Healthcare

BackgroundIntravenous Tissue Plasminogen Activator (IV rt-PA) significantly improves AIS patients functional outcomes within the treatment window, yet the usage of IV rt-PA among AIS patients are substantially lower in China than in developed countries. Healthcare resource utilization manages effective treatment patterns for patients who are adherent to IV rt-PA. This study investigates the association between healthcare resource inputs and IV rt-PA adherence and the impact of Gross Regional Product (GRP) on IV rt-PA. Methods1,456 hospitals from 31 provinces with 158,003 acute ischemic stroke patients who had received IV rt-PA between 2015-2019 were recruited by the Chinese Stroke Center Alliance. The study outcome was the adherence rate of IV rt-PA in each hospital. Healthcare resource input was identified from three aspects: human, material, and economic. Multivariable linear regression was conducted by adjusting healthcare system characteristics and by further adjustment of GRP. ResultsThe median (interquartile range) of IV rt-PA rate was 19.1% (8.6% -34.6%). Physician-nurse ratio ({beta}=0.023, p<0.001), nurse-bed ratio ({beta}=0.0343, p<0.001), and total health expenditure ({beta}=0.00002, p<0.001) were positively associated with the IV rt-PA adherence rate after controlling healthcare system factors. Through additional adjusting of GRP, only health expenditure was significantly positively associated with IV rt-PA adherence rate ({beta}=0.000018, p<0.001). ConclusionsMore health spending and being equipped with equally proportional physician-nurses and nurse-bed combinations in the provincial hospital will increase adherence to IV rt-PA among AIS patients. The difference in GRP among provinces may stimulate hospitals to provide more healthcare input from the workforce, thus indirectly increasing the usage of IV rt-PA.

Uterine fibroid, also called leiomyomas, is the most common tumor in women, affecting more than 70% of women over the age of 50. As a generally benign disease, the uterine fibroid can potentially contribute to female stroke through different pathological conditions. The relationship between uterine fibroids and stroke was occasionally reported in sporadic case reports. However, fibroids-related stroke still remains elusive at the population level. This study conducted Mendelian randomization (MR) analysis to investigate the risk of stroke (outcome) following uterine fibroid (exposure). Furthermore, through interrogating the largest clinically representative cohort of 521,612 participants, this study had sufficient power to detect the causality of uterine fibroid on different stroke subtypes, thus discovering the small vessel ischemic stroke (IS) as the most significant stroke subtype associated with uterine fibroids. In conclusion, this study explicitly indicates that uterine fibroids can causally increase the risk of stroke, rather than just a benign disease. This finding strongly suggests the importance of encompassing female populations in stroke studies and the investigation of fibroid-related stroke as a novel stroke subtype from animal models through clinical trials. HighlightsO_LIUterine fibroids can causally increase the risk of stroke, rather than just a benign disease. C_LIO_LISmall vessel ischemic stroke is the most significant stroke subtype associated with uterine fibroids. C_LI

BackgroungCervical cancer (CC) is one of the common gynecological malignancies, which has a serious negative impact on the quality of life of patients, and brings huge economic pressure and burden to society. The most effective treatment for CC has become an important issue worldwide. MethodIn order to determine the current research hotspots and development trends in a particular field, we conducted a bibliometric analysis of the top 100 cited papers. To achieve this, we searched for the top 100 most cited papers on the Science Citation Index Expanded (SCI Expanded) on the Web of Science (WOS), based on the CCS (citation count score). We then reviewed relevant literature from different years, countries/regions, institutions, authors, keywords, and references. Using VOS viewer and Cite Space software, we constructed a knowledge map, and finally compiled the relevant information we retrieved from the literature using Excel. Through this process, we were able to make predictions about the current focus and trends in the field. ResultsBetween 2013 and 2023, numerous journals published the top 100 cited research papers. The International Agency for Research on Cancer and the American Cancer Society were the most cited institutions. The United States contributed the most papers, followed by France and England. The top 5 keyword co-occurrences were cervical cancer, women, human papillomavirus, United States, and colorectal cancer. Cluster analysis results suggest that future research in CCS may focus on prophylaxis and HPV vaccination. ConclusionBibliometric analysis can quickly and intuitively identify the focus and boundaries of cervical cancer research. Our findings suggest that prophylaxis and HPV vaccination may be the focus and trend for future research on cervical cancer.

