Managing reusable medical devices incurs substantial health care costs and complexity, particularly in integrated care settings. This complexity hampers care quality, safety, and costs. Studying logistical innovations within integrated care can provide insights to medical devices use among staff effectively.This study aimed to establish the feasibility of a logistical intervention through outsourcing and a web portal. The goal was to provide insights into users’ acceptability of the intervention, on whether the intervention was successfully implemented, and on the intervention’s preliminary efficacy, thus benefiting practitioners and researchers.This paper presents a mixed methods feasibility study at a large chain-wide health care provider in the Netherlands. The intervention entailed outsourcing noncritical reusable medical devices and introducing a web portal for device management. A questionnaire gauged perceived ordering and delivery times, satisfaction with the ordering and delivery process, compliance with safety and hygiene certification, and effects on the care delivery process. Qualitative data in the form of observations, documentation, and interviews were used to identify implementing challenges. Using on-site stocktaking and data from information systems, we analyzed the utilization, costs, and rental time of medical devices before and after the intervention for wheelchairs and anti–pressure ulcer mattresses.Looking at the acceptability of the intervention, a high user satisfaction with the ordering and delivery process was reported . With respect to preliminary efficacy, we noted a reduction in the utilization of wheelchairs , and a halted increase in the utilization of anti–pressure ulcer mattresses. In addition, nurses who used the web portal reported shorter ordering times for wheelchairs (−2.7 min) and anti–pressure ulcer mattresses (−3.1 min), as well as shorter delivery times for wheelchairs (−0.5 d). Moreover, an increase in device certification was reported , indicating higher levels of safety and hygiene standards. In theory, these improvements should translate into better outcomes in terms of costs and the quality of care. However, we were unable to establish a reduction in total care costs or a reduced rental time per device. Furthermore, respondents did not identify improvements in safety or the quality of care. Although implementation challenges related to the diverse supply base and complexities with different care financers were observed, the overall implementation of the intervention was considered successful.This study confirms the feasibility of our intervention, in terms of acceptability, implementation success, and preliminary efficacy. The integrated management of medical devices should enable a reduction in costs, required devices, and material waste, as well as higher quality care. However, several challenges remain related to the implementation of such interventions. Managing medical devices is a complex but important element in the delivery of high-quality care and has considerable effect on the financial bottom line of health care providers ,2. If noAchieving better management of medical devices is particularly challenging when one considers that health care providers are still working toward more integrated care delivery . AlthougWhen pursuing integrated care delivery, supportive IT becomes pivotal, including in relation to medical device management . Care prWe conducted a mixed methods study to assess the feasibility of a logistical intervention, where a health care provider outsourced several noncritical reusable medical devices to a third-party provider and introduced a web portal to support medical device management. Feasibility is based on the extent to which an intervention is considered acceptable by the users; whether the intervention is successfully implemented; and, finally, the intervention’s preliminary efficacy. Our aims with regard to outsourcing were to reduce the (1) total utilization days of the medical devices; (2) delivery time; and (3) time and money spent on cleaning, maintaining, and internally transporting the devices. We aimed to achieve our goals by using a web portal that supports medical staff by reducing the time taken to order a device when needed and to deregister it when no longer needed and that provides them with easy insight into device availability from their own location. With this study, we provide practitioners and researchers with knowledge on the potential benefits of, and challenges related to, outsourcing medical devices, assisted by IT, in an integrated care provider setting.The study took place between January 2019 and June 2022 in the context of a large regional health care provider in the Netherlands. The organization, which was established after a merger of a hospital, several nursing homes, and home care providers, consists of 1 hospital, 17 nursing homes, and 3 residential care centers; it also provides home-based care at several locations. Since the merger, the health care provider has moved toward becoming a more integrated care organization . It was the first such organization to receive chain-wide accreditation worldwide from the Joint Commission International ). t test (Excel 2016). Differences in the average reported ordering time and delivery time before and after the intervention were assessed by means of a paired 2-tailed t test.The questionnaire data were analyzed by distinguishing three user groups: (1) nurses who used the web portal for both wheelchairs and anti–pressure ulcer mattresses, (2) nurses who used the web portal for only 1 type of device, and (3) nurses who had never used the web portal or had stopped using it. The questionnaire responses were analyzed by comparing the average difference between reported ordering time and delivery time before and after the intervention and on the average score per item on questions regarding ordering satisfaction and the perceived effects of the intervention. Differences in average ordering satisfaction and perceived effects among the user groups were assessed by means of a 2-tailed The interview data were analyzed with the aim to thoroughly understand the challenges that emerged from the transition to outsourcing and the implementation of the web portal—and how the care provider dealt with these challenges—as well as to highlight the challenges that the intervention did not resolve. Led by the first author, we performed the analysis using ATLAS.ti software (ATLAS.ti Scientific Software Development GmbH) and Excel, following the 3-step grounded theory approach of Corbin and Strauss  as discuThe data regarding rental of medical devices were routinely collected by the health care provider for administrative purposes and not linked to individual patients. The data processed in this study are not considered to constitute medical research involving human participants as defined in the 1964 Helsinki declaration. As such, the statutes of the institutional review board of the faculty of economics and business of the University of Groningen indicate that the study does not require ethics approval by a review committee. Nevertheless, all the methods described in this study were conducted in accordance with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.All interview and questionnaire respondents were informed about the purpose of the data collection and the data processing procedure, and they consented to participate.The results are presented in 3 parts. In the first part, we evaluated the acceptability of the intervention by nursing staff. In the second part, we addressed to what extent the intervention was successfully implemented and what enabling or limiting factors have been established. Finally, in the third part, we offered a preliminary assessment of the efficacy of the intervention in terms of device utilization, costs, ordering and delivery time, quality of care, and compliance with safety and hygiene standards.User satisfaction, as measured in the questionnaire responses, indicates how the nursing staff rate the new ordering process that is based on outsourcing and the web portal. Nurses (N=45) who were responsible for ordering reusable medical devices completed the questionnaire. Of the 45 nurses, 28 (62%) reported using the web portal for ordering both wheelchairs and anti–pressure ulcer mattresses, 10 (22%) used the web portal only for anti–pressure ulcer mattresses and not for wheelchairs, and 7 (16%) reported not using the web portal and sticking with the earlier procedure of telephoning and emailing.most satisfied and 5=least satisfied). Nearly half  of the respondents fully agreed with the statement that the ordering process is easy. Nurses who only ordered anti–pressure ulcer mattresses via the web portal reported an average satisfaction score of 2.3 (SD 0.6), which was a statistically significant (P=.003) lower rating than that of nurses who ordered both types of equipment via the web portal. Respondents who did not order both types of equipment via the web portal  reported either being unaware of the web portal, unsure of how to use it, or dissatisfied with its functionality.User satisfaction with the ordering process, with specific attention to the use of the web portal, was generally rated highly . Nurses insight into availability dimension was rated the highest, with an average rating of 1.8  shows that there is room for improvement. On the basis of the observational and interview data, we explain in the following subsections how the implementation of the intervention is hampered by the complex context of the care market in which this chain-wide care provider is embedded.Although most of the nurses reported that they do follow the new ordering process, several mentioned that they still use other ordering methods, such as ordering via email or telephone or by ordering from other suppliers. To an extent, this is inevitable in the current situation because some of the more specialized devices, such as customized wheelchairs, are only available from other suppliers and not from the one involved in the intervention. A problem is that this then leads to ambiguity about what ordering process should be used for which type of device, thereby structurally hampering a full uptake of the intervention. This is exemplified by several remarks in response to the questionnaire:I do not order wheelchairs via [supplier of study] but via the occupational therapy department, who arrange it with another supplier.Head nurse 1Besides working as a nurse, I also work as an occupational therapy coach, so I order devices via email.Head nurse 1In addition, nurses reported that there are still many device types where the internal ordering process is experienced as too cumbersome and slow:I particularly have problems with the purchasing process when something is not available from [supplier of study]...I need to go through the purchasing and infection prevention department, the whole process sometimes takes 4 to 6 weeks. The patient may have already passed away by then.Occupational health nurse 2These quotations illustrate that nursing staff will only fully adapt to, and benefit from, the new ordering process when it is implemented on an organization-wide scale, with a larger range of device types available. However, given the diverse supply base as well as the various care financers involved, this seems challenging.At the outset of our study, we expected the chain-wide health care provider in this study to have a unique opportunity to simplify the management of reusable medical devices; namely, because the provider is active