Medical Information Research Articles

Herbal medicine use in patients seeking treatment in emergency departments

To ascertain the extent of toxicological profiles around their medical use, herbal medicine use problems need to be consistently traced for consumer safety. Medical information regarding botanical use in various diseases or disorders, as well as adverse/toxicological effects of the botanicals, was sourced from scientific databases. Patients who request medical care at hospitals may be using at least one formulation of botanicals at the time of the visit, and some of the used medicinal plant products possess the potential to be the cause of toxicity as well as herb–conventional drug interactions. Emergency healthcare providers must be aware of some potential adverse events that may be seen in admitted emergency department patients when the herbal medicine is used alone or concomitantly with conventional medicine. Moreover, emergency healthcare providers must be knowledgeable of herbal medicine practices to ensure that optimal treatments will be selected for these patients.

A Qualitative Review of Misinformation on Alopecia

Background: Alopecia is common and can lead to significant distress for patients. Patients often seek medical information on the Internet, which may leave them susceptible to misinformation from poor-quality sources. The aim of this study was to qualitatively assess misinformation available online related to alopecia. Summary: Several alopecia-related myths were identified, including false causes, criticism of conventional treatments, and bogus “natural” cures or remedies. False causes included headwear, haircare practices, and sexual practices. Treatments which were criticized included minoxidil, finasteride, topical corticosteroids, ciclosporin, methotrexate, and Janus kinase inhibitors. Alternative unfounded therapies which were touted included mineral supplements, biotin, B vitamin complexes, fish oils, shark cartilage, onion juice, rosemary oil, horsetail extract, and saw palmetto. Key Messages: Misinformation related to alopecia is prevalent online and may lead to suboptimal therapeutic outcomes. Dermatologists and other healthcare professionals should combat misinformation when encountered.

Association between prognostic nutritional index and mortality risk in patients with community-acquired pneumonia: a retrospective study.

The prognostic nutritional index (PNI), reflecting the body's immune-nutritional status, has been established as a correlate of prognosis across various diseases. However, its significance in community-acquired pneumonia (CAP) remains unclear. This study investigated the relationship between PNI and clinical outcomes in CAP patients. In this retrospective cohort study, we aimed to evaluate the prognostic value of the PNI in adults with CAP admitted to the ICU. Participants were selected from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database and categorized into quartiles (Q1-Q4) according to their PNI values. We employed Kaplan-Meier survival analysis, multivariate Cox regression, and restricted cubic spline (RCS) models to explore the association between PNI and the clinical outcomes of these CAP patients. In this study, we included 1,608 patients with CAP. The observed 30-day and 90-day mortality rates stood at 30.85% and 39.99%, respectively. Patients with higher PNI levels exhibited a reduced risk of both 30-day and 90-day mortality. Following adjustment for confounders, PNI showed a significant negative association with 30-day mortality [HR, 0.93 (0.91-0.94), P < 0.001] and 90-day mortality [HR, 0.94 (0.92-0.95), P < 0.001]. RCS analysis revealed a consistent trend of declining all-cause mortality risk corresponding to increasing PNI values. PNI demonstrated predictive value for 30-day and 90-day mortality in CAP patients, with AUCs of 0.71 and 0.68, respectively. Combining PNI with CURB-65 enhanced the predictive value of CURB-65. Our investigation identified a significant negative association between the PNI and the risk of mortality in patients with CAP. Additionally, the PNI demonstrated superior predictive value for mortality risk in CAP patients when compared to the CURB-65 scoring system.

Assessing the ability of GPT-4o to visually recognize medications and provide patient education.

Various studies have investigated the ability of ChatGPT (OpenAI) to provide medication information; however, a new promising feature has now been added, which allows visual input and is yet to be evaluated. Here, we aimed to qualitatively assess its ability to visually recognize medications, through medication picture input, and provide patient education via written and visual output. The responses were evaluated by accuracy, precision and clarity using a 4-point Likert-like scale. In regards to handling visual input and providing written responses, GPT-4o was able to recognize all 20 tested medications from packaging pictures, even with blurring, retrieve their active ingredients, identify formulations and dosage forms and provide detailed, yet concise enough, patient education in an almost completely accurate, precise and clear manner with a score of 3.55 ± 0.605 (85%). In contrast, the visual output through GPT-4o generated images illustrating usage instructions contained many errors that would either hinder the effectiveness of the medication or cause direct harm to the patient with a poor score of 1.5 ± 0.577 (16.7%). In conclusion, GPT-4o is capable of identifying medications from pictures and exhibits contrasting patient education performance between written and visual output with very impressive and poor scores, respectively.

