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BackgroundOver the past 30 years, there have been significant advances in the understanding of the mechanisms associated with loss and recovery of consciousness following severe brain injury. This work has provided a strong grounding for the development of novel restorative therapeutic interventions. Although all interventions are aimed at modulating and thereby restoring brain function, the landscape of existing interventions encompasses a very wide scope of techniques and protocols. Despite vigorous research efforts, few approaches have been assessed with rigorous, high-quality randomized controlled trials. As a growing number of exploratory interventions emerge, it is paramount to develop standardized approaches to reporting results. The successful evaluation of novel interventions depends on implementation of shared nomenclature and infrastructure. To address this gap, the Neurocritical Care Society's Curing Coma Campaign convened nine working groups and charged them with developing common data elements (CDEs). Here, we report the work of the Therapeutic Interventions Working Group.MethodsThe working group reviewed existing CDEs relevant to therapeutic interventions within the National Institutes of Health National Institute of Neurological Disorders and Stroke database and reviewed the literature for assessing key areas of research in the intervention space. CDEs were then proposed, iteratively discussed and reviewed, classified, and organized in a case report form (CRF).ResultsWe developed a unified CRF, including CDEs and key design elements (i.e., methodological or protocol parameters), divided into five sections: (1) patient information, (2) general study information, (3) behavioral interventions, (4) pharmacological interventions, and (5) device interventions.ConclusionsThe newly created CRF enhances systematization of future work by proposing a portfolio of measures that should be collected in the development and implementation of studies assessing novel interventions intended to increase the level of consciousness or rate of recovery of consciousness in patients with disorders of consciousness.

Background: Clinical management of persons with disorders of consciousness (DoC) is dedicated largely to optimizing recovery. However, selecting a measure to evaluate the extent of recovery is challenging because few measures are designed to precisely assess the full range of potential outcomes, from prolonged DoC to return of preinjury functioning. Measures that are designed specifically to assess persons with DoC are often performance-based and only validated for in-person use. Moreover, there are no published recommendations addressing which outcome measures should be used to evaluate DoC recovery. The resulting inconsistency in the measures selected by individual investigators to assess outcome prevents comparison of results across DoC studies. The National Institute of Neurological Disorders and Stroke (NINDS) common data elements (CDEs) is an amalgamation of standardized variables and tools that are recommended for use in studies of neurologic diseases and injuries. The Neurocritical Care Society Curing Coma Campaign launched an initiative to develop CDEs specifically for DoC and invited our group to recommend CDE outcomes and endpoints for persons with DoCs. Methods: The Curing Coma Campaign Outcomes and Endpoints CDE Workgroup, consisting of experts in adult and pediatric neurocritical care, neurology, and neuroscience, used a previously established five-step process to identify and select candidate CDEs: (1) review of existing NINDS CDEs, (2) nomination and systematic vetting of new CDEs, (3) CDE classification, (4) iterative review and approval of panel recommendations, and (5) development of case report forms. Results: Among hundreds of existing NINDS outcome and endpoint CDE measures, we identified 20 for adults and 18 for children that can be used to assess the full range of recovery from coma. We also proposed 14 new outcome and endpoint CDE measures for adults and 5 for children. Conclusions: The DoC outcome and endpoint CDEs are a starting point in the broader effort to standardize outcome evaluation of persons with DoC. The ultimate goal is to harmonize DoC studies and allow for more precise assessment of outcomes after severe brain injury or illness. An iterative approach is required to modify and adjust these outcome and endpoint CDEs as new evidence emerges. [ABSTRACT FROM AUTHOR]

Introduction Injuries are the leading cause of medical encounters with over 2 million medical encounters for musculoskeletal (MSK) conditions and over 700,000 acute injuries per year. Musculoskeletal injuries (MSKIs) are by far the leading health and readiness problem of the U.S. Military. The Proceedings of the International Collaborative Effort on Injury Statistics published a list of 12 data elements deemed necessary for injury prevention in the civilian population; however, there are no standardized list of common data elements (CDEs) across the DoD specifically designed to study MSKIs in the Military Health System (MHS). This study aims to address this gap in knowledge by defining CDEs across the DoD for MSKIs, establishing a CDE dictionary, and compiling other necessary information to quantify MSKI disease burden in the MHS. Materials and Methods Between November 2022 and March 2023, we conducted an environmental scan of current MSKI data metrics across the DoD. We used snowball sampling with active engagement of groups housing datasets that contained MSKI data elements to determine CDEs as well as information on readiness databases across the DoD containing up-to-date personnel information on disease, hospitalizations, limited duty days (LDDs), and deployability status for all military personnel, as well as MSKI-specific measures from the MHS Dashboard which tracks key performance measures. Results We identified 8 unique databases: 5 containing demographic and diagnostic information (Defense Medical Surveillance System, Medical Assessment and Readiness Systems, Military Health System Data Repository, Person-Data Environment, and Soldier Performance, Health, and Readiness Database); and 3 containing LDD information (Aeromedical Services Information Management System, eProfile, and Limited Duty Sailor Marines Readiness Tracker). Nine CDEs were identified: DoD number, sex, race, ethnicity, branch of service, rank, diagnosis, Common Procedural Terminology coding, and cause codes, as they may be captured in any database that is a derivative of the Military Health System Data Repository. Medical Assessment and Readiness Systems contained most variables of interest, excluding injury/place of region and time in service. The Limited Duty Sailor Marines Readiness Tracker contains a variable corresponding to "days on limited duty." The Aeromedical Services Information Management System uses the "release date" and "profile date" to calculate LDDs. The eProfile system determines LDDs by the difference between the "expiration date" and "approved date." In addition, we identified 2 measures on the MHS Dashboard. One measures the percentage of service members (SMs) who are on limited duty for longer than 90 days because of an MSKI and the other tracks the percentage of SMs that are not medically ready for deployment because of a deployment-limiting medical condition. Conclusions This article identifies core data elements needed to understand and prevent MSKIs and where these data elements can be found. These elements should inform researchers and result in evidence-informed policy decisions supporting SM health to optimize military force readiness. [ABSTRACT FROM AUTHOR]

Background and purpose: Traumatic brain injury (TBI) is a major source of health loss and disability worldwide. Accurate and timely diagnosis of TBI is critical for appropriate treatment and management of the condition. Neuroimaging plays a crucial role in the diagnosis and characterization of TBI. Computed tomography (CT) is the first-line diagnostic imaging modality typically utilized in patients with suspected acute mild, moderate and severe TBI. Radiology reports play a crucial role in the diagnostic process, providing critical information about the location and extent of brain injury, as well as factors that could prevent secondary injury. However, the complexity and variability of radiology reports can make it challenging for healthcare providers to extract the necessary information for diagnosis and treatment planning. Methods/results/conclusion: In this article, we report the efforts of an international group of TBI imaging experts to develop a clinical radiology report template for CT scans obtained in patients suspected of TBI and consisting of fourteen different subdivisions (CT technique, mechanism of injury or clinical history, presence of scalp injuries, fractures, potential vascular injuries, potential injuries involving the extra-axial spaces, brain parenchymal injuries, potential injuries involving the cerebrospinal fluid spaces and the ventricular system, mass effect, secondary injuries, prior or coexisting pathology). [ABSTRACT FROM AUTHOR]

Standardised forms for capturing clinical data promote consistency in data collection and analysis across research sites, enabling faster, higher-quality evidence generation. ISARIC and the World Health Organization have developed case report forms (CRFs) for the clinical characterisation of several infectious disease outbreaks. To improve the design and quality of future forms, we analysed the inclusion and completion rates of the 243 fields on the ISARIC-WHO COVID-19 CRF. Data from 42 diverse collaborations, covering 1886 hospitals and 950,064 patients, were analysed. A mean of 129.6 fields (53%) were included in the adapted CRFs implemented across the sites. Consistent patterns of field inclusion and completion aligned with globally recognised research priorities in outbreaks of novel infectious diseases. Outcome status was the most highly included (95.2%) and completed (89.8%) field, followed by admission demographics (79.1% and 91.6%), comorbidities (77.9% and 79.0%), signs and symptoms (68.9% and 78.4%), and vitals (70.3% and 69.1%). Mean field completion was higher in severe patients (70.2%) than in all patients (61.6%). The results reveal how clinical characterisation CRFs can be streamlined to reduce data collection time, including the modularisation of CRFs, to offer a choice of data volume collection and the separation of critical care interventions. This data-driven approach to designing CRFs enhances the efficiency of data collection to inform patient care and public health response. [ABSTRACT FROM AUTHOR]

Standardised forms for capturing clinical data promote consistency in data collection and analysis across research sites, enabling faster, higher-quality evidence generation. ISARIC and the World Health Organization have developed case report forms (CRFs) for the clinical characterisation of several infectious disease outbreaks. To improve the design and quality of future forms, we analysed the inclusion and completion rates of the 243 fields on the ISARIC-WHO COVID-19 CRF. Data from 42 diverse collaborations, covering 1886 hospitals and 950,064 patients, were analysed. A mean of 129.6 fields (53%) were included in the adapted CRFs implemented across the sites. Consistent patterns of field inclusion and completion aligned with globally recognised research priorities in outbreaks of novel infectious diseases. Outcome status was the most highly included (95.2%) and completed (89.8%) field, followed by admission demographics (79.1% and 91.6%), comorbidities (77.9% and 79.0%), signs and symptoms (68.9% and 78.4%), and vitals (70.3% and 69.1%). Mean field completion was higher in severe patients (70.2%) than in all patients (61.6%). The results reveal how clinical characterisation CRFs can be streamlined to reduce data collection time, including the modularisation of CRFs, to offer a choice of data volume collection and the separation of critical care interventions. This data-driven approach to designing CRFs enhances the efficiency of data collection to inform patient care and public health response.