across the 3 care domains in the Netherlands , we expected that it would be able to pool devices across these domains, thereby reducing its device supply base and the number of ordering methods. However, in practice, device suppliers tend to specialize their service and product range to a specific care domain, thereby forming a barrier to fulfilling our initial expectations:It is partly a very practical issue. Device suppliers have contracts with a selection of health care providers and device manufacturers...When it comes to maintenance, some spare parts can only be supplied by a specific manufacturer, which does not always align with the device type demanded by the health care provider. At the same time, our goal is—and it will be the same for [name of care provider]—to deliver affordable and personalized care for clients, and that sometimes creates tensions.Policy advisor of municipalityFurthermore, the care path of a single patient can span multiple domains. In this situation, the ordering methods and device suppliers ordinarily change during the care process. Consequently, to meet individual patient needs and to prevent long waiting times, nursing staff put much effort and time into the process of ordering devices. Essentially, they take care of the service and coordination duties that should partly be the responsibility of device suppliers and care financers:When a patient goes home after rehabilitation, we sometimes sell them our bed trapeze; otherwise, the patient has to order it, and it may not arrive in time. Also, we may order a wheelchair for short-term use under the Social Care Act from the supplier. If a patient needs longer-term care, we also order wheelchairs under the Long-term Care Act or other devices via the care insurer...So, unfortunately, we put quite some time and effort into coordinating the device process for patients.Occupational health nurse 1These findings show that the multitude of stakeholders and processes that are part of health care markets limit the extent to which nursing staff benefit from the transition to outsourcing and the implementation of the web portal and hamper a structural implementation of such solutions.On the basis of comparing the use of wheelchairs and anti–pressure ulcer mattresses before and after the intervention, we now present the findings of our preliminary efficacy analysis.P=.03) by 1106 (SD 106) days per month on average . This reduction in total rental time amounts to the most clearly visible pattern across the 8 devices included in the intervention. For the other types of devices, such as lifting slings and low-low beds, we also observed considerable reductions in utilization days, albeit with a less consistent drop. The total number of utilization days of anti–pressure ulcer mattresses gradually increased over time (P<.001).ver time . On the As indicated in The cost of renting anti–pressure ulcer mattresses was on average US $32,381 per month after the intervention compared with US $25,445 per month before the intervention. The cost of renting wheelchairs was on average US $4501 per month after the intervention. No accurate data were available on ownership costs for wheelchairs, including the actual purchase price and the maintenance, procurement, storage, and material-handling costs. In addition, for both types of devices, there were no data available on the historical patterns of care delivery volumes and the disease burden of patients. Hence, a valid comparison of costs before and after the intervention was deemed infeasible by the researchers involved as well as the managers at the care provider under study.P=.04) and anti–pressure ulcer mattresses (P=.03) and statistically significant reduced delivery times for wheelchairs only (P=.01). Nurses who only ordered anti–pressure ulcer mattresses via the web portal and ordered wheelchairs via other channels reported reduced ordering times, albeit not statistically significant, for both devices (P=.35 and P=.26). These results are summarized in devices are available faster with a score of 2.2 , indicating some improvement.The questionnaire results show how nurses perceived the ordering and delivery times before and after the intervention. Nurses who ordered both types of devices via the web portal reported statistically significant reduced ordering times for both wheelchairs . Of the 45 respondents, 22 (49%) fully agreed that there were fewer uncertified devices.Compliance with safety and hygiene standards was measured by responses to the statement On the basis of the averaged questionnaire responses , nurses P=.03), was observed. The increase in the required number of anti–pressure ulcer mattresses stabilized after the introduction of the web portal. For both wheelchairs and anti–pressure ulcer mattresses, we found shorter reported ordering and delivery times, but rental times per device did not reduce. Hence, the web portal may support the ordering and delivery processes, but there is no indication that it triggers a more efficient use of devices. After the intervention, a higher degree of device certification was reported, thereby increasing compliance with safety and hygiene standards. In theory, these improvements should translate into better outcomes in terms of costs and the quality of care. However, based on the findings, we could not establish that a reduction in overall costs had been achieved, and nurses did not report improvements in safety and the quality of care. Although, for all 8 types of reported medical devices, the implementation of the intervention was successful, based on observations and interviews, several challenges were highlighted related to improving the chain-wide management of medical devices. These challenges relate to the diverse nature of the supply base and complexities with having multiple care financers. In essence, these findings show the difficulties of managing, and catering to, the various stakeholder interests involved in the care chain, and this will be more elaborately reflected upon in the following subsection.This study addresses the feasibility of a 2-fold logistical intervention aimed at outsourcing the management of reusable medical devices and the introduction of a web portal facilitating the ordering and use of these devices. The findings show that, with respect to acceptability, user satisfaction with the ordering and delivery process was high. Concerning preliminary efficacy, a reduction in the required number of wheelchairs, which was significantly related to outsourcing (The literature on health care logistics suggests that better management of medical devices—for example, through better forecasting, standardized replenishment, and delivery procedures—supported by materials management information systems can lead to a reduction in device stock and increase the occupancy rate of devices ,7. In teWe recognize that there is a lot of freedom in deciding which expenses and savings to include in comparing the outcomes of an intervention, and, as a result, establishing changes in overall costs is especially challenging . Our casWith respect to the quality of care, it would be highly beneficial if health care providers were able to show positive effects from better device management. Our questionnaire indicated that nursing staff did perceive an increase in the speed of device delivery and improvements in terms of compliance with safety and hygiene standards. We would expect this to contribute to the satisfaction of patients by reducing waiting time and increasing the available capacity, that is, the amount of time nurses have available for the direct care process. However, indicators related to patient satisfaction and safety remain hard to monitor because quality inspections are usually based on samples and periodic inspections. This exemplifies the usefulness of using patient-reported outcomes and experience measures ,32, as wOur findings, supported by insights from previous studies ,29-33, iReflecting on the studied case enables us to provide recommendations for practice. Given the recently increased EU standards regarding the traceability and safety of medical devices , the preNevertheless, it seems that realizing a broad rollout of such an intervention and obtaining benefits in terms of cost savings and quality improvements remain a challenge, particularly for chain-wide care providers. This is especially the case because they are dealing with an extensive and complex device supply base. Top management needs to be aware of the related issues and challenges, particularly in a setting of care delivery that crosses the traditional boundaries of curative, long-term, and home care domains. For practice to structurally benefit from solutions such as outsourcing and web ordering portals, it is recommended to aim at reducing the complexity of the supply base, improving communication and support toward nursing staff, and establishing clear performance measures for evaluation purposes.This study assessed the feasibility of an intervention based on qualitative and quantitative data collected before and after the intervention. Several limitations warrant mention. First, although our data indicate clear improvements over time, there are several potentially confounding factors that have not been considered explicitly; for example, although care registration data did not indicate considerable changes in patient numbers or disease burden, this was not part of the statistical analyses. Other examples include developments in treatment methods that may affect device use as well as disruptions in the supply and care process, such as those seen during the COVID-19 pandemic.Second, our study took place against the backdrop of the introduction of the 2021 EU Medical Device Regulation. This context places our results within a framework of heightened standards for the traceability and safety of medical devices and shows a glimpse of the complex landscape that health care providers must navigate within the newly imposed regulatory constraints.Third and last, the questionnaire on user experience that provided relevant insights that add to the basic device data was sent out only after the intervention, and it was targeted at nursing staff and not at patients. As such, we lack firsthand experiences from the latter group. This is especially relevant because our respondents did not report any clear effects on patient satisfaction or any effect on care quality, which provides an important direction for further study. This again stresses the importance of measuring patient experiences and outcomes over time for both care and research purposes.The integrated management of medical devices should lead to reduced costs and fewer required devices, higher quality of care, and reduced material waste. This feasibility study confirms this potential when it comes to acceptability, implementation success, and the preliminary efficacy of the presented intervention. Nevertheless, at a time when the integration of care chains is becoming more important, our research also highlights some of the difficulties when putting integration into practice; for example, in a health care system context that is based on market principles, it remains an immense challenge to achieve a more coherent way of managing medical devices, even for a single care provider when operating across traditional health care boundaries. In addition, the ongoing challenges in achieving transparency on prices and on the quality of care again prove key to measuring the efficacy of integrated medical device management which, in turn, is pivotal to achieving long-term implementation.


