Midlife and old-age cardiovascular risk factors, educational attainment, and cognition at 90-years – population-based study with 48-years of follow-up

by Anni Varjonen, Toni Saari, Sari Aaltonen, Teemu Palviainen, Mia Urjansson, Paula Iso-Markku, Jaakko Kaprio, Eero Vuoksimaa

We examined the associations of midlife and old-age cardiovascular risk factors, education, and midlife dementia risk scores with cognition at 90 + years, using data from a population-based study with 48 years of follow-up. Participants were 96 individuals aged 90–97 from the older Finnish Twin Cohort study. Individual cardiovascular risk factors assessed via questionnaires in 1975, 1981, 1990, and 2021–2023 included blood pressure, body mass index, physical activity, and cholesterol, and self-reported educational attainment. The Cardiovascular Risk Factors, Aging, and Dementia (CAIDE) score and an educational-occupational attainment score were used as midlife dementia risk scores. Cognitive assessments included semantic fluency, immediate and delayed recall from a 10-word list learning task, and a composite cognitive score. Regression analyses were conducted with dementia risk factors predicting cognition at 90 + years, adjusting for age, sex, education, follow-up time, and apolipoprotein E genotype (ε4-carrier vs non-carriers). Results showed that higher education and higher educational-occupational score were associated with better cognitive performance in all cognitive measures. Those with high midlife blood pressure scored significantly higher in all cognitive tests than those with normal blood pressure. Conversely, those with high old-age blood pressure scored lower in semantic fluency and composite cognitive score, but not in immediate or delayed recall. Other cardiovascular risk factors and the CAIDE score did not show consistent associations with cognition. Education appears to have a long-lasting protective effect in cognitive aging, whereas midlife and old-age cardiovascular risk factors were not significantly associated with cognition at 90 + years.

Mapping unconventional <i>Leishmania</i> in human and animal leishmaniasis: A scoping review protocol on pathogen diversity, geographic distribution and knowledge gaps

by Denis Sereno, Tahar Kernif, Renato Leon, Kholoud Kahime, Souad Guernaoui, Chaymaa Harkat, Mario J. Grijalva, Omar Hamarsheh, Anita G. Villacis, Bachir Medrouh, Thiago Vasconcelos Dos Santos, Razika Beniklef, Naouel Eddaikra, Phlippe Holzmuller

Introduction

Leishmaniases are a vector-borne parasitic diseases with diverse clinical manifestations involving multiple Leishmania species and animal hosts. While most leishmaniasis cases are caused by a few well characterized Leishmania species, reports describe infections by unconventional or emerging Leishmania taxa, atypical clinical presentations from classical species, and occurrences of atypical Leishmania in animal hosts. These underrecognized infections present diagnostic and therapeutic challenges and are rarely reflected in surveillance systems or clinical guidelines. A systematic mapping of this evolving landscape is needed to guide future diagnostics, policy, and research priorities.

Methods and analysis

Following the Joanna Briggs Institute (JBI) methodology and PRISMA-ScR guidelines, we will search PubMed, Embase, Cochrane Library (CENTRAL), PROSPERO, Web of Science, and Global Index Medicus, as well as relevant grey literature. Eligible studies will include human cases with clinical presentations that diverge from those typically associated with well-characterized Leishmania species, reports involving unconventional or emerging Leishmania species, and animal cases of veterinary relevance caused by non-classical species, regardless of study design. Dual independent screening of records and data extraction using a standardized charting form will be conducted. Discrepancies between reviewers will be resolved by consensus. Data will be summarized descriptively through tables, figures, and thematic synthesis. Research gaps will be identified to inform future studies and public health strategies.

Dissemination

This review will use data from published sources and findings will be disseminated through publication in a peer-reviewed journal, presentations at scientific conferences, and sharing with relevant stakeholders. The results are intended to inform clinicians, researchers, and policymakers about the evolving landscape of leishmaniasis and to highlight priorities for future research and surveillance.

