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Abdominal Radiology (New York) Jun 2024Accurate, automated MRI series identification is important for many applications, including display ("hanging") protocols, machine learning, and radiomics. The use of...
Accurate, automated MRI series identification is important for many applications, including display ("hanging") protocols, machine learning, and radiomics. The use of the series description or a pixel-based classifier each has limitations. We demonstrate a combined approach utilizing a DICOM metadata-based classifier and selective use of a pixel-based classifier to identify abdominal MRI series. The metadata classifier was assessed alone as Group metadata and combined with selective use of the pixel-based classifier for predictions with less than 70% certainty (Group combined). The overall accuracy (mean and 95% confidence intervals) for Groups metadata and combined on the test dataset were 0.870 CI (0.824,0.912) and 0.930 CI (0.893,0.963), respectively. With this combined metadata and pixel-based approach, we demonstrate accurate classification of 95% or greater for all pre-contrast MRI series and improved performance for some post-contrast series.
PubMed: 38860997
DOI: 10.1007/s00261-024-04379-5 -
Virus Evolution 2024Seasonal influenza virus predominantly evolves through antigenic drift, marked by the accumulation of mutations at antigenic sites. Because of antigenic drift, influenza...
Seasonal influenza virus predominantly evolves through antigenic drift, marked by the accumulation of mutations at antigenic sites. Because of antigenic drift, influenza vaccines are frequently updated, though their efficacy may still be limited due to strain mismatches. Despite the high levels of viral diversity observed across populations, most human studies reveal limited intrahost diversity, leaving the origin of population-level viral diversity unclear. Previous studies show host characteristics, such as immunity, might affect within-host viral evolution. Here we investigate influenza A viral diversity in children aged between 6 months and 18 years. Influenza virus evolution in children is less well characterized than in adults, yet may be associated with higher levels of viral diversity given the lower level of pre-existing immunity and longer durations of infection in children. We obtained influenza isolates from banked influenza A-positive nasopharyngeal swabs collected at the Children's Hospital of Philadelphia during the 2017-18 influenza season. Using next-generation sequencing, we evaluated the population of influenza viruses present in each sample. We characterized within-host viral diversity using the number and frequency of intrahost single-nucleotide variants (iSNVs) detected in each sample. We related viral diversity to clinical metadata, including subjects' age, vaccination status, and comorbid conditions, as well as sample metadata such as virus strain and cycle threshold. Consistent with previous studies, most samples contained low levels of diversity with no clear association between the subjects' age, vaccine status, or health status. Further, there was no enrichment of iSNVs near known antigenic sites. Taken together, these findings are consistent with previous observations that the majority of intrahost influenza virus infection is characterized by low viral diversity without evidence of diversifying selection.
PubMed: 38859985
DOI: 10.1093/ve/veae034 -
Journal of the American Medical... Jun 2024Precise literature recommendation and summarization are crucial for biomedical professionals. While the latest iteration of generative pretrained transformer (GPT)...
OBJECTIVES
Precise literature recommendation and summarization are crucial for biomedical professionals. While the latest iteration of generative pretrained transformer (GPT) incorporates 2 distinct modes-real-time search and pretrained model utilization-it encounters challenges in dealing with these tasks. Specifically, the real-time search can pinpoint some relevant articles but occasionally provides fabricated papers, whereas the pretrained model excels in generating well-structured summaries but struggles to cite specific sources. In response, this study introduces RefAI, an innovative retrieval-augmented generative tool designed to synergize the strengths of large language models (LLMs) while overcoming their limitations.
MATERIALS AND METHODS
RefAI utilized PubMed for systematic literature retrieval, employed a novel multivariable algorithm for article recommendation, and leveraged GPT-4 turbo for summarization. Ten queries under 2 prevalent topics ("cancer immunotherapy and target therapy" and "LLMs in medicine") were chosen as use cases and 3 established counterparts (ChatGPT-4, ScholarAI, and Gemini) as our baselines. The evaluation was conducted by 10 domain experts through standard statistical analyses for performance comparison.
RESULTS
The overall performance of RefAI surpassed that of the baselines across 5 evaluated dimensions-relevance and quality for literature recommendation, accuracy, comprehensiveness, and reference integration for summarization, with the majority exhibiting statistically significant improvements (P-values <.05).
DISCUSSION
RefAI demonstrated substantial improvements in literature recommendation and summarization over existing tools, addressing issues like fabricated papers, metadata inaccuracies, restricted recommendations, and poor reference integration.
CONCLUSION
By augmenting LLM with external resources and a novel ranking algorithm, RefAI is uniquely capable of recommending high-quality literature and generating well-structured summaries, holding the potential to meet the critical needs of biomedical professionals in navigating and synthesizing vast amounts of scientific literature.
