAMs showed good calibration and higher scores were associated with higher VTE rates. VTE developed in 35,557 patients (2.8%) within 90 days of admission. The ability of both models to predict 90-day VTE was low (AUCs: Caprini, 0.56; 95% confidence interval [CI], 0.56-0.56; Padua, 0.59; 95% CI, 0.58-0.59). Prediction remained low for surgical (Caprini, 0.54; 95% CI, 0.53-0.54; Padua, 0.56; 95% CI, 0.56-0.57) and non-surgical patients (Caprini, 0.59; 95% CI, 0.58-0.59; Padua, 0.59; 95% CI, 0.59-0.60). There was no clinically meaningful change in predictive performance in any of the sensitivity analyses. ConclusionsCaprini and Padua RAM scores have low ability to predict VTE events in a cohort of unselected consecutive hospitalizations. Improved VTE RAMs must be developed before they can be applied to a general hospital population.

The use of a multi-sensor core scanner workflow as the backbone of a digital core repository

Abstract A core repository is a physical record of a country's or commercial organization's subsurface wealth. Some of the largest core repositories hold thousands of kilometres of core material and it is a challenge to turn this physical archive into an accessible digital resource for all. Non-destructive multi-sensor core logger, hyperspectral and X-ray imaging techniques offer a unique chance to rescue valuable data trapped within core samples, improving the way that a core repository delivers data to academic or industrial end users. Here we present a case study of an archived petroleum core acquired in 1985 at the Osprey Field, UK Continental Shelf. Data from the UK National Data Repository are augmented by a multi-sensor core logger, hyperspectral and X-ray dataset that is uploaded into a cloud-based digital repository. The data were analysed using a multi-variant analysis to reclassify the original lithological interpretations, uncovering a greater proportion of clay and cemented horizons than was previously interpreted. A workflow is established to optimize the use of legacy cores and exploit the abundance of data trapped within the core repository using continuous multi-sensor core scanning and imaging data, which are stored within the virtual environment for visualization and access to all.

From Paper Files to Web-Based Application for Data-Driven Monitoring of HIV Programs: Nigeria's Journey to a National Data Repository for Decision-Making and Patient Care.

Timely and reliable data are crucial for clinical, epidemiologic, and program management decision making. Electronic health information systems provide platforms for managing large longitudinal patient records. Nigeria implemented the National Data Repository (NDR) to create a central data warehouse of all people living with human immunodeficiency virus (PLHIV) while providing useful functionalities to aid decision making at different levels of program implementation. We describe the Nigeria NDR and its development process, including its use for surveillance, research, and national HIV program monitoring toward achieving HIV epidemic control. Stakeholder engagement meetings were held in 2013 to gather information on data elements and vocabulary standards for reporting patient-level information, technical infrastructure, human capacity requirements, and information flow. Findings from these meetings guided the development of the NDR. An implementation guide provided common terminologies and data reporting structures for data exchange between the NDR and the electronic medical record (EMR) systems. Data from the EMR were encoded in extensible markup language and sent to the NDR over secure hypertext transfer protocol after going through a series of validation processes. By June 30, 2021, the NDR had up-to-date records of 1,477,064 (94.4%) patients receiving HIV treatment across 1,985 health facilities, of which 1,266,512 (85.7%) patient records had fingerprint template data to support unique patient identification and record linkage to prevent registration of the same patient under different identities. Data from the NDR was used to support HIV program monitoring, case-based surveillance and production of products like the monthly lists of patients who have treatment interruptions and dashboards for monitoring HIV test and start. The NDR enabled the availability of reliable and timely data for surveillance, research, and HIV program monitoring to guide program improvements to accelerate progress toward epidemic control.