Measurement properties of instruments used to measure health-related quality of life in pediatric and adults patients with inherited epidermolysis bullosa: A systematic review and meta-analysis protocol

by Mario Gómez-Martínez, Greta Arias-Merino, Juan Benito-Lozano, Ana Villaverde-Hueso, Renata Linertová, Verónica Alonso-Ferreira

Inherited Epidermolysis Bullosa (EB) is a group of rare, genetic skin diseases characterized by extreme fragility of the skin and mucous membranes, leading to blistering and wounds in response to minimal trauma or friction. These clinical manifestations significantly reduce health-related quality of life (HRQoL). The objective of this protocol article is to provide information about the methods planned to be used to assess the measurement properties of HRQoL instruments specifically developed for EB patients of all age groups through a systematic review and meta-analysis. The protocol followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses Protocols (PRISMA-P) guideline. The literature search will be conducted in PubMed, Web of Science (WOS) and EMBASE, including terminology that aligns with the four key elements of the COSMIN (COnsensus-based Standards for the selection of health Measurement INstruments) research question (construct, target population, measurement properties and type of PROM), as well as the terminology proposed by COSMIN for measurement properties. Studies that include information on measurement properties (specifically, validity and/or reliability) with a sample of patients with inherited EB will be selected. Both title and abstract screening and full text review, will be conducted by two independent reviewers using the Rayyan tool. In addition, the risk of bias will be assessed using the COSMIN-Risk of Bias checklist. The data from each study and each measurement property will be summarized in accordance with the COSMIN guidelines. The evidence gathered will strive to adjudicate data on measurements properties of HRQoL instruments used in EB patients, and the limitations of the future systematic review will be discussed. Ultimately, results of the future systematic review will help develop more personalized guidelines for the assessment of HRQoL in EB patients of all age groups. The protocol is registered in OSF with registration number vrm87: https://osf.io/vrm87/

Factors associated with prolonged hospitalizations for COVID-19 during the first three waves of the pandemic: Evidence from a Southeastern State of Brazil

by Juliana Rodrigues Tovar Garbin, Franciéle Marabotti Costa Leite, Ana Paula Brioschi dos Santos, Larissa Soares Dell’Antonio, Cristiano Soares da Silva Dell’Antonio, Luís Carlos Lopes-Júnior

A comprehensive understanding of the factors influencing the epidemiological dynamics of COVID-19 across the pandemic waves—particularly in terms of disease severity and mortality—is critical for optimizing healthcare services and prioritizing high-risk populations. Here we aim to analyze the factors associated with short-term and prolonged hospitalization for COVID-19 during the first three pandemic waves. We conducted a retrospective observational study using data from individuals reported in the e-SUS-VS system who were hospitalized for COVID-19 in a state in a southeast state of Brazil. Hospitalization duration was classified as short or prolonged based on a 7-day cutoff, corresponding to the median length of hospital stay during the second pandemic wave. Bivariate analyses were performed using the chi-square test for heterogeneity. Logistic regression models were used to estimate odds ratios (ORs) and their respective 95% confidence intervals (CIs), with statistical significance set at 5%. When analyzing hospitalization duration across the three waves, we found that 51.1% (95%CI: 49.3–53) of hospitalizations in the first wave were prolonged. In contrast, short-duration hospitalizations predominated in the second (54.7%; 95% CI: 52.4–57.0) and third (51.7%; 95% CI: 50.2–53.2) waves. Factors associated with prolonged hospitalization varied by wave. During the first wave, older adults (≥60 years) (OR=1.67; 95%CI: 1.35–2.06), individuals with ≥10 symptoms (OR=2.03; 95%CI: 1.04–3.94), obese individuals (OR=2.0; 95%CI: 1.53–2.74), and those with ≥2 comorbidities (OR=2.22; 95%CI: 1.71–2.89) were more likely to experience prolonged hospitalization. In the second wave, he likelihood of extended hospital stays was higher among individuals aged ≥60 years (OR=2.04; 95%CI: 1.58–2.62) and those with ≥2 comorbidities (OR=1.77; 95%CI: 1.29–2.41). In the third wave, prolonged hospitalization was more frequent among older adults (OR=1.89; 95%CI: 1.65–2.17,), individuals with 5–9 symptoms (OR=1.52; 95%CI: 1.20–1.92), obese individuals (OR=2.2; 95%CI: 1.78–2.73), and those with comorbidities (OR=1.45; 95%CI: 1.22–1.72 and OR=2.0; 95%CI: 1.69–2.45). In conclusion, we identified variations in hospitalization patterns across the pandemic waves, although the differences were relatively subtle. These variations likely reflect gradual shifts in the risk factors associated with prolonged hospital stays. Our findings highlight t the importance of implementing targeted public health interventions, particularly those designed to reduce disease severity and improve clinical outcomes among vulnerable populations at greater risk of extended hospitalization.