Analysis of high-frequency errors and linguistic patterns in EFL medical students' English writing: Insights from a learner corpus.

The perceived language barrier in English is said to hinder, and in certain instances, impede the global dissemination of knowledge, including medical information, to non-native English speakers within medical institutions. As English for medical purposes instructors, we contend that the issue persists in medical universities across various EFL contexts. Medical students face the challenge of presenting their research findings in English for international journals and conferences. Given this, the present research study aimed to compile a comprehensive catalog of high-frequency errors and examine them in recurring linguistic patterns commonly found in the writing of Iranian medical students. In conducting the present study, we developed a learner corpus of 1,040 essays (339,040 words and 18,235 sentences in total). Through using the results obtained from Wordsmith Tools 8 and sifting the leaner corpus, we identified 11 high-frequency errors and five commonly used linguistic patterns. Only five out of 11 high-frequency errors account for 61% of the total number of errors. Results also showed that a majority of errors were of grammatical nature. In this regard, cohesion and cohesive devices (16%) were the most prevalent errors followed by omission/misusing of articles/determiners (14%). Additionally, results showed that discourse markers were extensively used in the corpus (22.07%), followed by hedges (11.42%). The outcomes of this study are expected to assist English for medical purposes instructors in designing focused lesson plans and classroom activities. Ultimately, these efforts might contribute to enhancing medical education in non-English speaking universities.

Biomedical moral enhancement for psychopaths.

This study examines the ethical permissibility of biomedical moral enhancement (BME) for psychopaths, considering both coercive and voluntary approaches. To do so, I will first briefly explain what psychopaths are and some normative implications of these facts. I will then ethically examine three scenarios of BME for psychopaths: (1) coercive BME for non-criminal psychopaths, (2) coercive BME for psychopathic offenders, and (3) voluntary BME for psychopathic offenders. I will argue that coercive BME for non-criminal psychopaths is ethically problematic due to issues of cost, invasion of privacy, and stigmatic effects of compulsory diagnosis. Similarly, I will argue that coercive BME for criminals is impermissible due to violations of the rights to bodily and mental integrity. However, I will show that voluntary BME for offenders may be ethically permissible under certain conditions, challenging the critique that the consent of vulnerable prisoners cannot be considered fully voluntary. I argue that when an offender is provided with sufficient medical and legal information, incentives such as the possibility of parole review based on BME results do not preclude the voluntariness of consent. Ultimately, I aim to advance the debate on BME for psychopaths by delineating and defending conditions for the ethical permissibility of voluntary BME.

AI-Driven Cardiomegaly Detection Using Cutting-Edge Chest X–ray imagery

This project aims to develop an innovative approach for detecting cardiomegaly, a condition characterized by an enlarged heart, using machine learning techniques, specifically Support Vector Machines (SVM), and state-of-the-art chest X-ray imagery. Cardiomegaly serves as a significant indicator of various cardiac diseases, and early detection through accurate imaging analysis can lead to timely intervention and improved patient outcomes. The proposed machine learning solution utilizes SVM algorithms trained on a diverse dataset of chest X-ray images to automatically identify signs of cardiomegaly with high precision and reliability. By harnessing the power of SVM, this system offers a non-invasive and cost-effective method for screening large populations for cardiac abnormalities, facilitating early diagnosis and appropriate medical management. Key features of the developed solution include robust feature extraction techniques, real-time analysis, and integration with existing healthcare infrastructure for seamless implementation in clinical settings. Moreover, the system prioritizes patient privacy and data security by adhering to relevant regulations and standards governing medical imaging and information management. Overall, this project represents a significant advancement in the field of cardiac health monitoring, providing healthcare professionals with a valuable tool for early detection and management of cardiomegaly, ultimately improving patient care and reducing the burden of cardio vascular disease

Utility of Generative Artificial Intelligence for Patient Care Counseling for Mandibular Fractures.