BackgroundHandwriting is one of the fundamental skills for school-aged children, and it is an intricate and interacting process. An innovative computerized handwriting assessment system, the Smart Handwriting Analysis and Recognition Platform (SHARP) was used to provide a comprehensive and quantitative analysis of Chinese handwriting performance and identify children with handwriting difficulties objectively, accurately, and efficiently. Aims/ObjectivesThe purpose of this study is to provide quantitative data on childrens Chinese handwriting process and products using SHARP; to investigate the handwriting difficulties in children with neurodevelopmental problems, and to explore the associations between handwriting and sensorimotor performance, including fine motor skills, visual perceptual skills, visual-motor integration, and oculomotor proficiency. Material and MethodsTypically developing students and students with neurodevelopmental problems were recruited through teachers and therapists from six primary schools in Hong Kong. SHARP and tests of sensorimotor skills were performed. ResultsThe quantitative analysis using the SHARP system showed a progressive developmental change in handwriting performance among the typically developing children at their primary education. There were also significant differences between the typically developing students group and those with neurodevelopmental problems, both in handwriting speed and writing errors. Significant associations between the handwriting process parameters and fine motor skills were identified, while handwriting product parameters were closely correlated with visual-perceptual skills of these typical developing students. Conclusions and SignificanceSHARP appears to provide a comprehensive, quantitative and objective evaluation of students handwriting performances, thus assisting both teachers and parents in comparing students performance objectively, thus identifying students with handwriting difficulties as early as P1 level. It was observed that handwriting performance has strong relationships with young childrens visual perceptual skills and fine motor skills. The findings could help to facilitate early intervention for those students with handwriting problems.

AimPersonalized medicine is part of the future frontier of public health and precision healthcare systems have been implemented for years, both within Europe and beyond. To establish the state of the art of Sino-EU science and innovation in Personalized medicine, we have mined the major dedicated databases globally. Here we present the updated mapping on the Sino-EU collaborations. Patents, scientific publications and preprints related to Personalized medicine have been mapped and analyzed after being extracted through databases mining. The integration of the previous mapping provides a more complete overview, which does not show relevant variations, confirming previous trends. In this work we complete the mapping by providing a digital tool for consulting the various data collected.

This paper examines the impact of COVID-19 vaccination on political support. We exploit Japans age-based COVID-19 vaccine roll-out, prioritizing people aged 65 years and older. A regression discontinuity design based on a large-scale online survey reveals that COVID-19 vaccination increases favorable opinions of the vaccination progress in municipalities and infection control measures of municipal governments. By contrast, there is no significant effect on support for the central government. We also discovered that people with chronic diseases and low socioeconomic status are more affected. These results show that reciprocal motives and political information play an important role in evaluating public policies.

BackgroudGenerative language models (GLM) utilize machine learning algorithms to perform various tasks such as text generation, question response, and sentence completion by imitating the language that humans understand and use. PurposeThis study was to fine-tune the Llama2 language model using text data from books on the diagnosis and treatment of musculoskeletal system in physical therapy and compare it to the base model to determine its usability in medical fields. ResultsCompared to the base model, the fine-tuned model consistently generated answers specific to the musculoskeletal system diagnosis and treatment, demonstrating improved understanding of the specialized domain. ConclusionThe model fine-tuned for musculoskeletal diagnosis and treatment books provided more detailed information related to musculoskeletal topics, and the use of this fine-tuned model could be helpful in medical education and the acquisition of specialized knowledge.

BackgroundThe SARS-Cov-2 pandemic (COVID-19) sudden onset disrupted the direct access to face-to-face nutrition consultation fostering the rapid adoption of Telehealth by dietitians. ObjectiveThis study investigates Telehealth use among Lebanese Licensed Dietitians (LDs) amid COVID-19, in the absence of national Telehealth practical guidelines (TPG), and offers insights on Telehealth application under uncertainties of pandemic event, economic crisis, and destructed infrastructure occurring simultaneously in Lebanon. DesignA cross-sectional study during March 2023, using an anonymous online survey (44 questions), diffused through the Lebanese Order of Dietitians and social media platforms. ParticipantsThe sample (n=94) consisted mostly of females (98.9%) and young dietitians (mean(SD) age: 30.54(6.41) years) having a mean(SD) of 7.89(5.7) years of experience. Most respondents identified clinical nutrition as their primary practice area (87.2%), mostly in weight management (84%). Main outcome measuresTelehealth experience amid COVID-19 including tools utilized in remote consultations, barriers, facilitators, and perspectives of Telehealth use. Statistical analysesDescriptive analysis (counts, frequencies) using SPSS version 28. ResultsAlthough 48.4% of LDs reported using Telehealth prior COVID-19, this proportion increased to 97.8% during the pandemic. The most common tools used were WhatsApp (90.3%), Zoom (72.0%), and E-mails (41.9%). Reported barriers included bad internet connection (74.2%), patients preferring face-to-face consultation (61.3%), and patients lacking technical literacy (33.3%); benefits included scheduling and time flexibility (83.9%), decrease in practice-related costs (77.4%), and compliance with social distancing measures (53.8%). The majority agreed that Telehealth is needed (78.5%) and applicable in the Lebanese context (64.6%) and expressed the need for Telehealth trainings (78.5%) and TPG for nutrition care (74.2%). ConclusionsThis study recognizes increasing use of Telehealth in Lebanon, warranting the development of Telehealth nutrition care infrastructure comprising national regulations and evidence-based practical guidelines to respond to the innovation in the healthcare industry, and to assure Telehealth sustainability in LDs routine practice.