<i>In vivo</i> study of the radioadaptive response and low-dose hyper-radiosensitivity for chromosome breaks induced by gamma rays in wild-type <i>Drosophila melanogaster</i> larval neuroblasts: Dose and dose rate dependence

by Claudia Di Dio, Antonella Porrazzo, Alex De Gregorio, Patrizia Morciano, Maria Antonella Tabocchini, Giovanni Cenci, Francesca Cipressa, Giuseppe Esposito

Although the biological effects of low doses/dose rates of ionising radiation have been extensively studied both in vitro and in vivo, there are still knowledge gaps to be filled. For example, the mechanisms underlying the phenomena of radioadaptive responses and hypersensitivity to low doses of radiation are still not fully understood. This study aims to investigate the phenomenon of radioadaptive response in Drosophila melanogaster larval neuroblasts, focusing on the influence of different gamma priming doses and priming dose rates. We examined the modulation of cytogenetic damage, specifically the frequency of chromosome breaks, induced by a challenging dose of 10 Gy following different priming doses (0–2.7 Gy) delivered at dose rates ranging from 1.4 to 17 mGy/h. Our findings reveal the presence of a distinct window in which radioadaptive responses occurs, notably above a certain threshold dose when delivered at a rate of 1.4 mGy/h. Consistently with our previous results, we confirmed that the maximal protection was observed at a priming dose of 0.4 Gy delivered at 2.5 mGy/h. Additionally, we studied the occurrence of chromosome breaks after irradiating larval neuroblasts at doses ranging from 0.7 to 10 Gy. Notably, in this case we observed a low-dose hyper-radiosensitivity phenomenon up to 2.7 Gy, followed by increased resistance above 2.7 Gy. Our results provide insight into the complex cellular responses to low-dose/dose rate radiation and have implications in various fields, including radiation protection, diagnostics, theragnostics and biodosimetry.

The assessment of physiotherapy practice is a robust measure of entry-level physiotherapy standards: Reliability and validity evidence from a large, representative sample

by Alan Reubenson, Leo Ng, Vidya Lawton, Irmina Nahon, Rebecca Terry, Claire Baldwin, Julia Blackford, Alex Bond, Rosemary Corrigan, Megan Dalton, Amabile Borges Dario, Michael Donovan, Ruth Dunwoodie, Genevieve M. Dwyer, Roma Forbes, Alison Francis-Cracknell, Janelle Gill, Andrea Hams, Anne Jones, Taryn Jones, Belinda Judd, Ewan Kennedy, Prue Morgan, Tanya Palmer, Casey Peiris, Carolyn Taylor, Debra Virtue, Cherie Zischke, Daniel F. Gucciardi, on behalf of the Physiotherapy Clinical Education Research Collaborative (PCERC)

The Assessment of Physiotherapy Practice (APP) is a 20-item assessment instrument used to assess entry-level physiotherapy practice in Australia, New Zealand and other international locations. Initial APP reliability and validity evidence supported a unidimensional or single latent factor as the best representation of entry-level physiotherapy practice performance. However, there remains inconsistency in how the APP is interpreted and operationalised across Australian and New Zealand universities offering entry-level physiotherapy programs. In essence, the presumption that the psychometric integrity of the APP generalises across people, time, and contexts remains largely untested. This multi-site, archival replication study utilised APP assessment data from 8,979 clinical placement assessments, across 19 Australian and New Zealand universities, graduating entry-level physiotherapy students (n=1865) in 2019. Structural representation of APP scores were examined via confirmatory factor analysis and penalised structural equation models. Factor analyses indicated a 2-factor representation, with four items (1–4) for the professional dimension and 16 items (5–20) for the clinical dimension, is the best approximation of entry-level physiotherapy performance. Measurement invariance analyses supported the robustness of this 2-factor representation over time and across diverse practice areas in both penultimate and final years of study. The findings provide strong evidence for the psychometric integrity of the APP, and the 2-factor alternative interpretation and operationalisation is recommended. To meet entry-level standards students should be assessed as competent across both professional and clinical dimensions of physiotherapy practice.

