ChatGPT: Literate or intelligent about UN sustainable development goals?

Generative AI tools, such as ChatGPT, are progressively transforming numerous sectors, demonstrating a capacity to impact human life dramatically. This research seeks to evaluate the UN Sustainable Development Goals (SDGs) literacy of ChatGPT, which is crucial for diverse stakeholders involved in SDG-related policies. Experimental outcomes from two widely used Sustainability Assessment tests-the UN SDG Fitness Test and Sustainability Literacy Test (SULITEST) - suggest that ChatGPT exhibits high SDG literacy, yet its comprehensive SDG intelligence needs further exploration. The Fitness Test gauges eight vital competencies across introductory, intermediate, and advanced levels. Accurate mapping of these to the test questions is essential for partial evaluation of SDG intelligence. To assess SDG intelligence, the questions from both tests were mapped to 17 SDGs and eight cross-cutting SDG core competencies, but both test questionnaires were found to be insufficient. SULITEST could satisfactorily map only 5 out of 8 competencies, whereas the Fitness Test managed to map 6 out of 8. Regarding the coverage of the Fitness Test and SULITEST, their mapping to the 17 SDGs, both tests fell short. Most SDGs were underrepresented in both instruments, with certain SDGs not represented at all. Consequently, both tools proved ineffective in assessing SDG intelligence through SDG coverage. The study recommends future versions of ChatGPT to enhance competencies such as collaboration, critical thinking, systems thinking, and others to achieve the SDGs. It concludes that while AI models like ChatGPT hold considerable potential in sustainable development, their usage must be approached carefully, considering current limitations and ethical implications.

Top 100 highly cited sustainability researchers

The announcement of the UN Sustainable Development Goals (SDGs) provided a fresh direction to sustainability research that spans different disciplines. Consequently, scholarly databases made available the mapping of research publications to different SDGs, unleashing many opportunities for analysis. In this work, the top 100 Highly Cited Sustainability Researchers (HCSRs) and information related to them, such as the institutions they belong to, the type of these institutions, the geographical diversity of these researchers, and gender representation patterns, are analyzed. Also, from their publications, their publication pattern, including (i) the least and most researched SDGs, (ii) their Open Access publishing pattern, (iii) their collaboration pattern (iv) the pattern of their research impact, are analyzed. The most sought thematic areas of their research, top journals in which they publish, important research categories handled by these journals, etc., are also investigated. The most significant contribution of these researchers and their recent contributions are also discussed. The data indicates a significant disparity in research focus among the top 100 HCSRs, with most concentrating on "Good Health and Well Being," "Zero Hunger," and "Quality Education," while notably fewer researchers focus on "Decent Work and Economic Growth" and "No Poverty," underscoring the need for a more balanced research agenda across all SDGs. The study reveals that the United States, China, and the United Kingdom are the leading contributors to the top 100 HCSRs, suggesting that these countries are predominant in global sustainability research output, while nations like Iran and Saudi Arabia also make notable, albeit smaller, contributions. The institutional affiliations of HCSRs show a significant imbalance, with only 16 from private institutions compared to 84 from public ones. Specifically, it shows that out of the top 100 researchers, 93 are men, while only 7 are women. The analysis of authorship in publications by HCSRs reveals a tendency towards middle and last author positions, underscoring their collaborative and leadership roles within the research community. All these analyses can inform academia, industry, and policymakers about the most significant developments in research regarding SDGs.

Timing of Radiotherapy (RT) After Radical Prostatectomy (RP): Long-term outcomes in the RADICALS-RT trial [NCT00541047]

BACKGROUND

The optimal timing of radiotherapy (RT) after radical prostatectomy for prostate cancer has been uncertain. RADICALS-RT compared efficacy and safety of adjuvant RT versus an observation policy with salvage RT for PSA failure.

METHODS

RADICALS-RT was a randomised controlled trial enrolling patients with ≥1 risk factor (pT3/4, Gleason 7-10, positive margins, pre-op PSA≥10ng/ml) for recurrence after radical prostatectomy. Patients were randomised 1:1 to adjuvant RT ("Adjuvant-RT") or an observation policy with salvage RT for PSA failure ("Salvage-RT") defined as PSA≥0.1ng/ml or 3 consecutive rises. Stratification factors were Gleason score, margin status, planned RT schedule (52.5Gy/20 fractions or 66Gy/33 fractions) and treatment centre. The primary outcome measure was freedom-from-distant metastasis, designed with 80% power to detect an improvement from 90% with Salvage-RT (control) to 95% at 10yr with Adjuvant-RT. Secondary outcome measures were bPFS, freedom-from-non-protocol hormone therapy, safety and patient-reported outcomes. Standard survival analysis methods were used; HR<1 favours Adjuvant-RT.

FINDINGS

Between Oct-2007 and Dec-2016, 1396 participants from UK, Denmark, Canada and Ireland were randomised: 699 Salvage-RT, 697 Adjuvant-RT. Allocated groups were balanced with median age 65yr. 93% (649/697) Adjuvant-RT reported RT within 6m after randomisation; 39% (270/699) Salvage-RT reported RT during follow-up. Median follow-up was 7.8 years. With 80 distant metastasis events, 10yr FFDM was 93% for Adjuvant-RT and 90% for Salvage-RT: HR=0.68 (95%CI 0·43-1·07, p=0·095). Of 109 deaths, 17 were due to prostate cancer. Overall survival was not improved (HR=0.980, 95%CI 0.667-1.440, p=0.917). Adjuvant-RT reported worse urinary and faecal incontinence one year after randomisation (p=0.001); faecal incontinence remained significant after ten years (p=0.017).

INTERPRETATION

Long-term results from RADICALS-RT confirm adjuvant RT after radical prostatectomy increases the risk of urinary and bowel morbidity, but does not meaningfully improve disease control. An observation policy with salvage RT for PSA failure should be the current standard after radical prostatectomy.

Evaluating human resources management literacy: A performance analysis of ChatGPT and bard

This study presents a comprehensive analysis comparing the literacy levels of two Generative Artificial Intelligence (GAI) tools, ChatGPT and Bard, using a dataset of 134 questions from the Human Resources (HR) domain. The generated responses are evaluated for accuracy, relevance, and clarity. We find that ChatGPT outperforms Bard in overall accuracy (84.3% vs. 82.8%). This difference in performance suggests that ChatGPT could serve as a robotic advisor in transactional HR roles. In contrast, Bard may possess additional safeguards against misuse in the HR function, making it less capable of generating responses to certain types of questions. Statistical tests reveal that although the two systems differ in their mean accuracy, relevance, and clarity of the responses, the observed differences are not always statistically significant, implying that both tools may be more complementary than competitive. The Pearson correlation coefficients further support this by showing weak to non-existent relationships in performance metrics between the two tools. Confirmation queries don't improve ChatGPT or Bard's response accuracy. The study thus contributes to emerging research on the utility of GAI tools in Human Resources Management and suggests that involving certified HR professionals in the design phase could enhance underlying language model performance.

Diagnosis Unreliability of ChatGPT for Journal Evaluation

Purpose

Academic and other researchers have limited tools with which to address the current proliferation of predatory and hijacked journals. These journals can have negative effects on science, research funding, and the dissemination of information. As most predatory and hijacked journals are not error free, this study used ChatGPT, an artificial intelligence (AI) technology tool, to conduct an evaluation of journal quality.

Methods

Predatory and hijacked journals were analyzed for reliability using ChatGPT, and the reliability of result have been discussed.

Results

It shows that ChatGPT is an unreliable tool for journal quality evaluation for both hijacked and predatory journals.

Conclusion

To show how to address this gap, an early trial version of Journal Checker Chatbot has been developed and is discussed as an alternative chatbot that can assist researchers in detecting hijacked journals.

