Optimising Clinical Epidemiology in Disease Outbreaks: Analysis of ISARIC-WHO COVID-19 Case Report Form Utilisation.

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.

Common Data Elements for Disorders of Consciousness: Recommendations from the Working Group on Outcomes and Endpoints.

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.

Linked Exposures Across Databases: an exposure common data elements aggregation framework to facilitate clinical exposure review.

Understanding the health outcomes of military exposures is of critical importance for Veterans, their health care team, and national leaders. Approximately 43% of Veterans report military exposure concerns to their VA providers. Understanding the causal influences of environmental exposures on health is a complex exposure science task and often requires interpreting multiple data sources; particularly when exposure pathways and multi-exposure interactions are ill-defined, as is the case for complex and emerging military service exposures. Thus, there is a need to standardize clinically meaningful exposure metrics from different data sources to guide clinicians and researchers with a consistent model for investigating and communicating exposure risk profiles. The Linked Exposures Across Databases (LEAD) framework provides a unifying model for characterizing exposures from different exposure databases with a focus on providing clinically relevant exposure metrics. Application of LEAD is demonstrated through comparison of different military exposure data sources: Veteran Military Occupational and Environmental Exposure Assessment Tool (VMOAT), Individual Longitudinal Exposure Record (ILER) database, and a military incident report database, the Explosive Ordnance Disposal Information Management System (EODIMS). This cohesive method for evaluating military exposures leverages established information with new sources of data and has the potential to influence how military exposure data is integrated into exposure health care and investigational models.

The Australian Traumatic Brain Injury Initiative: Systematic Review of Clinical Factors Associated with Outcomes in People with Moderate-Severe Traumatic Brain Injury.

The aim of the Australian Traumatic Brain Injury Initiative (AUS-TBI) is to design a data dictionary to inform data collection and facilitate prediction of outcomes for moderate-severe traumatic brain injury (TBI) across Australia. The process has engaged diverse stakeholders across six areas: social, health, clinical, biological, acute interventions, and long-term outcomes. Here, we report the results of the clinical review. Standardized searches were implemented across databases to April 2022. English-language reports of studies evaluating an association between a clinical factor and any clinical outcome in at least 100 patients with moderate-severe TBI were included. Abstracts, and full-text records, were independently screened by at least two reviewers in Covidence. The findings were assessed through a consensus process to determine inclusion in the AUS-TBI data resource. The searches retrieved 22,441 records, of which 1137 were screened at full text and 313 papers were included. The clinical outcomes identified were predominantly measures of survival and disability. The clinical predictors most frequently associated with these outcomes were the Glasgow Coma Scale, pupil reactivity, and blood pressure measures. Following discussion with an expert consensus group, 15 were recommended for inclusion in the data dictionary. This review identified numerous studies evaluating associations between clinical factors and outcomes in patients with moderate-severe TBI. A small number of factors were reported consistently, however, how and when these factors were assessed varied. The findings of this review and the subsequent consensus process have informed the development of an evidence-informed data dictionary for moderate-severe TBI in Australia.

Standardized reporting for Head CT Scans in patients suspected of traumatic brain injury (TBI): An international expert endeavor.

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).

Standardizing imaging findings representation: harnessing Common Data Elements semantics and Fast Healthcare Interoperability Resources structures.

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.

Application of the Delphi method to the development of common data elements for social drivers of health: A systematic scoping review.

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.

Collecting and capturing social factors that affect individuals' health is imperative. Social drivers of health data allow researchers to understand health disparities to make healthcare available, accessible, and affordable. However, collecting common health data elements has challenged researchers due to limited resources to facilitate change. Incorporating various stakeholders, such as individuals and patient advocacy groups, can effectively contribute to the research process as community advisors. This article reviews the studies that used the Delphi method and brings together experts to agree on guidelines for collecting common data elements. The article's findings reveal that experts are healthcare professionals and researchers, leaving out the crucial input from patients and caregivers. This article emphasized that developing a standard set of data elements can improve the standardization of social drivers of health. Common data elements provide the opportunity to improve patients' and social circumstances and their efforts toward health outcomes.

The Australian Traumatic Brain Injury Initiative: Review and Recommendations for Outcome Measures for Use With Adults and Children After Moderate-to-Severe Traumatic Brain Injury.

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: Statement of Working Principles and Rapid Review of Methods to Define Data Dictionaries for Neurological Conditions.

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.

Heterogeneity in Measures of Illness among Patients with Myalgic Encephalomyelitis/Chronic Fatigue Syndrome Is Not Explained by Clinical Practice: A Study in Seven U.S. Specialty Clinics.