Protein hydrolysates from fish wastes: nutritional characteristics and its inclusion in diets for <i>Octopus maya</i>

by Honorio Cruz-López, Cristina Pascual, Magalli Sanchez, Pedro Domingues, Carlos Rosas, Pedro Gallardo

The utilization of fish waste protein as an alternative to crab and squid protein presents an important alternative for octopus fattening. During this study, nutritional characteristics of fish protein hydrolysate (FPH) and its inclusion in prepared diets were evaluated on growth performance and enzyme activity of digestive gland of O. maya juveniles. FPH were prepared using fish waste and their nutritional properties were evaluated. Four diets with different levels of FPH (0%, 10%, 15%, and 20%) in substitution for crab meals were fed to octopuses (mean body weight 100 mg) individually distributed for 70 days. Regarding yield, at the end of the hydrolysis period (day 15) the FPH fraction constitutes 67% of the total silage (dried powder). Small peptides were recorded in FPH (-1) and eight non-essential amino acids (NEAAs; 427 mg g^-1). Also, the free amino acids (FAAs) content was 8.3% of the total amino acids content with the predominance of taurine. Octopuses fed with FPH15 had the highest weight gain (3.06 g), SGR (4.76% day^-1), and survival (90%) compared to FPH0. Total alkaline protease activity of octopuses digestive gland was lower in FPH20 (3550 U mg of protein⁻¹) than in the control (5277 U mg of protein⁻¹). Incorporating protein hydrolysate derived from fish waste into prepared diet may offer unique advantages in promoting optimal growth and general physiological well-being for O. maya.

Hypertension associated with serotonin reuptake inhibitors: A new analysis in the WHO pharmacovigilance database and examination of dose-dependency

by Basile Chrétien, Andry Rabiaza, Nishida Kazuki, Sophie Fedrizzi, Marion Sassier, Charles Dolladille, Joachim Alexandre, Xavier Humbert

Introduction

Recent literature has reported instances of drug associated with hypertension with serotonin reuptake inhibitors (SRIs). Nonetheless, the association between SRIs and hypertension development is the subject of ongoing debate. It remains uncertain whether this is indicative of a class effect, and if dose-effect exist. To investigate the potential class effect associating SRIs with hypertension reporting, we utilized real-world data from VigiBase®, the World Health Organization (WHO) pharmacovigilance database.

Methods

We conducted an updated disproportionality analysis within VigiBase® to identify a signal of hypertension reporting with individual SRIs by calculating adjusted reporting odds ratios (aRORs) within a multivariate case/non-case study design. Additionally, we explored the presence of a dose-effect relationship.

Results

The database contained 13,682 reports of SRI associated with hypertension (2.2%), predominantly in women (70.0%). Hypertension was most reported in the 45-64 years old age group (44.8%). A total of 3,879 cases were associated with sertraline, 2,862 with fluoxetine, 2,516 with citalopram, 2,586 with escitalopram, 2,441 with paroxetine, 201 with fluvoxamine and 8 with zimeldine.A significant ROR was observed for all SRIs in both univariate (RORs ranging from 1.39 to 1.54) and multivariable analyses (aRORs ranging from 1.16 to 1.40) after adjustments for age group, sex, concurrent antihypertensive medication and drugs knowns to induce hypertension, except for fluvoxamine and zimeldine. No dose-response relationship was identified.

Conclusion

This investigation, conducted under real life conditions, unveils a notable pharmacovigilance safety signal associating SRI usage with hypertension reporting. No dose-response effect was detectable. Further longitudinal studies are warranted.

Lung cancer screening with volume computed tomography is cost-effective in Greece

by Xuanqi Pan, Katerina Togka, Hilde ten Berge, Lisa de Jong, Harry Groen, Maarten J. Postma, Eleftherios Zervas, Ioannis Gkiozos, Christoforos Foroulis, Kyriaki Tavernaraki, Sofia Lampaki, Georgia Kourlaba, Antonios Moraris, Sofia Agelaki, Konstantinos Syrigos

Objective

This study aimed to assess the cost-effectiveness of lung cancer screening (LCS) employing volume-based low-dose computed tomography (LDCT) in contrast to the absence of screening, targeting an asymptomatic high-risk population in Greece, leveraging the outcomes derived from the NELSON study, the largest European randomized control trial dedicated to LCS.

Methods

A validated model incorporating a decision tree and an integrated state-transition Markov model was used to simulate the identification, diagnosis, and treatments for a population at high risk of developing lung cancer, from a healthcare payer perspective. Screen-detected lung cancers, costs, life years (LYs), quality-adjusted life years (QALYs), and the incremental cost-effectiveness ratio (ICER) were predicted. Sensitivity and scenario analyses were conducted to assess the robustness and reliability of the model’s outcomes under varying parameters and hypothetical situations.

Results

Annual LCS with volume-based LDCT detected 17,104 more lung cancer patients at early-stage among 207,885 screening population, leading to 8,761 premature lung cancer deaths averted. In addition, in contrast to no screening, LCS yielded 86,207 LYs gained and 50,207 incremental QALYs at an additional cost of €278,971,940, resulting in an ICER of €3,236 per LY and €5,505 per QALY, over a lifetime horizon. These estimates were robust in sensitivity analyses.