Fake news research trends, linkages to generative artificial intelligence and sustainable development goals

In the digital age, where information is a cornerstone for decision-making, social media's not-so-regulated environment has intensified the prevalence of fake news, with significant implications for both individuals and societies. This study employs a bibliometric analysis of a large corpus of 9678 publications spanning 2013-2022 to scrutinize the evolution of fake news research, identifying leading authors, institutions, and nations. Three thematic clusters emerge: Disinformation in social media, COVID-19-induced infodemics, and techno-scientific advancements in auto-detection. This work introduces three novel contributions: 1) a pioneering mapping of fake news research to Sustainable Development Goals (SDGs), indicating its influence on areas like health (SDG 3), peace (SDG 16), and industry (SDG 9); 2) the utilization of Prominence percentile metrics to discern critical and economically prioritized research areas, such as misinformation and object detection in deep learning; and 3) an evaluation of generative AI's role in the propagation and realism of fake news, raising pressing ethical concerns. These contributions collectively provide a comprehensive overview of the current state and future trajectories of fake news research, offering valuable insights for academia, policymakers, and industry.

Achievement of Target Gain Larger than Unity in an Inertial Fusion Experiment

On December 5, 2022, an indirect drive fusion implosion on the National Ignition Facility (NIF) achieved a target gain G_{target} of 1.5. This is the first laboratory demonstration of exceeding "scientific breakeven" (or G_{target}>1) where 2.05 MJ of 351 nm laser light produced 3.1 MJ of total fusion yield, a result which significantly exceeds the Lawson criterion for fusion ignition as reported in a previous NIF implosion [H. Abu-Shawareb et al. (Indirect Drive ICF Collaboration), Phys. Rev. Lett. 129, 075001 (2022)PRLTAO0031-900710.1103/PhysRevLett.129.075001]. This achievement is the culmination of more than five decades of research and gives proof that laboratory fusion, based on fundamental physics principles, is possible. This Letter reports on the target, laser, design, and experimental advancements that led to this result.

Mapping autism's research landscape: trends in autism screening and its alignment with sustainable development goals

Introduction

Autism Spectrum Disorder is a complex neurodevelopmental syndrome that profoundly affects social interactions, communication, and sensory perception. The research traced the evolution of autism research from 2011-2022, specifically focusing on the screening and diagnosis of children and students.

Methods

Through an analysis of 12,262 publications using the PRISMA framework, bibliographic coupling, science mapping, and citation analysis, this study illuminates the growth trajectory of ASD research and significant disparities in diagnosis and services.

Results

The study indicates an increasing trend in autism research, with a strong representation of female authorship. Open Access journals show a higher average citation impact compared to their closed counterparts. A keyword co-occurrence analysis revealed four central research themes: Child Development and Support Systems, Early Identification and Intervention, Prevalence and Etiology, and Mental Health. The pandemic's onset has prioritized research areas like mental health, telehealth, and service accessibility.

Discussion

Recommendations on a global level stress the importance of developing timely biological markers for ASD, amplifying Disability Inclusion research, and personalizing mental health services to bridge these critical service gaps. These strategies, underpinned by interdisciplinary collaboration and telehealth innovation, particularly in low-resource settings, can offer a roadmap for inclusive, context-sensitive interventions at local levels that directly support SDG3's aim for health and well-being for all.

Applications of artificial intelligence and machine learning in the financial services industry: A bibliometric review

This bibliometric review examines the research state of artificial intelligence (AI) and machine learning (ML) applications in the Banking, Financial Services, and Insurance (BFSI) sector. The study focuses on Scopus-indexed articles to identify key research clusters. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol, 39,498 articles were screened, resulting in 1045 articles meeting the inclusion criteria. N-gram analysis identified 177 unique terms in the article titles and abstracts. Co-occurrence analysis revealed nine distinct clusters covering fintech, risk management, anti-money laundering, and actuarial science, among others. These clusters offer a comprehensive overview of the multifaceted research landscape. The identified clusters can guide future research and inform study design. Policymakers, researchers, and practitioners in the BFSI sector can benefit from the study's findings, which identify research gaps and opportunities. This study contributes to the growing literature on bibliometrics, providing insights into AI and ML applications in the BFSI sector. The findings have practical implications, advancing our understanding of AI and ML's role in benefiting academia and industry.

A Toolkit for Detecting Fallacious Calls for Papers from Potential Predatory Journals

Purpose

Flattering emails are crucial in tempting authors to submit papers to predatory journals. Although there is ample literature regarding the questionable practices of predatory journals, the nature and detection of spam emails need more attention. Current research provides insight into fallacious calls for papers from potential predatory journals and develops a toolkit in this regard.

Methods

In this study, we analyzed three datasets of calls for papers from potential predatory journals and legitimate journals using a text mining approach and R programming language.

Results

Overall, most potential predatory journals use similar language and templates in their calls for papers. Importantly, these journals praise themselves in glorious terms involving positive words that may be rarely seen in emails from legitimate journals. Based on these findings, we developed a lexicon for detecting unsolicited calls for papers from potential predatory journals.

Conclusion

We conclude that calls for papers from potential predatory journals and legitimate journals are different, and it can help to distinguish them. By providing an educational plan and easily usable tools, we can deal with predatory journals better than previously.

Darkweb research: Past, present, and future trends and mapping to sustainable development goals

The Darkweb, part of the deep web, can be accessed only through specialized computer software and used for illegal activities such as cybercrime, drug trafficking, and exploitation. Technological advancements like Tor, bitcoin, and cryptocurrencies allow criminals to carry out these activities anonymously, leading to increased use of the Darkweb. At the same time, computers have become an integral part of our daily lives, shaping our behavior, and influencing how we interact with each other and the world. This work carries out the bibliometric study on the research conducted on Darkweb over the last decade. The findings illustrate that most research on Darkweb can be clustered into four areas based on keyword co-occurrence analysis: (i) network security, malware, and cyber-attacks, (ii) cybercrime, data privacy, and cryptography, (iii) machine learning, social media, and artificial intelligence, and (iv) drug trafficking, cryptomarket. National Science Foundation from the United States is the top funder. Darkweb activities interfere with the Sustainable Development Goals (SDG) laid forth by the United Nations to promote peace and sustainability for current and future generations. SDG 16 (Peace, Justice, and Strong Institutions) has the highest number of publications and citations but has an inverse relationship with Darkweb, as the latter undermines the former. This study highlights the need for further research in bitcoin, blockchain, IoT, NLP, cryptocurrencies, phishing and cybercrime, botnets and malware, digital forensics, and electronic crime countermeasures about the Darkweb. The study further elucidates the multi-dimensional nature of the Darkweb, emphasizing the intricate relationship between technology, psychology, and geopolitics. This comprehensive understanding serves as a cornerstone for evolving effective countermeasures and calls for an interdisciplinary research approach. The study also delves into the psychological motivations driving individuals towards illegal activities on the Darkweb, highlighting the urgency for targeted interventions to promote pro-social online behavior.

Detection of fake papers in the era of artificial intelligence

OBJECTIVES

Paper mills, companies that write scientific papers and gain acceptance for them, then sell authorships of these papers, present a key challenge in medicine and other healthcare fields. This challenge is becoming more acute with artificial intelligence (AI), where AI writes the manuscripts and then the paper mills sell the authorships of these papers. The aim of the current research is to provide a method for detecting fake papers.

METHODS

The method reported in this article uses a machine learning approach to create decision trees to identify fake papers. The data were collected from Web of Science and multiple journals in various fields.

RESULTS

The article presents a method to identify fake papers based on the results of decision trees. Use of this method in a case study indicated its effectiveness in identifying a fake paper.

CONCLUSIONS

This method to identify fake papers is applicable for authors, editors, and publishers across fields to investigate a single paper or to conduct an analysis of a group of manuscripts. Clinicians and others can use this method to evaluate articles they find in a search to ensure they are not fake articles and instead report actual research that was peer reviewed prior to publication in a journal.