Polycystic Ovarian Syndrome (PCOS) is the leading endocrine disorder in women of childbearing age with a prevalence of more than 15% among this group.A few authors suggest that there are abnormalities in the energy expenditure of women with PCOS, resulting from a reduction in the resting metabolic rate, especially in those with IR.Some studies have shown that the plasma levels of GLP-1 and PYY in the postprandial period are lower in women with PCOS,Signs of body fat storage, such as insulin, leptin and adiponectin, also participate in the process of controlling food intake, as they indicate the state of energy reserve and alter appetite when necessary.Weight loss has been the main option for treating PCOS. Low-glycemic diets and lifestyle changes associated or not to physical exercise lead to weight loss, reduce hyperandrogenism, increase ovulation and pregnancy rates, and are also beneficial in reducing hyperinsulinemia and its metabolic consequences.The association of PCOS with IR, and, consequently, with hyperinsulinemia is known for decades, and in addition to its effect on the reproductive system, it is related to the high prevalence of obesity, glucose intolerance (GI), type 2 diabetes mellitus (DM2), dyslipidemia and vascular inflammatory processes. Consistent pictures with the metabolic syndrome, elevated triglycerides and LDL, and reduced HDL are frequent.By considering these evidences, it is reasonable to propose that the main focus addressed in therapeutic strategies for weight loss in PCOS should also take into account the approach to IR. The use of insulin sensitizers reduces endogenous insulin requirements, with preservation of β cells, and it may protect insulin-resistant patients from developing DM2.Despite the extensive literature on the deleterious role of IR in the evolution of PCOS and its association with changes in control mechanisms of caloric intake and satiation/satiety and the benefits of insulin sensitizers in disease therapy, important international societies have been reluctant to recommend its use associated with diet, lifestyle and physical exercise as the primary therapy of PCOS.In the first consensus published as a group in 2004, even though the European Society of Human Reproduction (ESHERE) and the American Society of Reproductive Medicine (ASRM) recognized the high prevalence of IR in women with PCOS, they did not recommend IR screening in these patients by considering the restricted validity of clinical tests for its diagnosis. The group recognized some studies that showed the progression of GI to DM2 may be delayed by lifestyle changes and pharmacological intervention with insulin sensitizers, but did not recommend the use of these drugs routinely in the treatment of PCOS with IR.Four years later, the Thessaloniki ESHRE/ASRM-Sponsored PCOS Consensus Workshop Group proposed that “before any intervention is initiated, preconceptional counseling should be emphasized on the importance of lifestyle, especially weight reduction and exercise in overweight women, smoking, and alcohol consumption,” and recommended restricting the use of metformin (MTF) to women with PCOS and GI. Thus, the presence of IR should not be a reason for prescribing MTF.If IR is a step preceding GI, it did not seem reasonable to wait for the worsening of the metabolic profile in order to introduce insulin-sensitizing therapy. Considering the poor results obtained with lifestyle and diet changes on weight loss, we believe it is unreasonable to let the patient stay for a longer time under high levels of insulinemia and all its consequences.However, the ESHERE and ASRM maintained the same position in a new version of the Amsterdam consensus published in 2011: “Diet and lifestyle are the first choice in improving fertility and prevention of diabetes (Level B). Metformin may be used for impaired glucose tolerance (IGT) and DM2 (Level A.).” Management of women at risk for DM2 should include diet and lifestyle improvement as first-line treatment. Treatment with MTF is indicated to those patients with IGT who do not respond adequately to calorie restriction and lifestyle changes.”In a debate (pro x con) between two experts ,If the use of MTF has been practically a consensus for treating young, lean or obese, adolescents for some time, why not also apply it to adult women in the age group of 20 to 35 years, which corresponds to the prevailing age of patients with PCOS seeking care for the treatment of menstrual disorders and infertility? These are relatively young patients who may have their prognosis worsened and increased risk of metabolic syndrome if there is no intervention. Hence, it is reasonable to think that the benefits of insulins sensitizers could also reach this age group.According to some authors, there are no data supporting the treatment of PCOS with MTF based on the measures of IR by arguing that the parameters for its calculation are not sensitive neither specific.Another argument against the use of MTF as first-line treatment for PCOS is the lack of data on the results of IR treatment per se in PCOS. Therefore, the metabolic assessment of women with PCOS should focus on detecting conditions that justify the intervention, such as GI, metabolic syndrome and elevated HDL levels.In fact, randomized clinical trials in women with PCOS are needed to check the efficacy of insulin sensitizers for the improvement of metabolic endpoints. The criticism of the literature is that much information was obtained in studies investigating non-metabolic endpoints in PCOS or that non-PCOS populations were studied.In the specific case of PCOS, it is easy to imagine how difficult it would be to carry out a randomized clinical study to identify patients at risk and conduct a longitudinal study of cohorts of women with PCOS beyond 60 years of age to determine with greater precision the time and efficacy of the interventions studied for answering if insulin sensitizers used in patients with IR definitely prevent GI or DM2. Many patients would be followed up for decades and after entering their postmenopausal period.The lack of these studies may mean we do not have definitive answers to elucidate endpoints. However, the lack of these answers should not be enough reason to stop prescribing those drugs for these patients. Numerous evidences based on experimental cohort or epidemiological studies also have their value. By exclusively valuing evidence-based medicine obtained in randomized clinical trials or systematic reviews with meta-analysis, we certainly fail to cover numerous clinical situations, as in the case of PCOS. In these situations, it is absolutely pertinent to use evidence based on medicine rather than evidence-based medicine for decision-making in the face of individualized clinical situations. Thus, studies with less rigorous designs may have their place in everyday practice for the care of a particular individual.Although the FDA has approved MTF for DM2 treatment, it has been used off label for more than 40 years to reduce the signs and symptoms of PCOS and normalize the various parameters that assess risks for DM2, obese and non-obese, children, adolescents and adults.Finally, in the last ASRM/ESHERE consensus, it was recognized the validity of a more comprehensive use of MTF in the treatment of PCOS, based on evidence of its clear benefits in the specific PCOS group or subgroups by improving weight, BMI, hip-waist ratio, testosterone and glucose, especially in obese patients, since metabolic benefits are more accentuated in patients with increased BMI. Thus, in addition to lifestyle changes, the use of MTF was recommended in adult women with PCOS for the treatment of overweight and hormonal and metabolic changes. The benefit of MTF use in adolescents diagnosed with PCOS was also considered.Faced with so much evidence, restricting the use of insulin sensitizers for patients with PCOS no longer made sense. This new position of the most important societies of the specialty expands the range to patients with PCOS that can benefit from these drugs. The restriction on its use until recently may have deprived thousands of patients of the benefit of reducing IR and its consequences. It is known that IR is related to endothelial dysfunction and that it progresses with time. Endothelial dysfunction caused by IR has been related to reduced nitric oxide bioavailability and changes in endothelial regeneration. Research on the use of insulin sensitizers for the treatment of polycystic ovaries in rats has shown that endothelial dysfunction is the direct result of hyperandrogenism induced by IR, and treatment with MTF improves insulin sensitivity and blood pressure and reestablishes normal endothelial function, even with the weight gain of animals.Professionals from all over the world follow guidelines of the major American and European specialty societies, which impact direct on the therapeutics adopted globally. Therefore, the wider use of insulin sensitizers brings great prospects of more concrete clinical results regarding this therapy for both young and adult patients with PCOS, especially obese patients, as a first-line treatment. We believe that gynecologists are able to prescribe this drug because international experience has shown this is a low-risk product that has been increasingly used in patients with PCOS, youngsters, adolescents and adults, obese or non-obese, including pregnant patients with PCOS and gestational diabetes, and in hypertension during pregnancy.