Conclusions

LCS with volume-based LDCT, targeting an asymptomatic high-risk population, is highly cost-effective in Greece. Implementing LCS ensures efficient allocation of public healthcare resources while delivering substantial clinical benefits to lung cancer patients.

Deaf children with cochlear implants in Chile: A national analysis of health determinants and outcomes in the Latin American context

by Mario Bustos-Rubilar, Fiona Kyle, Merle Mahon

Deafness from birth represents a critical challenge for children’s communication, with substantial public health considerations. One intervention has been cochlear implants (CI) for children with severe to profound deafness. Since 2008, Chile has implemented regulations to provide a CI at an early age. However, wide variability exists in factors and expected outcomes without previous national studies. This study aimed to characterise deaf children with CI in Chile and evaluate the impact of CI on speech perception and production, social inclusion, and parental satisfaction. We conducted a prospective study using hospital clinical records and an online questionnaire with 107 deaf children under 15 who had received CIs from 2017 to 2019. We characterised factors and outcomes and investigated the relationship between demographic, audiological, and social determinants of health and outcomes, including communication at home, CAPII, SIR, Geers and Moog Scale, Social Inclusion, and Parental Satisfaction. Our study showed a national profile of deaf children with CI, representing 70% of those implanted from 2017 to 2019. CI beneficiaries lived in more developed boroughs (.54) compared to the national average (.37). Communication and speech perception outcomes varied and were concerning, yet more positive outcomes were presented for social inclusion and parental satisfaction. We found an association between the measured outcomes and children’s age, a socio-economic factor, CI use and CI training. This novel national study supports integrating public services close to each beneficiary’s borough to improve outcomes with the device. CI use and parental training might be crucial measures during rehabilitation treatment.

SEMdag: Fast learning of Directed Acyclic Graphs via node or layer ordering

by Mario Grassi, Barbara Tarantino

A Directed Acyclic Graph (DAG) offers an easy approach to define causal structures among gathered nodes: causal linkages are represented by arrows between the variables, leading from cause to effect. Recently, industry and academics have paid close attention to DAG structure learning from observable data, and many techniques have been put out to address the problem. We provide a two-step approach, named SEMdag(), that can be used to quickly learn high-dimensional linear SEMs. It is included in the R package SEMgraph and employs a two-stage order-based search using previous knowledge (Knowledge-based, KB) or data-driven method (Bottom-up, BU), under the premise that a linear SEM with equal variance error terms is assumed. We evaluated our framework’s for finding plausible DAGs against six well-known causal discovery techniques (ARGES, GES, PC, LiNGAM, CAM, NOTEARS). We conducted a series of experiments using observed expression (or RNA-seq) data, taking into account a pair of training and testing datasets for four distinct diseases: Amyotrophic Lateral Sclerosis (ALS), Breast cancer (BRCA), Coronavirus disease (COVID-19) and ST-elevation myocardial infarction (STEMI). The results show that the SEMdag() procedure can recover a graph structure with good disease prediction performance evaluated by a conventional supervised learning algorithm (RF): in the scenario where the initial graph is sparse, the BU approach may be a better choice than the KB one; in the case where the graph is denser, both BU an KB report high performance, with highest score for KB approach based on topological layers. Besides its superior disease predictive performance compared to previous research, SEMdag() offers the user the flexibility to define distinct structure learning algorithms and can handle high dimensional issues with less computing load. SEMdag() function is implemented in the R package SEMgraph, easily available at https://CRAN.R-project.org/package=SEMgraph.

A standard procedure for constructing a multi-level social vulnerability index using CLSA and SOS data as working examples

by Jasmine C. Mah, Olga Theou, Mario Ulises Perez-Zepeda, Jodie L. Penwarden, Judith Godin, Kenneth Rockwood, Melissa K. Andrew

Background

The construct of social vulnerability attempts to understand social circumstances not merely as a descriptor, but as a predictor of adverse health events. It can be measured by aggregating social deficits in a social vulnerability index (SVI). We describe a standard procedure for constructing a multi-level SVI using two working examples.

Methods

First, we describe a six-step approach to constructing a SVI. Then, we conducted a secondary analysis of a clinical dataset (Canadian Immunization Research Network’s Serious Outcomes Surveillance Network (SOS)) and a population-based dataset (Canadian Longitudinal Study on Aging (CLSA)). In both datasets, we construct SVIs, use descriptive statistics to report distributions by age and sex, and perform a multivariable linear regression of social vulnerability on frailty.