Objectives Designing a framework representing radiology results in a standards-based data structure using joint Radiological Society of North America/American College of Radiology Common Data Elements (CDEs) as the semantic labels on standard structures. This allows radiologist-created report data to integrate with artificial intelligence-generated results for use throughout downstream systems. Materials and Methods We developed a framework modeling radiology findings as Health Level 7 (HL7) Fast Healthcare Interoperability Resources (FHIR) observations using CDE set/element identifiers as standardized semantic labels. This framework deploys CDE identifiers to specify radiology findings and attributes, providing consistent labels for radiology report concepts—diagnoses, recommendations, tabular/quantitative data—with built-in integration with RadLex, SNOMED CT, LOINC, and other ontologies. Observation structures fit within larger HL7 FHIR DiagnosticReport resources, providing output including both nuanced text and structured data. Results Labeling radiology findings as discrete data for interchange between systems requires two components: structure and semantics. CDE definitions provide semantic identifiers for findings and their component values. The FHIR observation resource specifies a structure for associating identifiers with radiology findings in the context of reports, with CDE-encoded observations referring to definitions for CDE identifiers in a central repository. The discussion includes an example of encoding pulmonary nodules on a chest CT as CDE-labeled observations, demonstrating the application of this framework to exchange findings throughout the imaging workflow, making imaging data available to downstream clinical systems. Discussion CDE-labeled observations establish a lingua franca for encoding, exchanging, and consuming radiology data at the level of individual findings, facilitating use throughout healthcare systems. Importance CDE-labeled FHIR observation objects can increase the value of radiology results by facilitating their use throughout patient care. [ABSTRACT FROM AUTHOR]

Collaborative data science requires standardized, harmonized, interoperable, and ethically sourced data. Developing an agreed-upon set of elements requires capturing different perspectives on the importance and feasibility of the data elements through a consensus development approach. This study reports on the systematic scoping review of literature that examined the inclusion of diverse stakeholder groups and sources of social drivers of health variables in consensus-based common data element (CDE) sets. This systematic scoping review included sources from PubMed, Embase, CINAHL, WoS MEDLINE, and PsycINFO databases. Extracted data included the stakeholder groups engaged in the Delphi process, sources of CDE sets, and inclusion of social drivers data across 11 individual and 6 social domains. Of the 384 studies matching the search string, 22 were included in the final review. All studies involved experts with healthcare expertise directly relevant to the developed CDE set, and only six (27%) studies engaged health consumers. Literature reviews and expert input were the most frequent sources of CDE sets. Seven studies (32%) did not report the inclusion of any demographic variables in the CDE sets, and each demographic SDoH domain was included in at least one study with age and sex assigned at birth included in all studies, and social driver domains included only in four studies (18%). The Delphi technique engages diverse expert groups around the development of SDoH data elements. Future studies can benefit by involving health consumers as experts. [ABSTRACT FROM AUTHOR]

Background: The recent publication of practice guidelines for management of patients with disorders of consciousness (DoC) in the United States and Europe was a major step forward in improving the accuracy and consistency of terminology, diagnostic criteria, and prognostication in this population. There remains a pressing need for a more precise brain injury classification system that combines clinical semiology with neuroimaging, electrophysiologic, and other biomarker data. To address this need, the National Institute of Neurological Disorders and Stroke launched the Common Data Elements (CDEs) initiative to facilitate systematic collection of high-quality research data in studies involving patients with neurological disease. The Neurocritical Care Society's Curing Coma Campaign expanded this effort in 2018 to develop CDEs for DoC. Herein, we present CDE recommendations for behavioral phenotyping of patients with DoC. Methods: The Behavioral Phenotyping Workgroup used a preestablished, five-step process to identify and select candidate CDEs that included review of existing National Institute of Neurological Disorders and Stroke CDEs, nomination and systematic vetting of new CDEs, CDE classification, iterative review, and approval of panel recommendations and development of corresponding case review forms. Results: We identified a slate of existing and newly proposed basic, supplemental, and exploratory CDEs that can be used for behavioral phenotyping of adult and pediatric patients with DoC. Conclusions: The proposed behavioral phenotyping CDEs will assist with international harmonization of DoC studies and allow for more precise characterization of study cohorts, favorably impacting observational studies and clinical trials aimed at improving outcome in this population. [ABSTRACT FROM AUTHOR]

ObjectiveOne aim of the Back Pain Consortium (BACPAC) Research Program is to develop an integrated model of chronic low back pain that is informed by combined data from translational research and clinical trials. We describe efforts to maximize data harmonization and accessibility to facilitate Consortium-wide analyses.MethodsConsortium-wide working groups established harmonized data elements to be collected in all studies and developed standards for tabular and nontabular data (eg, imaging and omics). The BACPAC Data Portal was developed to facilitate research collaboration across the Consortium.ResultsClinical experts developed the BACPAC Minimum Dataset with required domains and outcome measures to be collected by use of questionnaires across projects. Other nonrequired domain-specific measures are collected by multiple studies. To optimize cross-study analyses, a modified data standard was developed on the basis of the Clinical Data Interchange Standards Consortium Study Data Tabulation Model to harmonize data structures and facilitate integration of baseline characteristics, participant-reported outcomes, chronic low back pain treatments, clinical exam, functional performance, psychosocial characteristics, quantitative sensory testing, imaging, and biomechanical data. Standards to accommodate the unique features of chronic low back pain data were adopted. Research units submit standardized study data to the BACPAC Data Portal, developed as a secure cloud-based central data repository and computing infrastructure for researchers to access and conduct analyses on data collected by or acquired for BACPAC.ConclusionsBACPAC harmonization efforts and data standards serve as an innovative model for data integration that could be used as a framework for other consortia with multiple, decentralized research programs.

The Australian Traumatic Brain Injury Initiative (AUS-TBI) aims to select a set of measures to comprehensively predict and assess outcomes following moderate-to-severe traumatic brain injury (TBI) across Australia. The aim of this article was to report on the implementation and findings of an evidence-based consensus approach to develop AUS-TBI recommendations for outcome measures following adult and pediatric moderate-to-severe TBI. Following consultation with a panel of expert clinicians, Aboriginal and Torres Strait Islander representatives and a Living Experience group, and preliminary literature searches with a broader focus, a decision was made to focus on measures of mortality, everyday functional outcomes, and quality of life. Standardized searches of bibliographic databases were conducted through March 2022. Characteristics of 75 outcome measures were extracted from 1485 primary studies. Consensus meetings among the AUS-TBI Steering Committee, an expert panel of clinicians and researchers and a group of individuals with lived experience of TBI resulted in the production of a final list of 11 core outcome measures: the Functional Independence Measure (FIM); Glasgow Outcome Scale-Extended (GOS-E); Satisfaction With Life Scale (SWLS) (adult); mortality; EuroQol-5 Dimensions (EQ5D); Mayo-Portland Adaptability Inventory (MPAI); Return to Work /Study (adult and pediatric); Functional Independence Measure for Children (WEEFIM); Glasgow Outcome Scale Modified for Children (GOS-E PEDS); Paediatric Quality of Life Scale (PEDS-QL); and Strengths and Difficulties Questionnaire (pediatric). These 11 outcome measures will be included as common data elements in the AUS-TBI data dictionary. Review Registration PROSPERO (CRD42022290954).