BackgroundPrevious prediction models have predicted a single outcome (e.g. gait) from several patient characteristics at one point (e.g. on admission). However, in clinical practice, it is important to predict an overall patient characteristic by incorporating multiple outcomes. This study aimed to develop a prediction model of overall patient characteristics in acute stroke patients using latent class analysis. MethodsThis retrospective observational study analyzed stroke patients admitted to acute care hospitals (37 hospitals, N=10,270) between January 2005 and March 2016 from the Japan Association of Rehabilitation Database. Overall, 6,881 patients were classified into latent classes based on their outcomes. The prediction model was developed based on patient characteristics and functional ability at admission. We selected the following outcome variables at discharge for classification using latent class analysis: Functional Independence Measure (functional abilities and cognitive functions), subscales of the National Institutes of Health Stroke Scale (upper extremity function), length of hospital stay, and discharge destination. The predictor variables were age, Functional Independence Measure (functional abilities and comprehension), subscales of the National Institutes of Health Stroke Scale (upper extremity function), stroke type, and amount of rehabilitation (physical, occupational, and speech therapies) per day during hospitalization. ResultsPatients (N=6,881) were classified into nine classes based on latent class analysis regarding patient characteristics at discharge (class size: 4-29%). Class 1 was the mildest (shorter stay and highest possibility of home discharge), and Class 2 was the most severe (longer stay and the highest possibility of transfers including deaths). Different gradations characterized Classes 3-9; these patient characteristics were clinically acceptable. Predictor variables at admission that predicted class membership were significant (odds ratio: 0.0- 107.9, P<.001). ConclusionsBased on these findings, the model developed in this study could predict an overall patient characteristic combining multiple outcomes, helping determine the appropriate rehabilitation intensity. In actual clinical practice, internal and external validation is required.

ObjectiveEach nation develops a guideline for managing and preventing cardiovascular disease (CVD) based on the available literature and the evidence-based consensus in their guidelines recommendations. The goal of this review is to appraise the quality of many guidelines recommended by several international organizations for the early detection and prevention of CVD. MethodsWe conducted a scoping review using a few guideline-specific databases using Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) as the reporting guideline for this review. We used the Appraisal of Guidelines for Research and Evaluation II (AGREE II) instrument to rate the methodological quality and rigorousness of the included guidelines for CVD prevention and early detection. ResultsOut of the 2,466 guidelines identified by our search, based on our eligibility criteria, we included a total of 20 distinct guidelines globally focused on screening for CVD prevention and early detection. (70%) of these guidelines were classified as "strongly recommended" while only (90%) were classified as just "recommended". The AGREE II appraisal domains with the highest median scores (percentile 25th, 75th) were "Clarity of Presentation" 92% (81, 95.5), followed by Applicability 88% (73, 93). The Rigour of Development and Editorial Independence were the lowest scores with a median of 78% (66.5, 84) and 75% (60.5, 92). ConclusionsUsing AGREE II quality appraisal tool, we provided a critical quality appraisal of several international CVD prevention guidelines and reveal opportunities to improve the CVD prevention guidelines quality. What is already known in this review?O_LIEach community develops a guideline for screening and managing CVD prevention based on the current evidence and evidence-based consensus. C_LIO_LIAGREE II tool is an internationally standardized instrument to report the rigorousness of development, transparency, and methodological quality of the clinical practice guidelines. C_LI What this review addsO_LIThis review provided a critical quality appraisal of several international CVD prevention guidelines. C_LIO_LIThe highest AGREE II domain median score was "Clarity of Presentation" while the least domains were "Editorial Independence" and "Rigour of Development". C_LIO_LI70% of these guidelines were classified as "strongly recommended". C_LI How this review might affect research, practice, or policyO_LIThis review provided a critical quality appraisal of many CVD prevention guidelines and revealed opportunities to improve CVD prevention guidelines quality. C_LI

