Preprint Articles Research Articles

Predicting the Utility of Scientific Articles for Emerging Pandemics Using Their Titles and Natural Language Processing.

Not all scientific publications are equally useful to policy-makers tasked with mitigating the spread and impact of diseases, especially at the start of novel epidemics and pandemics. The urgent need for actionable, evidence-based information is paramount, but the nature of preprint and peer-reviewed articles published during these times is often at odds with such goals. For example, a lack of novel results and a focus on opinions rather than evidence were common in coronavirus disease (COVID-19) publications at the start of the pandemic in 2019. In this work, we seek to automatically judge the utility of these scientific articles, from a public health policy making persepctive, using only their titles. Deep learning natural language processing (NLP) models were trained on scientific COVID-19 publication titles from the CORD-19 dataset and evaluated against expert-curated COVID-19 evidence to measure their real-world feasibility at screening these scientific publications in an automated manner. This work demonstrates that it is possible to judge the utility of COVID-19 scientific articles, from a public health policy-making perspective, based on their title alone, using deep natural language processing (NLP) models. NLP models can be successfully trained on scienticic articles and used by public health experts to triage and filter the hundreds of new daily publications on novel diseases such as COVID-19 at the start of pandemics.

Real-world effectiveness of sotrovimab for the treatment of SARS-CoV-2 infection during Omicron BA.2 and BA.5 subvariant predominance: a systematic literature review

PurposeTo evaluate clinical outcomes associated with sotrovimab use during Omicron BA.2 and BA.5 predominance.MethodsElectronic databases were searched for observational studies published in peer-reviewed journals, preprint articles and conference abstracts from January 1, 2022 to February 27, 2023.ResultsThe 14 studies identified were heterogeneous in terms of study design, population, endpoints and definitions. They included > 1.7 million high-risk patients with COVID-19, of whom approximately 41,000 received sotrovimab (range n = 20–5979 during BA.2 and n = 76–1383 during BA.5 predominance). Four studies compared the effectiveness of sotrovimab with untreated or no monoclonal antibody treatment controls, two compared sotrovimab with other treatments, and three single-arm studies compared outcomes during BA.2 and/or BA.5 versus BA.1. Five studies descriptively reported rates of clinical outcomes in patients treated with sotrovimab. Rates of COVID-19-related hospitalization or mortality (0.95–4.0% during BA.2; 0.5–2.0% during BA.5) and all-cause mortality (1.7–2.0% during BA.2; 3.4% during combined BA.2 and BA.5 periods) among sotrovimab-treated patients were consistently low. During BA.2, a lower risk of all-cause hospitalization or mortality was reported across studies with sotrovimab versus untreated cohorts. Compared with other treatments, sotrovimab was associated with a lower (molnupiravir) or similar (nirmatrelvir/ritonavir) risk of COVID-19-related hospitalization or mortality during BA.2 and BA.5. There was no significant difference in outcomes between the BA.1, BA.2 and BA.5 periods.ConclusionsThis systematic literature review suggests continued effectiveness of sotrovimab in preventing severe clinical outcomes during BA.2 and BA.5 predominance, both against active/untreated comparators and compared with BA.1 predominance.

Clinical trials and their impact on policy during COVID-19: a review.