Genetic Risk Factors for End-Stage Hip Osteoarthritis Treated With Total Hip Arthroplasty: A Genome-wide Association Study

BackgroundAlthough a genetic component to hip osteoarthritis (OA) has been described, focused evaluation of the genetic components of end-stage disease is limited. We present a genomewide association study for patients undergoing total hip arthroplasty (THA) to characterize the genetic risk factors associated with end-stage hip osteoarthritis (ESHO), defined as utilization of the procedure. MethodsPatients who underwent primary THA for hip OA were identified in a national patient data repository using administrative codes. Fifteen thousand three hundred and fifty-five patients with ESHO and 374,193 control patients were identified. Whole genome regression of genotypic data for patients who underwent primary THA for hip OA corrected for age, sex, and body mass index (BMI) was performed. Multivariate logistic regression models were used to evaluate the composite genetic risk from the identified genetic variants. ResultsThere were 13 significant genes identified. Composite genetic factors resulted in an odds ratio 1.04 for ESHO (P < .001). The effect of genetics was lower than that of age (Odds Ratio (OR): 2.38; P < .001) and BMI (1.81; P < .001). ConclusionMultiple genetic variants, including 5 novel loci, were associated with end-stage hip OA treated with primary THA. Age and BMI were associated with greater odds of developing end-stage disease when compared to genetic factors.

Reviewing Introduction Histories, Pathways, Invasiveness, and Impact of Non-Indigenous Species in Danish Marine Waters

Non-indigenous species (NIS) are of concern for biodiversity conservation and ecosystem functioning. We present an updated list of NIS, including cryptogenic species, from Danish marine waters containing 123 species. Benthic invertebrates (36%) and phytoplankton (28%) dominate the list, but fish (15%) and macroalgae (13%) are also important. The Limfjord in Northern Jutland emerges as a hotspot for the introduction of NIS. Data from multiple sources were included, i.e., the National Monitoring Program (NOVANA), the National Fish Atlas project, the citizen science project Arter.dk, research articles, and annual national reports of the ICES working group ITMO. Forty-six NIS species were subject to expert judging using a modified Harmonia protocol; 19 were found to fulfil the four selected criteria identifying a species as being ‘invasive’. Additionally, 38 species, not yet recorded in Danish waters, were evaluated using the same method, and 31 were found to fulfil the ‘invasive’ criteria. For nine selected species, introduction history, distribution maps, and time-series diagrams are presented. Our data document that the national monitoring efforts should be expanded to record macrozooplankton, coastal fish, and mobile epibenthic species. Furthermore, the national data repository, Arter.dk, should be expanded to enable more detailed documentation of new NIS records.

Using AI tools to fill an incomplete well log dataset: A workflow

One issue commonly found when working with well log data is the irregular abundance/availability of the different recorded parameters. This is especially applicable when working with datasets collected in different campaigns that may span through the years, even decades, or different companies. Artificial Intelligence may be useful to fill gaps in the original database, resulting in a more complete, standardised one. In this work we present a workflow that can be followed to fills gaps in a dataset using different AI techniques. It consists of four main steps: 1) feature combination selection; 2) hyperparameter tuning; 3) performance assessment and best option choice; 4) blind testing. The process can be performed iteratively, successively populating the database with missing parameters, starting with those for which there are more available training data and whose results are more reliable. In this work, we present an example in which we filled an incomplete dataset consisting of wells provided by the UK National Data Repository (NDR) of the Oil & Gas Authority (OGA). The performance of some of the most commonly used artificial intelligence methods (support vector machine, random forest, multi-layer perceptron) was tested varying their hyperparameters until reaching an adequate result.

Effect of Test and Treat on clinical outcomes in Nigeria: A national retrospective study.