PubMed: 38857454
DOI: 10.1093/jamia/ocae129 -
Journal of Medical Internet Research Jun 2024It is necessary to harmonize and standardize data variables used in case report forms (CRFs) of clinical studies to facilitate the merging and sharing of the collected...
BACKGROUND
It is necessary to harmonize and standardize data variables used in case report forms (CRFs) of clinical studies to facilitate the merging and sharing of the collected patient data across several clinical studies. This is particularly true for clinical studies that focus on infectious diseases. Public health may be highly dependent on the findings of such studies. Hence, there is an elevated urgency to generate meaningful, reliable insights, ideally based on a high sample number and quality data. The implementation of core data elements and the incorporation of interoperability standards can facilitate the creation of harmonized clinical data sets.
OBJECTIVE
This study's objective was to compare, harmonize, and standardize variables focused on diagnostic tests used as part of CRFs in 6 international clinical studies of infectious diseases in order to, ultimately, then make available the panstudy common data elements (CDEs) for ongoing and future studies to foster interoperability and comparability of collected data across trials.
METHODS
We reviewed and compared the metadata that comprised the CRFs used for data collection in and across all 6 infectious disease studies under consideration in order to identify CDEs. We examined the availability of international semantic standard codes within the Systemized Nomenclature of Medicine - Clinical Terms, the National Cancer Institute Thesaurus, and the Logical Observation Identifiers Names and Codes system for the unambiguous representation of diagnostic testing information that makes up the CDEs. We then proposed 2 data models that incorporate semantic and syntactic standards for the identified CDEs.
RESULTS
Of 216 variables that were considered in the scope of the analysis, we identified 11 CDEs to describe diagnostic tests (in particular, serology and sequencing) for infectious diseases: viral lineage/clade; test date, type, performer, and manufacturer; target gene; quantitative and qualitative results; and specimen identifier, type, and collection date.
CONCLUSIONS
The identification of CDEs for infectious diseases is the first step in facilitating the exchange and possible merging of a subset of data across clinical studies (and with that, large research projects) for possible shared analysis to increase the power of findings. The path to harmonization and standardization of clinical study data in the interest of interoperability can be paved in 2 ways. First, a map to standard terminologies ensures that each data element's (variable's) definition is unambiguous and that it has a single, unique interpretation across studies. Second, the exchange of these data is assisted by "wrapping" them in a standard exchange format, such as Fast Health care Interoperability Resources or the Clinical Data Interchange Standards Consortium's Clinical Data Acquisition Standards Harmonization Model.
Topics: Humans; Communicable Diseases; Semantics; Common Data Elements
PubMed: 38857066
DOI: 10.2196/50049 -
Frontiers in Public Health 2024Türkiye confirmed its first case of SARS-CoV-2 on March 11, 2020, coinciding with the declaration of the global COVID-19 pandemic. Subsequently, Türkiye swiftly...
BACKGROUND
Türkiye confirmed its first case of SARS-CoV-2 on March 11, 2020, coinciding with the declaration of the global COVID-19 pandemic. Subsequently, Türkiye swiftly increased testing capacity and implemented genomic sequencing in 2020. This paper describes Türkiye's journey of establishing genomic surveillance as a middle-income country with limited prior sequencing capacity and analyses sequencing data from the first two years of the pandemic. We highlight the achievements and challenges experienced and distill globally relevant lessons.
METHODS
We tracked the evolution of the COVID-19 pandemic in Türkiye from December 2020 to February 2022 through a timeline and analysed epidemiological, vaccination, and testing data. To investigate the phylodynamic and phylogeographic aspects of SARS-CoV-2, we used Nextstrain to analyze 31,629 high-quality genomes sampled from seven regions nationwide.
RESULTS
Türkiye's epidemiological curve, mirroring global trends, featured four distinct waves, each coinciding with the emergence and spread of variants of concern (VOCs). Utilizing locally manufactured kits to expand testing capacity and introducing variant-specific quantitative reverse transcription polymerase chain reaction (RT-qPCR) tests developed in partnership with a private company was a strategic advantage in Türkiye, given the scarcity and fragmented global supply chain early in the pandemic. Türkiye contributed more than 86,000 genomic sequences to global databases by February 2022, ensuring that Turkish data was reflected globally. The synergy of variant-specific RT-qPCR kits and genomic sequencing enabled cost-effective monitoring of VOCs. However, data analysis was constrained by a weak sequencing sampling strategy and fragmented data management systems, limiting the application of sequencing data to guide the public health response. Phylodynamic analysis indicated that Türkiye's geographical position as an international travel hub influenced both national and global transmission of each VOC despite travel restrictions.