The scientific community widely acknowledges that the gut microbiota plays a critical role in maintaining host health and can be altered by a range of factors, such as antibiotic use, diet, stress, and infections. Therefore, this study utilized bibliometric analysis to thoroughly investigate research trends in the microbiota and antibiotics. Scopus was used to extract papers linked to microbiota and antibiotics published between 2002 and 2021, and both Microsoft Excel and VOSviewer were used to conduct the analysis of the data. A total of 2,816 publications discussed the connection between the microbiota and antibiotics. Growth occurred in two stages: the first (2002–2015) was characterized by fairly slow publication production, while the second (2016–2021) saw a rapid increase in publishing progress. The United States has the most publications, 654, representing 23.22% of the total. China came second with 372 publications (13.21%), followed by the United Kingdom with 161 publications (5.72%) and India with 157 publications (5.58%). In addition, publications on ‘altered intestinal microbiota composition with antibiotic treatment’ were introduced after 2017, while ‘gut microbiota and antimicrobial resistance’ and ‘probiotics as an alternative antimicrobial therapy’ were introduced before 2017. Based on these results, this study provides an in-depth look at key moments in the history of microbiota and antibiotic research, as well as possible directions for future research in different areas of microbiota and antibiotic research. Therefore, it is suggested that more attention should be given to the latest promising hotspots, such as how antibiotic treatment changes the composition of the gut microbiota. Research in recent decades has focused on and linked the gastrointestinal microbiome to many diseases and human health2.Many microbes, including viruses, bacteria, fungi, protozoa, and archaea, colonize the human gastrointestinal tract (GI), termed the gut microbiota3. Colonization resistance may occur directly through competitive bacterial interaction or host defense against pathogens, which is triggered indirectly by bacteria. Many studies have shown not only the association but also the causality of many diseases with gut microbiomes. Furthermore, studies have revealed that intrinsic and extrinsic factors, mainly drugs, can affect gut microbiome function and/or composition, ultimately affecting human health2.The gut microbiota protects the GI tract against infection using different mechanisms that contribute to resistance against colonization by exogenous microorganisms and protection against fatal pathogens6, has been brought to light by research conducted in recent years. Because research output plays an important function in science development by providing a key association between the production of knowledge and its application, the volume of research that encompasses almost all of the world’s regions that are interested in the production of health sciences is growing. This is one of the reasons why there is a growing interest in the production of health sciences. Despite the fact that only a few bibliometric studies have been conducted in the field of gut microbiota11, none of them have investigated the links between the microbiota and antibiotics. To fill this gap, the authors of this study used bibliometric analysis to thoroughly investigate the key research trends related to microbiota and antibiotics. Bibliometric analysis refers to the quantitative and qualitative examination of the literature in a specific field utilizing statistical and mathematical methods. Over the past decade, numerous studies have been conducted to explore bibliometrics in various scientific disciplines14. Unlike systematic reviews, which aim to answer a particular research question based on a limited number of publications, bibliometric analysis aims to provide a comprehensive overview of the literature in a particular field15. Similarly, it differs from scoping reviews, which focus on identifying the nature and scope of research evidence16. Despite these differences, bibliometric analysis remains a valuable tool for obtaining a snapshot of both national and international contributions to the literature in a particular field, as well as identifying research gaps that future studies may address14. By investigating the global links between the research dynamics and hotspots of the microbiota and antibiotics, this paper aims to gain insight into the research trends of the microbiota and antibiotics to provide references for future research. Furthermore, by gaining insights into the research trends and hotspots in the field, policymakers and funding agencies can make informed decisions about where to allocate research resources and prioritize future research efforts.The importance of the gut microbiome, as well as its connection to health, the immune system, and the use of antibiotics17. Typically, either SciVerse Scopus or Web of Knowledge is used as the single database, and no gray literature is included in the analysis. For this particular study, publications relevant to microbiota and antibiotics from 2002 to 2021 were retrieved using SciVerse Scopus, which was chosen due to its many advantages over other databases, such as Web of Science, Medline, and Google Scholar19. One of the key features of Scopus is its ability to provide bibliometric indicators in a direct and simple way. Additionally, Scopus includes 100% of Medline's publications, so by using Scopus, publications in Medline are automatically included as well. Many academics have extensively used the Scopus database, one of the most complete, systematic, and reliable databases, for bibliometric analysis and visualization of the scientific literature. Because the Scopus database is always accessible, we decided to perform the literature retrieval from it on a single day, December 1, 2022, to eliminate any potential for bias that daily additions to the database could have caused.In bibliometric analysis, documents are retrieved from a single database and then analyzed both quantitatively and qualitatively22 and antibiotics26). These terms were then included in the Scopus Engine. Each of the chosen “keywords” was used as an entry for the “Article Title”. The keywords used in the study, ‘antibiotics’ or ‘antimicrobials’, ‘antibiotics’ or ‘antimicrobials’, were those related to antibiotics per se rather than other related terminology, such as specific name or class of antibiotics.The terms related to the microbiota and antibiotics were identified using PubMed Medical Subject Headings (MeSH) and relevant publications on the topics  were relevant to the topic being looked up. The author contacted two bibliometrics professionals and requested that they verify false-positive results by reviewing the titles and abstracts of the most-cited documents that were supplied to them. When experts established that there were no false positive results, the search query was deemed to have reached its conclusion. The correlation test was implemented between the information retrieved by the search query and the real findings for the top ten active researchers to validate that there are no false-negative results. The fact that the correlation test yielded a strong correlation (r = 0.952) and a significant result (p < 0.01) provides evidence that the search query was accurate. This particular validation method has been used in bibliometric investigations carried out in the past and published in the literaturehttps://www.vosviewer.com/), which is a free online program that can be used for mapping purposes30. The VOSviewer application was used to create network visualization maps that presented international research collaboration and research hotspots.The data retrieved were transferred to Microsoft Excel for analysis and tabulation. Export data included types of retrieved documents, the annual growth of publications, prolific countries, prolific institutions, prolific funding agencies, the most cited publications, and journals involved in publishing the retrieved documents. The retrieved data were also exported to VOSviewer v.1.6.18  original articles, 292 reviews, and 299 (10.62) other documents, including letters, conference papers, and editorials.Figure Table Ministry of Education of China and the Chinese Academy of Sciences published the highest number of articles, with 35 publications each. Next came Wageningen University & Research with 33 publications and INSERM with 30 publications.The top 10 institutions in terms of the amount of research they have conducted in this area are listed in Table The National Natural Science Foundation of China supported the highest number of articles, with 178 publications, followed by the National Institutes of Health with 162 publications and the National Institute of Allergy and Infectious Diseases with 83 publications.Table Plos One , followed by Frontiers in Microbiology , Scientific Reports , and Microorganisms . With an IF of 16.837, Microbiome was the most influential journal of the top 10 prolific journals.Table 40. The work that received the most citations in this area was written by Dethlefsen et al.35 and published in PLoS Biology. The works by Dethlefsen and Relman37 and Cho et al.34 received the second and third most citations, respectively.The 10 most cited publications on the microbiota and antibiotics are shown in Table By mapping the cooccurrences of terms in articles on microbiota and antibiotics, research areas were grouped into 3 clusters. There were 49,251 terms, and 111 of those terms appeared at least 100 times. The visual network map reveals that three clusters can be formed from all of these terms , followed by "ampicillin" (n = 258), "ciprofloxacin" (n = 244), and "metronidazole" (n = 233).Table 43. However, no bibliometric research has been conducted on the links between antibiotic use and the microbiota. In the current study, we analyzed global trends and research horizons on the microbiota and antibiotics through bibliometric analysis to look back over the past 20 years. Researchers were shown to have a significant interest in microbiota and antibiotics, as evidenced by the increasing number of annual publications. The United States held the leadership position in microbiota and antibiotics with regard to publications and collaboration. However, this position cannot be separated from its substantial support from financial institutions.To date, studies have revealed a link between the microbiota and several neurological and digestive diseases. The gut microbiota has become a focus of intense investigation in various diseases during the past two decades due to the growing interest in the function of intestinal microbe alterations in the pathogenesis of diseases. The status and tendencies of the gut microbiota in particular subjects are increasingly being investigated using bibliometric analysis44. This is likely due to several factors, including the availability of research funding, a strong infrastructure for scientific research, and a robust pharmaceutical industry. The United States is also home to several prestigious universities and research institutions that attract talented researchers and scientists from all over the world.The results of this study indicate that the United States, China, the United Kingdom, and India