LDA2Net Digging under the surface of COVID-19 scientific literature topics via a network-based approach.

During the COVID-19 pandemic, the scientific literature related to SARS-COV-2 has been growing dramatically. These literary items encompass a varied set of topics, ranging from vaccination to protective equipment efficacy as well as lockdown policy evaluations. As a result, the development of automatic methods that allow an in-depth exploration of this growing literature has become a relevant issue, both to identify the topical trends of COVID-related research and to zoom-in on its sub-themes. This work proposes a novel methodology, called LDA2Net, which combines topic modelling and network analysis, to investigate topics under their surface. More specifically, LDA2Net exploits the frequencies of consecutive words pairs (i.e. bigram) to build those network structures underlying the hidden topics extracted from large volumes of text by Latent Dirichlet Allocation (LDA). Results are promising and suggest that the topic model efficacy is magnified by the network-based representation. In particular, such enrichment is noticeable when it comes to displaying and exploring the topics at different levels of granularity.

CoMentG: comprehensive retrieval of generic relationships between biomedical concepts from the scientific literature.

The CoMentG resource contains millions of relationships between terms of biomedical interest obtained from the scientific literature. At the core of the system is a methodology for detecting significant co-mentions of concepts in the entire PubMed corpus. That method was applied to nine sets of terms covering the most important classes of biomedical concepts: diseases, symptoms/clinical signs, molecular functions, biological processes, cellular compartments, anatomic parts, cell types, bacteria and chemical compounds. We obtained more than 7 million relationships between more than 74 000 terms, and many types of relationships were not available in any other resource. As the terms were obtained from widely used resources and ontologies, the relationships are given using the standard identifiers provided by them and hence can be linked to other data. A web interface allows users to browse these associations, searching for relationships for a set of terms of interests provided as input, such as between a disease and their associated symptoms, underlying molecular processes or affected tissues. The results are presented in an interactive interface where the user can explore the reported relationships in different ways and follow links to other resources. Database URL: https://csbg.cnb.csic.es/CoMentG/.

Towards building a trustworthy pipeline integrating Neuroscience Gateway and Open Science Chain.

When the scientific dataset evolves or is reused in workflows creating derived datasets, the integrity of the dataset with its metadata information, including provenance, needs to be securely preserved while providing assurances that they are not accidentally or maliciously altered during the process. Providing a secure method to efficiently share and verify the data as well as metadata is essential for the reuse of the scientific data. The National Science Foundation (NSF) funded Open Science Chain (OSC) utilizes consortium blockchain to provide a cyberinfrastructure solution to maintain integrity of the provenance metadata for published datasets and provides a way to perform independent verification of the dataset while promoting reuse and reproducibility. The NSF- and National Institutes of Health (NIH)-funded Neuroscience Gateway (NSG) provides a freely available web portal that allows neuroscience researchers to execute computational data analysis pipeline on high performance computing resources. Combined, the OSC and NSG platforms form an efficient, integrated framework to automatically and securely preserve and verify the integrity of the artifacts used in research workflows while using the NSG platform. This paper presents the results of the first study that integrates OSC-NSG frameworks to track the provenance of neurophysiological signal data analysis to study brain network dynamics using the Neuro-Integrative Connectivity tool, which is deployed in the NSG platform. Database URL: https://www.opensciencechain.org.

Reporting form and content of research priorities identified in knee osteoarthritis clinical practice guidelines: a methodological literature analysis.