The Australian Traumatic Brain Injury Initiative (AUS-TBI) aims to develop a health informatics approach to collect data predictive of outcomes for persons with moderate-severe TBI across Australia. Central to this approach is a data dictionary; however, no systematic reviews of methods to define and develop data dictionaries exist to-date. This rapid systematic review aimed to identify and characterize methods for designing data dictionaries to collect outcomes or variables in persons with neurological conditions. Database searches were conducted from inception through October 2021. Records were screened in two stages against set criteria to identify methods to define data dictionaries for neurological conditions (International Classification of Diseases, 11th Revision: 08, 22, and 23). Standardized data were extracted. Processes were checked at each stage by independent review of a random 25% of records. Consensus was reached through discussion where necessary. Thirty-nine initiatives were identified across 29 neurological conditions. No single established or recommended method for defining a data dictionary was identified. Nine initiatives conducted systematic reviews to collate information before implementing a consensus process. Thirty-seven initiatives consulted with end-users. Methods of consultation were ?roundtable? discussion (n?=?30); with facilitation (n?=?16); that was iterative (n?=?27); and frequently conducted in-person (n?=?27). Researcher stakeholders were involved in all initiatives and clinicians in 25. Importantly, only six initiatives involved persons with lived experience of TBI and four involved carers. Methods for defining data dictionaries were variable and reporting is sparse. Our findings are instructive for AUS-TBI and can be used to further development of methods for defining data dictionaries.

Background: Limited availability and poor quality of data in medical records and trauma registries impede progress to achieve injury-related health equity across the lifespan. Methods: We used a Nominal Group Technique (NGT) in-person workgroup and a national web-based Delphi process to identify common data elements (CDE) that should be collected. Results: The 12 participants in the NGT workgroup and 23 participants in the national Delphi process identified 10 equity-related CDE and guiding lessons for research on collection of these data. Conclusions: These high-priority CDE define a detailed, equity-oriented approach to guide research to achieve injury-related health equity across the lifespan.

Pooling and comparing data from the existing global network of burn registers represents a powerful, yet untapped, opportunity to improve burn prevention and care. There have been no studies investigating whether registers are sufficiently similar to allow data comparisons. It is also not known what differences exist that could bias analyses. Understanding this information is essential prior to any future data sharing. The aim of this project was to compare the variables collected in countrywide and intercountry burn registers to understand their similarities and differences. Register custodians were invited to participate and share their data dictionaries. Inclusion and exclusion criteria were compared to understand each register population. Descriptive statistics were calculated for the number of unique variables. Variables were classified into themes. Definition, method, timing of measurement, and response options were compared for a sample of register concepts. 13 burn registries participated in the study. Inclusion criteria varied between registers. Median number of variables per register was 94 (range 28 - 890), of which 24% (range 4.8 – 100%) were required to be collected. Six themes (patient information, admission details, injury, inpatient, outpatient, other) and 41 subthemes were identified. Register concepts of age and timing of injury show similarities in data collection. Intent, mechanism, inhalational injury, infection, and patient death show greater variation in measurement. We found some commonalities between registers and some differences. Commonalities would assist in any future efforts to pool and compare data between registers. Differences between registers could introduce selection and measurement bias, which needs to be addressed in any strategy aiming to facilitate burn register data sharing. We recommend the development of common data elements used in an international minimum data set for burn injuries, including standard definitions and methods of measurement, as the next step in achieving burn register data sharing. • We investigated similarities and differences of 13 international burn registers. • The 2759 variables collected can be categorised into 6 themes and 41 subthemes. • Inclusion criteria differences may lead to selection bias in data comparisons. • Mapping examples are provided to show how variable harmonisation could be achieved. • Creation of common data elements would reduce measurement bias in data comparisons. [ABSTRACT FROM AUTHOR]

Genicular artery embolization (GAE) is an emerging, potentially effective treatment option in patients with knee osteoarthritis (OA). This study aimed to describe the current state of common design data elements (CDDEs) and core outcome measures (COMs) in recent trials of GAE for knee OA. A comprehensive search of seven online databases were searched within the Nested Knowledge AutoLit living review platform, followed by categorization of primary and secondary outcomes. Studies were tagged with the relevant outcomes of interest in each article. Results were synthesized and examined for the CDDEs. Pain is the most frequent reported outcome, present in 23 of the 24 studies (95.8%). However, there is considerable variability in the description of in the study designs, procedural techniques, embolic materials, time points, and MRI parameters. Greater consistency is observed in eligibility criteria, and adverse events reporting. Although findings thus far have been favorable, current data is still constrained by the heterogeneity of the study design, embolization area nomenclature, limited follow-up, and in many cases, the absence of control group. To enhance the potential for future meta-analyses and robust, evidence-based evaluations of GAE as a treatment for knee OA, further research is required to address the identified shortcomings. By establishing more standardized protocols, the efficacy and safety of GAE can be more accurately assessed and understood. [ABSTRACT FROM AUTHOR]

Background: In patients with disorders of consciousness (DoC), laboratory and molecular biomarkers may help define endotypes, identify therapeutic targets, prognosticate outcomes, and guide patient selection in clinical trials. We performed a systematic review to identify common data elements (CDEs) and key design elements (KDEs) for future coma and DoC research. Methods: The Curing Coma Campaign Biospecimens and Biomarkers work group, composed of seven invited members, reviewed existing biomarker and biospecimens CDEs and conducted a systematic literature review for laboratory and molecular biomarkers using predetermined search words and standardized methodology. Identified CDEs and KDEs were adjudicated into core, basic, supplemental, or experimental CDEs per National Institutes of Health classification based on level of evidence, reproducibility, and generalizability across different diseases through a consensus process. Results: Among existing National Institutes of Health CDEs, those developed for ischemic stroke, traumatic brain injury, and subarachnoid hemorrhage were most relevant to DoC and included. KDEs were common to all disease states and included biospecimen collection time points, baseline indicator, biological source, anatomical location of collection, collection method, and processing and storage methodology. Additionally, two disease core, nine basic, 24 supplemental, and 59 exploratory biomarker CDEs were identified. Results were summarized and generated into a Laboratory Data and Biospecimens Case Report Form (CRF) and underwent public review. A final CRF version 1.0 is reported here. Conclusions: Exponential growth in biomarkers development has generated a growing number of potential experimental biomarkers associated with DoC, but few meet the quality, reproducibility, and generalizability criteria to be classified as core and basic biomarker and biospecimen CDEs. Identification and adaptation of KDEs, however, contribute to standardizing methodology to promote harmonization of future biomarker and biospecimens studies in DoC. Development of this CRF serves as a basic building block for future DoC studies. [ABSTRACT FROM AUTHOR]

Background: The fundamental gap obstructing forward progress of evidenced-based care in pediatric and neonatal disorders of consciousness (DoC) is the lack of defining consensus-based terminology to perform comparative research. This lack of shared nomenclature in pediatric DoC stems from the inherently recursive dilemma of the inability to reliably measure consciousness in the very young. However, recent advancements in validated clinical examinations and technologically sophisticated biomarkers of brain activity linked to future abilities are unlocking this previously formidable challenge to understanding the DoC in the developing brain. Methods: To address this need, the first of its kind international convergence of an interdisciplinary team of pediatric DoC experts was organized by the Neurocritical Care Society's Curing Coma Campaign. The multidisciplinary panel of pediatric DoC experts proposed pediatric-tailored common data elements (CDEs) covering each of the CDE working groups including behavioral phenotyping, biospecimens, electrophysiology, family and goals of care, neuroimaging, outcome and endpoints, physiology and big Data, therapies, and pediatrics. Results: We report the working groups' pediatric-focused DoC CDE recommendations and disseminate CDEs to be used in studies of pediatric patients with DoC. Conclusions: The CDEs recommended support the vision of progressing collaborative and successful internationally collaborative pediatric coma research. [ABSTRACT FROM AUTHOR]

The convergence of an interdisciplinary team of neurocritical care specialists to organize the Curing Coma Campaign is the first effort of its kind to coordinate national and international research efforts aimed at a deeper understanding of disorders of consciousness (DoC). This process of understanding includes translational research from bench to bedside, descriptions of systems of care delivery, diagnosis, treatment, rehabilitation, and ethical frameworks. The description and measurement of varying confounding factors related to hospital care was thought to be critical in furthering meaningful research in patients with DoC. Interdisciplinary hospital care is inherently varied across geographical areas as well as community and academic medical centers. Access to monitoring technologies, specialist consultation (medical, nursing, pharmacy, respiratory, and rehabilitation), staffing resources, specialty intensive and acute care units, specialty medications and specific surgical, diagnostic and interventional procedures, and imaging is variable, and the impact on patient outcome in terms of DoC is largely unknown. The heterogeneity of causes in DoC is the source of some expected variability in care and treatment of patients, which necessitated the development of a common nomenclature and set of data elements for meaningful measurement across studies. Guideline adherence in hemorrhagic stroke and severe traumatic brain injury may also be variable due to moderate or low levels of evidence for many recommendations. This article outlines the process of the development of common data elements for hospital course, confounders, and medications to streamline definitions and variables to collect for clinical studies of DoC. [ABSTRACT FROM AUTHOR]