Of over 8,000 recorded randomised trials addressing COVID-19, around 80% were of treatments, and 17% have reported results. Approximately 1% were adaptive or platform trials, with 25 having results available, across 29 journal articles and 10 preprint articles. We conducted an extensive literature review to address four questions about COVID-19 trials, particularly the role and impact of platform/adaptive trials and lessons learned. The key findings were: Q1. Social value in conducting trials and uptake into policy? COVID-19 drug treatments varied substantially and changed considerably, with drugs found effective in definitive clinical trials replacing unproven drugs. Dexamethasone has likely saved ½-2 million lives, and was cost effective across a range of countries and populations, whereas the cost effectiveness of remdesivir is uncertain. Published economic and health system impacts of COVID-19 treatments were infrequent. Q2. Issues with adaptive trial designs. Of the 77 platform trials registered, 6 major platform trials, with approximately 50 treatment arms, recruited ~135,000 participants with funding over $100 million. Q3. Models of good practice. Streamlined set-up processes such as flexible and fast-track funding, ethics, and governance approvals are vital. To facilitate recruitment, simple and streamlined research processes, and pre-existing research networks to coordinate trial planning, design, conduct and practice change are crucial to success. Q4. Potential conflicts to avoid? When treating patients through trials, balancing individual and collective rights and allocating scarce resources between healthcare and research are challenging. Tensions occur between commercial and non-commercial sectors, and academic and public health interests, such as publication and funding driven indicators and the public good. There is a need to (i) reduce small, repetitive, single centre trials, (ii) increase coordination to ensure robust research conducted for treatments, and (iii) a wider adoption of adaptive/platform trial designs to respond to fast-evolving evidence landscape.

Nursing Care for the Elderly with Cancer in Palliative Care: Integrative Literature Review

Objective: To know the scientific evidence in the national literature on nursing care for the elderly with cancer in palliative care from 2011 to 2021.
 Methodology: Integrative Literature Review (INR) Study, using the following databases: SciELO, VHL and CAPES Periodicals. Articles published in Portuguese, English and Spanish were selected for this study; research available in full and online published between the years 2011 and 2021, in the areas of field research and excluding gray literature publications, editorials, letters to the editor, incomplete articles, reflective studies and studies that did not address the topic relevant to the objective of the study, published before the proposed period or pre-print articles. After this moment, the textual corpus was prepared with the conclusions of the articles selected in the final sample, for processing and analysis in the IRAMuTeQ® software.
 Results: 10 articles were selected to compose this Integrative Review, from the years 2020, 2018, 2011, 2011 and 2021. With 4 publications located in the CAPES database, 4 in the VHL and 2 in SciELO. The interpretation of the corpus generated the following classes: 1) Humanized care for the elderly with cancer in palliative and family care; 2) The importance of palliative care for the physical, spiritual and emotional well-being of the elderly; 3) Nursing interventions for the elderly in palliative care and terminality process.
 Conclusion: The nurse's assistance is indispensable in the execution of palliative care, being the professional responsible for guiding, recording and explaining the oncological process in which their patients are, and offering the improvement and relief of their health condition.

Comparison of effect estimates between preprints and peer-reviewed journal articles of COVID-19 trials

BackgroundPreprints are increasingly used to disseminate research results, providing multiple sources of information for the same study. We assessed the consistency in effect estimates between preprint and subsequent journal article of COVID-19 randomized controlled trials.MethodsThe study utilized data from the COVID-NMA living systematic review of pharmacological treatments for COVID-19 (covid-nma.com) up to July 20, 2022. We identified randomized controlled trials (RCTs) evaluating pharmacological treatments vs. standard of care/placebo for patients with COVID-19 that were originally posted as preprints and subsequently published as journal articles. Trials that did not report the same analysis in both documents were excluded. Data were extracted independently by pairs of researchers with consensus to resolve disagreements. Effect estimates extracted from the first preprint were compared to effect estimates from the journal article.ResultsThe search identified 135 RCTs originally posted as a preprint and subsequently published as a journal article. We excluded 26 RCTs that did not meet the eligibility criteria, of which 13 RCTs reported an interim analysis in the preprint and a final analysis in the journal article. Overall, 109 preprint–article RCTs were included in the analysis. The median (interquartile range) delay between preprint and journal article was 121 (73–187) days, the median sample size was 150 (71–464) participants, 76% of RCTs had been prospectively registered, 60% received industry or mixed funding, 72% were multicentric trials. The overall risk of bias was rated as ‘some concern’ for 80% of RCTs. We found that 81 preprint–article pairs of RCTs were consistent for all outcomes reported. There were nine RCTs with at least one outcome with a discrepancy in the number of participants with outcome events or the number of participants analyzed, which yielded a minor change in the estimate of the effect. Furthermore, six RCTs had at least one outcome missing in the journal article and 14 RCTs had at least one outcome added in the journal article compared to the preprint. There was a change in the direction of effect in one RCT. No changes in statistical significance or conclusions were found.ConclusionsEffect estimates were generally consistent between COVID-19 preprints and subsequent journal articles. The main results and interpretation did not change in any trial. Nevertheless, some outcomes were added and deleted in some journal articles.

