Multiligament Knee Reconstruction With Suture Tape Augmentation: Patient-Reported Outcomes at Minimum 2-Year Follow-up.

BACKGROUND: Multiligament knee injury (MLKI) is a severe subclass of orthopedic injury and can result in significant functional impairment. Novel MLKI graft constructs such as suture augmentation aim to enhance graft strength and optimize knee stability. The purpose of this study was to present patient-reported outcome measurements of a cohort at a minimum follow-up of 2 years after multiligament knee reconstruction (MLKR) with suture augmentation. MATERIALS AND METHODS: A retrospective chart review was performed to identify patients who underwent MLKR with suture augmentation. Demographic and injury-specific variables were gathered preoperatively and postoperatively. Patients were contacted at a minimum of 2 years postoperatively to collect Patient-Reported Outcomes Measurement Information System, Multiligament Quality of Life, and Lysholm knee scores. RESULTS: Twenty-seven patients underwent MLKR with suture augmentation, with 15 being female (55.6%) and 12 being male (44.4%). The mean pain score was 49.93±9.96, the mean physical function score was 49.56±10.94, and the mean mobility score was 47.56±8.58. The mean physical impairment score was 33.96±23.69, the mean emotional impairment score was 36.55±26.60, the mean activity limitation score was 28.00±25.61, and the mean societal involvement score was 30.09±27.45. The mean Lysholm knee score for the cohort was 67.93±22.36. CONCLUSION: Patients who underwent MLKR with suture augmentation had satisfactory scores across all patient-reported outcome measurements. On the basis of these criteria, the average patient achieved an acceptable clinical outcome, demonstrating that MLKR with suture augmentation is a safe and efficacious surgical technique for the treatment of MLKI. [Orthopedics. 202x;4x(x):xx-xx.].

A qualitative interview study to determine barriers and facilitators of implementing automated decision support tools for genomic data access.

Data access committees (DAC) gatekeep access to secured genomic and related health datasets yet are challenged to keep pace with the rising volume and complexity of data generation. Automated decision support (ADS) systems have been shown to support consistency, compliance, and coordination of data access review decisions. However, we lack understanding of how DAC members perceive the value add of ADS, if any, on the quality and effectiveness of their reviews. In this qualitative study, we report findings from 13 semi-structured interviews with DAC members from around the world to identify relevant barriers and facilitators to implementing ADS for genomic data access management. Participants generally supported pilot studies that test ADS performance, for example in cataloging data types, verifying user credentials and tagging datasets for use terms. Concerns related to over-automation, lack of human oversight, low prioritization, and misalignment with institutional missions tempered enthusiasm for ADS among the DAC members we engaged. Tensions for change in institutional settings within which DACs operated was a powerful motivator for why DAC members considered the implementation of ADS into their access workflows, as well as perceptions of the relative advantage of ADS over the status quo. Future research is needed to build the evidence base around the comparative effectiveness and decisional outcomes of institutions that do/not use ADS into their workflows.

Efficacy of Postoperative Opioid-Sparing Regimens for Hand Surgery: A Systematic Review of Randomized Controlled Trials.

PURPOSE: Multiple interventions have been implemented to reduce opioid prescribing in upper extremity surgery. However, few studies have evaluated pain relief and patient satisfaction as related to failure of these protocols. We sought to evaluate the efficacy of limited and nonopioid ("opioid-sparing") regimens for upper extremity surgery as it pertains to patient satisfaction, pain experienced, and need for additional refills/rescue analgesia. METHODS: We aimed to systematically review randomized controlled trials of opioid-sparing approaches in upper extremity surgery. An initial search of studies evaluating opioid-sparing regimens after upper extremity surgery from the elbow distal yielded 1,320 studies, with nine meeting inclusion criteria. Patient demographics, surgery type, postoperative pain regimen, satisfaction measurements, and number of patients inadequately treated within each study were recorded. Outcomes were assessed using descriptive statistics. RESULTS: Nine randomized controlled trials with 1,480 patients were included. Six of nine studies (67%) reported superiority or equivalence of pain relief with nonopioid or limited opioid regimens. However, across all studies, 4.2% to 25% of patients were not adequately treated by the opioid-sparing protocols. This includes four of seven studies (57%) assessing number of medication refills or rescue analgesia reporting increased pill consumption, refills, or rescue dosing with limited/nonopioid regimens. Five of six studies (83%) reporting satisfaction outcomes found no difference in satisfaction with pain control, medication strength, and overall surgical experience using opioid-sparing regimens. CONCLUSIONS: Opioid-sparing regimens provide adequate pain relief for most upper extremity surgery patients. However, a meaningful number of patients on opioid-sparing regimens required greater medication refills and increased use of rescue analgesia. These patients also reported no difference in satisfaction compared with limited/nonopioid regimens. TYPE OF STUDY/LEVEL OF EVIDENCE: Therapeutic II.