Background: The implementation of multimodality monitoring in the clinical management of patients with disorders of consciousness (DoC) results in physiological measurements that can be collected in a continuous and regular fashion or even at waveform resolution. Such data are considered part of the "Big Data" available in intensive care units and are potentially suitable for health care-focused artificial intelligence research. Despite the richness in content of the physiological measurements, and the clinical implications shown by derived metrics based on those measurements, they have been largely neglected from previous attempts in harmonizing data collection and standardizing reporting of results as part of common data elements (CDEs) efforts. CDEs aim to provide a framework for unifying data in clinical research and help in implementing a systematic approach that can facilitate reliable comparison of results from clinical studies in DoC as well in international research collaborations. Methods: To address this need, the Neurocritical Care Society's Curing Coma Campaign convened a multidisciplinary panel of DoC "Physiology and Big Data" experts to propose CDEs for data collection and reporting in this field. Results: We report the recommendations of this CDE development panel and disseminate CDEs to be used in physiologic and big data studies of patients with DoC. Conclusions: These CDEs will support progress in the field of DoC physiologic and big data and facilitate international collaboration. [ABSTRACT FROM AUTHOR]

Background: To facilitate comparative research, it is essential for the fields of neurocritical care and rehabilitation to establish common data elements (CDEs) for disorders of consciousness (DoC). Our objective was to identify CDEs related to goals-of-care decisions and family/surrogate decision-making for patients with DoC. Methods: To achieve this, we formed nine CDE working groups as part of the Neurocritical Care Society's Curing Coma Campaign. Our working group focused on goals-of-care decisions and family/surrogate decision-makers created five subgroups: (1) clinical variables of surrogates, (2) psychological distress of surrogates, (3) decision-making quality, (4) quality of communication, and (5) quality of end-of-life care. Each subgroup searched for existing relevant CDEs in the National Institutes of Health/CDE catalog and conducted an extensive literature search for additional relevant study instruments to be recommended. We classified each CDE according to the standard definitions of "core", "basic", "exploratory", or "supplemental", as well as their use for studying the acute or chronic phase of DoC, or both. Results: We identified 32 relevant preexisting National Institutes of Health CDEs across all subgroups. A total of 34 new instruments were added across all subgroups. Only one CDE was recommended as disease core, the "mode of death" of the patient from the clinical variables subgroup. Conclusions: Our findings provide valuable CDEs specific to goals-of-care decisions and family/surrogate decision-making for patients with DoC that can be used to standardize studies to generate high-quality and reproducible research in this area. [ABSTRACT FROM AUTHOR]

Background: Electroencephalography (EEG) has long been recognized as an important tool in the investigation of disorders of consciousness (DoC). From inspection of the raw EEG to the implementation of quantitative EEG, and more recently in the use of perturbed EEG, it is paramount to providing accurate diagnostic and prognostic information in the care of patients with DoC. However, a nomenclature for variables that establishes a convention for naming, defining, and structuring data for clinical research variables currently is lacking. As such, the Neurocritical Care Society's Curing Coma Campaign convened nine working groups composed of experts in the field to construct common data elements (CDEs) to provide recommendations for DoC, with the main goal of facilitating data collection and standardization of reporting. This article summarizes the recommendations of the electrophysiology DoC working group. Methods: After assessing previously published pertinent CDEs, we developed new CDEs and categorized them into "disease core," "basic," "supplemental," and "exploratory." Key EEG design elements, defined as concepts that pertained to a methodological parameter relevant to the acquisition, processing, or analysis of data, were also included but were not classified as CDEs. Results: After identifying existing pertinent CDEs and developing novel CDEs for electrophysiology in DoC, variables were organized into a framework based on the two primary categories of resting state EEG and perturbed EEG. Using this categorical framework, two case report forms were generated by the working group. Conclusions: Adherence to the recommendations outlined by the electrophysiology working group in the resting state EEG and perturbed EEG case report forms will facilitate data collection and sharing in DoC research on an international level. In turn, this will allow for more informed and reliable comparison of results across studies, facilitating further advancement in the realm of DoC research. [ABSTRACT FROM AUTHOR]

Background: Over the past 5 decades, advances in neuroimaging have yielded insights into the pathophysiologic mechanisms that cause disorders of consciousness (DoC) in patients with severe brain injuries. Structural, functional, metabolic, and perfusion imaging studies have revealed specific neuroanatomic regions, such as the brainstem tegmentum, thalamus, posterior cingulate cortex, medial prefrontal cortex, and occipital cortex, where lesions correlate with the current or future state of consciousness. Advanced imaging modalities, such as diffusion tensor imaging, resting-state functional magnetic resonance imaging (fMRI), and task-based fMRI, have been used to improve the accuracy of diagnosis and long-term prognosis, culminating in the endorsement of fMRI for the clinical evaluation of patients with DoC in the 2018 US (task-based fMRI) and 2020 European (task-based and resting-state fMRI) guidelines. As diverse neuroimaging techniques are increasingly used for patients with DoC in research and clinical settings, the need for a standardized approach to reporting results is clear. The success of future multicenter collaborations and international trials fundamentally depends on the implementation of a shared nomenclature and infrastructure. Methods: To address this need, the Neurocritical Care Society's Curing Coma Campaign convened an international panel of DoC neuroimaging experts to propose common data elements (CDEs) for data collection and reporting in this field. Results: We report the recommendations of this CDE development panel and disseminate CDEs to be used in neuroimaging studies of patients with DoC. Conclusions: These CDEs will support progress in the field of DoC neuroimaging and facilitate international collaboration. [ABSTRACT FROM AUTHOR]

Purpose: Heterogeneous reporting in baseline variables in patients undergoing transsphenoidal resection of pituitary adenoma precludes meaningful meta-analysis. We therefore examined trends in reported baseline variables, and degree of heterogeneity of reported variables in 30 years of literature. Methods: A systematic review of PubMed and Embase was conducted on studies that reported outcomes for transsphenoidal surgery for pituitary adenoma 1990–2021. The protocol was registered a priori and adhered to the PRISMA statement. Full-text studies in English with > 10 patients (prospective), > 500 patients (retrospective), or randomised trials were included. Results: 178 studies were included, comprising 427,659 patients: 52 retrospective (29%); 118 prospective (66%); 9 randomised controlled trials (5%). The majority of studies were published in the last 10 years (71%) and originated from North America (38%). Most studies described patient demographics, such as age (165 studies, 93%) and sex (164 studies, 92%). Ethnicity (24%) and co-morbidities (25%) were less frequently reported. Clinical baseline variables included endocrine (60%), ophthalmic (34%), nasal (7%), and cognitive (5%). Preoperative radiological variables were described in 132 studies (74%). MRI alone was the most utilised imaging modality (67%). Further specific radiological baseline variables included: tumour diameter (52 studies, 39%); tumour volume (28 studies, 21%); cavernous sinus invasion (53 studies, 40%); Wilson Hardy grade (25 studies, 19%); Knosp grade (36 studies, 27%). Conclusions: There is heterogeneity in the reporting of baseline variables in patients undergoing transsphenoidal surgery for pituitary adenoma. This review supports the need to develop a common data element to facilitate meaningful comparative research, trial design, and reduce research inefficiency. [ABSTRACT FROM AUTHOR]

Abstract Background Systematic approaches are needed to accurately characterize the dynamic use of implementation strategies and how they change over time. We describe the development and preliminary evaluation of the Longitudinal Implementation Strategy Tracking System (LISTS), a novel methodology to document and characterize implementation strategies use over time. Methods The development and initial evaluation of the LISTS method was conducted within the Improving the Management of SymPtoms during And following Cancer Treatment (IMPACT) Research Consortium (supported by funding provided through the NCI Cancer MoonshotSM). The IMPACT Consortium includes a coordinating center and three hybrid effectiveness-implementation studies testing routine symptom surveillance and integration of symptom management interventions in ambulatory oncology care settings. LISTS was created to increase the precision and reliability of dynamic changes in implementation strategy use over time. It includes three components: (1) a strategy assessment, (2) a data capture platform, and (3) a User’s Guide. An iterative process between implementation researchers and practitioners was used to develop, pilot test, and refine the LISTS method prior to evaluating its use in three stepped-wedge trials within the IMPACT Consortium. The LISTS method was used with research and practice teams for approximately 12 months and subsequently we evaluated its feasibility, acceptability, and usability using established instruments and novel questions developed specifically for this study. Results Initial evaluation of LISTS indicates that it is a feasible and acceptable method, with content validity, for characterizing and tracking the use of implementation strategies over time. Users of LISTS highlighted several opportunities for improving the method for use in future and more diverse implementation studies. Conclusions The LISTS method was developed collaboratively between researchers and practitioners to fill a research gap in systematically tracking implementation strategy use and modifications in research studies and other implementation efforts. Preliminary feedback from LISTS users indicate it is feasible and usable. Potential future developments include additional features, fewer data elements, and interoperability with alternative data entry platforms. LISTS offers a systematic method that encourages the use of common data elements to support data analysis across sites and synthesis across studies. Future research is needed to further adapt, refine, and evaluate the LISTS method in studies with employ diverse study designs and address varying delivery settings, health conditions, and intervention types.