The article focuses on measuring the fluctuations in countries development as a result of the COVID-19 pandemic. The obtained measures make it possible to predict the extent of the impact of risks to public health on the economy, financial-budgetary, political-institutional development of states in the future, as well as the social determinants of public health. This assessment represents a new paradigm that makes it possible to effectively evaluate the manifestations of the consequences of COVID-19 and to identify the relevant determinants of the lack of resilience of the medical and social security systems to the coronavirus pandemic around the world. We picked the determinant of national development indicators of the 59 countries in order to measure the fluctuations in their economic development. In addition, we applied the binary response model for identifying the economic, financial-budgetary, and political-institutional development change with the happiness index of the countries being the dependent variable. The analysis of our empirical model made it possible for us to conclude that economic and financial-budgetary components have significantly increased the influence on well-being during the COVID-19 pandemic. In contrast, we observed the decrease in the impact of political and institutional indicators during the same period.

BackgroundGestational duration has a non-negligible impact on eye diseases. However, the long-term role of cytokines on the causal relationship of maternal gestational age on offspring visual impairment remains unclear. MethodsWe perform a lifecourse-network Mendelian randomization (MR) to explore the causal relationships among maternal gestational duration (from EGG and iPSYCH, N=84,689), neonatal/adult cytokines (from the NHGRI-EBI Catalog, N=764/4,618) and adult eye diseases (from FinnGen consotium, N=309,154) using summary-level data from large genome-wide association studies. Multiplicative random effects inverse variance weighted (IVW) and multivariable-IVW method are the main analysis methods and the other 15 pleiotropy-robust methods, weak IV-robust methods and outliers-robust methods are performed as auxiliary methods. ResultsWe find that maternal gestational age (early preterm birth, preterm birth, gestational duration and postterm birth) has causal relationships with 42 eye diseases. Specially, four neonatal cytokines: TNF-, IL10, GROA and CTACK, as well as four adult cytokines: CTACK, IL10, IL12p70 and IL6.26 are mediators in the causal relationships between early preterm birth and preterm birth to 8 eye diseases. However, after adjusting for these mediators, null direct causal effect of early preterm birth and preterm birth on 8 eye diseases can be found. In addition, there is no mediator in the causal relationships from gestational duration and postterm birth to eye diseases. ConclusionThe influences of maternal gestational duration on the offspring eye diseases through cytokines are long-term and lifecourse.

The author withdrew this manuscript owing to rewriting theory, all constructs, and correction and revision according to the peer review comments during the development and discussion phase of the research. Therefore, the author would not wish this work to be cited as a reference for the project. If you have any questions, please contact the corresponding author.

Generative AI tools such as ChatGPT are increasingly used by the public to seek guidance on diet and physical activity for type 2 diabetes (T2D) prevention and management. However, the consistency of model outputs across different users and disease-stage scenarios remains insufficiently characterized. This pilot study aims to evaluate the word-level and semantic-level consistency of GPT-4os diet and physical activity responses for type 2 diabetes prevention and management. We designed 12 prompts covering four categories: prediabetes, diagnosed type 2 diabetes (T2D), diagnosed T2D with complications, and general questions that did not specify dysglycemia stage. Word-level similarity was quantified with Term Frequency-Inverse Document Frequency (TF-IDF) cosine scores; sentence-level semantic similarity was measured using large language models (LLMs) - DeBERTa-v3 MNLI to calculate the entailment probabilities. The results showed that mean cosine similarity across users was moderate (0.44-0.66), whereas mean entailment similarity was higher (0.68-0.81). Across stages, word-level similarity was low to moderate (0.28-0.63) and entailment similarity remained moderate to high (0.63-0.80). Low similarity commonly referenced distinct food choices, operational details, safety warnings, and stage-specific suggestions. GPT-4o generated semantically consistent but variably detailed responses and the moderate semantic variation suggested limited differentiation of response content across diabetes-related stages in this pilot consistency assessment.