In Nigeria, results from the pilot of the Test and Treat strategy showed higher loss to follow up (LTFU) among people living with HIV compared to before its implementation. The aim of this evaluation was to assess the effects of antiretroviral therapy (ART) initiation within 14 days on LTFU at 12 months and viral suppression. We conducted a retrospective cohort study using routinely collected de-identified patient-level data hosted on the Nigeria National Data Repository from 1,007 facilities. The study population included people living with HIV age ≥15. We used multivariable Cox proportional frailty hazard models to assess time to LTFU comparing ART initiation strategy and multivariable log-binomial regression for viral suppression. Overall, 26,937 (38.13%) were LTFU at 12 months. Among individuals initiated within 14 days, 38.4% were LTFU by 12 months compared to 35.4% for individuals initiated >14 days (p<0.001). In the adjusted analysis, individuals who were initiated ≤14 days after HIV diagnosis had a higher hazard of being LTFU (aHR 1.15, 95% CI 1.10-1.20) than individuals initiated after 14 days of HIV diagnosis. Among individuals with viral load results, 86.2% were virally suppressed. The adjusted risk ratio for viral suppression among individuals who were initiated ≤14 days compared to >14 days was not statistically significant. LTFU was higher among individuals who were initiated within 14 days compared to greater than 14 days after HIV diagnosis. There was no difference for viral suppression. The provision of early tailored interventions to support newly diagnosed people living may contribute to reducing LTFU.

Utility of a Clinically Guided Data-Driven Approach for Predicting Breast Cancer Complications: An Application Using a Population-Based Claims Data Set.

With earlier detection and an increasing number of breast cancer (BCa) survivors, more women are living with side effects of BCa treatment. A predictive approach to studying treatment-related adverse events (AEs) may generate proactive strategies; however, many studies are descriptive in nature. Focusing on short-term AEs, we determine the performance of prediction models of disease- or treatment-related AEs among women diagnosed with BCa. We used administrative claims data from the Blue Health Intelligence National Data Repository. The study sample included female individuals age 18 years and older who were diagnosed with BCa and received cancer-directed treatment between January 1, 2014, and August 1, 2019. Using the information available in the claims data, we constructed longitudinal patient histories and identified disease- and treatment-related AEs occurring within 6 months of treatment. The following prediction models were developed: logistic regression, Lasso regression, gradient boosted tree (GBT), and random forest (RF). We compared models using the area under the receiver operating characteristic curve and its CI, among other metrics. Data were extracted for 267,473 members meeting study inclusion criteria. The area under the curve for the logistic regression model was 0.82 (0.82-0.86), compared with 0.89 (0.87-0.90) for the Lasso, 0.91 (0.89-0.93) for the GBT, and 0.90 (0.93-0.89) for the RF models. The sensitivity was 0.96 for the GBT, Lasso, and RF models, whereas the specificity was 0.42, 0.44, and 0.39 for the GBT, Lasso, and RF models, respectively. Positive predictive values were 0.96 across all three models. Prediction models developed using big data methods and grounded in a clinically guided framework have the potential to reliably predict short-term treatment-related AEs among women diagnosed with BCa.

Understanding Sexual Assault Survivors’ Perspectives on Archiving Qualitative Data: Implications for Feminist Approaches to Open Science

The open science movement has framed data sharing as necessary and achievable best practices for high-quality science. Feminist psychologists have complicated that narrative by questioning the purpose of data sharing across different paradigms, methodologies, and research populations. In these debates, the academic community has centered the needs and voices of researchers, and participants’ perspectives are largely missing from this literature. In this study, we sought to understand how research participants feel about sharing qualitative data on a sensitive subject—sexual victimization. As part of a participatory action research project, we conducted qualitative interviews with sexual assault survivors about their post-assault help-seeking experiences. The federal funding agency that supported this project requires researchers to archive de-identified data in a national data repository (the National Archive of Criminal Justice Data [NACJD]). All participants consented to archiving data, and the vast majority expressed positive views about data sharing because they wanted to help other survivors. Participants emphasized that our participatory action research approach and our stated goal of helping survivors were important considerations in their decisions regarding data sharing. Researchers should obtain informed consent from their participants for data sharing/archiving, and discuss their dissemination plans during the informed consent process.

Don't Let Perfect Be the Enemy of Good: A Proof of Concept for a Custom National Data Repository of Quality Measures for Free and Charitable Clinics.