Abstract Real world evidence is now accepted by authorities charged with assessing the benefits and harms of new therapies. Clinical trials based on real world evidence are much less expensive than randomized clinical trials that do not rely on “real world evidence” such as contained in electronic health records (EHR). Consequently, we can expect an increase in the number of reports of these types of trials, which we identify here as ‘EHR-sourced trials.’ ‘In this selected literature review, we discuss the various designs and the ethical issues they raise. EHR-sourced trials have the potential to improve/increase common data elements and other aspects of the EHR and related systems. Caution is advised, however, in drawing causal inferences about the relationships among EHR variables. Nevertheless, we anticipate that EHR-CTs will play a central role in answering research and regulatory questions.

It is important to measure quality of life (QoL) after traumatic brain injury (TBI), yet limited studies have compared QoL inventories. In 2579 TBI patients, orthopedic trauma controls, and healthy friend control participants, we compared the Quality of Life After Brain Injury-Overall Scale (QOLIBRI-OS), developed for TBI patients, to the Satisfaction with Life Scale (SWLS), an index of generic life satisfaction. We tested the hypothesis that group differences (TBI and orthopedic trauma vs. healthy friend controls) would be larger for the QOLIBRI-OS than the SWLS and that the QOLIBRI-OS would manifest more substantial changes over time in the injured groups, demonstrating more relevance of the QOLIBRI-OS to traumatic injury recovery. (1) We compared the group differences (TBI vs. orthopedic trauma control vs. friend control) in QoL as indexed by the SWLS versus the QOLIBRI-OS and (2) characterized changes across time in these two inventories across 1 year in these three groups. Our secondary objective was to characterize the relationship between TBI severity and QoL. As compared with healthy friend controls, the QOLIBRI reflected greater reductions in QoL than the SWLS for both the TBI group (all time points) and the orthopedic trauma control group (2 weeks and 3 months). The QOLIBRI-OS better captured expected improvements in QoL during the injury recovery course in injured groups than the SWLS, which demonstrated smaller changes over time. TBI severity was not consistently or robustly associated with self-reported QoL. The findings imply that, as compared with the SWLS, the QOLIBRI-OS appears to identify QoL issues more specifically relevant to traumatically injured patients and may be a more appropriate primary QoL outcome measure for research focused on the sequelae of traumatic injuries.

The National Institutes of Health/National Institute of Neurological Disorders and Stroke (NIH-NINDS) Traumatic Brain Injury (TBI) Imaging Common Data Elements (CDEs) are standardized definitions for pathological intracranial lesions based on their appearance on neuroimaging studies. The NIH-NINDS TBI Imaging CDEs were designed to be as consistent as possible with the U.S. Food and Drug Administration (FDA) definition of biomarkers as "an indicator of normal biological processes, pathogenic processes, or biological responses to an exposure or intervention." However, the FDA qualification process for biomarkers requires proof of reliable biomarker test measurements. We determined the interrater reliability of TBI Imaging CDEs on subacute brain magnetic resonance imaging (MRI) performed on 517 mild TBI patients presenting to 11 U.S. level 1 trauma centers. Three U.S. board-certified neuroradiologists independently evaluated brain MRI performed 2 weeks post-injury for the following CDEs: traumatic axonal injury (TAI), diffuse axonal injury (DAI), and brain contusion. We found very high interrater agreement for brain contusion, with prevalence- and bias-adjusted kappa (PABAK) values for pairs of readers from 0.92 [95% confidence interval, 0.88-0.95] to 0.94 [0.90-0.96]. We found intermediate agreement for TAI and DAI, with PABAK values of 0.74-0.78 [0.70-0.82]. The near-perfect agreement for subacute brain contusion is likely attributable to the high conspicuity and distinctive appearance of these lesions on T1-weighted images. Interrater agreement for TAI and DAI was lower, because signal void in small vascular structures, and artifactual foci of signal void, can be difficult to distinguish from the punctate round or linear areas of slight hemorrhage that are a common hallmark of TAI/DAI on MRI.

Genotype-phenotype association studies often combine phenotype data from multiple studies to increase statistical power. Harmonization of the data usually requires substantial effort due to heterogeneity in phenotype definitions, study design, data collection procedures, and data-set organization. Here we describe a centralized system for phenotype harmonization that includes input from phenotype domain and study experts, quality control, documentation, reproducible results, and data-sharing mechanisms. This system was developed for the National Heart, Lung, and Blood Institute's Trans-Omics for Precision Medicine (TOPMed) program, which is generating genomic and other -omics data for more than 80 studies with extensive phenotype data. To date, 63 phenotypes have been harmonized across thousands of participants (recruited in 1948-2012) from up to 17 studies per phenotype. Here we discuss challenges in this undertaking and how they were addressed. The harmonized phenotype data and associated documentation have been submitted to National Institutes of Health data repositories for controlled access by the scientific community. We also provide materials to facilitate future harmonization efforts by the community, which include 1) the software code used to generate the 63 harmonized phenotypes, enabling others to reproduce, modify, or extend these harmonizations to additional studies, and 2) the results of labeling thousands of phenotype variables with controlled vocabulary terms.

Recent biomarker innovations hold potential for transforming diagnosis, prognostic modeling, and precision therapeutic targeting of traumatic brain injury (TBI). However, many biomarkers, including brain imaging, genomics, and proteomics, involve vast quantities of high-throughput and high-content data. Management, curation, analysis, and evidence synthesis of these data are not trivial tasks. In this review, we discuss data management concepts and statistical and data sharing strategies when dealing with biomarker data in the context of TBI research. We propose that application of biomarkers involves three distinct steps-discovery, evaluation, and evidence synthesis. First, complex/big data has to be reduced to useful data elements at the stage of biomarker discovery. Second, inferential statistical approaches must be applied to these biomarker data elements for assessment of biomarker clinical utility and validity. Last, synthesis of relevant research is required to support practice guidelines and enable health decisions informed by the highest quality, up-to-date evidence available. We focus our discussion around recent experiences from the International Traumatic Brain Injury Research (InTBIR) initiative, with a specific focus on four major clinical projects (Transforming Research and Clinical Knowledge in TBI, Collaborative European NeuroTrauma Effectiveness Research in TBI, Collaborative Research on Acute Traumatic Brain Injury in Intensive Care Medicine in Europe, and Approaches and Decisions in Acute Pediatric TBI Trial), which are currently enrolling subjects in North America and Europe. We discuss common data elements, data collection efforts, data-sharing opportunities, and challenges, as well as examine the statistical techniques required to realize successful adoption and use of biomarkers in the clinic as a foundation for precision medicine in TBI.

Background: A summary of clinical findings and laboratory data is collected in patient summary sheets. The aim of this study was to determine the frequency of laboratory data reported in the summary sheets based on the classification of diagnoses in ICD-10. Methods: A descriptive-cross sectional study was performed on summary sheets of patients admitted to the pediatric ward from March 2015 to February 2016.The laboratory data of these sheets were extracted using a data collection form. Because of high number of data in each sheet and given that, depending on the diagnosis, the reported laboratory data were different, to simplify the presentation of the results the data were categorized based on patients’ diagnoses which were coded by ICD-10. Results: A total of 10224 laboratory data were extracted, which included 47 unique data elements. The highest number of laboratory data was related to hematology (N = 14) and the lowest number was related to urine and stool analysis (N = 6). Conclusions: Laboratory data are recorded in summary sheets in accordance with patient's diagnosis. Therefore, it is possible to process the existing summary sheets and extract the registration rules, then implement these rules in hospital information systems to generate electronic summary sheets.