OBJECTIVES: Clinical practice guideline (CPG) developers conduct systematic summaries of research evidence, providing them great capacity and ability to identify research priorities. We systematically analysed the reporting form and content of research priorities in CPGs related to knee osteoarthritis (KOA) to provide a valuable reference for guideline developers and clinicians. DESIGN: A methodological literature analysis was done and the characteristics of the reporting form and the content of the research priorities identified in KOA CPGs were summarised. DATA SOURCES: Six databases (PubMed, Embase, China National Knowledge Infrastructure, VIP Database for Chinese Technical Periodicals, Wanfang and Chinese Biomedical Literature Database) were searched for CPGs published from 1 January 2017 to 4 December 2022. The official websites of 40 authoritative orthopaedic societies, rheumatology societies and guideline development organisations were additionally searched. ELIGIBILITY CRITERIA: We included all KOA CPGs published in English or Chinese from 1 January 2017 that included at least one recommendation for KOA. We excluded duplicate publications, older versions of CPGs as well as guidance documents for guideline development. DATA EXTRACTION AND SYNTHESIS: Reviewers worked in pairs and independently screened and extracted the data. Descriptive statistics were used, and absolute frequencies and proportions of related items were calculated. RESULTS: 187 research priorities reported in 41 KOA CPGs were identified. 24 CPGs reported research priorities, of which 17 (41.5%) presented overall research priorities for the entire guideline rather than for specific recommendations. 110 (58.8%) research priorities were put forward due to lack of evidence. Meanwhile, more than 70% of the research priorities reflected the P (population) and I (intervention) structural elements, with 135 (72.2%) and 146 (78.1%), respectively. More than half of the research priorities (118, 63.8%) revolved around evaluating the efficacy of interventions. Research priorities primarily focused on physical activity (32, 17.3%), physical therapy (30, 16.2%), surgical therapy (27, 14.6%) and pharmacological treatment (26, 14.1%). CONCLUSIONS: Research priorities reported in KOA CPGs mainly focused on evaluating non-pharmacological interventions. There exists considerable room for improvement for a comprehensive and standardised generation and reporting of research priorities in KOA CPGs.

Kaplan-Meier Survival Analysis: Practical Insights for Clinicians.

This article aims to provide a guide that will help healthcare professionals and clinical researchers from all fields that deal with Kaplan-Meier curves. Survival analysis methods are among the most frequently used in the medical sciences and in clinical research. Overall survival, progression free survival, time to recurrence, or any other clinically relevant parameter represented by a Kaplan-Meier curve will be discussed. We will present a practical and straightforward interpretation of these curves, setting aside intricate mathematical considerations. Our focus will be on essential concepts that interface with biological sciences and medicine in order to guarantee proficiency in one of the most popular yet frequently misunderstood methods in clinical research. Being familiar with these concepts is not only essential for designing new clinical studies but also for critically assessing and interpreting published data.

Language bias in orthodontic systematic reviews: A meta-epidemiological study.

BACKGROUND: Orthodontic systematic reviews (SRs) include studies published mostly in English than non-English languages. Including only English studies in SRs may result in a language bias. This meta-epidemiological study aimed to evaluate the language bias impact on orthodontic SRs. DATA SOURCE: SRs published in high-impact orthodontic journals between 2017 and 2021 were retrieved through an electronic search of PubMed in June 2022. Additionally, Cochrane oral health group was searched for orthodontic systematic reviews published in the same period. DATA COLLECTION AND ANALYSIS: Study selection and data extraction were performed by two authors. Multivariable logistic regression was implemented to explore the association of including non-English studies with the SRs characteristics. For the meta-epidemiological analysis, one meta-analysis from each SRs with at least three trials, including one non-English trial was extracted. The average difference in SMD was obtained using a random-effects meta-analysis. RESULTS: 174 SRs were included in this study. Almost one-quarter (n = 45/174, 26%) of these SRs included at least one non-English study. The association between SRs characteristics and including non-English studies was not statistically significant except for the restriction on language: the odds of including non-English studies reduced by 89% in SRs with a language restriction (OR: 0.11, 95%CI: 0.01 0.55, P< 0.01). Out of the sample, only fourteen meta-analyses were included in the meta-epidemiological analysis. The meta-epidemiological analysis revealed that non-English studies tended to overestimate the summary SMD by approximately 0.30, but this was not statistically significant when random-effects model was employed due to substantial statistical heterogeneity (ΔSMD = -0.29, 95%CI: -0.63 to 0.05, P = 0.37). As such, the overestimation of meta-analysis results by including non-English studies was statistically non-significant. CONCLUSION: Language bias has non-negligible impact on the results of orthodontic SRs. Orthodontic systematic reviews should abstain from language restrictions and use sensitivity analysis to assess the impact of language on the conclusions, as non-English studies may have a lower quality.