Ayurveda research: Emerging trends and mapping to sustainable development goals

Ayurveda is India's prominent traditional medical system. The World Health Organization has stated the need for more evidence and data from conventional medicine methods to inform policymakers, regulatory bodies, healthcare stakeholders, and the public about its safe, effective, and equitable use. This study aims to provide a comprehensive analysis of the emerging trends in Ayurveda research, mapping research to the UN Sustainable Development Goals (SDG) and examining the impact of COVID-19. Using bibliometric methods, the researchers analyzed a total of 11,773 publications between 1993 and 2022 to understand the temporal evolution of publications, open-access publications, patterns of author collaboration, top-performing countries, and co-citation networks. The keyword co-occurrence analysis identifies networks of concentrated studies on Ayurveda research themes relating to the four clusters, Alternative and Traditional Medicine, Bioactive Compounds and Biological Activities, Analytical Techniques and Herbal Standardization, and Herbal Medicines and Immunomodulation, reflecting the diverse research areas within Ayurveda. The last cluster included research related to the SARS-CoV-2 virus, suggesting research on herbal approaches to immune modulation in the context of COVID-19. The most prominent SDG among these research themes was Good Health and Well-being (SDG 3), emphasizing the potential of natural products and traditional medicine in promoting holistic health and combating antibiotic resistance.

Transparency in research: An analysis of ChatGPT usage acknowledgment by authors across disciplines and geographies

This investigation systematically reviews the recognition of generative AI tools, particularly ChatGPT, in scholarly literature. Utilizing 1,226 publications from the Dimensions database, ranging from November 2022 to July 2023, the research scrutinizes temporal trends and distribution across disciplines and regions. U.S.-based authors lead in acknowledgments, with notable contributions from China and India. Predominantly, Biomedical and Clinical Sciences, as well as Information and Computing Sciences, are engaging with these AI tools. Publications like "The Lancet Digital Health" and platforms such as "bioRxiv" are recurrent venues for such acknowledgments, highlighting AI's growing impact on research dissemination. The analysis is confined to the Dimensions database, thus potentially overlooking other sources and grey literature. Additionally, the study abstains from examining the acknowledgments' quality or ethical considerations. Findings are beneficial for stakeholders, providing a basis for policy and scholarly discourse on ethical AI use in academia. This study represents the inaugural comprehensive empirical assessment of AI acknowledgment patterns in academic contexts, addressing a previously unexplored aspect of scholarly communication.

Mapping sustainability reporting research with the UN's sustainable development goal

Non-financial reporting (NFR) has become crucial to corporate sustainability strategies as companies demonstrate their commitment to the environmental, social, and governance actions outlined in the United Nations Sustainable Development Goals (SDGs) Agenda 2030. Among the various mandatory NFR initiatives, Sustainability Reporting (SR) has emerged as a widely adopted practice by companies worldwide. A gap that the study addresses is the theoretical perspectives on SR in the context of SDG. Then we conduct a bibliometric and science mapping analysis of research trends on SR and precisely map SR research to SDGs which is also a gap in the current literature. We find an exponential increase in the number of publications and citations on SR, particularly after 2015, which coincides with increased public awareness and scrutiny of the SDGs. At the country level, Australia leads with a total of 13 SDGs, followed by the UK, Spain, and Italy, which each address 12 SDGs. Emerging economies such as Indonesia, Malaysia, and India have also increased their contributions since 2019. A keyword co-occurrence analysis identified three main clusters: stakeholder engagement, corporate governance, and accountability; sustainable development goals and climate change; and sustainability reporting and global reporting initiatives. All three clusters had highly cited publications related to SDG 8 (decent work), SDG 9 (industry innovation), and SDG 12 (responsible consumption). This highlights the interdisciplinary nature of SR and its relevance to multiple SDGs. The study is distinctive in that we utilized social network analysis to examine the SDG network based on SR publications, which also affirmed the centrality of SDG 9 and 12. We utilized the prominence percentile, which indicates the momentum of a particular topic, to identify future topics in SR that align with the SDGs. These include cause-related marketing, environmentally preferable purchasing decisions, environmental management systems, education for sustainability, and green computing.

Natural cubic splines for the analysis of Alzheimer's clinical trials

Mixed model repeated measures (MMRM) is the most common analysis approach used in clinical trials for Alzheimer's disease and other progressive diseases measured with continuous outcomes over time. The model treats time as a categorical variable, which allows an unconstrained estimate of the mean for each study visit in each randomized group. Categorizing time in this way can be problematic when assessments occur off-schedule, as including off-schedule visits can induce bias, and excluding them ignores valuable information and violates the intention to treat principle. This problem has been exacerbated by clinical trial visits which have been delayed due to the COVID19 pandemic. As an alternative to MMRM, we propose a constrained longitudinal data analysis with natural cubic splines that treats time as continuous and uses test version effects to model the mean over time. Compared to categorical-time models like MMRM and models that assume a proportional treatment effect, the spline model is shown to be more parsimonious and precise in real clinical trial datasets, and has better power and Type I error in a variety of simulation scenarios.

The contribution of dynamics to macaque body and face patch responses

Previous functional imaging studies demonstrated body-selective patches in the primate visual temporal cortex, comparing activations to static bodies and static images of other categories. However, the use of static instead of dynamic displays of moving bodies may have underestimated the extent of the body patch network. Indeed, body dynamics provide information about action and emotion and may be processed in patches not activated by static images. Thus, to map with fMRI the full extent of the macaque body patch system in the visual temporal cortex, we employed dynamic displays of natural-acting monkey bodies, dynamic monkey faces, objects, and scrambled versions of these videos, all presented during fixation. We found nine body patches in the visual temporal cortex, starting posteriorly in the superior temporal sulcus (STS) and ending anteriorly in the temporal pole. Unlike for static images, body patches were present consistently in both the lower and upper banks of the STS. Overall, body patches showed a higher activation by dynamic displays than by matched static images, which, for identical stimulus displays, was less the case for the neighboring face patches. These data provide the groundwork for future single-unit recording studies to reveal the spatiotemporal features the neurons of these body patches encode. These fMRI findings suggest that dynamics have a stronger contribution to population responses in body than face patches.

Early Osteoarthritis Questionnaire (EOAQ): a tool to assess knee osteoarthritis at initial stage

Background

Early stage of osteoarthritis (OA) is characterized by joint stiffness and pain as well as by subclinical structural changes that may affect cartilage, synovium, and bone. At the moment, the lack of a validated definition of early osteoarthritis (EOA) does not allow to make an early diagnosis and adopt a therapeutic strategy to slow disease progression. Also, no questionnaires are available to evaluate the early stage, and therefore this remains an unmet need.

Objective

Therefore, the purpose of the technical experts panel (TEP) of 'International Symposium of intra-articular treatment' (ISIAT) was to create a specific questionnaire to evaluate and monitor the follow-up and clinical progress of patients affected by early knee OA.

Design

The items for the Early Osteoarthritis Questionnaire (EOAQ) were identified according to the following steps: items generation, items reduction, and pre-test submission.

Methods

During the first step, literature has been reviewed and a comprehensive list of items about pain and function in knee EOA was drafted. Then, during the ISIAT (5th edition 2019), the draft has been discussed by the board, which reformulated, deleted, or subdivided some of the items. After the ISIAT symposium, the draft was submitted to 24 subjects affected by knee OA. A score based on the importance and the frequency was created and the items with a score ⩾0.75 were selected. After intermediate evaluation made by a sample of patients, the second and final version of the questionnaire EOAQ was submitted to the whole board for final analysis and acceptance in a second meeting (29 January 2021).