BackgroundStroke-associated pneumonia (SAP) is a frequent complication of stroke, characterized by its high incidence rate, and it can have a severe impact on the prognosis of patients. The limitations of current clinical treatment measures underscore the critical need to identify high-risk factors promptly to decrease the incidence of SAP. ObjectiveTo analyze the risk factors of SAP in stroke patients, construct a predictive model of SAP based on the SHAP interpretable machine learning method, and explain the important variables. MethodsA total of 763 stroke patients admitted to the Second Affiliated Hospital of Anhui University of Traditional Chinese Medicine from July 1, 2023, to May 31, 2024, were selected and randomly divided into the model training set (n=457) and model validation set (n=306) according to the ratio of 6:4. Firstly, the included data were sorted out, and then Lasso regression was used to screen the included characteristic variables. Based on the tidymodels framework, Using decision tree (DT), logistic regression, extreme gradient boosting (XGBoost), support vector machine (SVM), The classification model was constructed by five machine learning methods, including SVM and LightGBM. The grid search and 5-fold cross validation were used to optimize the hyperparameter optimization strategy and the performance index of the model. The predictive performance of the model was evaluated by the area under the receiver operating curve (AUC), calibration curve, and decision curve analysis (DCA), and we used Shapley additive explanation (SHAP) to account for the model predictions and provide interpretable insights. ResultsThe incidence of SAP in this study was 31.72% (242/763). Six variables were selected by Lasso regression, including nasogastric tube use, age, ADL score, Alb, Hs-CRP, and Hb. The model with the best performance in the validation set was the XGBoost model, with an AUC of 0.926, an accuracy of 0.914, and an F1 score of 0.889. Its calibration curve and DCA showed good performance. SHAP algorithm showed that ADL score ranked first in importance. ConclusionThe model constructed using XGBoost has good prediction performance and clinical applicability, which is expected to support clinical decision-making and improve the prognosis of patients.

Introduction.Digital technologies are increasingly influencing childrens lives, with many seeking digital platforms for nutritional education. This study aims to assess the usability and acceptability of Ajyal Salima, a nutrition awareness digital platform targeting children aged 9-11, in four Arab countries. Methods.A qualitative study was led across four countries: Lebanon, Bahrain, Palestine, and Jordan. Semi-structured focus groups were conducted with children and parents, and one-to-one interviews were held with teachers. Data was analyzed using thematic content analysis. Results.Four major themes emerged: platforms usability, content enjoyment, changes in childrens habits and recommendations to improve the platform. Overall, parents and teachers found the digital experience positive and useful and the content appropriate for children, particularly younger age groups. Challenges included registration difficulties, technical problems, internet accessibility, low parental involvement, and difficulties integrating the platform into teachers schedules. The platforms animations were less effective in sustaining childrens attention amid evolving digital standards. Conclusion.To enhance the platforms effectiveness, recommendations include simplifying the registration process, enhancing content interactivity, aligning the platform with school curricula, and equipping teachers with supportive resources. Fostering stronger school-family partnerships and engaging parents through community initiatives may be considered to maximize the platforms potential to promote healthier eating habits and improve nutritional awareness among children and their families, across the region.

IntroductionStroke survivors tend to have low motivation for rehabilitation, which prevent them from completing the rehabilitation training task effectively and participating in daily activities. Reward strategies can stimulate patients motivation for rehabilitation, but the duration of their effect is unknown. tDCS is a technique capable of promoting plastic changes and functional reorganization of cortical functional areas. When it acts on dlPFC, it can improve the functional connectivity of brain areas associated with goal-directed behavior. Reward strategies combined with tDCS (RstDCS) have been shown to make normal individuals work harder at performing tasks. However, there are no studies on whether this combined strategy improves motivation in stroke patients and whether it has a long-lasting effect on motivation maintenance. Methods and analysis87 stroke survivors who have low motivation and upper extremity dysfunction will be randomized to receive conventional, Rs, or RstDCS treatment. Patients in each group will undertake 15 sessions of tDCS real or sham stimulation of the left dlPFC for 3 weeks in conjunction with conventional rehabilitation or reward strategy training. Following this, the RS treatment group and RstDCS treatment group will be given a 3-week outpatient self-monitoring training program, while the conventional group will be given home rehabilitation instruction prior to discharge. Rehabilitation motivation is the primary outcome measure and will be assessed using RMS. RMS,FMA, FIM and ICF activity and social engagement scale will be compared at baseline, 3 weeks, 6 weeks, and 3 months after enrollment. Ethics and disseminationThe study has been approved by the Ethics Committee of Yueyang Hospital of Integrated Chinese and Western Medicine Affiliated to SHUTCM (2021-122). All participating patients will provide written informed consent. The results will be disseminated through (open access) peer-reviewed publications, networks of scientists, professionals, and the public. Trial registration number: ChiCTR2300069068

Responsible Research and Innovation (RRI) seeks to align the research results with the needs of society to respond to current and future problems, also encompassing financial instruments, innovative public policies, and the distribution of resources. These policies should prioritize research in those areas with the greatest impact on society, and particularly in health research, this impact should be focused on responding to clinical problems of the population rather than economic impact. A methodology is proposed that uses information from open sources to identify discrepancies between the results of the most translational research of a region and its health needs, in order to provide useful information for the formulation of innovation policies.