Investigating the Roles and Responsibilities of Institutional Signing Officials After Data Sharing Policy Reform for Federally Funded Research in the United States: National Survey.

BACKGROUND: New federal policies along with rapid growth in data generation, storage, and analysis tools are together driving scientific data sharing in the United States. At the same, triangulating human research data from diverse sources can also create situations where data are used for future research in ways that individuals and communities may consider objectionable. Institutional gatekeepers, namely, signing officials (SOs), are therefore at the helm of compliant management and sharing of human data for research. Of those with data governance responsibilities, SOs most often serve as signatories for investigators who deposit, access, and share research data between institutions. Although SOs play important leadership roles in compliant data sharing, we know surprisingly little about their scope of work, roles, and oversight responsibilities. OBJECTIVE: The purpose of this study was to describe existing institutional policies and practices of US SOs who manage human genomic data access, as well as how these may change in the wake of new Data Management and Sharing requirements for National Institutes of Health-funded research in the United States. METHODS: We administered an anonymous survey to institutional SOs recruited from biomedical research institutions across the United States. Survey items probed where data generated from extramurally funded research are deposited, how researchers outside the institution access these data, and what happens to these data after extramural funding ends. RESULTS: In total, 56 institutional SOs participated in the survey. We found that SOs frequently approve duplicate data deposits and impose stricter access controls when data use limitations are unclear or unspecified. In addition, 21% (n=12) of SOs knew where data from federally funded projects are deposited after project funding sunsets. As a consequence, most investigators deposit their scientific data into "a National Institutes of Health-funded repository" to meet the Data Management and Sharing requirements but also within the "institution's own repository" or a third-party repository. CONCLUSIONS: Our findings inform 5 policy recommendations and best practices for US SOs to improve coordination and develop comprehensive and consistent data governance policies that balance the need for scientific progress with effective human data protections.

Achieving Procedural Parity in Managing Access to Genomic and Related Health Data: A Global Survey of Data Access Committee Members.

Data access committees (DACs) are critical players in the data sharing ecosystem. DACs review requests for access to data held in one or more repositories and where specific constraints determine how the data may be used and by whom. Our team surveyed DAC members affiliated with genomic data repositories worldwide to understand standard processes and procedures, operational metrics, bottlenecks, and efficiencies, as well as their perspectives on possible improvements to quality review. We found that DAC operations and systemic issues were common across repositories globally. In general, DAC members endeavored to achieve an appropriate balance of review efficiency, quality, and compliance. Our results suggest a similarly proportionate path forward that helps DACs pursue mutual improvements to efficiency and compliance without sacrificing review quality.

Antibiotic Prophylaxis in the Management of Distal Fingertip Amputation and Crush Injury.

Purpose: We sought to investigate the role of prophylactic antibiotics for distal fingertip crush injury or transphalangeal amputation treated outside of an operating room and better understand the factors that contribute to antibiotic-prescribing decisions. We hypothesized that prophylactic antibiotics do not meaningfully reduce the incidence of infection and that antibiotics are prescribed in a predictable way. Methods: This is a retrospective review of all patients treated in a MedStar-affiliated emergency department or urgent care for nonsurgical distal fingertip trauma in 2019. Patient demographics, comorbidities, injury characteristics, interventions, and follow-up details were recorded. Exclusion criteria included signs of infection at the time of presentation, minor injuries not requiring intervention, bite wounds, one-time intravenous antibiotic administration without oral course, and surgical intervention. Outcomes included infection and interventions at follow-up. Chi-square analysis was performed, comparing antibiotic and no-antibiotic groups. A stepwise binomial regression was used to evaluate for variables predictive of antibiotic prescription. Results: We identified eight infections in 323 patients included in the study (2.5% incidence of infection). There was no statistically significant difference in the incidence of infection between patients treated with antibiotics (2.7%) and those who did not receive antibiotics (2.2%). However, due to the low incidence of infections, we were likely underpowered for this analysis. We also created a model to predict antibiotic prescribing, which achieved an area under the receiver operating characteristic curve of 0.86 (P < .0001) based on age, bleeding disorders, depressive disorders, open wound status, amputation, fractures, and encounter type. Conclusions: The low incidence of infection (2.5%) and lack of a meaningful difference between the groups call into question prophylactic antibiotic prescribing after these distal fingertip injuries. Our model does predict provider prescribing habits, identifying areas for potential practice pattern change. Type of study/level of evidence: Therapeutic III.