Results

After an exhaustive elaboration, the final version of the questionnaire contains two domains (Clinical Features and Patients Reported Outcome) with respectively 2 and 9 questions, for a total of 11 questions. Questions mainly explored the fields of early symptoms and patients reported outcomes. Marginally, the need of the symptoms treatment and the use of painkillers were investigated.

Conclusions

Adoption of diagnostic criteria of early OA is strongly encouraged and a specific questionnaire for the whole management of the clinical features and patients' outcome might really improve the evolution of OA in the early stages of the disease, when the treatment is expected to be more effective.

Lawson Criterion for Ignition Exceeded in an Inertial Fusion Experiment

For more than half a century, researchers around the world have been engaged in attempts to achieve fusion ignition as a proof of principle of various fusion concepts. Following the Lawson criterion, an ignited plasma is one where the fusion heating power is high enough to overcome all the physical processes that cool the fusion plasma, creating a positive thermodynamic feedback loop with rapidly increasing temperature. In inertially confined fusion, ignition is a state where the fusion plasma can begin "burn propagation" into surrounding cold fuel, enabling the possibility of high energy gain. While "scientific breakeven" (i.e., unity target gain) has not yet been achieved (here target gain is 0.72, 1.37 MJ of fusion for 1.92 MJ of laser energy), this Letter reports the first controlled fusion experiment, using laser indirect drive, on the National Ignition Facility to produce capsule gain (here 5.8) and reach ignition by nine different formulations of the Lawson criterion.

Pattern of contraceptive use, determinants and fertility intentions among tribal women in Kerala, India: a cross-sectional study

OBJECTIVES

To assess the pattern of contraceptive use and its determinants, knowledge regarding contraceptives including oral contraceptive pills and fertility intentions among tribal women in the reproductive age group.

DESIGN

Community-based cross-sectional study.

SETTING

Community development blocks in a predominantly tribal district of Wayanad in Kerala, India.

PARTICIPANTS

Women in the reproductive age group (15-49 years) from the tribal groups in the district numbering 2495.

OUTCOME MEASURES

PRIMARY: Prevalence of contraceptive use and its determinants.

SECONDARY

Knowledge regarding contraceptives in general, oral contraceptives and fertility intentions.

RESULTS

The mean age of the study participants was 30.8 years (SD=9.8) and belonged to various tribal groups such as Paniya (59.2%), Kurichiyar (13.6%) and Adiya (10.9%). Current use of contraceptive was reported by about a fourth, 658 (26.4%) (95% CI 27.9 to 24.9) of women. Following logistic regression, belonging to Paniya tribe (adjusted OR (aOR) 2.67, 95% CI 1.49 to 4.77; p<0.001) and age at menarche >13 years (aOR 1.69, 95% CI 1.14 to 2.52; p<0.009) had significantly higher use of contraceptives whereas social vulnerability as indicated by staying in a kutcha house had a lesser likelihood of use of contraceptive (aOR 0.55, 95% CI 0.31 to 0.95; p<0.03). Oral contraceptive use was low (4.8%) among this population and no abuse was observed.Less than half (47%) of the respondents had an above average knowledge on contraception. Multivariable logistic regression indicated that above average knowledge was 2.2 times more likely with higher education (95% CI 1.2 to 3.9), lesser among those who desired more than two children (aOR 0.59; 95% CI 0.38 to 0.94; p<0.02).Two children per family was the preferred choice for 1060 (42.5%) women. No gender bias in favour of the male child was observed.

CONCLUSION

Awareness and use of contraceptives are poor though the fertility is not commensurately high. Along with developing targeted responses to contraceptive use among Indigenous people with indigenous data, awareness also requires attention. Ethnographic studies are also necessary to determine the differences in contraceptive use including traditional methods among the various Indigenous groups.

Virtual Laboratories- A historical review and bibliometric analysis of the past three decades

Online and virtual teaching-learning has been a panacea that most educational institutions adopted from the dire need created by COVID-19. We provide a comprehensive bibliometric study of 9523 publications on virtual laboratories in higher education covering the years 1991 to 2021. Influential bibliometrics such as publications and citations, productive countries, contributing institutions, funders, journals, authors, and bibliographic couplings were studied using the Scientific Procedures and Rationales for Systematic Literature Reviews (SPAR-4-SLR) protocol. A new metric to complement citations called Field Weighted Citation Impact was introduced that considers the differences in research behavior across disciplines. Findings show that 72% of the research work was published between 2011-and 2021, most likely due to digitalization, with the highest number of publications in 2020-2021 highlighting the impact of the pandemic. Top contributing institutions were from the developed economies of Spain, Germany, and the United States. The citation impact from publications with international co-authors is the highest, highlighting the importance of co-authoring papers with different countries. For the first time, Altmetrics in the context of virtual labs were studied though a very low correlation was observed between citations and Altmetrics Attention Score. Still, the overall percentage of publications with attention showed linear growth. Our work also highlights that virtual laboratory could play a significant role in achieving the United Nations Sustainable Development Goals, specifically SDG4-Quality Education, which largely remains under-addressed.

Alzheimer’s Disease Clinical Trial Research Adaptation Following COVID-19 Pandemic Onset: National Sample of Alzheimer’s Clinical Trial Consortium Sites

Background

The COVID-19 pandemic created challenges in clinical research operations that required immediate and lasting changes.

Ojbectives

The purpose of this study was to explore adaptations to clinical trial research due to COVID-19 and develop a theoretical framework of emergent strategies related to pandemic mitigation in a national network of Alzheimer’s disease clinical trial sites.

Design

This qualitative study used a grounded theory approach including semi-structured interviews, constant comparative methods, and multi-level, iterative coding.

Participants

Twenty-six member sites of the Alzheimer’s Clinical Trial Consortium participated with a total of 49 participants.

Results

Findings demonstrate processes of adaptation following COVID-19 onset including establishing safety as priority, focus on scientific preservation, accommodations (creating policies, leadership mindset, maintaining operations, and determining research procedures), and evaluation of changes throughout the course of the pandemic. Communication and maintaining integrity were vital throughout these processes.

Conclusion

Processes of accommodation among clinical research sites during the pandemic provide critical insights and direction for future clinical trials development and emergent methods in Alzheimer’s disease and other therapeutic areas.

Sensitivity of the Preclinical Alzheimer's Cognitive Composite (PACC), PACC5, and Repeatable Battery for Neuropsychological Status (RBANS) to Amyloid Status in Preclinical Alzheimer's Disease -Atabecestat Phase 2b/3 EARLY Clinical Trial

BACKGROUND

Cognitive composites commonly serve as primary outcomes in Alzheimer's disease (AD) secondary prevention trials.

OBJECTIVE

To evaluate the association between amyloid (Aβ) burden level (+/-) and performance on three separate composite endpoints: Preclinical Alzheimer's Cognitive Composite (PACC), PACC+Semantic Fluency (PACC5), and Repeatable Battery for Neuropsychological Status (RBANS).

DESIGN

Screening data from the randomized, double-blind, placebo-controlled, phase 2b/3 atabecestat EARLY study in preclinical AD participants were used in this analysis.

SETTING

The EARLY study was conducted at 143 centers across 14 countries.

PARTICIPANTS

3,569 cognitively unimpaired older adults (Clinical Dementia Rating of 0; aged 60-85 years) screened for inclusion in the EARLY study with Aβ status and at least PACC or RBANS at screening were included. Participants were categorized as those with non-pathological Aβ levels (Aβ-, n=2,824) and those with pathological Aβ levels (Aβ+, n=745) based on florbetapir uptake or levels of cerebrospinal fluid Aβ1-42.

MEASUREMENTS

Analysis of Covariance models controlling for age, sex, and education were used to examine the difference in PACC, PACC5, and RBANS between Aβ groups. Nonparametric bootstrap was used to compare sensitivity of composites to differentiate between Aβ status.