CONCLUSION
This paper provides valuable insights into the testing and genomic surveillance systems adopted by Türkiye during the COVID-19 pandemic, proposing important lessons for countries developing national systems. The findings underscore the need for robust testing and sampling strategies, streamlined sample referral, and integrated data management with metadata linkage and data quality crucial for impactful epidemiological analysis. We recommend developing national genomic surveillance strategies to guide sustainable and integrated expansion of capacities built for COVID-19 and to optimize the effective utilization of sequencing data for public health action.
Topics: Humans; COVID-19; SARS-CoV-2; Genomics; Pandemics; Genome, Viral; Male
PubMed: 38855447
DOI: 10.3389/fpubh.2024.1332109 -
Frontiers in Water May 2024Antimicrobial resistance (AMR) is a world-wide public health threat that is projected to lead to 10 million annual deaths globally by 2050. The AMR public health issue...
Antimicrobial resistance (AMR) is a world-wide public health threat that is projected to lead to 10 million annual deaths globally by 2050. The AMR public health issue has led to the development of action plans to combat AMR, including improved antimicrobial stewardship, development of new antimicrobials, and advanced monitoring. The National Antimicrobial Resistance Monitoring System (NARMS) led by the United States (U.S) Food and Drug Administration along with the U.S. Centers for Disease Control and U.S. Department of Agriculture has monitored antimicrobial resistant bacteria in retail meats, humans, and food animals since the mid 1990's. NARMS is currently exploring an integrated One Health monitoring model recognizing that human, animal, plant, and environmental systems are linked to public health. Since 2020, the U.S. Environmental Protection Agency has led an interagency NARMS environmental working group (EWG) to implement a surface water AMR monitoring program (SWAM) at watershed and national scales. The NARMS EWG divided the development of the environmental monitoring effort into five areas: (i) defining objectives and questions, (ii) designing study/sampling design, (iii) selecting AMR indicators, (iv) establishing analytical methods, and (v) developing data management/analytics/metadata plans. For each of these areas, the consensus among the scientific community and literature was reviewed and carefully considered prior to the development of this environmental monitoring program. The data produced from the SWAM effort will help develop robust surface water monitoring programs with the goal of assessing public health risks associated with AMR pathogens in surface water (e.g., recreational water exposures), provide a comprehensive picture of how resistant strains are related spatially and temporally within a watershed, and help assess how anthropogenic drivers and intervention strategies impact the transmission of AMR within human, animal, and environmental systems.
PubMed: 38855419
DOI: 10.3389/frwa.2024.1359109 -
Cancer Research and Treatment Jun 2024In 2024, medical researchers in the Republic of Korea were invited to amend the health and medical data utilization guidelines (Government Publications Registration...
PURPOSE
In 2024, medical researchers in the Republic of Korea were invited to amend the health and medical data utilization guidelines (Government Publications Registration Number: 11-1352000-0052828-14). This study aimed to show the overall impact of the guideline revision, with a focus on clinical genomic data.
MATERIALS AND METHODS
This study amended the pseudonymization of genomic data defined in the previous version through a joint study led by the Ministry of Health and Welfare, the Korea Health Information Service, and the Korea Genome Organization. To develop the previous version, we held three conferences with four main medical research institutes and seven academic societies. We conducted two surveys targeting special genome experts in academia, industry, and institutes.
RESULTS
We found that cases of pseudonymization in the application of genome data were rare and that there was ambiguity in the terminology used in the previous version of the guidelines. Most experts (> ~90%) agreed that the 'reserved' condition should be eliminated to make genomic data available after pseudonymization. In this study, the scope of genomic data was defined as clinical next generation sequencing data, including FASTQ, BAM/SAM, VCF, and medical records. Pseudonymization targets genomic sequences and metadata, embedding specific elements, such as germline mutations, short tandem repeats, single-nucleotide polymorphisms, and identifiable data (for example, ID or environmental values). Expression data generated from multi-omics can be used without pseudonymization.
CONCLUSION
This amendment will not only enhance the safe use of healthcare data but also promote advancements in disease prevention, diagnosis, and treatment.
PubMed: 38853539
DOI: 10.4143/crt.2024.146 -
European Heart Journal. Cardiovascular... Jun 2024Direct oral anticoagulants (DOACs) are increasingly used off-label to treat patients with left ventricular thrombus (LVT). We analyzed available meta-data comparing...
AIMS
Direct oral anticoagulants (DOACs) are increasingly used off-label to treat patients with left ventricular thrombus (LVT). We analyzed available meta-data comparing DOACs and vitamin K antagonists (VKAs) for efficacy and safety.
METHODS
We conducted a systematic search and meta-analysis of observational and randomized data comparing DOACs versus VKAs in patients with LVT. Endpoints of interest were stroke or systemic embolism, thrombus resolution, all-cause death, and a composite bleeding endpoint. Estimates were pooled using a random-effect model meta-analysis, and their robustness was investigated using sensitivity and influential analyses.