Background: One of the goals of the Multi-site Clinical Assessment of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (MCAM) study was to evaluate whether clinicians experienced in diagnosing and caring for patients with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) recognized the same clinical entity. Methods: We enrolled participants from seven specialty clinics in the United States. We used baseline data (n = 465) on standardized questions measuring general clinical characteristics, functional impairment, post-exertional malaise, fatigue, sleep, neurocognitive/autonomic symptoms, pain, and other symptoms to evaluate whether patient characteristics differed by clinic. Results: We found few statistically significant and no clinically significant differences between clinics in their patients' standardized measures of ME/CFS symptoms and function. Strikingly, patients in each clinic sample and overall showed a wide distribution in all scores and measures. Conclusions: Illness heterogeneity may be an inherent feature of ME/CFS. Presenting research data in scatter plots or histograms will help clarify the challenge. Relying on case-control study designs without subgrouping or stratification of ME/CFS illness characteristics may limit the reproducibility of research findings and could obscure underlying mechanisms.

Identifying Common Data Elements to Achieve Injury-related Health Equity Across the Lifespan: A Consensus-Driven Approach.

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.

Connecting Chronic Pain and Opioid Use Disorder Clinical Trials Through Data Harmonization: Wake Forest IMPOWR Dissemination, Education, and Coordination Center (IDEA-CC).

The National Institutes of Health (NIH) has developed the NIH HEAL Integrative Management of chronic Pain and OUD for Whole Recovery (IMPOWR) network to address the interconnected nature of chronic pain (CP) and opioid use disorder (OUD), which are influenced by mental health. The network aims to develop integrated treatment pathways across multiple sites in the United States. The IMPOWR Dissemination, Education, and Coordination Center (IDEA-CC) is proposed to support the NIH HEAL IMPOWR network by developing a CP- and OUD-focused infrastructure that includes measures of stigma, trauma, and quality of life. This includes deploying a data framework to link clinical sites, developing an educational infrastructure to address stigma and health disparities, and disseminating research findings. The IDEA-CC will standardize data collection processes, develop web-based data commons, and facilitate data sharing opportunities. The IDEA-CC will support the development and validation of composite CP and OUD measures and will develop educational materials to address stigma and health disparities. Overall, the IDEA-CC will create a research community and data commons that connect NIH HEAL IMPOWR centers to translate findings and develop a key CP-OUD research data, and education infrastructure.

The Australian Traumatic Brain Injury Initiative: Systematic Review and Consensus Process to Determine the Predictive Value of Pre-existing Health Conditions for People with Moderate-Severe Traumatic Brain Injury.

The first aim of the Australian Traumatic Brain Injury Initiative (AUS-TBI) encompasses development of a set of measures that comprehensively predict outcomes for people with moderate-severe TBI across Australia. This process engaged diverse stakeholders and information sources across six areas: social, health, and clinical factors; biological markers; treatments; and longer-term outcomes. Here, we report the systematic review of pre-existing health conditions as predictors of outcome for people with moderate-severe TBI. Standardized searches were implemented across databases until March 31, 2022. English-language reports of studies evaluating association between pre-existing health conditions and clinical outcome in at least 10 patients with moderate-severe TBI were included. A predefined algorithm was used to assign a judgement of predictive value to each observed association. The list of identified pre-existing health conditions was then discussed with key stakeholders during a consensus meeting to determine the feasibility of incorporating them into standard care. The searches retrieved 22,217 records, of which 47 articles were included. The process led to identification of 88 unique health predictors (homologized to 21 predictor categories) of 55 outcomes (homologized to 19 outcome categories). Only pre-existing health conditions with high and moderate predictive values were discussed during the consensus meeting. Following the consensus meeting, 5 out of 11 were included (migraine, mental health conditions, ≥4 pre-existing health conditions, osteoporosis, and body mass index [BMI]) as common data elements in the AUS-TBI data dictionary. Upon further discussion, 3 additional pre-existing health conditions were included. These are pre-existing heart disease, frailty score, and previous incidence of TBI.

Imaging Findings in Acute Traumatic Brain Injury: a National Institute of Neurological Disorders and Stroke Common Data Element-Based Pictorial Review and Analysis of Over 4000 Admission Brain Computed Tomography Scans from the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) Study.