Results

Procedures for drafting a list of candidate social items, selecting deficits for inclusion, and screening deficits to meet inclusion criteria were applied to yield a 18-deficit SVI for the SOS and 74-deficit SVI for the CLSA. Deficits in each SVI were re-scored between 0 and 1, where 1 indicates the greater risk. Finally, the sum of all deficits is calculated into an index. In the SOS, SVI was associated with age only for females and was weakly associated with frailty (r = 0.26, p Conclusion

We present a standard method of constructing a SVI by incorporating factors from multiple social domains and levels in a social-ecological model. This SVI can be used to improve our understanding of social vulnerability and its impacts on the health of communities and individuals.

Microbiota composition of <i>Culex perexiguus</i> mosquitoes during the West Nile virus outbreak in southern Spain

by Marta Garrigós, Mario Garrido, María José Ruiz-López, María José García-López, Jesús Veiga, Sergio Magallanes, Ramón Soriguer, Isabel Moreno-Indias, Jordi Figuerola, Josué Martínez-de la Puente

West Nile virus (WNV) is a flavivirus naturally circulating between mosquito vectors and birds, occasionally infecting horses and humans and causing epidemiologically relevant outbreaks. In Spain, the first big WNV outbreak was recorded in 2020, resulting in 77 people infected and 8 fatalities, most of them in southern Spain. Culex perexiguus was identified as the primary vector of WNV maintaining its enzootic circulation of the virus. Growing evidence highlights the role of mosquito microbiota as a key component determining the vectorial capacity of mosquitoes, largely contributing to disease epidemiology. Here, we develop, to our knowledge, the first identification of the microbiota composition of this mosquito vector under natural conditions and test for the potential relationship between mosquito microbiota composition and WNV infection. To do so, we collected mosquitoes in a natural area of southern Spain during the 2020 WNV outbreak and identified the microbiota composition of mosquitoes using a 16S rRNA gene metabarcoding approach. The microbiota of Cx. perexiguus was dominated by the phylum Proteobacteria. The most abundant families were Burkholderiaceae and Erwiniaceae, including the genera Burkholderia, Erwinia, and Pantoea. The genus Wolbachia, which use to dominate the microbiota of Cx. pipiens and negatively interact with WNV according to the literature, had a low prevalence and relative abundance in Cx. perexiguus and its abundance did not differ between WNV-positive and WNV-negative mosquito pools. The microbiota diversity and composition of Cx. perexiguus were not significantly related to the WNV infection status. These results provide the first identification of the mosquito microbiota in an endemic area of WNV circulation in Spain.

The state of artificial intelligence in medical research: A survey of corresponding authors from top medical journals

by Michele Salvagno, Alessandro De Cassai, Stefano Zorzi, Mario Zaccarelli, Marco Pasetto, Elda Diletta Sterchele, Dmytro Chumachenko, Alberto Giovanni Gerli, Razvan Azamfirei, Fabio Silvio Taccone

Natural Language Processing (NLP) is a subset of artificial intelligence that enables machines to understand and respond to human language through Large Language Models (LLMs)‥ These models have diverse applications in fields such as medical research, scientific writing, and publishing, but concerns such as hallucination, ethical issues, bias, and cybersecurity need to be addressed. To understand the scientific community’s understanding and perspective on the role of Artificial Intelligence (AI) in research and authorship, a survey was designed for corresponding authors in top medical journals. An online survey was conducted from July 13^th, 2023, to September 1^st, 2023, using the SurveyMonkey web instrument, and the population of interest were corresponding authors who published in 2022 in the 15 highest-impact medical journals, as ranked by the Journal Citation Report. The survey link has been sent to all the identified corresponding authors by mail. A total of 266 authors answered, and 236 entered the final analysis. Most of the researchers (40.6%) reported having moderate familiarity with artificial intelligence, while a minority (4.4%) had no associated knowledge. Furthermore, the vast majority (79.0%) believe that artificial intelligence will play a major role in the future of research. Of note, no correlation between academic metrics and artificial intelligence knowledge or confidence was found. The results indicate that although researchers have varying degrees of familiarity with artificial intelligence, its use in scientific research is still in its early phases. Despite lacking formal AI training, many scholars publishing in high-impact journals have started integrating such technologies into their projects, including rephrasing, translation, and proofreading tasks. Efforts should focus on providing training for their effective use, establishing guidelines by journal editors, and creating software applications that bundle multiple integrated tools into a single platform.