To determine the readability and accuracy of information regarding mandible fractures generated by Chat Generative Pre-trained Transformer (ChatGPT) versions 3.5 and 4o. Patients are increasingly turning to generative artificial intelligence to answer medical queries. To date, the accuracy and readability of responses regarding mandible fractures have not been assessed. Twenty patient questions regarding mandible fractures were developed by querying AlsoAsked (https://alsoasked.com), SearchResponse (https://searchresponse.io), and Answer the Public (https://answerthepublic.com/). Questions were posed to ChatGPT 3.5 and 4o. Readability was assessed by calculating the Flesch Kincaid Reading Ease, Flesch Kincaid Grade Level, number of sentences, and percentage of complex words. Accuracy was assessed by a board-certified facial plastic and reconstructive otolaryngologist using a 5-point Likert Scale. No significant differences were observed between the two versions for readability or accuracy. Readability was above recommended levels for patient education materials. Accuracy was low, and a majority of responses were deemed inappropriate for patient use with multiple inaccuracies and/or missing information. ChatGPT produced responses written at a high level inappropriate for the average patient, in addition to containing several inaccurate statements. Patients and clinicians should be aware of the limitations of generative artificial intelligence when seeking medical information regarding mandible fractures.

Envisioning the Future of the Neurosurgical Operating Room with the Concept of the Medical Metaverse.

The medical metaverse can be defined as a virtual spatiotemporal framework wherein higher-dimensional medical information is generated, exchanged, and utilized through communication among medical personnel or patients. This occurs through the integration of cutting-edge technologies such as augmented reality (AR), virtual reality (VR), artificial intelligence (AI), big data, cloud computing, and others. We can envision a future neurosurgical operating room that utilizes such medical metaverse concept such as shared extended reality (AR/VR) of surgical field, AI-powered intraoperative neurophysiological monitoring, and real-time intraoperative tissue diagnosis. The future neurosurgical operation room will evolve into a true medical metaverse where participants of surgery can communicate in overlapping virtual layers of surgery, monitoring, and diagnosis.

Paediatric Nurses' Personal Accounts of Being Told Not to Disclose Information to Children With Serious Illness-An Interpretative Phenomenological Study.

To explore the experiences, and perceptions of nurses who are told to withhold clinical information from children diagnosed with serious illnesses. An interpretative qualitative phenomenological design was used for the study. Sampling was purposive and data were collected using semi-structured interviews from nurses working in a paediatric setting within the preceding 5 years. Nurse-participants described their personal experiences of withholding situations ('non-disclosure directives'). Their accounts of specific examples of situations ('personal accounts') were extracted from the interview transcripts and analysed using inductive content analysis to identify patterns and concepts within the descriptions. Data management was supported using Dedoose. Nurse-participants were interviewed face-to face and online between November 2019 and December 2020. Twenty-six Australian nurses who have cared for seriously ill children within the preceding 5 years participated in the study. Thirty-nine accounts of non-disclosure situations (personal accounts) were extracted from interview transcripts. Four types of non-disclosure were identified in the personal accounts: withholding information, temporary withholding, lying and combined withholding/lying. The inductive content analysis identified three key aspects of nurse-participants' accounts: beliefs and perceptions (about the child and parents), the nature of the experience and feelings about the experience. Moral distress occurred when nurses' actions conflicted with their moral values in response to a non-disclosure directive, particularly when asked to directly lie to children. Nurses felt disempowered by the parent's authority and the institutional hierarchy that limited their ability to participate in discussions where a non-disclosure directive was given. Nurse-participants were afforded a platform for reflection which proved valuable in allowing them to process their experiences in a non-disclosure situation. Nurses directed to withhold medical information from children should be afforded opportunities for reflection to mitigate moral distress. Nurses should be included in the planning of ethically appropriate responses to withholding directives.

Contemporary and prospective use of azathioprine (AZA) in viral, rheumatic, and dermatological disorders: a review of pharmacogenomic and nanotechnology applications.