Purpose:Free and charitable clinics (FCCs), nonprofits that utilize volunteer licensed health care professionals to provide health services at no cost or a small fee to low-income uninsured patients who are disproportionately from underrepresented communities, have been part of the safety net for over a century. Approximately 1400 known FCCs serve two million patients annually. Despite their longevity and sizable number, evidence regarding the quality of care in FCCs is lacking. We report new evidence generated by a national initiative, the Roadmap to Health Equity. Established in 2017, this consortium is co-led by two national organizations serving FCCs and an academic institution. It has involved more than 150 FCC stakeholders with the shared goal of improving the quality of care and reducing inequities. The centerpiece is a custom national data repository of 15 validated clinical quality measures and patient-level characteristics.Methods:Fifty FCCs pilot tested the data repository. Clinics submitted patient-level data on two blood pressure (BP) measures and at least one additional measure. Descriptive statistics were stratified by sex, race, ethnicity, and language.Results:In 2021, 33 pilot FCCs from 21 states reported data across 13 of the 15 clinical measures, representing 34,359 unique patients. For example, on average, 60% of patients had controlled BP, but Black patients had lower rates of BP control than Hispanic and White patients (55.9% vs. 62.1% and 63.0%, respectively).Conclusion:Our findings demonstrate a proof of concept. By standardizing quality measures alongside patient characteristics, clinics can become aware of racial/ethnic inequalities in health outcomes. This information can motivate clinics to investigate the causes and implement solutions. In an environment where outcome data from FCCs are scarce, the new national data repository lays the foundation for routine stratified reporting of a range of quality outcomes for an important safety net for the uninsured.

Polar biodiversity data: From a national marine platform to a global data portal

SummaryGlobal access to accurate biodiversity data is a prerequisite to our progress in understanding biodiversity dynamics in ecosystems and any changes that are occurring. Despite recent major advancements in sharing data on the world’s species, one of the remaining challenges relates to the mechanics of guiding data systematically from its provenance to end users. It can take considerable effort to orchestrate a successful sampling campaign, manage samples obtained in often extreme, remote conditions and to secure preservation of, and access to, the acquired data. Here, we briefly describe biodiversity data flow from a polar ship to a national data repository and onward to a global data portal. This paper highlights a few crucial points in this process, which aims to provide information systematically into the mosaic of our polar species biodiversity knowledge. This flexible workflow can be modified for other data types and adopted by other data repositories.

Organ Care System Heart Perfusion Registry (OHP Registry) - Overview of a National Data Repository of Ex-Vivo Perfusion in DBD and DCD Heart Transplantation

<h3>Purpose</h3> Organ Care System (OCS, Transmedics Inc) is the first clinically available system for ex-vivo normothermic heart perfusion. OHP Registry is a prospective real-world registry of Donation after Brain Death (DBD) or Donation after Circulatory Death (DCD) heart transplantation in hearts perfused and assessed on OCS Heart. OHP Registry will collect OCS ex-vivo perfusion & assessment parameters and post-transplant short & long-term clinical outcomes of heart transplant recipients in the U.S. <h3>Methods</h3> All adult heart transplant recipients of DBD or DCD heart allografts perfused and assessed on OCS Heart technology will be included, along with data on hearts perfused and assessed on OCS Heart but not transplanted. OCS Heart perfusion and assessment parameters will be prospectively collected. All recipients will be followed up to 5 years post-transplant. Patient and graft survival will be compared to a UNOS/SRTR cohort of heart transplant recipients of cold stored donor hearts transplanted at the same OHP Registry centers over the same period of time. <h3>Results</h3> Endpoints: Patient and graft survival at 1, 2, 3, 4, 5 years post-transplantation. Incidence of moderate or severe heart primary graft dysfunction (left or right ventricle) defined according to ISHLT 2014 consensus definitions. OCS Heart utilization rate defined as the number of hearts transplanted by OCS perfusion and assessment, divided by the total number of hearts perfused and assessed on the OCS Heart System. <h3>Conclusion</h3> We anticipate analyses of OHP Registry will provide important data that will inform clinical care. We plan to present regular updates at future ISHLT Annual Meetings.