have made the most progress in microbiota-related antibiotic research in the past two decades, with the United States leading the way. This research is critical to combating antibiotic resistance, which is a global concern. It is essential that countries continue to invest in scientific research to develop new strategies for the use of antibiotics and combat this issue. According to the results, the United States has been at the forefront of antibiotic research trends44, making this research a priority. In addition, the country has invested heavily in scientific research in recent years and has a growing pharmaceutical industry.China ranked second in microbiota-related antibiotic research trends, indicating that the country has made significant strides in this field in recent years. China has a large population and has been hard hit by antibiotic-resistant infections46. The UK has a long history of scientific research and innovation and is home to several renowned universities and research institutions.The United Kingdom ranked third in the results, indicating that the country has also been active in microbiota-related research26, making this research a priority. However, India faces several challenges in the field of scientific research, including limited funding, a lack of infrastructure, and brain drain, where talented scientists leave the country for better opportunities elsewhere.India ranked fourth in the results, indicating that the country has progressed in microbiota-related antibiotic research. India is home to a large population with a high burden of infectious diseasesaltered composition of the gut microbiota with antibiotic treatment was particularly interesting in the current study. Treatment with antibiotics has been shown to decrease the diversity of bacteria in the intestinal microbiome, causing metabolic changes that increase the potential subsequent susceptibility of the intestinal tract to colonization. This allows exogenous pathogens to invade the GI tract and cause infection, in addition to the development of antibiotic resistance48. Antibiotics may also disrupt the normal balance between the gut microbiota and various species. For example, Clostridium difficile may result from the antibiotic effect of antibiotics on decreasing species diversity49. Administration of a combination of gentamicin, meropenem, and vancomycin in adults resulted in a decrease in Bifidobacterium and butyrate-producing species and an increase in the prevalence of Enterobacteriaceae during the first treatment, which was then partially restored within the next month, while some bacterial species remained undetectable for longer periods in the gut50.The current study identified three research themes related to antibiotic use and microbiota. These research themes were closely related. The research theme that focused on the 51. Intestinal bacteria resistant to antibiotics can be passed from mother to child during birth and may remain for weeks. Twelve percent of the commensal E. coli bacteria in the Swedish study were positive for tetracycline resistance despite never being exposed to antibiotics52. As bacteria sensitive to the antibiotic are eliminated, resistant bacteria for the same antibiotic start to take their place by multiplying. After antibiotic treatment, the diversity of the bacterial species is reduced, while the total microbial load may increase. For example, evidence showed that patients treated with a week of b-lactams doubled the fecal microbial load in fecal samples47. Even if transient, colonization with multidrug-resistant bacteria can lead to the transfer of antibiotic resistance genes into the microbiota, which can eventually result in increased resistance to a variety of effective antibiotics and an increased risk of fatal infection53.In the current study, ‘gut microbiota and antimicrobial resistance’ was among the most popular hot topics in research on the links between antibiotic use and the gut microbiota. Antibiotic resistance genes are present in the human gut microbiome. The number of resistance genes in the stomach increases rapidly during antibiotic therapy and gradually decreases once treatment ends54. Although probiotic treatment also alters the luminal microbiota, this luminal alteration of the microbiota by probiotics could significantly influence systemic metabolism, including insulin resistance55. Multidrug-resistant bacteria, such as carbapenemase-producing enterobacteria, extended-spectrum beta-lactamase strains and vancomycin-resistant enterococci, are all serious pathogens that cause a high mortality rate and are considered an important public health problem56. Therefore, strategies to prevent the colonization of the luminal microbiota, especially in the colon, could be achieved using probiotics. However, little is known about their biological action despite substantial research on probiotics in recent years57.Another topic that has received much attention is ‘probiotics as an alternative antimicrobial therapy’. There is evidence that probiotics may help treat and prevent infectious diseases40. Furthermore, these results demonstrate the increased emphasis and attention given to this area of research in recent years. For example, the most frequently cited article on the subject is published in PLoS Biology and has been cited 1695 times. This investigation used pyrosequencing technology to identify changes that occur in the microbiota population of three individuals before and after ciprofloxacin treatment35. The study clearly showed how ciprofloxacin impacted the diversity of the bacterial population in the intestine and its variability and balance. Furthermore, numerous taxa were unable to return to normal after six months of treatment35. The paper by Dethlefsen and Relman37, which was published in Proceedings of the National Academy of Sciences of the United States of America, was the second most cited article. This article was conducted to test the influence of the use of ciprofloxacin antibiotic on the communities of normal intestinal flora by studying approximately 1.7 million hypervariable 16S rRNA tags of 16S rRNA of the bacteria37. Ciprofloxacin greatly affected the bacterial population within 3–4 days of treatment. However, these populations began to recover after one week of stopping antibiotics, and although the recovery was imperfect, they did not return to their former status37.The results of our research demonstrate that several subtopics closely related to study hotspots were highlighted in the most cited publications on the links between antibiotics and the microbiotaNature34. Again, the investigators adopted an animal model to examine the effect of administering a low-dose antibiotic to a young murine on the composition of the gut microbiome and its metabolic pathway. As a result, several changes were documented. An example of these changes is the alteration of essential genes responsible for converting carbohydrates to short-chain fatty acids34.The third most cited paper was published in 40, published in Science, was the fourth most cited article. This study showed how antibacterial lectin, called RegIIIγ, maintains mutualism between the gut microbiota and the host intestine. This material forms a thin layer as a physical barrier between the microbiota and the intestinal epithelial lining. However, losing this zone was associated with an increase in colonic bacteria and, consequently, activation of the immune response40. The paper by Sartor31, published in Gastroenterology, was the fifth most cited article. This review article highlighted a key topic of rationale for manipulating gut microbiota in the treatment of inflammatory bowel disease (IBD). Although this therapeutic strategy is uncontested, clinical studies do not follow standard criteria based on rigorous evidence for the use of these therapeutic modalities. However, some experts have proposed the use of ciprofloxacin and/or metronidazole or certain types of probiotics to treat IBD31.The paper by Vaishnava et al.The study highlights that research on altered intestinal microbiota composition with antibiotic treatment was introduced after 2017. Therefore, it is necessary to explore the implications of such alterations in the gut microbiota for host health and how these changes can be mitigated.The study also shows that research on gut microbiota and antimicrobial resistance has been ongoing for several years. However, further research is needed to investigate the mechanisms by which the microbiota contribute to antimicrobial resistance and how this knowledge can be utilized to develop new strategies to combat antibiotic resistance.The study highlights the importance of probiotics as an alternative antimicrobial therapy, and it is necessary to further explore their potential to reduce antibiotic use and mitigate the negative effects of antibiotics on the gut microbiota.The study emphasizes that various factors, including diet and stress, can disrupt the gut microbiota. Therefore, it is necessary to explore how these factors influence the composition of the gut microbiota and antibiotic efficacy and how this knowledge can be used to optimize antibiotic therapy.The study of the links between the microbiota and antibiotic use is a rapidly evolving field and is expected to continue to be an area of intense research in the coming years. Based on the current trajectory of research related to the impact of antibiotics on the human microbiome and its consequences on health, there are several future perspectives to consider:This study is the first comprehensive bibliometric investigation of the links between antibiotics and microbiota research conducted worldwide. The study of the connection between antibiotics and the microbiota is still in its infancy, but it is expected to develop further soon. Therefore, scientific researchers, clinicians, and medical educators use the aforementioned development hotspots as a foundation and guide for developing new projects in their respective fields.59.The current study has some limitations. First, we only extracted data from the Scopus database where it was necessary to do so to conform to the data formatting requirements of visualization tools such as VOSviewer. Nevertheless, the Scopus database, one of the most generally accessible and well-known resources globally, has been utilized in several previously conducted bibliometric research projects of a particularly high standard. Second, however, we are concerned with ‘antibiotics’ or ‘antimicrobials’, ‘antibiotics’ or ‘antimicrobials’, were those related to antibiotics per se rather than other related terminology, such as specific name or class of antibiotics. It is important to note that we must acknowledge the potential for bias in our sample selection due to the exclusion of certain publications that use specific antibiotic names in their titles. We are committed to ensuring that our research is as representative and unbiased as possible, and we urge caution in drawing conclusions from studies that may not have taken this into account. Third, the bibliometric analysis cannot directly assess the quality of the evidence presented in the publications. It can only provide a quantitative assessment of the impact of the publication, such as how many times it has been cited or the number of publications in a particular field. The quality of evidence presented in a publication depends on many factors, including study design, the methods used, and the validity of the results. Bibliometric analysis cannot assess these factors. Finally, the scope of the present study was limited to the title search and only contained search terms related to the microbiota and antibiotics. Therefore, it is possible that this study missed some articles that used the terms ‘microbiota’ and “antibiotics” or closely related terms as keywords or appeared anywhere in the text of the publication. However, if these false negative outcomes occur, their impact on overall results will be minimalNational Natural Science Foundation of China and the National Institutes of Health provide significant support for this type of research. Therefore, it is recommended that researchers pay more attention to the latest promising hotspots, including altered intestinal microbiota composition with antibiotic treatment. Further research in these areas could provide new insights and strategies to maintain host health and combat antibiotic resistance.This study is the first bibliometric analysis that objectively and thoroughly examines global microbiota trends related to antibiotic research over the past 20 years. In conclusion, this study provides a comprehensive summary of the current trends in global publications and helps researchers determine the current hot topics in this area. Currently, the number of publications in this field is increasing every year, with the United States and China making the greatest contributions. Furthermore, the