Craniocervical instability in patients with Ehlers­Danlos syndromes: outcomes analysis following occipito­cervical fusion of published cases.

This critique provides a critical analysis of the outcomes following occipito-cervical fusion in patients with Ehlers-Danlos syndromes (EDS) and craniocervical instability. The study examines the efficacy of the surgical intervention and evaluates its impact on patient outcomes. While the article offers valuable insights into the management of EDS-related craniocervical instability, several limitations and areas for improvement are identified, including sample size constraints, the absence of a control group, and the need for long-term follow-up data. Future research efforts should focus on addressing these concerns to optimize treatment outcomes for individuals with EDS.

Inter-reviewer reliability of human literature reviewing and implications for the introduction of machine-assisted systematic reviews: a mixed-methods review.

OBJECTIVES: Our main objective is to assess the inter-reviewer reliability (IRR) reported in published systematic literature reviews (SLRs). Our secondary objective is to determine the expected IRR by authors of SLRs for both human and machine-assisted reviews. METHODS: We performed a review of SLRs of randomised controlled trials using the PubMed and Embase databases. Data were extracted on IRR by means of Cohen's kappa score of abstract/title screening, full-text screening and data extraction in combination with review team size, items screened and the quality of the review was assessed with the A MeaSurement Tool to Assess systematic Reviews 2. In addition, we performed a survey of authors of SLRs on their expectations of machine learning automation and human performed IRR in SLRs. RESULTS: After removal of duplicates, 836 articles were screened for abstract, and 413 were screened full text. In total, 45 eligible articles were included. The average Cohen's kappa score reported was 0.82 (SD=0.11, n=12) for abstract screening, 0.77 (SD=0.18, n=14) for full-text screening, 0.86 (SD=0.07, n=15) for the whole screening process and 0.88 (SD=0.08, n=16) for data extraction. No association was observed between the IRR reported and review team size, items screened and quality of the SLR. The survey (n=37) showed overlapping expected Cohen's kappa values ranging between approximately 0.6-0.9 for either human or machine learning-assisted SLRs. No trend was observed between reviewer experience and expected IRR. Authors expect a higher-than-average IRR for machine learning-assisted SLR compared with human based SLR in both screening and data extraction. CONCLUSION: Currently, it is not common to report on IRR in the scientific literature for either human and machine learning-assisted SLRs. This mixed-methods review gives first guidance on the human IRR benchmark, which could be used as a minimal threshold for IRR in machine learning-assisted SLRs. PROSPERO REGISTRATION NUMBER: CRD42023386706.

Competence By Design: a transformational national model of time-variable competency-based postgraduate medical education.

Postgraduate medical education is an essential societal enterprise that prepares highly skilled physicians for the health workforce. In recent years, PGME systems have been criticized worldwide for problems with variable graduate abilities, concerns about patient safety, and issues with teaching and assessment methods. In response, competency based medical education approaches, with an emphasis on graduate outcomes, have been proposed as the direction for 21st century health profession education. However, there are few published models of large-scale implementation of these approaches. We describe the rationale and design for a national, time-variable competency-based multi-specialty system for postgraduate medical education called Competence by Design. Fourteen innovations were bundled to create this new system, using the Van Melle Core Components of competency based medical education as the basis for the transformation. The successful execution of this transformational training system shows competency based medical education can be implemented at scale. The lessons learned in the early implementation of Competence by Design can inform competency based medical education innovation efforts across professions worldwide.

A survey of surveys: an evaluation of the quality of published surveys in neurosurgery.