Azathioprine (AZA) has been extensively used for immunomodulatory effects in autoimmune disorders and transplantation. This article is proposed to review the contemporary and prospective use of AZA in viral, rheumatic, and dermatological disorders. The primary objective is to draw attention to possible developments in regards to AZA application in recent years, with an emphasis on the use of pharmacogenomics and nanotechnology to improve its efficacy in practice. This study reveals that AZA, having the active metabolites 6-mercaptopurine (6-MP) and 6-thioguanine (6-TG), may be useful in the treatment of systemic lupus erythematosus (SLE), pemphigus vulgaris, and psoriasis. Pharmacogenomic testing of thiopurine methyltransferase (TPMT) and Nudix hydrolase 15 (NUDT15) genotypes minimizes the occurrence of myelosuppression. Furthermore, new formulations of AZA using biocompatible polymers and nanoparticles for drug delivery were reported to improve its efficacy and lower systemic toxicity. This paper aims to establish the multifunctional nature of AZA in modern medicine, thus emphasizing its potential for other applications. Through the combination of pharmacogenomic analysis along with nanotechnology application, AZA makes the promise of enhancing patients' treatment efficacy and extending the stock of medical information available. These advancements offer new possibilities for application of precision medicine and improvements in the use of AZA therapy.

Disparities in Patient Portal Activation and Usage at a Large Pediatric Academic Institution.

Access to personal medical information promotes patient understanding of health issues and enables patient self-advocacy of healthcare needs. The advent of electronic medical record systems and the 2016 21st Century CURES Act promoted and encouraged patient access to personal medical information, yet technology-dependent modalities have often disadvantaged certain communities. We sought to evaluate whether disparities existed in access to patient portals at our institution, the main pediatric care provider in an area serving one million children. We evaluated the activation of patient portal accounts at our institution over the past decade (2010-2021). Portal activation data were analyzed by ethnic background and language preference and income information available based on primary home access location. Further, we evaluated portal activation rates over time and across institutional interventions. A logistic regression model was used to identify important demographic associations with portal account status. Over 1 million patients were served at our pediatric institution over the study period with 47.7% having ever activated their patient portals. Univariate analyses and ultimately logistic regression modeling demonstrated significant differences in portal activation by ethnicity (odds ratio (confidence interval):1.36 (1.34, 1.37)), language preference (1.39 (1.37, 1.40)), and median household income (1.00001 (1.00001, 1.00001)). Interim interventions were successful in improving portal activation rates. Overall, electronic medical record portal activation was less prevalent among Hispanic, non-English speakers, and patients living in communities with lower median household income. Opportunities for interventions exist to reduce healthcare disparities in these underserved communities.

“Design of a Trustworthy Cloud-Native National Digital Health Information Infrastructure for Secure Data Management and Use”

Abstract Since 2022, Malawi Ministry of Health (MoH) designated the development of a National Digital Health Information System (NDHIS) as one of the most important pillars of its national health strategy. This system is built upon a distributed computing infrastructure employing the following state-of-art technologies: (1) digital healthcare devices to capture medical data; (2) Kubernetes-based Cloud-Native Computing architecture to simplify system management and service deployment; (3) Zero-Trust Secure Communication to protect confidentiality, integrity and access rights of medical data transported over the Internet; (4) Trusted Computing to allow medical data to be processed by certified software without compromising data privacy and sovereignty. Trustworthiness, including reliability, security, privacy and business integrity, of this system was ensured by a peer-to-peer network of trusted medical information guards deployed as the gatekeepers of every computing node on this system. This NDHIS shall facilitate Malawi to attain universal health coverage by 2030 through its scalability and operation efficiency. It shall improve medical data quality and security by adopting a paperless approach. It will also enable MoH to offer data rental services to healthcare researchers and AI model developers around the world. This project is spearheaded by the Digital Health Division (DHD) under MoH. The trustworthy computing infrastructure was designed by a taskforce assembled by the DHD in collaboration with Luke International in Norway, and a consortium of hardware and software solution providers in Taiwan. A prototype that can connect community clinics with a district hospital has been tested at the Taiwan Pingtung Christian Hospital.