Systematic Review of Complications Associated With Proximal Hamstring Tendon Repair.

Background: Although several complications of proximal hamstring tendon ruptures have been reported in the literature, few studies have comprehensively analyzed the complication profile of proximal hamstring tendon repair. Purpose: To identify the overall rate of complications following proximal hamstring tendon repair and to differentiate these complications into categories. Study Design: Systematic review; Level of evidence, 4. Methods: Included in this review were studies that examined surgical repair of proximal hamstring tendon ruptures; all studies were in English and had an evidence level of 4 or higher. No restrictions were made regarding publication date or methodological quality. Data regarding complications were extracted to calculate the overall complication rate as well as the rate of major and minor complications. A quantitative data synthesis was conducted using the chi-square test to compare the proportion of patients who experienced complications with the endoscopic versus open approach. Results: A total of 43 articles including 2833 proximal hamstring tendon repairs were identified. The overall postoperative complication rate was 15.3% (n = 433). The rate of major complications was 4.6%, including a 1.7% rate of sciatic nerve injury, 0.8% rate of venous thromboembolism, 0.8% reoperation rate, 0.8% rerupture rate, and 0.4% rate of deep infection. Minor complications included a 2.4% rate of posterior femoral cutaneous nerve injury, 2.3% rate of persistent hamstring myopathy, 2.2% rate of persistent sitting pain, 1.8% rate of peri-incisional numbness, 1.1% rate of superficial infection, and 0.8% rate of hematoma/seroma. Conclusion: Proximal hamstring tendon repair is associated with an overall complication rate of 15.3%, including a 4.6% rate of major complications.

Aligning NIH's existing data use restrictions to the GA4GH DUO standard.

It is widely accepted that large-scale genomic data (e.g., whole-genome sequencing, whole-exome sequencing, and genome-wide association study data) be shared through a controlled-access mechanism. This protects the privacy of research participants and ensures downstream uses of data align with participants' informed consent regarding future sharing of their data. In 2019, GA4GH approved the Data Use Ontology (DUO) standard to define data use terms with machine-readable representations to represent how a dataset can be used. We endeavored to determine the parity of existing data use restrictions ("Data Use Limitations" [DULs]) for datasets registered in the National Institutes of Health database for Genotypes and Phenotypes (dbGaP) with the DUO standard. We found substantial (93%) parity between the dbGaP DULs (n = 3,575) and DUO. This study demonstrates the comprehensiveness of the DUO standard and encourages data stewards to standardize data use restrictions in machine-readable formats to facilitate data sharing.

Leveraging Algorithms to Improve Decision-Making Workflows for Genomic Data Access and Management.

Studies on the ethics of automating clinical or research decision making using artificial intelligence and other algorithmic tools abound. Less attention has been paid, however, to the scope for, and ethics of, automating decision making within regulatory apparatuses governing the access, use, and exchange of data involving humans for research. In this article, we map how the binary logic flows and real-time capabilities of automated decision support (ADS) systems may be leveraged to accelerate one rate-limiting step in scientific discovery: data access management. We contend that improved auditability, consistency, and efficiency of the data access request process using ADS systems have the potential to yield fairer outcomes in requests for data largely sourced from biospecimens and biobanked samples. This procedural justice rationale reinforces a broader set of participant and data subject rights that data access committees (DACs) indirectly protect. DACs protect the rights of citizens to benefit from science by bringing researchers closer to the data they need to advance that science. DACs also protect the informational dignities of individuals and communities by ensuring the data being accessed are used in ways consistent with participant values. We discuss the development of the Global Alliance for Genomics and Health Data Use Ontology standard as a test case of ADS for genomic data access management specifically, and we synthesize relevant ethical, legal, and social challenges to its implementation in practice. We conclude with an agenda of future research needed to thoughtfully advance strategies for computational governance that endeavor to instill public trust in, and maximize the scientific value of, health-related human data across data types, environments, and user communities.