RESULTS

Of 3,569 participants, 2,116 were women (59%); 3,006 were Caucasian (84%); mean (SD) age was 68.98 (5.28) years. Aβ+ participants performed worse versus Aβ- participants on all cognitive composites though the magnitude of the Aβ effect was generally small. The Aβ+/- effect size for the PACC (Cohen's d=-0.15) was significantly greater than the RBANS (d=-0.097) while the PACC5 effect size (d=-0.139) was numerically larger than the RBANS. When examining subscores from the composites, memory tests (i.e., Free and Cued Selective Reminding Test, Figure Recall) and speed of processing (i.e., Digit-Symbol/Coding on the PACC/RBANS) exhibited the largest Aβ+/- effect sizes.

CONCLUSIONS

Cross-sectional relationships between Aβ and cognition among clinically unimpaired older adults are detectable on multi-domain cognitive composites but are relatively small in magnitude. The Aβ+/- group effect was statistically larger for PACC and marginally larger for PACC5 versus RBANS. However, interpretation of composite sensitivity to Aβ status cross-sectionally cannot be generalized to sensitivity to change over time.

Item-Level Investigation of Participant and Study Partner Report on the Cognitive Function Index from the A4 Study Screening Data

BACKGROUND

Greater subjective cognitive changes on the Cognitive Function Index (CFI) was previously found to be associated with elevated amyloid (Aß) status in participants screening for the A4 Study, reported by study partners and the participants themselves. While the total score on the CFI related to amyloid for both sources respectively, potential differences in the specific types of cognitive changes reported by either participants or their study partners was not investigated.

OBJECTIVES

To determine the specific types of subjective cognitive changes endorsed by participants and their study partners that are associated with amyloid status in individuals screening for an AD prevention trial.

DESIGN, SETTING, PARTICIPANTS

Four thousand four hundred and eighty-six cognitively unimpaired (CDR=0; MMSE 25-30) participants (ages 65-85) screening for the A4 Study completed florbetapir (Aß) Positron Emission Tomography (PET) imaging. Participants were classified as elevated amyloid (Aß+; n=1323) or non-elevated amyloid (Aß-; n=3163).

MEASUREMENTS

Prior to amyloid PET imaging, subjective report of changes in cognitive functioning were measured using the CFI (15 item questionnaire; Yes/Maybe/No response options) and administered separately to both participants and their study partners (i.e., a family member or friend in regular contact with the participant). The impact of demographic factors on CFI report was investigated. For each item of the CFI, the relationship between Aß and CFI response was investigated using an ordinal mixed effects model for participant and study partner report.

RESULTS

Independent of Aß status, participants were more likely to report 'Yes' or 'Maybe' compared to the study partners for nearly all CFI items. Older age (r= 0.06, p<0.001) and lower education (r=-0.08, p<0.001) of the participant were associated with higher CFI. Highest coincident odds ratios related to Aß+ for both respondents included items assessing whether 'a substantial decline in memory' had occurred in the last year (ORsp= 1.35 [95% CI 1.11, 1.63]; ORp= 1.55 [95% CI 1.34, 1.79]) and whether the participant had 'seen a doctor about memory' (ORsp= 1.56 [95% CI 1.25, 1.95]; ORp =1.71 [95% CI 1.37, 2.12]). For two items, associations were significant for only study partner report; whether the participant 'Repeats questions' (ORsp = 1.30 [95% CI 1.07, 1.57]) and has 'trouble following the news' (ORsp= 1.46[95% CI 1.12, 1.91]). One question was significant only for participant report; 'trouble driving' (ORp= 1.25 [95% CI 1.04, 1.49]).

CONCLUSIONS

Elevated Aβ is associated with greater reporting of subjective cognitive changes as measured by the CFI in this cognitively unimpaired population. While participants were more likely than study partners to endorse change on most CFI items, unique CFI items were associated with elevated Aß for participants and their study partners, supporting the value of both sources of information in clinical trials.

The Trial-Ready Cohort for Preclinical/Prodromal Alzheimer's Disease (TRC-PAD) Project: An Overview

The Trial-Ready Cohort for Preclinical/prodromal Alzheimer’s Disease (TRC-PAD) project is a collaborative effort to establish an efficient mechanism for recruiting participants into very early stage Alzheimer’s disease trials. Clinically normal and mildly symptomatic individuals are followed longitudinally in a web-based component called the Alzheimer’s Prevention Trial Webstudy (APT Webstudy), with quarterly assessment of cognition and subjective concerns. The Webstudy data is used to predict the likelihood of brain amyloid elevation; individuals at relatively high risk are invited for in-person assessment in the TRC screeing phase, during which a cognitive battery is administered and Apolipoprotein E genotype is obtained followed by reassessment of risk of amyloid elevation. After an initial validation study, plasma amyloid peptide ratios will be included in this risk assessment. Based on this second risk calculation, individuals may have amyloid testing by PET scan or lumbar puncture, with those potentially eligible for trials followed in the TRC, while the rest are invited to remain in the APT Webstudy. To date, over 30,000 individuals have participated in the Webstudy; enrollment in the TRC is in its early stage.

Viscosupplementation for the treatment of osteoarthritis. The contribution of EUROVISCO group

Viscosupplementation (VS) is a symptomatic treatment for knee and other joint osteoarthritis (OA). Despite a long history of use, conflicting opinions remain on the best clinical indications and the most appropriate patients to be treated with intra-articular hyaluronic acid (IA-HA), the optimal dosing regimen and the modalities of retreatment. A multidisciplinary committee of European experts on OA (EUROVISCO) was constituted to formulate recommendations, aimed at helping physicians in the decision-making and the optimal achievement of VS. Before each session members were tasked to collate an exhaustive literature review. Level of evidence and strength of recommendation were based on the level of agreement for each item according to the Delphi method. In 2015, a consensus position was proposed for 24 statements. Among those that obtained a consensual agreement, the working group stressed that VS is effective in mild/moderate knee OA but is not an alternative to surgery in advanced OA, and that dosing regimen must be supported by controlled trials. In 2018, two decision algorithms for the retreatment with IA-HA in knee OA were published. Among the key recommendations, the experts recommended to re-treat every year patients with high risk of OA progression, even if not symptomatic. In 2020, EUROVISCO published two sets of recommendations for the design of clinical trials on the disease-modifying effect of VS and for optimizing the results of VS. The working group underlined that an accurate analysis of radiological features and symptoms and a careful clinical examination may improve the chances of success of VS, as well as good technique of injection and the use of imaging guidance. Based on the exhaustive analysis of the literature and their own clinical experience, the EUROVISCO experts offer a wide range of recommendations intended to help practitioners, particularly in certain cases where the specific characteristics of the patients make the therapeutic decision difficult.

Intranasal Insulin Reduces White Matter Hyperintensity Progression in Association with Improvements in Cognition and CSF Biomarker Profiles in Mild Cognitive Impairment and Alzheimer's Disease

BACKGROUND

Intranasally administered insulin has shown promise in both rodent and human studies in Alzheimer's disease; however, both effects and mechanisms require elucidation.

OBJECTIVE

We assessed the effects of intranasally administered insulin on white matter health and its association with cognition and cerebral spinal fluid biomarker profiles in adults with mild cognitive impairment or Alzheimer's disease in secondary analyses from a prior phase 2 clinical trial (NCT01767909).

DESIGN

A randomized (1:1) double-blind clinical trial.

SETTING

Twelve sites across the United States.

PARTICIPANTS

Adults with mild cognitive impairment or Alzheimer's disease.

INTERVENTION

Participants received either twice daily placebo or insulin (20 IU Humulin R U-100 b.i.d.) intranasally for 12 months. Seventy-eight participants were screened, of whom 49 (32 men) were enrolled.