Background: Systematic approaches are needed to accurately characterize the dynamic use of implementation strategies and how they change over time. We describe the development and preliminary evaluation of the Longitudinal Implementation Strategy Tracking System (LISTS), a novel methodology to document and characterize implementation strategies use over time. Methods: The development and initial evaluation of the LISTS method was conducted within the Improving the Management of SymPtoms during And following Cancer Treatment (IMPACT) Research Consortium (supported by funding provided through the NCI Cancer MoonshotSM). The IMPACT Consortium includes a coordinating center and three hybrid effectiveness-implementation studies testing routine symptom surveillance and integration of symptom management interventions in ambulatory oncology care settings. LISTS was created to increase the precision and reliability of dynamic changes in implementation strategy use over time. It includes three components: (1) a strategy assessment, (2) a data capture platform, and (3) a User's Guide. An iterative process between implementation researchers and practitioners was used to develop, pilot test, and refine the LISTS method prior to evaluating its use in three stepped-wedge trials within the IMPACT Consortium. The LISTS method was used with research and practice teams for approximately 12 months and subsequently we evaluated its feasibility, acceptability, and usability using established instruments and novel questions developed specifically for this study. Results: Initial evaluation of LISTS indicates that it is a feasible and acceptable method, with content validity, for characterizing and tracking the use of implementation strategies over time. Users of LISTS highlighted several opportunities for improving the method for use in future and more diverse implementation studies. Conclusions: The LISTS method was developed collaboratively between researchers and practitioners to fill a research gap in systematically tracking implementation strategy use and modifications in research studies and other implementation efforts. Preliminary feedback from LISTS users indicate it is feasible and usable. Potential future developments include additional features, fewer data elements, and interoperability with alternative data entry platforms. LISTS offers a systematic method that encourages the use of common data elements to support data analysis across sites and synthesis across studies. Future research is needed to further adapt, refine, and evaluate the LISTS method in studies with employ diverse study designs and address varying delivery settings, health conditions, and intervention types. [ABSTRACT FROM AUTHOR]

Real world evidence is now accepted by authorities charged with assessing the benefits and harms of new therapies. Clinical trials based on real world evidence are much less expensive than randomized clinical trials that do not rely on "real world evidence" such as contained in electronic health records (EHR). Consequently, we can expect an increase in the number of reports of these types of trials, which we identify here as 'EHR-sourced trials.' 'In this selected literature review, we discuss the various designs and the ethical issues they raise. EHR-sourced trials have the potential to improve/increase common data elements and other aspects of the EHR and related systems. Caution is advised, however, in drawing causal inferences about the relationships among EHR variables. Nevertheless, we anticipate that EHR-CTs will play a central role in answering research and regulatory questions. [ABSTRACT FROM AUTHOR]

ObjectiveTo utilize, in an individual and institutional privacy-preserving manner, electronic health record (EHR) data from 202 hospitals by analyzing answers to COVID-19-related questions and posting these answers online.Materials and methodsWe developed a distributed, federated network of 12 health systems that harmonized their EHRs and submitted aggregate answers to consortia questions posted at https://www.covid19questions.org. Our consortium developed processes and implemented distributed algorithms to produce answers to a variety of questions. We were able to generate counts, descriptive statistics, and build a multivariate, iterative regression model without centralizing individual-level data.ResultsOur public website contains answers to various clinical questions, a web form for users to ask questions in natural language, and a list of items that are currently pending responses. The results show, for example, that patients who were taking angiotensin-converting enzyme inhibitors and angiotensin II receptor blockers, within the year before admission, had lower unadjusted in-hospital mortality rates. We also showed that, when adjusted for, age, sex, and ethnicity were not significantly associated with mortality. We demonstrated that it is possible to answer questions about COVID-19 using EHR data from systems that have different policies and must follow various regulations, without moving data out of their health systems.Discussion and conclusionsWe present an alternative or a complement to centralized COVID-19 registries of EHR data. We can use multivariate distributed logistic regression on observations recorded in the process of care to generate results without transferring individual-level data outside the health systems.

Traumatic brain injury (TBI) is an extremely complex condition due to heterogeneity in injury mechanism, underlying conditions, and secondary injury. Pre-clinical and clinical researchers face challenges with reproducibility that negatively impact translation and therapeutic development for improved TBI patient outcomes. To address this challenge, TBI Pre-clinical Working Groups expanded upon previous efforts and developed common data elements (CDEs) to describe the most frequently used experimental parameters. The working groups created 913 CDEs to describe study metadata, animal characteristics, animal history, injury models, and behavioral tests. Use cases applied a set of commonly used CDEs to address and evaluate the degree of missing data resulting from combining legacy data from different laboratories for two different outcome measures (Morris water maze [MWM]; RotorRod/Rotarod). Data were cleaned and harmonized to Form Structures containing the relevant CDEs and subjected to missing value analysis. For the MWM dataset (358 animals from five studies, 44 CDEs), 50% of the CDEs contained at least one missing value, while for the Rotarod dataset (97 animals from three studies, 48 CDEs), over 60% of CDEs contained at least one missing value. Overall, 35% of values were missing across the MWM dataset, and 33% of values were missing for the Rotarod dataset, demonstrating both the feasibility and the challenge of combining legacy datasets using CDEs. The CDEs and the associated forms created here are available to the broader pre-clinical research community to promote consistent and comprehensive data acquisition, as well as to facilitate data sharing and formation of data repositories. In addition to addressing the challenge of standardization in TBI pre-clinical studies, this effort is intended to bring attention to the discrepancies in assessment and outcome metrics among pre-clinical laboratories and ultimately accelerate translation to clinical research.

OBJECTIVE: Common data elements (CDEs) are standardized questions and answer choices that allow aggregation, analysis, and comparison of observations from multiple sources. Clinical CDEs are foundational for learning health care systems, a data-driven approach to health care focused on continuous improvement of outcomes. We aimed to create clinical CDEs for pediatric epilepsy. METHODS: A multiple stakeholder group (clinicians, researchers, parents, caregivers, advocates, and electronic health record [EHR] vendors) developed clinical CDEs for routine care of children with epilepsy. Initial drafts drew from clinical epilepsy note templates, CDEs created for clinical research, items in existing registries, consensus documents and guidelines, quality metrics, and outcomes needed for demonstration projects. The CDEs were refined through discussion and field testing. We describe the development process, rationale for CDE selection, findings from piloting, and the CDEs themselves. We also describe early implementation, including experience with EHR systems and compatibility with the International League Against Epilepsy classification of seizure types. RESULTS: Common data elements were drafted in August 2017 and finalized in January 2020. Prioritized outcomes included seizure control, seizure freedom, American Academy of Neurology quality measures, presence of common comorbidities, and quality of life. The CDEs were piloted at 224 visits at 10 centers. The final CDEs included 36 questions in nine sections (number of questions): diagnosis (1), seizure frequency (9), quality of life (2), epilepsy history (6), etiology (8), comorbidities (2), treatment (2), process measures (5), and longitudinal history notes (1). Seizures are categorized as generalized tonic-clonic (regardless of onset), motor, nonmotor, and epileptic spasms. Focality is collected as epilepsy type rather than seizure type. Seizure frequency is measured in nine levels (all used during piloting). The CDEs were implemented in three vendor systems. Early clinical adoption included 1294 encounters at one center. SIGNIFICANCE: We created, piloted, refined, finalized, and implemented a novel set of clinical CDEs for pediatric epilepsy.

Research data may have substantial impact beyond the original study objectives. The Collaborating Consortium of Cohorts Producing NIDA Opportunities (C3PNO) facilitates the combination of data and access to specimens from nine NIDA-funded cohorts in a virtual data repository (VDR). Unique challenges were addressed to create the VDR. An initial set of common data elements was agreed upon, selected based on their importance for a wide range of research proposals. Data were mapped to a common set of values. Bioethics consultations resulted in the development of various controls and procedures to protect against inadvertent disclosure of personally identifiable information. Standard operating procedures govern the evaluation of proposed concepts, and specimen and data use agreements ensure proper data handling and storage. Data from eight cohorts have been loaded into a relational database with tables capturing substance use, available specimens, and other participant data. A total of 6,177 participants were seen at a study visit within the past six months and are considered under active follow-up for C3PNO cohort participation as of the third data transfer, which occurred in January 2020. A total of 70,391 biospecimens of various types are available for these participants to test approved scientific hypotheses. Sociodemographic and clinical data accompany these samples. The VDR is a web-based interactive, searchable database available in the public domain, accessed at www.c3pno.org. The VDR are available to inform both consortium and external investigators interested in submitting concept sheets to address novel scientific questions to address high priority research on HIV/AIDS in the context of substance use.