Full publication of preprint articles in prevention research: an analysis of publication proportions and results consistency

There is concern that preprint articles will lead to an increase in the amount of scientifically invalid work available. The objectives of this study were to determine the proportion of prevention preprints published within 12 months, the consistency of the effect estimates and conclusions between preprint and published articles, and the reasons for the nonpublication of preprints. Of the 329 prevention preprints that met our eligibility criteria, almost half (48.9%) were published in a peer-reviewed journal within 12 months of being posted. While 16.8% published preprints showed some change in the magnitude of the primary outcome effect estimate, 4.4% were classified as having a major change. The style or wording of the conclusion changed in 42.2%, the content in 3.1%. Preprints on chemoprevention, with a cross-sectional design, and with public and noncommercial funding had the highest probabilities of publication. The main reasons for the nonpublication of preprints were journal rejection or lack of time. The reliability of preprint articles for evidence-based decision-making is questionable. Less than half of the preprint articles on prevention research are published in a peer-reviewed journal within 12 months, and significant changes in effect sizes and/or conclusions are still possible during the peer-review process.

Diabetes Research and Resource Sharing During the COVID-19 Pandemic: A Systematic Review and Experience from an Academic/Non-profit Resource Website.

The magnitude of the response of the diabetes professional community to the COVID-19 pandemic is not known. We aimed to examine diabetes technology research trends and resources offered by professional organizations during this period. We explored patterns of the response from the professional diabetes community to the pandemic by (1) systematically searching for articles related to diabetes, COVID-19, and diabetes technologies; (2) examining publication trends of research protocols (clinicaltrials.gov) and preprints (medRxiv); and (3) reviewing online resources from professional organizations including our website (COVIDinDiabetes.org; an Emory University-Diabetes Technology Society collaboration). We identified 492 articles published between December 2019 and December 2022 meeting our inclusion criteria. Telemedicine and continuous glucose monitoring were the most common reported technologies from most parts of the world. The largest number of preprint articles was published in 2020, with a decline in 2021 and 2022. The number of research protocols related to COVID-19 was the highest in 2020 and declined in 2021 and 2022. Resources from organizations included protocols adapted to treat patients with diabetes and COVID-19, training programs, emergency preparedness, and literature on diabetes and COVID-19. On our website (COVIDinDiabetes.org), there were 12 236 visits and 18 149 pageviews, with 1.6 actions per visits, with most visits coming from North America (N = 7233, 54.2%), South America (N = 2663, 21.8%), and Europe (N = 1219). We conclude that the COVID-19 pandemic promoted unprecedented global research productivity related to diabetes and COVID-19 and that the transition to the use of technology resources has been evident during this period.

Comparison of COVID-19 Preprint and Peer-Reviewed Versions of Studies on Therapies for Critically Ill Patients.

Significant increases in the volume of preprint articles due to the COVID-19 pandemic, we examined the reliability of preprint articles compared to their peer-reviewed publications. Preprint articles evaluating experimental studies of select treatment options (anticoagulation, dexamethasone, hydroxychloroquine, remdesivir, and tocilizumab) for COVID-19 in the critically ill, available in a peer-reviewed publication were screened for inclusion within Altmetric (n = 2040). A total of 40 articles met inclusion criteria, with 21 being randomly selected for evaluation. The primary outcome of this evaluation was a change in a study's reported primary outcome or statistical significance between preprint and peer-reviewed articles. Secondary outcomes included changes in primary/secondary outcome effect size and change in study conclusion. One article (4.8%, 95% CI 0.12%-23.8%) had a change in the primary outcome. Seven articles (33.3%, 95% CI 14.6%-57.0%) had a change in the primary outcome's effect measure. Five studies (23.8%, 95% CI 8.2%-47.2%) had changes in statistical significance of at least one secondary outcome. Four studies (19.0%, 95% CI 5.4%-41.9%) had a change in study conclusion. In preprint articles of COVID-19 treatments, the provided primary outcome is generally reliable, while interpretation of secondary outcomes should be made with caution, while awaiting completion of the peer-review process.