Introduction: Managing gestational weight gain (GWG) is crucial for the health of mothers and their children. Mobile applications (apps) specifically designed for pregnancy are emerging as modalities to deliver accessible lifestyle intervention at a low-cost. However, current studies are varied in results and suffer from heterogeneity. Thus, we conducted this systematic review and meta-analysis to summarize the efficacy of mobile apps in managing GWG and investigate variables that may contribute to heterogeneity. Methodology: Seven databases were systematically searched up to 9 November, 2024. Only randomized controlled trials (RCTs) were included. Outcomes were excessive GWG and inadequate GWG according to the 2009 Institute of Medicine (IOM) guideline. Quality appraisal was performed using the Cochrane Risk of Bias 2 (RoB 2) tool. Random-effect model meta-analysis was conducted using odds ratio (OR) as the summary measure alongside their 95% confidence intervals (CI). Results and Discussion: Fifteen RCTs were included. Mobile apps led to a significant overall decrease in excessive GWG (OR: 0.71; 95% CI: 0.54 to 0.95; p-value: 0.02; I2: 60%). Subgroup analysis showed that social media apps, self-monitoring functionalities, and overweight/obese patients are associated with a significant reduction in excessive GWG. However, there was significant evidence of small-study bias in the analysis. Moreover, mobile apps also significantly increased inadequate GWG (OR: 1.51; 95% CI: 1.04 to 2.21; I2: 0%). Meta-regression did not reveal any significant finding. Conclusion: In conclusion, mobile app interventions are shown to be effective in preventing excessive GWG, particularly social media apps and those with self-monitoring functionalities. However, the reduction in excessive GWG may only be seen in overweight and obese patients and more studies are needed to ascertain this finding. Lastly, mobile apps are associated with an increased risk of inadequate GWG and strategies to combat inadequate GWG are needed.

BackgroundChatGPT (Chat Generative Pre-trained Transformer) has initiated widespread conversation across various human sciences. We here performed a concise review combined with a SWOT (strengths, weaknesses, opportunities, threats) analysis on ChatGPT potentials in natural science including medicine. MethodsThis is a concise review of literature published in PUBMED from 01.12.2022 to 31.03.2023. The only search term used was "ChatGPT". Publications metrics (author, journal, and subdisciplines thereof) as well as findings of the SWOT analysis are presented. FindingsOf 178 studies in total, 160 could be evaluated. The average impact factor was 4,423 (0 - 96,216), average publication speed was 16 days (0-83 days). Of all articles, there were 77 editorials, 43 essays, 21 studies, six reviews, six case reports, six news, and one meta-analyses. Strengths of ChatGPT include well-formulated expression as well as the ability to formulate general contexts flawlessly and comprehensibly, whereas the time-limited scope as well as the need for correction by experts were identified as weaknesses and threats. Opportunities include assistance in formulating medical issues for non-native speakers as well as the chance to be involved in the development of such AI in a timely manner. InterpretationArtificial intelligences such as ChatGPT will revolutionize more than just the medical publishing landscape. One of the biggest dangers in this is uncontrolled use, so we would do well to establish control and security measures at an early stage. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSSince its release in 11/ 2022, only a few randomized controlled trials using ChatGPT have been published. To date, the majority of data stems from short notes or communication. Given the enormous interest (and also potential for misuse), we conducted a PUBMED literature search to create the most comprehensive evidence base currently available. We searched PUBMED for publications including the quote "ChatGPT" in English or German from 01.12.2022 until 31.03.2023. In order not risk any bias of evidence all related publications were screened initially. Added value of this studyThis is the most concise review for ChatGPT up to date. By means of a SWOT analysis, readers and researchers gain comprehensive insight to strengths, weaknesses, opportunities and threats of ChatGPT especially in the context of medical literature. Implications of all the available evidenceOur review may well serve as origin for further research related to the topic in order to create more evidence, strict regulations and policies in dealing with ChatGPT.