Chemokines, soluble PD-L1, and immune cell hyporesponsiveness are distinct features of SARS-CoV-2 critical illness.

Critically ill patients manifest many of the same immune features seen in coronavirus disease 2019 (COVID-19), including both "cytokine storm" and "immune suppression." However, direct comparisons of molecular and cellular profiles between contemporaneously enrolled critically ill patients with and without severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) are limited. We sought to identify immune signatures specifically enriched in critically ill patients with COVID-19 compared with patients without COVID-19. We enrolled a multisite prospective cohort of patients admitted under suspicion for COVID-19, who were then determined to be SARS-CoV-2-positive (n = 204) or -negative (n = 122). SARS-CoV-2-positive patients had higher plasma levels of CXCL10, sPD-L1, IFN-γ, CCL26, C-reactive protein (CRP), and TNF-α relative to SARS-CoV-2-negative patients adjusting for demographics and severity of illness (Bonferroni P value < 0.05). In contrast, the levels of IL-6, IL-8, IL-10, and IL-17A were not significantly different between the two groups. In SARS-CoV-2-positive patients, higher plasma levels of sPD-L1 and TNF-α were associated with fewer ventilator-free days (VFDs) and higher mortality rates (Bonferroni P value < 0.05). Lymphocyte chemoattractants such as CCL17 were associated with more severe respiratory failure in SARS-CoV-2-positive patients, but less severe respiratory failure in SARS-CoV-2-negative patients (P value for interaction < 0.01). Circulating T cells and monocytes from SARS-CoV-2-positive subjects were hyporesponsive to in vitro stimulation compared with SARS-CoV-2-negative subjects. Critically ill SARS-CoV-2-positive patients exhibit an immune signature of high interferon-induced lymphocyte chemoattractants (e.g., CXCL10 and CCL17) and immune cell hyporesponsiveness when directly compared with SARS-CoV-2-negative patients. This suggests a specific role for T-cell migration coupled with an immune-checkpoint regulatory response in COVID-19-related critical illness.

Reproducibility and reporting, the routes to progress in breath research-highlights from the Breath Biopsy Conference 2021.

With the continued presence of COVID-19 worldwide, it has been a challenge for the breath research community to progress with clinical studies and travel restrictions have also limited the opportunities to meet up, share ideas and celebrate the latest advances. The Breath Biopsy Conference 2021 offered the chance to catch up with the latest breath research and to share progress that researchers in the community have been able to make in these difficult times. Limited opportunities for clinical research have led many in the field to look more closely at different methods for breath collection and have contributed to the growing calls for consistent standards in how results are reported, shared and even how breath studies themselves are carried out. As such, standardization was a key theme for this year's event and featured prominently in the keynotes, discussions and throughout many of the presentations. With over 900 registrants, almost 400 live attendees and 16 speakers, the Breath Biopsy Conference continues to bring together breath research leaders from around the world. This article provides an overview of the highlights from this event.

Inverting the model of genomics data sharing with the NHGRI Genomic Data Science Analysis, Visualization, and Informatics Lab-space.

The NHGRI Genomic Data Science Analysis, Visualization, and Informatics Lab-space (AnVIL; https://anvilproject.org) was developed to address a widespread community need for a unified computing environment for genomics data storage, management, and analysis. In this perspective, we present AnVIL, describe its ecosystem and interoperability with other platforms, and highlight how this platform and associated initiatives contribute to improved genomic data sharing efforts. The AnVIL is a federated cloud platform designed to manage and store genomics and related data, enable population-scale analysis, and facilitate collaboration through the sharing of data, code, and analysis results. By inverting the traditional model of data sharing, the AnVIL eliminates the need for data movement while also adding security measures for active threat detection and monitoring and provides scalable, shared computing resources for any researcher. We describe the core data management and analysis components of the AnVIL, which currently consists of Terra, Gen3, Galaxy, RStudio/Bioconductor, Dockstore, and Jupyter, and describe several flagship genomics datasets available within the AnVIL. We continue to extend and innovate the AnVIL ecosystem by implementing new capabilities, including mechanisms for interoperability and responsible data sharing, while streamlining access management. The AnVIL opens many new opportunities for analysis, collaboration, and data sharing that are needed to drive research and to make discoveries through the joint analysis of hundreds of thousands to millions of genomes along with associated clinical and molecular data types.

Breathing new life into clinical testing and diagnostics: perspectives on volatile biomarkers from breath.