RESULTS
We identified 22 articles (18 observational studies, 4 small randomized clinical trials) reporting on a total of 3,587 patients (2,489 VKA vs. 1,098 DOAC therapy). The pooled estimates for stroke or systemic embolism (OR 0.81; 95% CI [0.57, 1.15]) and thrombus resolution (OR 1.12; 95% CI [0.86; 1.46]) were comparable, and there was low heterogeneity overall across the included studies. DOAC use was associated with lower odds of all-cause death (OR 0.65; 95%CI [0.46; 0.92]) and a composite bleeding endpoint (OR 0.67; 95%CI [0.47; 0.97]). A risk of bias was evident particularly for observational reports, with some publication bias suggested in funnel plots.
CONCLUSION
In this comprehensive analysis of mainly observational data, the use of DOACs was not associated with a significant difference in stroke or systemic embolism, or thrombus resolution compared to VKA therapy. The use of DOACs was associated with a lower rate of all-cause death and fewer bleeding events. Adequately sized randomized clinical trials are needed to confirm these findings, which could allow a wider adoption of DOACs in patients with LVT.
PubMed: 38845369
DOI: 10.1093/ehjcvp/pvae042 -
BMJ Paediatrics Open Jun 2024As a topic of inquiry in its own right, data management for interdisciplinary research projects is in its infancy. Key issues include the inability of researchers to...
INTRODUCTION
As a topic of inquiry in its own right, data management for interdisciplinary research projects is in its infancy. Key issues include the inability of researchers to effectively query diverse data outputs and to identify potentially important synergies between discipline-specific data. Equally problematic, few semantic ontologies exist to better support data organisation and discovery. Finally, while interdisciplinary research is widely regarded as beneficial to unpacking complex problems, non-researchers such as policy-makers and planners often struggle to use and interrogate the related datasets. To address these issues, the following article details the design and development of the UKRI GCRF Action Against Stunting Hub (AASH)'s All-Hub Data Repository (AHDR).
METHODS AND ANALYSIS
The AHDR is a single application, single authentication web-based platform comprising a data warehouse to store data from across the AASH's three study countries and to support data querying. Four novel components of the AHDR are described in the following article: (1) a unique data discovery tool; (2) a metadata catalogue that provides researchers with an interface to explore the AASH's data outputs and engage with a new semantic ontology related to child stunting; (3) an interdisciplinary aid to support a directed approach to identifying synergies and interactions between AASH data and (4) a decision support tool that will support non-researchers in engaging with the wider evidence-based outputs of the AASH.
ETHICS AND DISSEMINATION
Ethical approval for this study was granted by institutional ethics committees in the UK, India, Indonesia and Senegal. Results will be disseminated via publications in peer-reviewed journals; presentations at international conferences and community-level public engagement events; key stakeholder meetings; and in public repositories with appropriate Creative Commons licences allowing for the widest possible use.
Topics: Humans; Growth Disorders; Interdisciplinary Research; Child; United Kingdom; Databases, Factual; Child, Preschool
PubMed: 38843904
DOI: 10.1136/bmjpo-2023-002443 -
Cureus Jun 2024Background and objective While musculoskeletal (MSK) disorders account for a significant number of primary care and emergency department (ED) visits, there are widely...
Background and objective While musculoskeletal (MSK) disorders account for a significant number of primary care and emergency department (ED) visits, there are widely recognized shortcomings and gaps in MSK education throughout medical training. Undergraduate medical education (UME) frequently fails to impart clinically relevant MSK knowledge, while many emergency medicine (EM) residency graduates report feeling unprepared to manage MSK complaints. Existing MSK assessments are not tailored to EM and may inaccurately assess specialty-specific MSK knowledge. The novel validated Musculoskeletal Emergency Medicine Assessment Tool (MEAT) holds great promise in standardizing EM MSK knowledge assessment. This trial of feasibility was conducted to assess the viability and practicality of using MEAT to evaluate MSK knowledge among incoming resident physicians in EM programs. Methods This feasibility study involved 21 incoming EM resident physicians from two programs at a single institution. MEAT was administered online during orientation, and demographic data and survey metadata were collected. UME MSK education details were obtained, and MEAT scores were analyzed. Results Participants reported no difficulties in accessing or understanding the 50-question online MEAT, resulting in a 100% response rate. The average pretest score for all interns was 29.9, with a median of 30. Most participants had documented UME MSK education, but curricular content varied widely. The participants took an average of 32 minutes to complete the assessment. Conclusions MEAT demonstrated successful implementation and high response rates, suggesting a high level of feasibility. The tool can be used to assess baseline MSK knowledge and ultimately track progression during residency with the potential for evaluating educational interventions once further validation studies have been performed. Further adoption of MEAT across multiple EM residency programs will help to enhance the tool's generalizability.
PubMed: 38841295
DOI: 10.7759/cureus.61740