BackgroundStandardized collection of predictors of pediatric sepsis has enormous potential to increase data compatibility across research studies. The Pediatric Sepsis Predictor Standardization Working Group collaborated to define common data elements for pediatric sepsis predictors at the point of triage to serve as a standardized framework for data collection in resource-limited settings.MethodsA preliminary list of pediatric sepsis predictor variables was compiled through a systematic literature review and examination of global guideline documents. A 5-round modified Delphi that involved independent voting and active group discussions was conducted to select, standardize, and prioritize predictors. Considerations included the perceived predictive value of the candidate predictor at the point of triage, intra- and inter-rater measurement reliability, and the amount of time and material resources required to reliably collect the predictor in resource-limited settings.ResultsWe generated 116 common data elements for implementation in future studies. Each common data element includes a standardized prompt, suggested response values, and prioritization as tier 1 (essential), tier 2 (important), or tier 3 (exploratory). Branching logic was added to the predictors list to facilitate the design of efficient data collection methods, such as low-cost electronic case report forms on a mobile application. The set of common data elements are freely available on the Pediatric Sepsis CoLab Dataverse and a web-based feedback survey is available through the Pediatric Sepsis CoLab. Updated iterations will continuously be released based on feedback from the pediatric sepsis research community and emergence of new information.ConclusionRoutine use of the common data elements in future studies can allow data sharing between studies and contribute to development of powerful risk prediction algorithms. These algorithms may then be used to support clinical decision making at triage in resource-limited settings. Continued collaboration, engagement, and feedback from the pediatric sepsis research community will be important to ensure the common data elements remain applicable across a broad range of geographical and sociocultural settings.

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Background: Clinical trials addressing large core acute ischemic stroke (AIS) are ongoing across multiple international groups. Future development of clinical guidelines depends on meta-analyses of these trials calling for a degree of homogeneity of elements across the studies. This common data element study aims to provide an overview of key features of pertinent large core infarct trials. Methods: PubMed and ClinicalTrials.gov databases were screened for published and ongoing clinical trials assessing mechanical thrombectomy in patients with AIS with large core infarct. Nested Knowledge AutoLit living review platform was utilized to categorize primary and secondary outcomes as well as inclusion and exclusion criteria for patient selection in the trials. Results: The most reported data element was ASPECTS score but with varied definitions of what constitutes large core. Non-utility-weighted modified Rankin score (mRS) was reported in 6/7 studies as the primary outcome, while the utility-weighted mRS was the outcome of interest in the TESLA trial, all of them at the 3 months mark, with only LASTE looking for mRS shift at the 6 months mark. Secondary outcomes had more variations. Mortality is reported separately only in 4/7 trials, all at the 3‑month mark. Additionally, the TENSION trial reported the frequency of serious adverse events, including mortality, at the 1‑week and 12-month mark. Discussion: Overall, in large core trials there is a large degree of heterogeneity in the collected data elements. Differences in definition and timepoints render reaching a unified standard difficult, which hinders high quality meta-analyses and cohesive evidence-driven synthesis. [ABSTRACT FROM AUTHOR]

OBJECTIVES: Common data elements are a combination of a precisely defined question paired with a specified set of responses. Common data elements contribute to the National Institutes of Health-supported principle of Findable, Accessible, Interoperable, and Reusableness of research data. Routine use of Common data elements and standardized definitions within pediatric critical care research are likely to promote collaboration, improve quality, and consistency of data collection, improve overall efficiency of study or trial setup, and facilitate cross-study comparisons, meta-analysis, and merging of study cohorts. The purpose of this Pediatric Critical Care Medicine Perspective is to establish a road map for the development of multinational, multidisciplinary consensus-based common data elements that could be adapted for use within any pediatric critical care subject area. METHODS: We describe a multistep process for the creation of core domains of research (e.g. patient outcomes, health-related conditions, or aspects of health) and the development of common data elements within each core domain. We define a tiered approach to data collection based on relevance of each common data element to future studies and clinical practice within the field of interest. Additionally, we describe the use of the Delphi methods to achieve consensus of these common data element documents using an international, multidisciplinary panel of experts.

The premise of Open Science is that research and medical management will progress faster if data and knowledge are openly shared. The value of Open Science is nowhere more important and appreciated than in the rare disease (RD) community. Research into RDs has been limited by insufficient patient data and resources, a paucity of trained disease experts, and lack of therapeutics, leading to long delays in diagnosis and treatment. These issues can be ameliorated by following the principles and practices of sharing that are intrinsic to Open Science. Here, we describe how the RD community has adopted the core pillars of Open Science, adding new initiatives to promote care and research for RD patients and, ultimately, for all of medicine. We also present recommendations that can advance Open Science more globally.

Standardization and harmonization of data collection in studies on traumatic brain injury (TBI) is of paramount importance for meta-analyses across studies. Nearly 10 years ago, the first set of Common Data Elements for TBI (TBI-CDEs v1) were introduced to achieve these goals. The TBI-CDEs version 2 were developed in 2012 to broaden the approach to all ages, injury severity, and phases of recovery. We aimed to quantify the degree of harmonization of these data elements in three large, prospective multi-center studies conducted within the International Initiative for TBI Research (InTBIR). Data variables of the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI; adult and pediatric patients in Europe and Israel), Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI; adult and pediatric patients in the U.S.), and Approaches and Decisions in Acute Pediatric TBI (ADAPT; international study on severe pediatric TBI) studies were indexed and matched to the second version of the TBI CDEs. We focused on the CDE sub-categories of "Acute Hospitalized" (AH) and "Moderate/Severe TBI: Rehabilitation (Rehab). All "Core" and "Basic" level CDEs were considered. Closely related elements were reduced to one variable to prevent over-representation. Categorical elements and text elements for the same variable were likewise merged to one element for analysis. Following reduction and merging of related elements, 21 Core, 46 Basic AH, and 50 Basic Rehab elements were deemed harmonizable across studies. Gaps in global applicability were identified for four of the TBI CDEs and many of the outcome instruments, which are only available in the English language. Agreements of Core and Basic study CDEs for the AH domain with the TBI CDEs were respectively 81% and 91% for CENTER-TBI, 76% and 93% for TRACK-TBI, and 85% in ADAPT for both domains. For the domain Rehab, agreement with Basic TBI CDEs was 84% for CENTER-TBI, 94% for TRACK-TBI, and 71% for ADAPT. Non-harmonization was largely caused by absence of the elements in the studies. For elements present, the compatibility of coding with TBI CDEs was 90-99%. The degree of harmonization was greatest between CENTER-TBI and TRACK-TBI with 81-87% overlap within the TBI CDE sub-categories. The high degree of harmonization of study variables among these studies demonstrates the importance and utility of common data elements in TBI research. It also confirms the potential for future meta-analyses across these large studies, especially for CENTER TBI and TRACK TBI. The global applicability of the TBI CDEs needs to be improved for them to become a global standard for TBI research. CENTER-TBI, TRACK-TBI, and ADAPT, along with other studies within the InTBIR Initiative, provide a platform to inform further refinement and internationalization for the next version of the TBI CDEs.

The National Institutes of Health has established the PhenX Toolkit as a web-based resource containing consensus measures freely available to the research community. The National Institute of Mental Health (NIMH) has introduced the Mental Health Research Core Collection as part of the PhenX Toolkit and recently convened the PhenX Early Psychosis Working Group to generate the PhenX Early Psychosis Specialty Collection. The Working Group consisted of two complementary panels for clinical and translational research. We review the process, deliberations, and products of the translational research panel. The Early Psychosis Specialty Collection rationale for measure selection as well as additional information and protocols for obtaining each measure are available on the PhenX website (https://www.phenxtoolkit.org). The NIMH strongly encourages investigators to use instruments from the PhenX Mental Health Research Collections in NIMH-funded studies and discourages use of alternative measures to collect similar data without justification. We also discuss some of the potential advances that can be achieved by collecting common data elements across large-scale longitudinal studies of early psychosis.

Abstract Background Corrosive ingestion is still a major health problem, and its outcomes are often unpredicted. The implementation of a registry system for poisoning with corrosive substances may improve the quality of patient care and might be useful to manage this type of poisoning and its complications. Therefore, our study aimed to establish a minimum data set (MDS) for corrosive ingestion. Methods This was an applied study performed in 2022. First, a literature review was conducted to identify the potential data items to be included in the corrosive ingestion MDS. Then, a two-round Delphi survey was performed to attain an agreement among experts regarding the MDS content, and an additional Delphi step was used for confirming the final MDS by calculating the individual item content validity index (CVI) and content validity ratio (CVR) and by using other statistical tests. Results After the literature review, 285 data items were collected and sent to a two-round Delphi survey in the form of a questionnaire. In total, 75 experts participated in the Delphi stage, CVI, kappa, and CVR calculation. Finally, the MDS of the corrosive ingestion registry system was identified in two administrative and clinical sections with 21 and 152 data items, respectively. Conclusions The development of an MDS, as the first and most important step towards developing the corrosive ingestion registry, can become a standard basis for data collection, reporting, and analysis of corrosive ingestion. We hope this MDS will facilitate epidemiological surveys and assist policymakers by providing higher quality data capture to guide clinical practice and improve patient-centered outcomes.