Metformin for treatment of Covid-19: evidence from randomized trials

Background: Many observational studies suggest a possible benefit of metformin in treatment of severe coronavirus disease 2019 (Covid-19), but evidence from randomized trials is limited. Objective: To evaluate the therapeutic role of metformin in Covid-19 based on randomized trials. Methods: PubMed review until May 12, 2023. Key words are Covid-19, metformin, long Covid, mortality. Randomized trials, retrospective studies, pre-print articles, and meta-analyses are included.

Preprint of Obstetrics and Gynecology Articles During and After the COVID-19 Pandemic

: In this report, a brief historical overview of preprints focuses on the impact of the COVID-19 pandemic on the distribution of preprints in obstetrics and gynecology, and the benefits and drawbacks of preprints are described. Preprints are manuscripts that are published before peer review. They are widely available even though they are recent in biomedical science. The COVID-19 pandemic enhanced the number of preprints prominently. It is known that 5% of all preprint articles issued during the pandemic were in obstetrics and gynecology. Some benefits include the increased pace of being available and the exposure rate. Also, it provides an opportunity to check for plagiarism and prevent malpractice earlier. Challenges to the distribution of preprints also exist, such as the potential lack of quality, premature data, and the possibility of misguiding normal people. Given the high importance of data release in obstetrics and gynecology, both the authors and the publishers should regulate strict yet rational guidelines before letting the information become widely accessible.

Medical misinformation: A primer and recommendations for pharmacists

AbstractMedical misinformation is more pervasive today because of widespread and near instantaneous dissemination of information via the internet and social media platforms. Consequences of medical misinformation may include decreased uptake of needed health care resources, delays in seeking care, vaccine hesitancy, medication non‐compliance, increased disease outbreaks and/or burden, and increased hospitalization and mortality. It disproportionately impacts underserved populations, including Black patients, those who identify as LGBTQ+ (lesbian, gay, bisexual, transgender, queer, and more), and patients with reduced health literacy skills or who are digitally disadvantaged. Medical misinformation challenges health care professionals not only to provide the best care possible, but to assist patients in finding accurate information. Preprint publications, although potentially beneficial in rapidly disseminating new scientific discoveries, often have not undergone peer review and may contribute to the widespread propagation of inaccurate or overstated results, thereby perpetuating the spread of medical misinformation when it exists. The coronavirus disease 2019 (COVID‐19) pandemic highlighted the importance of practicing evidence‐based medicine and the need for cautious review of preprint publications and articles from predatory publishers in addition to usual and customary literature evaluation techniques. Everyone plays a role in preventing the spread of medical misinformation, with pharmacists uniquely positioned as trusted and highly accessible professionals who may help combat its spread. The goal of this article is to define medical misinformation and related terms, outline mechanisms by which it is spread, describe its clinical impact, highlight how it disproportionately impacts underserved populations, provide actionable strategies to prevent its spread, and give examples of practical tactics to help identify, correct, and alert individuals about the possible presence of medical misinformation.

Neonatal outcomes and indirect consequences following maternal SARS-CoV-2 infection in pregnancy: a systematic review

ObjectivesTo identify the association between maternal SARS-CoV-2 infection in pregnancy and individual neonatal morbidities and outcomes, particularly longer-term outcomes such as neurodevelopment.DesignSystematic review of outcomes of neonates born to pregnant...