PURPOSE: Surveys generate valuable data in epidemiologic and qualitative clinical research. The quality of a survey depends on its design, the number of responses it receives, and the reporting of the results. In this study, we aimed to assess the quality of surveys in neurosurgery. METHODS: Neurosurgical surveys published between 2000 and 2020 (inclusive) were identified from PubMed. Various datapoints regarding the surveys were collated. The number of citations received by the papers was determined from Google Scholar. A 6-dimensional quality assessment tool was applied to the surveys. Parameters from this tool were combined with the number of responses received to create the survey quality score (SQS). RESULTS: A total of 618 surveys were included for analysis. The target sample size correlated with the number of responses received. The response rate correlated positively with the target sample size and the number of reminders sent and negatively with the number of questions in the survey. The median number of authors on neurosurgery survey papers was 6. The number of authors correlated with the SQS and the number of citations received by published survey papers. The median normalized SQS for neurosurgical surveys was 65%. The nSQS independently predicted the citations received per year by surveys. CONCLUSIONS: The modifiable factors that correlated with improvements in survey design were optimizing the number of questions, maximizing the target sample size, and incorporating reminders in the survey design. Increasing the number of contributing authors led to improvements in survey quality. The SQS was validated and correlated well with the citations received by surveys.

The evolution of sepsis publications and global productivity: A bibliometric analysis between 1980 and 2020.

The literature study was conducted by using the Web of Science (WoS) database, employing bibliometric analysis to examine all papers released from 1980 to 2020. The search was performed using the terms "sepsis, septicemia, septic shock" specifically within the titles of the publications. The findings of the literature research revealed a total of 51,725 articles. Out of the total number of publications, 26,896 articles were identified, accounting for 51.9% of the total. The bibliometric study revealed that the United States had the largest number of papers (8693), followed by China (2807), Germany (2299), France (1606), and the United Kingdom (1932). The writers that exhibited the most prolific output in terms of article production on the topic of sepsis were Vincent, with a total of 217 articles, followed by Wang P with 154 articles, and Chaudry IH with 126 articles. The University of Pittsburgh, Brown University, and the University of Michigan were identified as the most productive universities, in that order. The findings from the prediction model revealed that the projected number of articles to be published in 2021 is estimated to be 2086, while the projected number for 2030 is estimated to be 2637. The literature has predominantly focused on disease markers and diagnostic methods, severity and effects of the disease, immunity and inflammation, effects of the disease in neonates and the neonatal period, and treatment and care. According to trend analysis results, recent focus in sepsis research includes a broad spectrum of investigations such as mortality rates, prognostic determinants, diagnostic methods, biomarkers, epidemiological insights, critical care strategies, infections, treatment outcomes, emergency department scenarios, pediatric assessments, and antibiotic interventions.

Elucidating the pathogenesis behind arteriovenous malformations of the central nervous system: a bibliometric analysis.

Arteriovenous malformations (AVMs) are vascular malformations of the central nervous system (CNS) with potential for significant consequences. The exact pathophysiologic mechanism of AVM formation is not fully understood. This study aims to evaluate bibliometric parameters and citations of the literature of AVMs to provide an overview of how the field has evolved. We performed an electronic search on Web of Science to identify the top 100 published and indexed articles with the highest number of citations discussing the pathogenesis of AVMs. This study yielded 1863 articles, of which the top 100 were selected based on the highest total citation count. These articles included 24% basic science, 46% clinical, and 30% review articles. The most-cited article was a clinical article from 2003, and the most recent was published in 2022. The median number of authors was 6, with the highest being 46 for a clinical article. The top 5 journals were identified, with the highest impact factor being 20.1. 13 countries were identified, with the US contributing the most articles (approximately 70%). Regarding genes of investigation, VEGF was one of the early genes investigated, while more interested in RAS/MAPK has been garnered since 2015. There is a growing interest in AVM genomics and pathogenesis research. While progress has been made in understanding clinical aspects and risk factors, the exact pathophysiological mechanisms and genetic basis of AVM formation remain incompletely understood. Further investigation of key genes in AVM pathogenesis can allow identification of potential therapeutic targets.

Trends and Patterns in Electronic Health Record Research (1991-2022): A Bibliometric Analysis of Australian Literature.