In recent decades, the use of common data elements has expanded across the health disciplines. This has included growth within programs of research focused on self-management and family nursing. Family nursing and self-management science may be expanded with the increased use of common concepts, measures, and theoretical frameworks. This article describes the experience of exploring the use of common data elements and identifying shared concepts from the perspective of one National Institute of Nursing Research funded Exploratory Center in Self-Management. Guidance offered by the Individual and Family Self-Management Theory is discussed, and implications for family research are presented. [ABSTRACT FROM AUTHOR]

Introduction: AO Spine RECODE-DCM was a multi-stakeholder priority setting partnership (PSP) to define the top ten research priorities for degenerative cervical myelopathy (DCM). Priorities were generated and iteratively refined using a series of surveys administered to surgeons, other healthcare professionals (oHCP) and people with DCM (PwDCM). The aim of this work was to utilise word clouds to enable the perspectives of people with the condition to be heard earlier in the PSP process than is traditionally the case. The objective was to evaluate the added value of word clouds in the process of defining research uncertainties in National Institute for Health Research (NIHR) James Lind Alliance (JLA) Priority Setting Partnerships. Methods: Patient-generated word clouds were created for the four survey subsections of the AO Spine RECODE-DCM PSP: diagnosis, treatment, long-term management and other issues. These were then evaluated as a nested methodological study. Word-clouds were created and iteratively refined by an online support group of people with DCM, before being curated by the RECODE-DCM management committee and expert healthcare professional representatives. The final word clouds were embedded within the surveys administered at random to 50% of participants. DCM research uncertainties suggested by participants were compared pre- and post-word cloud presentation. Results: A total of 215 (50.9%) participants were randomised to the word cloud stream, including 118 (55%) spinal surgeons, 52 (24%) PwDCM and 45 (21%) oHCP. Participants submitted 434 additional uncertainties after word cloud review: word count was lower and more uniform across each survey subsections compared to pre-word cloud uncertainties. Twenty-three (32%) of the final 74 PSP summary questions did not have a post-word cloud contribution and no summary question was formed exclusively on post-word cloud uncertainties. There were differences in mapping of pre- and post-word cloud uncertainties to summary questions, with greater mapping of post-word cloud uncertainties to the number 1 research question priority: raising awareness. Five of the final summary questions were more likely to map to the research uncertainties suggested by participants after having reviewed the word clouds. Conclusions: Word clouds may increase the perspective of underrepresented stakeholders in the research question gathering stage of priority setting partnerships. This may help steer the process towards research questions that are of highest priority for people with the condition. [ABSTRACT FROM AUTHOR]

Newborn screening (NBS) is a large-scale public health program in the US that screens 3.8 million newborns for up to 81 genetic conditions each year. Many of these conditions have comorbidities, including neurodevelopmental disorders (NDDs). These comorbidities can have a significant impact on health outcomes across the lifespan. Most screened conditions are inborn errors of metabolism. PKU, the first condition identified by NBS, is an inherited metabolic disorder that can cause developmental delays and intellectual/developmental disabilities if not treated. The Newborn Screening Translational Research Network (NBSTRN) is a program that has been funded by the National Institute of Child Health and Human Development since 2008. NBSTRN is charged with developing, maintaining, and enhancing tools, resources, and expertise supporting NBS research. One of the tasks led by NBSTRN is to provide direction for developing question/answer sets used in the Longitudinal Pediatric Data Resource (LPDR) to create consensus-based and standardized common data elements (CDEs) for NBS conditions. There is growing interest in the NBS community in assessing neurodevelopmental trajectories through long-term follow-up studies. This could be streamlined by employing uniform CDEs. To address this unmet need, we conducted a landscape analysis to (1) explore the co-occurrence of NDD-related comorbidities and NBS conditions using text mining in MedGen, (2) compile a list of NDD-related CDEs from existing repositories as well as LPDR data dictionaries, and (3) identify challenges and knowledge gaps hindering the early identification of risks for NDDs in NBS conditions. Our findings can inform future efforts toward advancing the research infrastructure for this established public health program. The renewed awareness of the risk of NDDs after a positive NBS and diagnosis could lead to improved treatment guidelines for mental health conditions.

RationaleThe Epilepsy Bioinformatics Study for Antiepileptogenic Therapy (EpiBioS4Rx) Centre without walls is an NIH funded multicenter consortium. One of EpiBioS4Rx projects is a preclinical post-traumatic epileptogenesis biomarker study that involves three study sites: The University of Eastern Finland, Monash University (Melbourne) and the University of California Los Angeles. Our objective is to create a platform for evaluating biomarkers and testing new antiepileptogenic treatments for post-traumatic epilepsy (PTE) using the lateral fluid percussion injury (FPI) model in rats. As only 30-50% of rats with severe lateral FPI develop PTE by 6 months post-injury, prolonged video-EEG monitoring is crucial to identify animals with PTE. Our objective is to harmonize the surgical and data collection procedures, equipment, and data analysis for chronic EEG recording in order to phenotype PTE in this rat model across the three study sites.MethodsTraumatic brain injury (TBI) was induced using lateral FPI in adult male Sprague-Dawley rats aged 11-12 weeks. Animals were divided into two cohorts: a) the long-term video-EEG follow-up cohort (Specific Aim 1), which was implanted with EEG electrodes within 24 h after the injury; and b) the magnetic resonance imaging (MRI) follow-up cohort (Specific Aim 2), at 5 months after lateral FPI. Four cortical epidural screw electrodes (2 ipsilateral, 2 contralateral) and three intracerebral bipolar electrodes were implanted (septal CA1 and the dentate gyrus, layers II and VI of the perilesional cortex both anterior and posterior to the injury site). During the 7th post-TBI month, animals underwent 4 weeks of continuous video-EEG recordings to diagnose of PTE.ResultsAll centers harmonized the induction of TBI and surgical procedures for the implantation of EEG recordings, utilizing 4 or more EEG recording channels to cover areas ipsilateral and contralateral to the brain injury, perilesional cortex and the hippocampus and dentate gyrus. Ground and reference screw electrodes were implanted. At all sites the minimum sampling rate was 512 Hz, utilizing a finite impulse response (FIR) and impedance below 10 KΩ through the entire recording. As part of the quality control criteria we avoided electrical noise, and monitoring changes in impedance over time and the appearance of noise on the recordings. To reduce electrical noise, we regularly checked the integrity of the cables, stability of the EEG recording cap and the appropriate connection of the electrodes with the cables. Following the pipeline presented in this article and after applying the quality control criteria to our EEG recordings all of the sites were successful to phenotype seizure in chronic EEG recordings of animals after TBI.DiscussionDespite differences in video-EEG acquisition equipment used, the three centers were able to consistently phenotype seizures in the lateral fluid-percussion model applying the pipeline presented here. The harmonization of methodology will help to improve the rigor of preclinical research, improving reproducibility of pre-clinical research in the search of biomarkers and therapies to prevent antiepileptogenesis.

Introduction: Risk factors for young adults with mTBI are not well understood. Improved understanding of age and sex as risk factors for impaired six-month outcomes in young adults is needed. Methods: Young adult mTBI subjects aged 18-39 years (18-29y; 30-39y) with six-month outcomes were extracted from the Transforming Research and Clinical Knowledge in Traumatic Brain Injury Pilot (TRACK-TBI Pilot) study. Multivariable regressions were performed for outcomes with age, sex, and the interaction factor age-group*sex as variables of interest, controlling for demographic and injury variables. Mean-differences (B) and 95% CIs are reported. Results: One hundred mTBI subjects (18-29y, 70%; 30-39y, 30%; male, 71%; female, 29%) met inclusion criteria. On multivariable analysis, age-group*sex was associated with six-month post-traumatic stress disorder (PTSD; PTSD Checklist-Civilian version); compared with female 30-39y, female 18-29y (B= -19.55 [-26.54, -4.45]), male 18-29y (B= -19.70 [-30.07, -9.33]), and male 30-39y (B= -15.49 [-26.54, -4.45]) were associated with decreased PTSD symptomatology. Female sex was associated with decreased six-month functional outcome (Glasgow Outcome Scale-Extended (GOSE): B= -0.6 [1.0, -0.1]). Comparatively, 30-39y scored higher on six-month nonverbal processing speed (Wechsler Adult Intelligence Scale-Processing Speed Index (WAIS-PSI); B= 11.88, 95% CI [1.66, 22.09]). Conclusions: Following mTBI, young adults aged 18-29y and 30-39y may have different risks for impairment. Sex may interact with age for PTSD symptomatology, with females 30-39y at highest risk. These results may be attributable to cortical maturation, biological response, social modifiers, and/or differential self-report. Confirmation in larger samples is needed; however, prevention and rehabilitation/counseling strategies after mTBI should likely be tailored for age and sex.