Interpretation of reference intervals and clinical decision limits

Reference intervals (RI) and clinical decision limits (CDL) are an important part of th e medical information needed to interpret the results of a laboratory tests. The emphasis is on the need to distinguish between the two concepts. RI allows to assess the compliance of the patient’s result with the values detected in a healthy population with a certain probability. CDL is associated with specific diseases and medical risks and may be more significant for clinical decision-making than RI. When interpreting RI and CDL, it is necessary to take into account the possibility of divergence of results on different analytical systems as a potential source of erroneous medical decisions.

Comparative Analysis of Artificial Intelligence Platforms in Generating Post-Operative Instructions for Rhinologic Surgery

AbstractRecently, artificial intelligence (AI) platforms such as ChatGPT and Google Gemini have progressed at a rapid pace. To allow for optimal medical outcomes and patient safety, it is crucial that patients have clearly written post-operative instructions. Patients are increasingly turning to AI platforms for medical information. Our objective was to evaluate the ability of ChatGPT versus Gemini to develop accurate and understandable post-operative instructions for patients undergoing endoscopic sinus surgery (ESS). Postoperative instructions on ESS, balloon sinuplasty, Caldwell Luc surgery, and septoplasty were generated using ChatGPT and Gemini. Measures of readability were calculated. The Patient Education Materials Assessment Tool was utilized to determine Understandability and Actionability. ChatGPT and Gemini were capable of generating understandable post-operative instructions but were poor for actionability and readability. While AI has a promising ability to generate accessible medical information, patients should be aware of its drawbacks especially when seeking postoperative instructions.

CANCER. Is this Forever? Examining the Relationship Between Event Centrality and Fear of Cancer Recurrence from a Cognitive-Behavioral Standpoint

The purpose of this study was to test a moderated mediation model. We first looked into whether fear of a cancer recurrence mediated the effect of time since diagnosis on trauma centrality, a concept rendering the impact of cancer on one’s self-identity. Secondly, we looked into whether the indirect effect would depend on the stage of diagnosis. We expected a more pronounced indirect effect for early stages as opposed to late stages. We acquired data from 234 cancer survivors (78.02% female; Mage= 35.58), who received a cancer diagnosis, were undergoing cancer treatment or had finished their treatment. Together with demographics and basic medical information, participants completed the Fear of Cancer Recurrence Inventory Short Form (FCRI-SF) and the Centrality of Event Scale – the Short - Form (CED-SF). In line with our expectations, the results confirmed an indirect effect of fear of cancer recurrence which was stronger for survivors in the early stage of diagnosis (i.e., I, II) as compared to those in the late stage (i.e., III, IV). Conclusions and Future Directions. The study emphasizes the significance of taking into account both the disease stage at diagnosis and the length of time since diagnosis when creating interventions to help cancer survivors address their fear of cancer recurrence. Theoretical ramifications and interpretive limitations are presented.

Integrating Art in Medical Visualization Techniques

The incorporation of art with medical visualisation techniques offers a significant improvement in the communication of medical information. Traditional methods of medical illustration were primarily concerned with anatomical precision, but introducing artistic aspects can expand knowledge, increase emotional resonance, and produce more effective visual storytelling. This study investigates how artistic principles such as composition, colour theory, and dynamic symmetry can enhance the clarity and effectiveness of medical images. Medical visualisation can go beyond simple representation by combining scientific rigour and artistic flair, resulting in a more profound link between the spectator and the medical facts, which improves patient understanding, physician communication, and educational outcomes. Case studies are offered to demonstrate the multidisciplinary approach’s potential, as well as the obstacles and opportunities it brings for future research. Keywords: Medical visualization, Medical illustration, Artistic integration, Data visualization, Visual communication in medicine

Map-Like Redness Development After Eradication Therapy for Helicobacter pylori Infection: Prospective Multicenter Observational Study.