Editorial on the Research TopicWomen in hypertensionWomen's history in science has always been a history of prejudice and discrimination, without equality with the opposite sex. Despite the great progresses, such discrimination is still present in the scientific world, especially in the so-called hard sciences , maybe due to old gender prejudices and stereotypes. In the academic world, female researchers currently represent more than half of all researchers, but this percentage decreases drastically as we advance in the university hierarchy, predisposing to a clear gender inequality. In the leading academic positions, gender differences are even more marked, denoting an unfair approach towards female leadership and an overall aged attitude that does not reflect the current educational status. Although history does not give much credit to female researchers, many scientific discoveries belong to women. Over time, various female personalities have made scientific history and have proven to be a source of inspiration for future generations. A famous example is Marie Curie, one of the first scientists recognized worldwide for her studies on radiation and radioactive materials (Nobel Prizes for Physics in 1903 and Chemistry in 1911). The story of Rosalind Franklin is yet another emblematic one since she created the foundations of molecular biology by providing experimental evidence of the helix structure of DNA, even though the Nobel Prize was later awarded to her male colleagues. Francoise Barre-Sinoussi was awarded the Nobel Prize for Medicine in 2008 following the discovery of the human immunodeficiency virus (HIV), essential to turn AIDS from a death sentence to a manageable disease. Rita Levi-Montalcini received the Nobel Prize for Medicine in 1986 for the identification of the nerve fiber growth factor Ngf contributing to the study of several diseases, such as tumors and Alzheimer's disease.Several projects aimed at gender equality are currently being developed, including this specific research topic, to promote female research, encourage women to be involved in scientific projects and, eventually, disseminate their results. Nevertheless, despite the progress that we have seen in recent years, gender equality is still far from being achieved. Sensitivity towards this problem has certainly grown and several initiatives are increasingly successful in promoting the much-needed cultural change.The current Research Topic, entitled “Women in hypertension”, promotes the work of female scientists in the field of hypertension contributing to counteracting the gender imbalance currently present in the research field. To support this purpose, both the editors and the reviewers of this Editorial are women, and only submissions headed by women (as first or last author) were considered. In this context, the editors themselves are an example of female leadership in pre-clinical and clinical research fields: the SEPHAR study, led by Prof. Maria Dorobantu, had a major impact on the actual understanding of overall cardiovascular disease –3; pre-cThe contributions of this Research Topic from female researchers demonstrate the remarkable contribution of females in the research field, contributing to advances in knowledge of hypertension. In the future, female participation in the scientific field and their access to leading positions in academia and science should be further encouraged and supported. In a society where we are aiming at overall transparency and fairness, where our only purpose should be notable progress in medicine and science regardless of the subspecialty, discrimination based on the researcher's gender has no place. The world has no gender but only brilliant minds at the service of science!


Antibiotic resistance is an issue of growing importance in the public health sphere. Medical interns are of great relevance when it comes to the source of this problem. This study therefore sought to ascertain which factors influence the management of antibiotic therapy by this population, in order to pinpoint the possible causes of misprescribing habits. We conducted a qualitative study based on focus group techniques, with groups consisting of medical interns from the Santiago de Compostela Clinical University Teaching Hospital. Our study identified factors which the participants considered to be determinants of antibiotic use and their relationship with the appearance of resistance. The single most repeated factor was the influence of the attending physician’s judgement; other factors included a high healthcare burden or prescribing inertia. This stage is an opportunity to correct misprescribing habits, by implementing educational interventions aimed at modifying the identified factors. Infections due to multiresistant bacteria are a serious public health problem , due to In this respect, a meta-analysis has shown that less than half of all hospitalised patients receive optimal antibiotic treatment in accordance with prescription guidelines . This haIn contrast to quantitative methods, qualitative methods in general and focus groups in particular, have the great advantage of enabling all the dimensions of the problem to be detected . Hence, Accordingly, this study sought to examine, from a qualitative standpoint, the factors that influence antibiotic use among the medical intern population, with the focus on their KAPB and sources of information used. Identifying these factors would make it possible to design antibiotic-prescribing training strategies at this crucial stage in the training of future health professionals.Seven focus groups were set up and held. Each consisted of four to six participants, amounting to a total of 35 medical interns from the Santiago de Compostela Clinical Hospital .After analysis of all the recordings, the main factors cited by the interns as determinants of antibiotic use and its relationship with appearance of resistance, were identified .The interns identified different items that influenced antibiotic use . Some ofOwn knowledgeNo important gaps in knowledge were found among the interns, when it came to assessing the need or lack of need to prescribe an antibiotic  is a stage in medical training, in which candidates who pass a selective examination undergo a specific training programme for each medical specialisation, lasting 4 to 5 years. During this period, the interns are rotated through the different hospital and out-of-hospital services, including the emergency service, which are relevant for their respective medical specialisations .We conducted a qualitative study using the focus-group method, regarded as the methodology best suited to analysing different experiences and attitudes from the standpoint of those involved. Our study targeted subjective opinions held by the medical community about antibiotic use, seeking a “point of saturation of information” at which no further new ideas would emerge. Valid and reliable results can be obtained in this way, ensuring a fully integrated approach to all the dimensions of the problem ,38.The script used during the sessions was drawn up by reference to previous studies based on focus groups of medical specialists, pharmacists and patients ,29,39.Our target study population was made up of medical interns from Santiago de Compostela Clinical University Teaching Hospital. The participants were recruited via social media, by telephone and through key informants , using convenience sampling, the method of selection most appropriate for the focus group technique . The parThe focus groups met in a lecture room belonging to the Santiago de Compostela Clinical University Teaching Hospital, and the sessions were moderated by two researchers, one who was acting as session leader and the other as moderator, avoiding parallel conversations or deviations from the established script. Notes were taken during the sessions to prevent subsequent confounding.The sessions were taped with an iOS-based recording application, using two devices placed in the centre of the group to ensure quality for transcription purposes. The sessions lasted for approximately 35 to 60 min each and were moderated by a researcher . Focus group sessions were held until a point was reached at which no new ideas were emerging (saturation of information), with this being applied as a criterion of study validity, i.e., once saturation is achieved, study quality is not enhanced by adding more units of information . The sesThe transcriptions were separately analysed by two researchers, a man and a woman, both medical interns in the Preventive Medicine and Public Health Department of Santiago de Compostela University  , in order to reduce any risk of research bias .We used a thematic and discourse analysis of the data, with it being discussed by all authors.The ideas extracted were then associated with concepts and codified, and new hypotheses were established according to the Constructivist Grounded Theory method ,42,43. DThe study was evaluated and approved by the Santiago-Lugo Research Ethics Committee. The participants were informed of the purpose of the study and the plan to record and transcribe the sessions, maintaining anonymity in the analysis of the recordings. All participants were briefed and gave their verbal consent to participate in the study.Improvement in antibiotics prescribing calls for complementary approaches from different settings. There seems to be a culture of antibiotic use and abuse. This article shows that this habit is acquired at the earliest stages of a doctor’s training. However, these are modifiable factors. These findings may well be of great utility when it comes to designing more direct, higher impact campaigns aimed at preventing the perpetuation of this inappropriate prescribing culture.