Electronic Heath Records (EHRs) play vital roles in facilitating streamlined service provision and governance across the Australian health system. Given the recent challenges due to the COVID-19 pandemic, an ageing population, health workforce silos, and growing inefficiencies in traditional systems, a detailed historical analysis of the use of EHR research in Australia is necessary. The aim of this study is to examine the trends and patterns in EHR research in Australia over the past three decades by employing bibliometric methods. A total of 951 articles published in 443 sources were included in the bibliometric analysis. The annual growth rate of EHR research in Australia was about 17.1%. Since 2022, the main trending topics in EHR research were COVID-19, opioid usage, and natural language processing. A thematic analysis indicated aged care, clinical decision support systems, cardiovascular disease, drug allergy, and adverse drug reaction as the "hot" themes in EHR research in Australia. This study reveals a significant uptrend in EHR research in Australia, highlighting the evolving intellectual and collaborative landscape of this interdisciplinary field. The data also provide guidance for policymakers and funding institutions in terms of the most significant contributions and key fields of research while also holding public interest.

Automatic categorization of self-acknowledged limitations in randomized controlled trial publications.

OBJECTIVE: Acknowledging study limitations in a scientific publication is a crucial element in scientific transparency and progress. However, limitation reporting is often inadequate. Natural language processing (NLP) methods could support automated reporting checks, improving research transparency. In this study, our objective was to develop a dataset and NLP methods to detect and categorize self-acknowledged limitations (e.g., sample size, blinding) reported in randomized controlled trial (RCT) publications. METHODS: We created a data model of limitation types in RCT studies and annotated a corpus of 200 full-text RCT publications using this data model. We fine-tuned BERT-based sentence classification models to recognize the limitation sentences and their types. To address the small size of the annotated corpus, we experimented with data augmentation approaches, including Easy Data Augmentation (EDA) and Prompt-Based Data Augmentation (PromDA). We applied the best-performing model to a set of about 12K RCT publications to characterize self-acknowledged limitations at larger scale. RESULTS: Our data model consists of 15 categories and 24 sub-categories (e.g., Population and its sub-category DiagnosticCriteria). We annotated 1090 instances of limitation types in 952 sentences (4.8 limitation sentences and 5.5 limitation types per article). A fine-tuned PubMedBERT model for limitation sentence classification improved upon our earlier model by about 1.5 absolute percentage points in F1 score (0.821 vs. 0.8) with statistical significance (p<.001). Our best-performing limitation type classification model, PubMedBERT fine-tuning with PromDA (Output View), achieved an F1 score of 0.7, improving upon the vanilla PubMedBERT model by 2.7 percentage points, with statistical significance (p<.001). CONCLUSION: The model could support automated screening tools which can be used by journals to draw the authors' attention to reporting issues. Automatic extraction of limitations from RCT publications could benefit peer review and evidence synthesis, and support advanced methods to search and aggregate the evidence from the clinical trial literature.

Trends of Publications and Country Rankings in Pediatrics, Perinatology, and Child Health from Asia: A Bibliometric Study from 1996 to 2022.

There is a need to analyze the trends of country-wise research output in child heath over the past few decades. A total of 7,87,812 global publications in pediatrics, perinatology and child health were found from 1996 to 2022 in SCOPUS, the largest abstract and citation database of peer-reviewed literature, covering over 35,000 journals from diverse disciplines. About 13.4% of these were published from Asia. There was an average growth of global publications of 3.53 times between 1996 and 2022, with China and India showing higher growth than the global average.

Prepublication abstract-only reports compared with full-text manuscripts for randomised controlled trials in inflammatory bowel disease: a systematic review.