In 2010, the National Institute of Neurological Disorders and Stroke (NINDS) created a set of common data elements (CDEs) to help standardize the assessment and reporting of imaging findings in traumatic brain injury (TBI). However, as opposed to other standardized radiology reporting systems, a visual overview and data to support the proposed standardized lexicon are lacking. We used over 4000 admission computed tomography (CT) scans of patients with TBI from the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study to develop an extensive pictorial overview of the NINDS TBI CDEs, with visual examples and background information on individual pathoanatomical lesion types, up to the level of supplemental and emerging information (e.g., location and estimated volumes). We documented the frequency of lesion occurrence, aiming to quantify the relative importance of different CDEs for characterizing TBI, and performed a critical appraisal of our experience with the intent to inform updating of the CDEs. In addition, we investigated the co-occurrence and clustering of lesion types and the distribution of six CT classification systems. The median age of the 4087 patients in our dataset was 50 years (interquartile range, 29-66; range, 0-96), including 238 patients under 18 years old (5.8%). Traumatic subarachnoid hemorrhage (45.3%), skull fractures (37.4%), contusions (31.3%), and acute subdural hematoma (28.9%) were the most frequently occurring CT findings in acute TBI. The ranking of these lesions was the same in patients with mild TBI (baseline Glasgow Coma Scale [GCS] score 13-15) compared with those with moderate-severe TBI (baseline GCS score 3-12), but the frequency of occurrence was up to three times higher in moderate-severe TBI. In most TBI patients with CT abnormalities, there was co-occurrence and clustering of different lesion types, with significant differences between mild and moderate-severe TBI patients. More specifically, lesion patterns were more complex in moderate-severe TBI patients, with more co-existing lesions and more frequent signs of mass effect. These patients also had higher and more heterogeneous CT score distributions, associated with worse predicted outcomes. The critical appraisal of the NINDS CDEs was highly positive, but revealed that full assessment can be time consuming, that some CDEs had very low frequencies, and identified a few redundancies and ambiguity in some definitions. Whilst primarily developed for research, implementation of CDE templates for use in clinical practice is advocated, but this will require development of an abbreviated version. In conclusion, with this study, we provide an educational resource for clinicians and researchers to help assess, characterize, and report the vast and complex spectrum of imaging findings in patients with TBI. Our data provides a comprehensive overview of the contemporary landscape of TBI imaging pathology in Europe, and the findings can serve as empirical evidence for updating the current NINDS radiologic CDEs to version 3.0.

Exploring the similarities and differences of burn registers globally: Results from a data dictionary comparison study.

INTRODUCTION: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

Landscape Analysis of Neurodevelopmental Comorbidities in Newborn Screening Conditions: Challenges and Opportunities.

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.

The Australian Traumatic Brain Injury Initiative: Systematic Review of the Effect of Acute Interventions on Outcome for People With Moderate-Severe Traumatic Brain Injury.

The Australian Traumatic Brain Injury Initiative (AUS-TBI) is developing a data resource to enable improved outcome prediction for people with moderate-severe TBI (msTBI) across Australia. Fundamental to this resource is the collaboratively designed data dictionary. This systematic review and consultation aimed to identify acute interventions with potential to modify clinical outcomes for people after msTBI, for inclusion in a data dictionary. Standardized searches were implemented across bibliographic databases from inception through April 2022. English-language reports of randomized controlled trials (RCTs) evaluating any association between any acute intervention and clinical outcome in at least 100 patients with msTBI, were included. A predefined algorithm was used to assign a value to each observed association. Consultation with AUS-TBI clinicians and researchers formed the consensus process for interventions to be included in a single data dictionary. Searches retrieved 14,455 records, of which 124 full-length RCTs were screened, with 35 studies included. These studies evaluated 26 unique acute interventions across 21 unique clinical outcomes. Only 4 interventions were considered to have medium modifying value for any outcome from the review, with an additional 8 interventions agreed upon through the consensus process. The interventions with medium value were tranexamic acid and phenytoin, which had a positive effect on an outcome; and decompressive craniectomy surgery and hypothermia, which negatively affected outcomes. From the systematic review and consensus process, 12 interventions were identified as potential modifiers to be included in the AUS-TBI national data resource.

Common Design, Data Elements and Core Outcome Measures Reported on Clinical Trials of Genicular Artery Embolization for Knee Osteoarthritis: An Interactive Systematic Review.

RATIONALE AND OBJECTIVES: 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. MATERIALS AND METHODS: 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. RESULTS: 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. CONCLUSION: 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.

Common Data Elements for Disorders of Consciousness: Recommendations from the Working Group in the Pediatric Population.

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.