MEASUREMENTS

Changes from baseline in global and regional white matter hyperintensity volume and gray matter volume were analyzed and related to changes in cerebral spinal fluid biomarkers, Alzheimer's Disease Assessment Scale-Cognition, Clinical Disease Rating-Sum of Boxes, Alzheimer's Disease Cooperative Study-Activities of Daily Living Scale, and a memory composite.

RESULTS

The insulin-treated group demonstrated significantly reduced changes in white matter hyperintensity volume in deep and frontal regions after 12 months, with a similar trend for global volume. White matter hyperintensity volume progression correlated with worsened Alzheimer's disease cerebral spinal fluid biomarker profile and cognitive function; however, patterns of correlations differed by treatment group.

CONCLUSION

Intranasal insulin treatment for 12 months reduced white matter hyperintensity volume progression and supports insulin's potential as a therapeutic option for Alzheimer's disease.

The Institute on Methods and Protocols for Advancement of Clinical Trials in ADRD (IMPACT-AD): A Novel Clinical Trials Training Program

BACKGROUND

Alzheimer's Disease and Related Dementias (ADRD) clinical trials require multidisciplinary expertise in medicine, biostatistics, trial design, biomarkers, ethics, and informatics.

OBJECTIVES

To provide focused interactive training in ADRD clinical trials to a diverse cadre of investigators.

DESIGN

The Institute on Methods and Protocols for Advancement of Clinical Trials in ADRD (IMPACT-AD) is a novel multidisciplinary clinical trial training program funded by the National Institute on Aging and the Alzheimer's Association with two educational tracks. The Professionals track includes individuals who fill a broad variety of roles including clinicians, study coordinators, psychometricians, and other study professionals who wish to further their knowledge and advance their careers in ADRD trials. The Fellowship track includes current and future principal investigators and focuses on the design, conduct and analysis of ADRD clinical trials.

SETTING

The 2020 inaugural iteration of IMPACT-AD was held via Zoom.

PARTICIPANTS

Thirty-five trainees (15 Fellowship track; 20 Professionals track) were selected from 104 applications (34% acceptance rate). Most (n=25, 71%) identified as female. Fifteen (43%) were of a non-white race; six (18%) were of Hispanic ethnicity; eight (23%) indicated they were the first person in their family to attend college.

MEASUREMENTS

Participants completed daily evaluations as well as pre- and post-course assessments of learning.

RESULTS

Across topic areas, >90% of trainees evaluated their change in knowledge based on the lectures as "very much" or "somewhat increased." The mean proportion correct responses in pre- and post-course assessments increased from 55% to 75% for the Professionals track and from 54% to 78% for the Fellowship track.

CONCLUSIONS

IMPACT-AD successfully launched a new training opportunity amid a global pandemic that preliminarily achieved the goals of attracting a diverse cohort and providing meaningful training. The course is funded through 2025.

Adoption of online proctored examinations by university students during COVID-19: Innovation diffusion study

COVID-19 global pandemic pushed a large number of higher educational institutions to use Online Proctored Exams (OPE) because of government-imposed lockdowns. Treating OPE as an educational technology innovation, we apply the diffusion of innovation theory in predicting factors affecting its adoption by university students which we believe is the first of its kind research study. The study presented here reviews OPE, its types, architecture, challenges, and prospects and then focuses on the student adoption experience at a large, multi-campus higher educational institution. We have used the fine-grained Aspect Level Sentiment Analysis to check the university students' attitudes towards the Online Proctored Exams. We then used linguistic features to extract the aspect terms present in the feedback comments which showed that 55% of university students having a positive attitude towards OPE. Results of our study show that innovation characteristics such as relative advantage, compatibility, ease of use, trialability, and observability were found to be positively related to acceptance of OPE.

The Computerized Cognitive Composite (C3) in an Alzheimer's Disease Secondary Prevention Trial

BACKGROUND

Computerized cognitive assessments may improve Alzheimer's disease (AD) secondary prevention trial efficiency and accuracy. However, they require validation against standard outcomes and relevant biomarkers.

OBJECTIVE

To assess the feasibility and validity of the tablet-based Computerized Cognitive Composite (C3).

DESIGN

Cross-sectional analysis of cognitive screening data from the A4 study (Anti-Amyloid in Asymptomatic AD).

SETTING

Multi-center international study.

PARTICIPANTS

Clinically normal (CN) older adults (65-85; n=4486).

MEASUREMENTS

Participants underwent florbetapir-Positron Emission Tomography for Aβ+/- classification. They completed the C3 and standard paper and pencil measures included in the Preclinical Alzheimer's Cognitive Composite (PACC). The C3 combines memory measures sensitive to change over time (Cogstate Brief Battery-One Card Learning) and measures shown to be declining early in AD including pattern separation (Behavioral Pattern Separation Test- Object- Lure Discrimination Index) and associative memory (Face Name Associative Memory Exam- Face-Name Matching). C3 acceptability and completion rates were assessed using qualitative and quantitative methods. C3 performance was explored in relation to Aβ+/- groups (n=1323/3163) and PACC.

RESULTS

C3 was feasible for CN older adults to complete. Rates of incomplete or invalid administrations were extremely low, even in the bottom quartile of cognitive performers (PACC). C3 was moderately correlated with PACC (r=0.39). Aβ+ performed worse on C3 compared with Aβ- [unadjusted Cohen's d=-0.22 (95%CI: -0.31,-0.13) p<0.001] and at a magnitude comparable to the PACC [d=-0.32 (95%CI: -0.41,-0.23) p<0.001]. Better C3 performance was observed in younger, more educated, and female participants.

CONCLUSIONS

These findings provide support for both the feasibility and validity of C3 and computerized cognitive outcomes more generally in AD secondary prevention trials.

RF Sputtered MoO3 Thin Film on Si (100) for Gas Sensing Applications

Molybdenum Trioxide (MoO3) films are grown on Si(100) substrates by reactive RF magnetron sputtering in plasma containing a mixture of Argon and Oxygen, using a pure Molybdenum target. In this paper, we report the deposition of (MoO3) films on Si(100) substrates under varying gas flow (O2 + Ar gas) (20 sccm to 30 sccm with the duration of deposition~ 1hr) by RF reactive magnetron sputtering at room temperature. To get crystalline MoO3 films annealing in O2 environment at 500 °C for 4 h is done. Phase formation and orientation of the film is characterized by Glancing incidence X-ray diffraction (GIXRD). The identification of the orthorhombic MoO3 phase is investigated by XRD and Raman spectroscopy. Raman lines at 819 cm-1 and 995 cm-1 are due to the (A1g, B1g) symmetric stretching (Mo-O–Mo) bond and asymmetric stretching band (Mo=O) respectively. Surface morphology and cross-sectional image of the deposited thin films were investigated by FE-SEM image. UV-Visible reflectance and cross-sectional FE-SEM image confirm the thickness of the MoO3 films with oxygen-rich and oxygen deficient phase formation occur. Reverse leakage current density of 20 sccm 1hr sample is low (1×10-6 mA/cm2) as compared to 30 sccm 1hr sample (1×10-3 mA/cm2). The higher leakage is due to crack formation during the ex-situ annealing of MoO3 films. This MoO3 films can be used in Gas sensing and switching devices.

Authors response to D Umbricht, letter to the editor referring Futility Analyses in Alzheimer's Disease (AD) Clinical Trials: A Risky Business. The Journal of Prevention of Alzheimer's Disease, 2020

Dr. Umbricht suggests that the two examples we cite in our viewpoint (1) support rather than call into question the value of interim futility analyses in Alzheimer’s disease (AD) trials. He points out that the first example, the Phase 3 trials of aducanumab, the futility analyses did indeed indicate a trend toward a beneficial treatment effect in one of the two trials though the planned pooled futility decision led to stopping the trials. In the second case, in which a futility analysis led to a halt, full analysis of available data suggested efficacy; a subsequent study was negative.