Map-like redness, pathological intestinal metaplasia, is observed in one-fourth to one-third of patients 1 year after Helicobacter pylori eradication therapy, mainly in the corpus, and is a newly identified endoscopic risk factor for gastric cancer development after eradication. However, it is unclear whether intestinal metaplasia is present before eradication at the site where the map-like redness appears. We aimed to identify endoscopic findings that predict the occurrence of map-like redness before H. pylori eradication. As a prospective multicenter trial, the characteristics of patients in whom map-like redness developed after eradication, and the association between the endoscopic severity of gastritis and the development of map-like redness in patients who underwent endoscopy before and 1-year after eradication were investigated. The rate of map-like redness in all 93 patients 1-year postsuccessful eradication was 30.1% (95% confidence interval [CI]: 21.0-40.5). All patients with map-like redness were endoscopically observed to have intestinal metaplasia before eradication, in the site that subsequently developed map-like redness. Patients who developed map-like redness were older, had more severe intestinal metaplasia and nodularity and a higher total score on the Kyoto Classification of Gastritis both before and after eradication than patients who did not. On multivariate analysis, map-like redness was found to be associated with posttreatment intestinal metaplasia (odds ratio: 8.144; 95% CI: 2.811-23.592). In all patients who developed map-like redness after eradication, endoscopic intestinal metaplasia was observed at the site developed map-like redness before eradication therapy. Map-like redness was especially observed in patients with more severe intestinal metaplasia at 1-year after eradication. Such patients require increased attention at surveillance endoscopy, owing to generally having a higher risk of gastric cancer development. University Hospital Medical Information Network: UMIN000044707.

Role of Charlson comorbidity index in predicting intensive care unit readmission in patients with aortic aneurysm.

The purpose of this study was to investigate the value of the Charlson comorbidity index (CCI) in predicting intensive care unit (ICU) readmission in aortic aneurysm (AA) patients. Patient information came from the Medical Information Mart for Intensive Care- IV (MIMIC-IV) database. The relationship between CCI and ICU readmission was analyzed by restricted cubic spline, generalized linear regression, trend analysis, and hierarchical analysis. The clinical value of CCI in predicting ICU readmission was analyzed by receiver operating characteristic curve, decision curve analysis, XGBoost regression, and random forest regression. A total of 523 patients with AA were enrolled in the study. Patients with AA who were readmitted to the ICU had higher width of red blood cell distribution width (RDW) and higher CCI. CCI had better performance and clinical net benefit for predicting ICU readmission than RDW. An independent nonlinear relationship was found between CCI and ICU readmission. The trend analysis suggested that the risk of ICU readmission increased with higher CCI scores. The hierarchical analysis showed that their association was mainly found in surgery requirement populations regardless of AA types. Further, CCI was found to have better clinical value in predicting ICU readmission of thoracic aortic aneurysm (TAA) patients undergoing surgery. Age, renal disease, chronic lung disease, and dementia were important components of CCI in predicting ICU readmission of TAA patients undergoing surgery. CCI was independently associated with the ICU readmission of AA patients in a positive relationship and had more favorable prediction performance in TAA patients who underwent surgery.

Generalized additive mixed model to evaluate the association between ventilatory ratio and mortality in patients: A retrospective cohort study.

Previous studies have indicated that a higher ventilatory ratio (VR) is associated with mortality. However, it is unknown whether dynamic changes in VR over time affect the prognosis of critically ill patients. This study aims to investigate the significance of VR during the progression of the disease in critically ill patients. The Medical Information Mart for Intensive Care III database was searched to identify critically ill patients. The primary outcome was 30-day mortality. Multivariable Cox regression was used to elucidate the relationship between the VR and mortality. Finally, we employed a generalized additive mixed model to compare trends in VR over time between survivors and non-survivors. A total of 8024 patients were enrolled. Multivariable Cox regression analysis identified a baseline VR ≥1.89 as an independent risk factor predicting 30-day mortality (hazard ratio: 2.10, 95% confidence interval: 1.89-2.33, P < .001) and 90-day mortality (hazard ratio: 2.18, 95% confidence interval: 1.97-2.41, P < .001) after adjusting for potential confounders. In the subgroup analyses, the observed association between VR and 30-day mortality showed consistent direction across most subgroups. The generalized additive mixed model results highlighted that the difference in VR between survivors and non-survivors increased by an average of 0.01 per day after adjusting for several covariates. In conclusion, VR dynamically mirrors pathophysiological changes in critically ill patients and its escalation is linked to higher mortality rates. Monitoring VR's dynamic shifts might offer more immediate prognostic information, thus aiding in timely interventions and risk stratification.