Comparison of Preprint Postings of Randomized Clinical Trials on COVID-19 and Corresponding Published Journal Articles

Randomized clinical trials (RCTs) on COVID-19 are increasingly being posted as preprints before publication in a scientific, peer-reviewed journal. To assess time to journal publication for COVID-19 RCT preprints and to compare differences between pairs of preprints and corresponding journal articles. This systematic review used a meta-epidemiologic approach to conduct a literature search using the World Health Organization COVID-19 database and Embase to identify preprints published between January 1 and December 31, 2021. This review included RCTs with human participants and research questions regarding the treatment or prevention of COVID-19. For each preprint, a literature search was done to locate the corresponding journal article. Two independent reviewers read the full text, extracted data, and assessed risk of bias using the Cochrane Risk of Bias 2 tool. Time to publication was analyzed using a Cox proportional hazards regression model. Differences between preprint and journal article pairs in terms of outcomes, analyses, results, or conclusions were described. Statistical analysis was performed on October 17, 2022. This study included 152 preprints. As of October 1, 2022, 119 of 152 preprints (78.3%) had been published in journals. The median time to publication was 186 days (range, 17-407 days). In a multivariable model, larger sample size and low risk of bias were associated with journal publication. With a sample size of less than 200 as the reference, sample sizes of 201 to 1000 and greater than 1000 had hazard ratios (HRs) of 1.23 (95% CI, 0.80-1.91) and 2.19 (95% CI, 1.36-3.53) for publication, respectively. With high risk of bias as the reference, medium-risk articles with some concerns for bias had an HR of 1.77 (95% CI, 1.02-3.09); those with a low risk of bias had an HR of 3.01 (95% CI, 1.71-5.30). Of the 119 published preprints, there were differences in terms of outcomes, analyses, results, or conclusions in 65 studies (54.6%). The main conclusion in the preprint contradicted the conclusion in the journal article for 2 studies (1.7%). These findings suggest that there is a substantial time lag from preprint posting to journal publication. Preprints with smaller sample sizes and high risk of bias were less likely to be published. Finally, although differences in terms of outcomes, analyses, results, or conclusions were observed for preprint and journal article pairs in most studies, the main conclusion remained consistent for the majority of studies.

Ti, F Codoped Sodium Manganate of Layered P2-Na 0.7 MnO 2.05 Cathode for High Capacity and Long-Life Sodium-Ion Battery

Ti, F Codoped Sodium Manganate of Layered P2-Na _0.7 MnO _2.05 Cathode for High Capacity and Long-Life Sodium-Ion Battery

Happy 25th Anniversary, EurJOC!

Happy 25th Anniversary, EurJOC!

Prevalence of long COVID-19 among healthcare workers: a systematic review and meta-analysis protocol

IntroductionA proportion of those who survive the acute phase of COVID-19 experience prolonged symptoms, commonly known as long COVID-19. Given that healthcare workers (HCWs) face an elevated risk of acute...

Three out of four published systematic reviews on COVID-19 treatments were not registered and one-third of those registered were published: a meta-research study

ObjectivesThe aim of this study is to describe (1) registered and (2) published systematic reviews (SRs) on COVID-19 treatments, and to analyze (3) the proportion of publications among registered SRs and (4) the proportion of registrations among published SRs. Study Design and SettingThis meta-research study (CRD42021240423) is part of CEOsys (http://www.covid-evidenz.de/). Two reviewers identified protocols in PROSPERO (registered January 2020 to September 2020) and SRs published as preprint or peer-reviewed article in L·OVE (Living OVerview of the Evidence) COVID-19 (by May 2021). SRs of all types assessing COVID-19 treatments in humans were included. ResultsWe included 239 PROSPERO protocols and 346 SRs published in L·OVE. In both samples, the affiliation of the corresponding author with an Asian institution, standard SR as review type, and meta-analysis as synthesis method were the most frequent characteristics. Living SRs made up ≤10%. A total of 71 of 239 (29.7%) PROSPERO protocols were published as SR by February 2022, that is, after at least 17 months of follow-up (25 of 71 as preprints, 35.2%). In L·OVE, 261 of 346 (75.4%) SRs published by May 2021 were not registered in PROSPERO. ConclusionOverall, one-third PROSPERO protocols were published and three-fourth published SRs were not registered. We strongly encourage authors to register and publish their SRs promptly to reduce research waste and to allocate resources efficiently during the pandemic and beyond.