The SVM (Linear Kernel) yielded the highest recognition rate at 98.70%.The wheels of railway vehicles are of paramount importance in relation to railroad operations and safety. Currently, the management of railway vehicle wheels is restricted to post-event inspections of the wheels whenever physical phenomena, such as abnormal vibrations and noise, occur during the operation of railway vehicles. To address this issue, this paper proposes a method for predicting abnormalities in railway wheels in advance and enhancing the learning and prediction performance of machine learning algorithms. Data were collected during the operation of Line 4 of the Busan Metro in South Korea by directly attaching sensors to the railway vehicles. Through the analysis of key factors in the collected data, factors that can be used for tire condition classification were derived. Additionally, through data distribution analysis and correlation analysis, factors for classifying tire conditions were identified. As a result, it was determined that the  The wheels of a railway vehicle are the most important part in relation to safety in railroad operation. They are structured to have a specific shape that prevents derailment, which can be caused by wearing of the wheel due to continuous friction with the rail, and at the same time to ensure stable riding comfort. However, in general, the wheels of railway vehicles receive a continuous contact load with the rail during the operation of the railway vehicle and, accordingly, damage to the wheel tread due to the continuous and ongoing contact load generates an impact load during operation. Therefore, it affects the truck parts where the wheels are installed, causing wheel damage and derailment, which can pose a risk to human safety, as well as a negative impact on customer convenience and reduced transportation due to delays and reduced ride comfort ,2,3,4.Currently, the wheel management of railway vehicles is limited to a follow-up inspection of the wheels whenever physical phenomena, such as abnormal vibration and noise caused during the operation of railway vehicles, are observed. Accordingly, there is a constant risk of human casualty and damage to railway vehicles due to wheel burnout. Furthermore, as maintenance is performed after the follow-up inspection of the wheel, the maintenance cost also increases, which is accompanied by economic loss.The maintenance system of Korean railway vehicles has reached a level where it can utilize RCM (Reliability Centered Maintenance) technology based on statistics through the establishment of an information system. However, since it is difficult to respond to accidental failures, continuous development for preventing failures during operation is necessary for core devices, such as motor blocks, bearings of axles, and wheels, which directly causes passenger safety and operation delays ,6.In general, ultrasonic technology, infrared cameras, and magnetic field methods are used to determine wheel abnormalities. There is an acoustic vibration technology that analyzes wheel vibrations and acoustic vibrations of railway vehicles to detect abnormalities and vibration changes due to damage or imbalance of wheels. There is also a technology that uses image processing technology to photograph and analyze the wheel surface of a railway vehicle to determine whether there is an abnormality ,8,9,10.However, most ongoing wheel state recognition research is based on steel wheels. In addition, there is a lack of research on machine learning-based tire condition recognition and tire condition recognition systems. Research on key element analysis of tire sensor data and research on rubber wheels must be carried out in order to apply to machine learning models.This paper proposes a system for recognizing and predicting the condition of railroad wheels using machine learning technology as one of the methods to address the aforementioned problem. In this paper, a machine learning algorithm trained on optimized training data is employed to monitor the condition of railroad vehicle wheels and predict anomalies in advance. This system goes beyond traditional post-inspection methods by analyzing data in real-time to detect and predict abnormalities.This paper provides a device and method to enhance the learning and prediction performance of the machine learning algorithm by selectively identifying and specifying training data through correlation analysis. It determines influencing factors that cause anomalies in railroad wheel axles moving along the rail. Using the identified final influencing factors, a machine learning algorithm is trained, and real-world data related to wheel axles corresponding to these final influencing factors are applied to predict anomalies. To collect suitable data, sensors were attached to trains, marking the first system of its kind in the relevant field, and data were collected from trains operating on the Busan Line 4 subway in South Korea. Based on the collected data, machine learning was performed by creating training datasets. Therefore, in this paper, in order to accurately classify the condition of tire wear, sensing data targeting Busan light rail wheels (rubber tires) were used. The data consisted of factors including 3-axis acceleration, temperature, and pressure, which have never been applied to tire condition classification before. We propose a method to classify the wear state of tires of light rail trains based on machine learning by measuring them.This paper consists of 6 chapters as follows: In this chapter, we look at studies on the status recognition of subway wheels and related studies on the status recognition of rubber tires.In “Infrared diagnostics of cracks in railway carriage wheels”, a method for detecting cracks in railway wheels was developed using infrared cameras and thermal imaging cameras. It was based on recording the change in surface temperature distribution of the wheel disc while the disc of the railway wheel was heated .“Supplementary magnetic tests for railway wheel sets” proposed a further step in the diagnosis of railway wheelsets based on the magnetic mechanic effect and magnetic processes that occur in the material because of aging due to the magnetic properties of steel .“A new measuring method of wheel–rail contact forces and related considerations” proposed a new method for measuring wheel–rail contact forces, using non-contact gap sensors without special wheelsets equipped with strain gauges, slip rings, or telemeters. It was measured from lateral distortion .In “Acoustic emission monitoring of wheel sets on moving trains,” an acoustic emission monitoring system for wheels of moving trains and trams was proposed using AE (Acoustic emission) sensors mounted on rails .“Profile parameters of wheelset detection for high speed freight train” presented a system to obtain accurate wheelset profile parameters by using lasers and high-speed cameras and applying non-contact light section technology .In “Wheel defect detection with machine learning”, we proposed two machine learning methods to automatically detect wheel defects based on the wheel vertical force measured by the sensor. SVM is used to classify time series data, and an artificial neural network is provided for image classification .“Machine Learning-Based Wheel Monitoring for Sapphire Wafers” used machine learning classification algorithms  to extract signals and characteristic parameters of the wheel during the polishing process using AE signals and radial/axial vibration signals .“A study on the fatigue characteristics and life prediction of the tire sidewall rubber” proposed a life prediction equation using strain energy density obtained by performing tensile and fatigue tests on tire sidewall compounds. The applicability of the research results to low fuel efficiency tires was examined by converting the fatigue life of the sidewall rubber into the expected mileage of the tire .“Definition of a new predictor for multiaxial fatigue crack nucleation in rubber” derived new predictive variables for fatigue crack nucleation of rubber. This is triggered by fatigue and motivated by microscopic mechanisms developed in the framework of Configurational Mechanics .Tire wear recognition technology is being actively researched as one of the core technologies of intelligent tire systems. Most studies use a method of predicting durability by analyzing rubber properties through simulation using tires attached to actual cars and testing the fatigue level of its elasticity. However, accurate predictions are difficult depending on the type of vehicle, driving habits, road conditions, etc., and it is difficult to deliver status information to drivers in real-time, such as remaining tire life ,19.In this study, sensing data composed of factors including 3-axis acceleration, temperature, and pressure were measured for Busan light rail wheels (rubber tires) that adopted an unmanned driving system to accurately classify the state of tire wear. We propose a method to classify the wear condition of tires of light rail trains based on machine learning, which has never been applied to tire condition classification, and achieved high accuracy .To analyze the factors that affect tire wear, a method for calculating the degree of influence by considering the characteristics of related factors and data analysis for related studies is used. The factors are classified into driving/non-driving conditions and described in The tire data for factor analysis is for 180,005 tires currently in use and 180,003 tires in the old state (worn). An analysis is conducted on tire state classification using acceleration factor patterns according to changes in light rail transit driving speed (test speed) and light rail transit load (test load).By analyzing the distribution of acceleration  data inside the tire according to the change in load and speed of the tire currently in use and tires in an old state, a factor highly correlated with the tire condition is sought. Z-axis occurs the most.Z-axis tends to decrease more significantly in tires in their old state than in tires currently in use. Through this, it is judged that the degree to which the Z-axis is affected by the tire’s state in the acceleration factor is large.In the driving environment, when the load is the same and the speed is changed, the data density according to the size of the The tire acceleration measurement data are affected by the tire’s state. Using data distribution characteristic analysis of the acceleration factor, it is possible to check if it is applicable to the recognizing condition algorithm.It is necessary to analyze the acceleration factor of the data acquired in the actual light rail transit driving environment and confirm if it is a factor that can classify the tire condition in the same way as the acceleration measurement data analysis result in the test environment.The accelerations  of the tire currently in use increase in magnitude in proportion to each