Human breath offers several benefits for diagnostic applications, including simple, noninvasive collection. Breath is a rich source of clinically-relevant biological information; this includes a volatile fraction, where greater than 1,000 volatile organic compounds (VOCs) have been described so far, and breath aerosols that carry nucleic acids, proteins, signaling molecules, and pathogens. Many of these factors, especially VOCs, are delivered to the lung by the systemic circulation, and diffusion of candidate biomarkers from blood into breath allows systematic profiling of organismal health. Biomarkers on breath offer the capability to advance early detection and precision medicine in areas of global clinical need. Breath tests are noninvasive and can be performed at home or in a primary care setting, which makes them well-suited for the kind of public screening program that could dramatically improve the early detection of conditions such as lung cancer. Since measurements of VOCs on breath largely report on metabolic changes, this too aids in the early detection of a broader range of illnesses and can be used to detect metabolic shifts that could be targeted through precision medicine. Furthermore, the ability to perform frequent sampling has envisioned applications in monitoring treatment responses. Breath has been investigated in respiratory, liver, gut, and neurological diseases and in contexts as diverse as infectious diseases and cancer. Preclinical research studies using breath have been ongoing for some time, yet only a few breath-based diagnostics tests are currently available and in widespread clinical use. Most recently, tests assessing the gut microbiome using hydrogen and methane on breath, in addition to tests using urea to detect Helicobacter pylori infections have been released, yet there are many more applications of breath tests still to be realized. Here, we discuss the strengths of breath as a clinical sampling matrix and the technical challenges to be addressed in developing it for clinical use. Historically, a lack of standardized methodologies has delayed the discovery and validation of biomarker candidates, resulting in a proliferation of early-stage pilot studies. We will explore how advancements in breath collection and analysis are in the process of driving renewed progress in the field, particularly in the context of gastrointestinal and chronic liver disease. Finally, we will provide a forward-looking outlook for developing the next generation of clinically relevant breath tests and how they may emerge into clinical practice.

The Data Use Ontology to streamline responsible access to human biomedical datasets.

Human biomedical datasets that are critical for research and clinical studies to benefit human health also often contain sensitive or potentially identifying information of individual participants. Thus, care must be taken when they are processed and made available to comply with ethical and regulatory frameworks and informed consent data conditions. To enable and streamline data access for these biomedical datasets, the Global Alliance for Genomics and Health (GA4GH) Data Use and Researcher Identities (DURI) work stream developed and approved the Data Use Ontology (DUO) standard. DUO is a hierarchical vocabulary of human and machine-readable data use terms that consistently and unambiguously represents a dataset's allowable data uses. DUO has been implemented by major international stakeholders such as the Broad and Sanger Institutes and is currently used in annotation of over 200,000 datasets worldwide. Using DUO in data management and access facilitates researchers' discovery and access of relevant datasets. DUO annotations increase the FAIRness of datasets and support data linkages using common data use profiles when integrating the data for secondary analyses. DUO is implemented in the Web Ontology Language (OWL) and, to increase community awareness and engagement, hosted in an open, centralized GitHub repository. DUO, together with the GA4GH Passport standard, offers a new, efficient, and streamlined data authorization and access framework that has enabled increased sharing of biomedical datasets worldwide.

GA4GH Passport standard for digital identity and access permissions.

The Global Alliance for Genomics and Health (GA4GH) supports international standards that enable a federated data sharing model for the research community while respecting data security, ethical and regulatory frameworks, and data authorization and access processes for sensitive data. The GA4GH Passport standard (Passport) defines a machine-readable digital identity that conveys roles and data access permissions (called "visas") for individual users. Visas are issued by data stewards, including data access committees (DACs) working with public databases, the entities responsible for the quality, integrity, and access arrangements for the datasets in the management of human biomedical data. Passports streamline management of data access rights across data systems by using visas that present a data user's digital identity and permissions across organizations, tools, environments, and services. We describe real-world implementations of the GA4GH Passport standard in use cases from ELIXIR Europe, National Institutes of Health, and the Autism Sharing Initiative. These implementations demonstrate that the Passport standard has provided transparent mechanisms for establishing permissions and authorizing data access across platforms.

Pursuing breath research in unprecedented circumstances-report from the Breath Biopsy Conference 2020.