Viewpoint: Futility Analyses in Alzheimer's Disease (AD) Clinical Trials: A Risky Business

In the standard, orderly progression of drug development trials, a moderately-sized Phase 2 trial demonstrates safety and efficacy of one or more doses of the investigational product, followed by large confirmatory Phase 3 trials of one or two doses leading to regulatory approval. The large and lengthy Phase 3 trials often include interim futility analyses using statistical methods to assess lack of benefit, so that programs “fail early” by identifying ineffective treatments early if evidence points toward lack of efficacy, in part to limit financial loss and redirect resources. For disease-modifying drug development programs in Alzheimer’s disease (AD), finding an optimal strategy is particularly challenging. A slowing of decline rather than symptomatic improvement indicates disease-modification, and primary outcomes for such trials are noisy and sometimes subjective. As a result, very large, lengthy trials are required to see efficacy signals, so Phase 2 trials may look like Phase 3 programs or Phase 3 trials may directly follow Phase 1 trials. In other words, enormous trials may be launched without sufficient evidence of preliminary efficacy of the doses studied, dramatically increasing the financial risk to sponsors. In such instances, futility analyses embedded in trials would seem to be particularly important.

The ORNATE India Project: United Kingdom-India Research Collaboration to tackle visual impairment due to diabetic retinopathy

INTRODUCTION

The ORNATE India project is funded by the UK Research and Innovation (UKRI) through the Global Challenges Research Fund. The aim is to build research capacity and capability in India and the UK to tackle global burden of diabetes-related visual impairment. As there are over 77 million people with diabetes in India, it is challenging to screen every person with diabetes annually for sight-threatening diabetic retinopathy (DR). Therefore, alternate safe approaches need to be developed so that those at-risk of visual impairment due to DR is identified promptly and treated.

METHODS

The project team utilised diverse global health strategies and research methods to co-design work packages to build research capacity and capability to ensure effective, affordable and efficient DR services are made available for the population. The strategies and methods employed included health system strengthening; implementation science; establishing care pathways; co-designing collaborative studies on affordable technologies, developing quality standards and guidelines to decrease variations in care; economic analysis; risk modelling and stratification. Five integrated work packages have been developed to deal with all aspects of DR care. These included implementation of a DR screening programme in the public health system in a district in Kerala, evaluating regional prevalence of diabetes and DR and assessing ideal tests for holistic screening for diabetes and its complications in 20 areas in India, utilising artificial intelligence on retinal images to facilitate DR screening, exploring biomarker and biosensor research to detect people at risk of diabetes complications, estimating cost of blindness in India and risk modelling to develop risk-based screening models for diabetes and its complications. A large collaborative network will be formed to propagate research, promote shared learning and bilateral exchanges between high- and middle-income countries to tackle diabetes-related blindness.

Non-Amyloid Approaches to Disease Modification for Alzheimer's Disease: An EU/US CTAD Task Force Report

While amyloid-targeting therapies continue to predominate in the Alzheimer’s disease (AD) drug development pipeline, there is increasing recognition that to effectively treat the disease it may be necessary to target other mechanisms and pathways as well. In December 2019, The EU/US CTAD Task Force discussed these alternative approaches to disease modification in AD, focusing on tau-targeting therapies, neurotrophin receptor modulation, anti-microbial strategies, and the innate immune response; as well as vascular approaches, aging, and non-pharmacological approaches such as lifestyle intervention strategies, photobiomodulation and neurostimulation. The Task Force proposed a general strategy to accelerate the development of alternative treatment approaches, which would include increased partnerships and collaborations, improved trial designs, and further exploration of combination therapy strategies.

It Is the Time to Think About a Treat-to-Target Strategy for Knee Osteoarthritis

Osteoarthritis (OA) is a rheumatic disease that affects the well-being of the patient, compromises physical and mental function, and affects other quality of life aspects. In the literature, several evidence-based guidelines and recommendations for the management of knee osteoarthritis (KOA) are available. These recommendations list the different therapeutic options rather than addressing a hierarchy between the treatments and defining the real target. Therefore, a question arises: are patients and physicians satisfied with the current management of KOA? Actually, the answer may be negative, thus suggesting a change in our therapeutic strategies. In this article, we address this challenge by suggesting that it is time to develop a “treat to target strategy” for KOA.

EUROVISCO Recommendations for Optimizing the Clinical Results of Viscosupplementation in Osteoarthritis

OBJECTIVES

The 3 aims of the work were to identify population subgroups that can benefit the most from viscosupplementation (VS), to provide recommendations on injection techniques, and to discuss VS appropriateness in clinical situations that are commonplace in daily practice.

METHODS

The task force members voted on their degree of agreement on 27 statements, 36 recommendations, and 22 clinical scenarios using a 9-point scale. The strength of agreement/appropriateness/recommendation (SOA/SOR) was classified as strong if the median agreement score was ≥8. The level of consensus (LOC) was also obtained.

RESULTS

Among the assumed predictors for VS failure, obesity, radiographic severity, large synovial fluid effusion, severe patellofemoral involvement, major malalignment, and gross joint instability received a large majority of agreements. The lateral mid-patellar approach was recommended for knee injection. Imaging guidance was unanimously recommended for hip and ankle. Agreement was achieved to strictly respect the dosing regimen proven by controlled trials. There was agreement for treating with VS patients with mild to moderate knee and hip OA, with normal weight or moderate overweight, insufficiently improved by first-line therapies, or who do not wish get oral treatment or who have contraindications to pain killers. The group considered the patient's wishes as a key element in therapeutic decision making.

CONCLUSION

Based on literature data and clinical experience, the EUROVISCO group proposed a set of recommendations for optimizing the results of VS, aimed to help practitioners, especially in some cases in which the patients' specificities make the therapeutic decision difficult.

The Trial-Ready Cohort for Preclinical and Prodromal Alzheimer's Disease (TRC-PAD): Experience from the First 3 Years

BACKGROUND:

The Trial-Ready Cohort for Preclinical and Prodromal Alzheimer’s disease (TRC-PAD) aims to accelerate enrollment for Alzheimer’s disease (AD) clinical trials by remotely identifying and tracking individuals who are at high risk for developing symptoms of AD, and referring these individuals to in-person cognitive and biomarker evaluation with the purpose of engaging them in clinical trials. A risk algorithm using statistical modeling to predict brain amyloidosis will be refined as TRC-PAD advances with a maturing data set.

OBJECTIVES:

To provide a summary of the steps taken to build this Trial-Ready cohort (TRC) and share results of the first 3 years of enrollment into the program.

DESIGN:

Participants are remotely enrolled in the Alzheimer Prevention Trials (APT) Webstudy with quarterly assessments, and through an algorithm identified as potentially at high risk, referred to clinical sites for biomarker confirmation, and enrolled into the TRC.

SETTING:

Both an online study and in-clinic non-interventional cohort study.

PARTICIPANTS:

APT Webstudy participants are aged 50 or older, with an interest in participation in AD therapeutic trials. TRC participants must have a study partner, stable medical condition, and elevated brain amyloid, as measured by amyloid positron emission tomography or cerebrospinal fluid analysis. Additional risk assessments include apolipoprotein E genotyping.

MEASUREMENTS:

In the APT Webstudy, participants complete the Cognitive Function Index and Cogstate Brief Battery. The TRC includes the Preclinical Alzheimer’s Cognitive Composite, comprised of the Free and Cued Selective Reminding Test, the Delayed Paragraph Recall score on the Logical Memory IIa test from the Wechsler Memory Scale, the Digit-Symbol Substitution test from the Wechsler Adult Intelligence Scale-Revised, and the Mini Mental State Examination total score (1).