other with a positive correlation and are not significantly affected by load changes. Accelerations  and accelerations  show a negative relationship, are inversely proportional, and are less affected by load changes. Since there is almost no change in the acceleration  correlation coefficient according to the load change, it is judged that the influence of the load change on each axis of acceleration is small.Z-axis shows a high correlation coefficient regardless of the change in test speed, so among the acceleration factors it is a factor that is greatly affected by driving.In the case of the same load, as the test speed increases, the correlation coefficient values of the X and Y axes decrease, so the degree of influence decreases as the driving speed increases. However, the Z-axis shows a high correlation coefficient regardless of the test speed change, as in the tire currently in use, so it can be seen that the degree of influence related to driving is a large factor. Therefore, through the coefficient value obtained by correlation analysis of the X, Y, and Z axes of the weight, the factor with the greatest influence in relation to driving is the Z-axis. When classified into tires currently in use and tires in the old state, the correlation coefficient value remains high in tires in the old state, so it seems to be applicable to state classification.Through the correlation analysis of the acceleration factor of tires in the old state, the correlation coefficient changes of each acceleration axis show a change similar to that of the tire currently in use, and it is equally confirmed that the effect is greater in relation to speed than load. Even when subjected to the same load, the The analysis process is performed to determine whether to apply the selected candidate factors as a recognizing condition factor by checking the degree of influence through correlation analysis with the tire state according to the tread depth.The main factors of the measured data show a different form when checking the pattern classified according to the tire state and can be used as a recognizing condition factor using these characteristics.From the raw data measured through light rail transit driving, data acquired at similar times are selected in consideration of the external environment  when driving, and converted into a file (CSV format) to be linked with the program.As shown in The raw data including factors measured through light rail transit driving were divided into tire conditions  according to the tread depth, and processed as data having the corresponding state as the target value light rail transit. The tires of the Busan Metro Line 4 electric train are equipped with three-axis  acceleration sensors inside the tires. Additionally, temperature and pressure sensors are attached to the four tires of the locomotive and trailer car. Four three-axis acceleration sensors are also installed near the tires of the locomotive and trailer cars.Furthermore, reflective plate-type (non-contact laser) sensors are attached to the four points on the wheels of the locomotive and trailer cars, allowing conversion to angular velocity, speed, and distance measurements. To ensure temporal synchronization between vehicle information  and collected data , an IMU sensor is installed at one point in the vehicle’s underside. This setup is integrated with a program capable of data analysis and synchronization.Furthermore, to synchronize the sensor data collected during the operation of the metro, the sampling rate of the acceleration sensors is set to 1000 Hz, while the sampling rate for the internal tire temperature/pressure sensors is set to 100 Hz due to their different requirements. The minimum synchronization frequency of 100 Hz is achieved.Among the factor data measured through light rail transit driving, the data measured with an operating speed of 60 km/h or more and the data with a tire internal temperature exceeding ±100 °C were removed and shown in The quality of the learning data is increased by selectively collecting data expected to cause wheel abnormalities and the learning data  that will be used to train the machine learning algorithm through quantitative data analysis techniques. By selecting and specifying the final influencing factors that cause wheel abnormalities, the load required for learning the machine learning algorithm was reduced and prediction performance was improved.To determine machine learning-based tire tread wear, feature data are created by converting vibration components of the acceleration sensor inside the tire into the frequency domain.SVM is used for classification and regression analysis and is a type of supervised learning algorithm for pattern recognition and data analysis. SVM is based on the concept of finding a hyperplane that best separates data points into two or more classes. When data cannot be separated linearly, a technique called the kernel trick is used. The kernel trick maps data points to a high-dimensional space that can be separated by a hyperplane. Kernels include linear, polynomial, and RBF  kernels .For SVM-based tire state recognition using acceleration data, an SVM classification model tested the classification accuracy using tires currently in use and tires in the old state. In addition, the tire acceleration data targeted 180,005 tires currently in use and 180,003 tires in the old state (worn), setting tires in the old state to 0 and tires currently in use to 1, depending on the state of the tire. Random Forest, a machine learning algorithm, can be used in the field of data classification and regression by generating a final learner by linearly combining it after generating several decision tree learners that learn arbitrarily. To prevent overfitting, it is an algorithm of the principle of randomly selecting an optimal reference variable. Random Forest is used because it is effective in processing large amounts of data and has the advantage of high model accuracy by minimizing overfitting problems . Figure Based on the SVM model, a tire condition  classification experiment is conducted, and light rail transit driving data measurement is conducted on 1,567,706 train data and 732,469 test data . As a result of predicting tire state  based on the SVM model, the accuracy of the Linear Kernel and RBF Kernel are measured at 98.70% and 96.55%, respectively. Based on the Random Forest model, the tire state  classification experiment is conducted, and the light rail transit driving data measurement is conducted for 1,566,871 train data and 732,469 test data . As a result of predicting tire state  based on the Random Forest model, the accuracy was measured at 89.68%. Looking at the tire state recognition results based on SVM (Linear Kernel) and SVM (RBF Kernel), it can be seen that the recognition rate of the tire state safety and warning is high, but the recognition rate of the tire state danger is relatively low.Looking at the Random Forest-based tire state recognition results, it can be seen that the warning tire state show a high recognition rate, but the tire state safety and danger recognition rates are relatively low.Z-axis acceleration data had a significant influence on tire condition, depending on its state. Data distribution analysis and correlation analysis were conducted on the accelerations  to analyze the relationship between acceleration components and the relationship between different acceleration axes for currently in use or old state (worn) tires. To determine the applicability of the tire condition recognition factors, correlation analysis of measurement factors for four tires of a single electric train was performed using data collected during the operation of the Busan Metro Line 4. Acceleration of the axle and tire internal temperature/pressure data were examined as potential factors for classifying tire conditions based on data distribution. For the generation of learning data, two round trips of data from four sections of the Line 4 were merged, resulting in a total of 1,567,706 training data samples and 732,469 test data samples. Preprocessing was applied to the data, including sampling synchronization and outlier removal. To classify tire conditions, machine learning algorithms such as Support Vector Machine (SVM) and Random Forest (RF) were utilized, using acceleration, temperature, and pressure data. Initially, classification models were experimented with for the currently in use and old state (worn) tires, and the accuracy was measured. Among the three models, the Random Forest achieved a classification accuracy of 89.68%. For SVM, the Linear Kernel and RBF Kernel achieved classification accuracies of 98.70% and 96.55%, respectively, with the Linear Kernel showing the highest accuracy of 98.70%. This study enhanced the learning and prediction performance of machine learning algorithms using temperature, pressure, and three-axis acceleration data, and the frequency-domain transformed features of acceleration sensor vibrations. It not only provided a method for predicting anomalies in railway vehicle wheels in advance, rather than relying on post-checks after anomalies occur, but also demonstrated the potential for future applications and scalability in the expanding field of metro railways. There were limitations to predictions regarding tire cracks and damage. Data can only be collected when cracked or damaged tires are operated by installing cracked or damaged tires on a train. However, there is a limit to installing cracked or damaged tires on a light rail train that must handle passengers and operate safely. In future research, we plan to conduct additional research using light rail that does not handle passengers, increase the accuracy of state recognition through wavelet noise reduction, and conduct additional research on tire state recognition using deep learning. An updated paper will be submitted as part of our ongoing efforts to predict tire condition.This paper aims to improve operational efficiency, reduce maintenance costs, and ensure the safe operation of electric trains by implementing proactive maintenance measures through tire condition recognition  during train operation. To achieve this goal, actual equipment, including tire pressure/temperature sensors, internal acceleration sensors, vehicle axis vibration sensors, vehicle speed, and vehicle motion sensors, was installed on the tires of Busan Subway Line 4, and data were collected during the train’s operation. There were difficulties in installing measurement sensors inside a moving tire. The rubber tires of light rail wheels have iron auxiliary wheels inside the tires, so if the tires are damaged during operation, the vehicle can be restored through the auxiliary wheels. There was difficulty installing the sensor because the gap between the auxiliary wheels and tires was narrow. The collected data was correlation analyzed to identify key factors that could be used for tire condition recognition. As a result, it was determined that the