The global outbreak of Sars-CoV-2 commencing early in 2020 had a dramatic impact on breath research, imposing abrupt restrictions but also presenting unforeseen opportunities. Taking place against the background of the COVID-19 pandemic, the 2020 Breath Biopsy Conference provided the breath research community with a platform to showcase and discuss the latest findings, including COVID-19 related research. As with most conferences under the present circumstance, it differed from its predecessor meetings by shifting to a virtual format, but retained its broad scope and interactive nature. The conference centred on four key themes, featuring applications of volatile organic compounds, breath biomarkers for liver disease, study design and data analytics, and, notably this year, breath-based endeavours to detect COVID-19 infection. This meeting report summarizes the events of the conference and spotlights selected contributions.

Comparison of host endothelial, epithelial and inflammatory response in ICU patients with and without COVID-19: a prospective observational cohort study.

BACKGROUND: Analyses of blood biomarkers involved in the host response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral infection can reveal distinct biological pathways and inform development and testing of therapeutics for COVID-19. Our objective was to evaluate host endothelial, epithelial and inflammatory biomarkers in COVID-19. METHODS: We prospectively enrolled 171 ICU patients, including 78 (46%) patients positive and 93 (54%) negative for SARS-CoV-2 infection from April to September, 2020. We compared 22 plasma biomarkers in blood collected within 24 h and 3 days after ICU admission. RESULTS: In critically ill COVID-19 and non-COVID-19 patients, the most common ICU admission diagnoses were respiratory failure or pneumonia, followed by sepsis and other diagnoses. Similar proportions of patients in both groups received invasive mechanical ventilation at the time of study enrollment. COVID-19 and non-COVID-19 patients had similar rates of acute respiratory distress syndrome, severe acute kidney injury, and in-hospital mortality. While concentrations of interleukin 6 and 8 were not different between groups, markers of epithelial cell injury (soluble receptor for advanced glycation end products, sRAGE) and acute phase proteins (serum amyloid A, SAA) were significantly higher in COVID-19 compared to non-COVID-19, adjusting for demographics and APACHE III scores. In contrast, angiopoietin 2:1 (Ang-2:1 ratio) and soluble tumor necrosis factor receptor 1 (sTNFR-1), markers of endothelial dysfunction and inflammation, were significantly lower in COVID-19 (p < 0.002). Ang-2:1 ratio and SAA were associated with mortality only in non-COVID-19 patients. CONCLUSIONS: These studies demonstrate that, unlike other well-studied causes of critical illness, endothelial dysfunction may not be characteristic of severe COVID-19 early after ICU admission. Pathways resulting in elaboration of acute phase proteins and inducing epithelial cell injury may be promising targets for therapeutics in COVID-19.

Empirical validation of an automated approach to data use oversight.

The current paradigm for data use oversight of biomedical datasets is onerous, extending the timescale and resources needed to obtain access for secondary analyses, thus hindering scientific discovery. For a researcher to utilize a controlled-access dataset, a data access committee must review her research plans to determine whether they are consistent with the data use limitations (DULs) specified by the informed consent form. The newly created GA4GH data use ontology (DUO) holds the potential to streamline this process by making data use oversight computable. Here, we describe an open-source software platform, the Data Use Oversight System (DUOS), that connects with DUO terminology to enable automated data use oversight. We analyze dbGaP data acquired since 2006, finding an exponential increase in data access requests, which will not be sustainable with current manual oversight review. We perform an empirical evaluation of DUOS and DUO on selected datasets from the Broad Institute's data repository. We were able to structure 118/123 of the evaluated DULs (96%) and 52/52 (100%) of research proposals using DUO terminology, and we find that DUOS' automated data access adjudication in all cases agreed with the DAC manual review. This first empirical evaluation of the feasibility of automated data use oversight demonstrates comparable accuracy to human-based data access oversight in real-world data governance.

Driving progress in exhaled breath biomarkers: Breath Biopsy Conference 2019.

November 2019 saw Cambridge, UK play host to the second Breath Biopsy Conference, a community-focused event aimed at sharing and supporting advancements in the collection and analysis of volatile organic compounds in exhaled breath. The event expanded upon the previous year's format, spanning two days and concluding with an expert panel discussion. Presentations covered detection, monitoring and precision medicine studies examining diseases including asthma, cirrhosis, cancer and tuberculosis. The meeting attracted representatives from diverse backgrounds, such as metabolomics, artificial intelligence, clinical research and chemical analysis. This meeting report offers an overview of what was presented and discussed during the conference.