RESULTS:

During the first 3 years of this program, the APT Webstudy has 30,650 consented participants, with 23 sites approved for in person screening, 112 participants have been referred for in-clinic screening visits with eighteen enrolled to the TRC. The majority of participants consented to APT Webstudy have a family history of AD (62%), identify as Caucasian (92.5%), have over twelve years of formal education (85%), and are women (73%). Follow up rates for the first quarterly assessment were 38.2% with 29.5% completing the follow up Cogstate Battery.

CONCLUSIONS:

After successfully designing and implementing this program, the study team’s priority is to improve diversity of participants both in the APT Webstudy and TRC, to continue enrollment into the TRC to our target of 2,000, and to improve longitudinal retention, while beginning the process of referring TRC participants into clinical trials.

Predicting Amyloid Burden to Accelerate Recruitment of Secondary Prevention Clinical Trials

BACKGROUND:

Screening to identify individuals with elevated brain amyloid (Aβ+) for clinical trials in Preclinical Alzheimer’s Disease (PAD), such as the Anti-Amyloid Treatment in Asymptomatic Alzheimer’s disease (A4) trial, is slow and costly. The Trial-Ready Cohort in Preclinical/Prodromal Alzheimer’s Disease (TRC-PAD) aims to accelerate and reduce costs of AD trial recruitment by maintaining a web-based registry of potential trial participants, and using predictive algorithms to assess their likelihood of suitability for PAD trials.

OBJECTIVES:

Here we describe how algorithms used to predict amyloid burden within TRC-PAD project were derived using screening data from the A4 trial.

DESIGN:

We apply machine learning techniques to predict amyloid positivity. Demographic variables, APOE genotype, and measures of cognition and function are considered as predictors. Model data were derived from the A4 trial.

SETTING:

TRC-PAD data are collected from web-based and in-person assessments and are used to predict the risk of elevated amyloid and assess eligibility for AD trials.

PARTICIPANTS:

Pre-randomization, cross-sectional data from the ongoing A4 trial are used to develop statistical models.

MEASUREMENTS:

Models use a range of cognitive tests and subjective memory assessments, along with demographic variables. Amyloid positivity in A4 was confirmed using positron emission tomography (PET).

RESULTS:

The A4 trial screened N=4,486 participants, of which N=1323 (29%) were classified as Aβ+ (SUVR ≥ 1.15). The Area under the Receiver Operating Characteristic curves for these models ranged from 0.60 (95% CI 0.56 to 0.64) for a web-based battery without APOE to 0.74 (95% CI 0.70 to 0.78) for an in-person battery. The number needed to screen to identify an Aβ+ individual is reduced from 3.39 in A4 to 2.62 in the remote setting without APOE, and 1.61 in the remote setting with APOE.

CONCLUSIONS:

Predictive algorithms in a web-based registry can improve the efficiency of screening in future secondary prevention trials. APOE status contributes most to predictive accuracy with cross-sectional data. Blood-based assays of amyloid will likely improve the prediction of amyloid PET positivity.

EUROVISCO Guidelines for the Design and Conduct of Clinical Trials Assessing the Disease-Modifying Effect of Knee Viscosupplementation

OBJECTIVES

Hyaluronic acid viscosupplementation is a commonly used intra-articular treatment for osteoarthritis (OA). Some recent preclinical and clinical trials have demonstrated a potential for its disease-modifying effects. The goal of this expert opinion, consensus-driven exercise is to provide guidelines for the design and conduct of clinical trials assessing the disease-modifying effect of viscosupplementation in the knee.

METHODS

The EUROVISCO group constitutes 10 members who had expertise in clinical research methodology in the field of OA and viscosupplementation. They initially drafted issues through an iterative process and had to vote on their degree of agreement on these recommendations. The scores were pooled to generate a median agreement score for each recommendation.

RESULTS

The document includes 31 recommendations regarding study population, imaging, clinical and biological assessment of disease-modifying effects of viscosupplementation. Agreements were reached on some recommendations. In particular, the experts reached unanimous agreement on double-blind study design, imaging primary outcomes, time interval between 2 radiographs, x-ray procedure standardization, and the combined use of imaging and biological markers. The group did not recommend the use of ultrasonography, computed tomography (CT) scan and CT arthrography as a tool for OA diagnosis or to assess progression over time.

CONCLUSION

In summary, the working group identified 31 recommendations that represent the current best practices regarding clinical trials that target the assessment of viscosupplementation disease-modifying effects in patients with knee OA. These recommendations integrate new imaging technologies and soluble biomarkers.

TRC-PAD: Accelerating Recruitment of AD Clinical Trials through Innovative Information Technology

BACKGROUND

The Trial-Ready Cohort for Preclinical/Prodromal Alzheimer's Disease (TRC-PAD) Informatics Platform (TRC-PAD IP) was developed to facilitate the efficient selection, recruitment, and assessment of study participants in support of the TRC-PAD program.

OBJECTIVES

Describe the innovative architecture, workflows, and components of the TRC-PAD IP.

DESIGN

The TRC-PAD IP was conceived as a secure, scalable, multi-tiered information management platform designed to facilitate high-throughput, cost-effective selection, recruitment, and assessment of TRC-PAD study participants and to develop a learning algorithm to select amyloid-bearing participants to participate in trials of early-stage Alzheimer's disease.

SETTING

TRC-PAD participants were evaluated using both web-based and in-person assessments to predict their risk of amyloid biomarker abnormalities and eligibility for preclinical and prodromal clinical trials. Participant data were integrated across multiple stages to inform the prediction of amyloid biomarker elevation.

PARTICIPANTS

TRC-PAD participants were age 50 and above, with an interest in participating in Alzheimer's research.

MEASUREMENTS

TRC-PAD participants' cognitive performance and subjective memory concerns were remotely assessed on a longitudinal basis to predict participant risk of biomarker abnormalities. Those participants determined to be at the highest risk were invited to an in-clinic screening visit for a full battery of clinical and cognitive assessments and amyloid biomarker confirmation using positron emission tomography (PET) or lumbar puncture (LP).

RESULTS

The TRC-PAD IP supported growth in recruitment, screening, and enrollment of TRC-PAD participants by leveraging a secure, scalable, cost-effective cloud-based information technology architecture.

CONCLUSIONS

The TRC-PAD program and its underlying information management infrastructure, TRC-PAD IP, have demonstrated feasibility concerning the program aims. The flexible and modular design of the TRC-PAD IP will accommodate the introduction of emerging diagnostic technologies.

Treat-to-target strategy for knee osteoarthritis. International technical expert panel consensus and good clinical practice statements

Background:

In this work, we aimed to establish a clinical target in the management of knee osteoarthritis (KOA) and to propose good clinical practice (GCP) statements for carrying out a treat-to-target strategy.

Methods:

A steering committee of seven experts had formulated a provisional set of recommendations that were exposed for discussion and modification to a technical expert panel (TEP) of 25 multidisciplinary experts from Europe, North America, South America and Asia. The level of evidence and strength of each recommendation was discussed. The TEP formulated overarching principles and GCP statements based on the level of agreement for each item with a vote using a 10-point numerical scale.

Results:

Two overarching principles and 10 GCP statements were formulated by the TEP. These GCP statements suggest: treatment should achieve clinical improvement bringing the patient to the Patient Acceptable Symptom State (PASS); pharmacological and nonpharmacological treatment should begin as early as possible, with an early diagnosis of symptomatic KOA; the patient should be evaluated every 3–6 months; risk factors of KOA progression should be identified and managed with patients at the beginning of the treatment and monitored regularly; treatment should be adapted according to patient phenotype and disease severity; healthy lifestyle must be promoted and monitored. The level of agreement average ranged from 8.7 to 9.6 on scale.

Conclusions:

The proposed overarching principles and GCP statements have the aim of involving patients, general practitioners and multidisciplinary specialists in sharing a therapeutic treat-to-target strategy for KOA management based on the best evidence and expert opinions.