O031 Machine learning models in renal transplantation: a systematic review and meta-analysis of predictive performance in graft outcomes

Abstract Introduction Kidney transplantation (KT) is currently the renal replacement therapy of choice for most patients with end-stage kidney disease. Despite many advancements, the variations in outcome and frequent occurrence of graft failure continue to pose important clinical and research challenges. The aim of this study was to carry out a systematic review of the current application of Machine Learning (ML) models in KT and perform a meta-analysis of these models in the prediction of graft outcomes. Methods This review was registered with the PROSPERO database (CRD42021247469) and all peer reviewed and preprint original articles that reported the sensitivity and specificity of AI-based models were included in the meta-analysis. Data were analysed using MetaDTA,,an interactive online software for meta-analysis of diagnostic studies. The diagnostic performance of the meta-analysis was assessed by a summary receiver operating characteristics (sROC) plot. Results 38 studies met the inclusion criteria for the review and 12 studies met the inclusion criteria for the meta-analysis. The most common models used were artificial neural networks, decision trees and Bayesian belief networks. Seven studies compared the predictive performance of ML models with traditional regression methods. The summary sensitivity and specificity of ML-based models were 0.84 (95% CI, 0.72–0.91) and 0.68 (95% CI, 0.57–0.77), respectively. The area under the SROC for all the available evidence was 0.83. The Diagnostic Odds Ratio of ML models was 11.19 (95% CI 6.66–18.75). Conclusion Our study shows that ML models can accurately predict outcomes following KT by the integration of the vast amounts of available clinical data. Take-home message This study confirms the superior ability of ML Models in handling complex relationships between large datasets, features and outcomes, which has definitely led to improved precision and accuracy of outcomes.

COVID-19 vaccination for children aged 5–11 years

COVID-19 vaccination for children aged 5–11 years

Increased Risk of New-Onset Diabetes after Recovery from COVID-19

Background: Several studies reported increased incidence of diabetes in individuals who recovered from coronavirus disease 2019 (COVID-19) caused by acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Objective: To determine risk, characteristics and potential mechanisms of new-onset diabetes in patients who recovered from COVID-19. Methods: PubMed search up to May 26, 2022. Search terms are diabetes, hyperglycemia, SARS-CoV-2, COVID-19, cytokines, glucocorticoids. Cohort retrospective studies, pertinent in-vitro studies, pre-print and review articles are included. Results: Large retrospective cohort studies have consistently shown increased risk of diabetes, mainly type 2, during a follow-up period of approximately 6-18 months after recovery from acute COVID-19. One cohort study also showed increased risk of diabetes (94% of cases were type 1 and type 2 diabetes) among pediatric population in the post COVID-19 period. Increased risk of incident diabetes occurred in non-hospitalized and hospitalized patients with COVID-19, with gradual incremental risk occurring in parallel to the severity of COVID-19. The largest cohort study has shown that older age, black race, higher body mass index (BMI), presence of cardiovascular disease, hypertension, and pre-diabetes further increased incident type 2 diabetes after COVID-19. Risk of new-onset diabetes after COVID-19 infection was greater than those following respiratory infections unrelated to COVID-19. Mechanisms of development of diabetes in the post-COVID-19 duration are unclear and likely multifactorial. Persistence of altered cytokines after apparent clinical cure of COVID-19 might worsen insulin resistance. In addition, direct invasion of pancreatic β-cells by SARS-CoV-2 could be among the underlying mechanisms. Conclusions: New-onset type 2 diabetes may be one of the sequelae of COVID-19 infection. Physicians and patients should be aware about the possible occurrence of this complication for early diagnosis and treatment.