INTRODUCTION: Randomised controlled trials (RCTs) of key therapies in inflammatory bowel disease (IBD) are often presented and available as abstracts for significant periods of time prior to full publication, often being employed to make strategic and clinical prescribing decisions. We compared the concordance of prepublication abstract-only reports and their respective full-text manuscripts. METHODS: Pairs of full-text manuscripts and their respective prepublication abstract-only reports for the same RCT outcomes, at the same time point of analysis were included. The RCTs were on treatments for IBD with full-text manuscripts published between 2010 and 2023. RESULTS: We found 77 pairs of full-text manuscripts and their prepublication abstract-only reports. There were significant mismatches in the reporting of stated planned outcomes (65/77 matched, p<0.001) and primary outcomes reported in their results sections (67/77, p<0.001); trial registrations (34/65, p<0.001); the number of randomised participants (49/77, p=0.18); participants reaching end of study (21/71, p<0.001) and primary outcome data (40/73, p<0.001). Authors conclusions matched (75/77, p=0.157). Authors did not provide explicit or implied justifications for the absence or non-concordance for any of the above items. CONCLUSIONS: Abstract-only reports have consistent issues with both limited reporting of key information and significant differences in data when compared with their later full-text publications. These are not related to further recruitment of patients or word count limitations and are never explained. As abstracts are often used in guidelines, reviews and stakeholder decision-making on prescribing, caution in their use is strongly suggested. Further work is needed to enhance minimum reporting standards in abstract-only works and ensure consistency with final published papers.

Emphasis should be placed on identifying and reporting research priorities to increase research value: An empirical analysis.

OBJECTIVES: To compared the presentation of research priorities in the GRADE (Grading of Recommendations Assessment, Development, and Evaluation) clinical practice guidelines (CPGs) developed under the guidance of the GRADE working group or its two co-chair, and the Chinese CPGs. METHODS: This was a methodological empirical analysis. We searched PubMed, Embase, and four Chinese databases (Wanfang, VIP Database for Chinese Technical Periodicals, China National Knowledge Infrastructure and Chinese Biomedical Literature Database) and retrieved nine Chinese guideline databases or Society websites as well as GRADE Pro websites. We included all eligible GRADE CPGs and a random sample of double number of Chinese CPGs, published 2018 to 2022. The reviewers independently screened and extracted the data, and we summarized and analyzed the reporting on the research priorities in the CPGs. RESULTS: Of the 135 eligible CPGs (45 GRADE CPGs and 90 Chinese CPGs), 668, 138 research priorities were identified respectively. More than 70% of the research priorities in GRADE CPGs and Chinese CPGs had population and intervention (PI) structure. 99 (14.8%) of GRADE CPG research priorities had PIC structures, compared with only 4(2.9%) in Chinese. And 28.4% (190) GRADE CPG research priorities reflected comparisons between PICO elements, approximately double those in Chinese. The types of research priorities among GRADE CPGs and Chinese CPGs were mostly focused on the efficacy of interventions, and the type of comparative effectiveness in the GRADE research priorities was double those in Chinese. CONCLUSIONS: There was still considerable room for improvement in the developing and reporting of research priorities in Chinese CPGs. Key PICO elements were inadequately presented, with more attention on intervention efficacy and insufficient consideration given to values, preferences, health equity, and feasibility. Identifying and reporting of research priorities deserves greater effort in the future.

Sex reporting of cells used in cancer research: A systematic review.

Sex and gender disparities in biomedical research have been emphasized to improve scientific knowledge applied for the health of both men and women. Despite sex differences in cancer incidence, prognosis, and responses to therapeutic agents, mechanistic explanations at molecular levels are far from enough. Recent studies suggested that cell sex is an important biological variable due to differences in sex chromosome gene expression and differences in events associated with developmental biology. The objective of this study was to analyze the reporting of sex of cells used in cancer research using articles published in Cancer Cell, Molecular Cancer, Journal of Hematology & Oncology, Journal for ImmunoTherapy of Cancer, and Cancer Research in 2020, and to examine whether there exists any sex bias. We found that the percentage of cells with sex notation in the article was 36.5%. Primary cells exhibited higher sex notation compared to cell lines. A higher percentage of female cells were used in cell cultures with sex notation. Also, sex-common cells omitted sex description more often compared to sex-specific cells. None of the cells isolated from embryo and esophagus reported the cell sex in the article. Our results indicate cell sex report in cancer research is limited to a small proportion of cells used in the study. These results call for acknowledging the sex of cells to increase the applicability of biomedical research discoveries.