Hasil untuk "Internal medicine"

H. Uchino, N. Ozono, N. Tanaka

Pamela M. Chiroque-Solano, M Lee Van Horn, Thomas Jaki

Precision medicine seeks to match patients with treatments that produce the greatest benefit. The Predicted Individual Treatment Effect (PITE)-the difference between predicted outcomes under treatment and control-quantifies this benefit but is difficult to estimate due to unobserved counterfactuals, high dimensionality, and complex interactions. We compared 30+ modeling strategies, including penalized and projection-based methods, flexible learners, and tree-ensembles, using a structured simulation framework varying sample size, dimensionality, multicollinearity, and interaction complexity. Performance was measured using root mean squared error (RMSE) for prediction accuracy and directional accuracy (DIR) for correctly classifying benefit versus harm. Internal validation produced optimistic estimates, whereas external validation with distributional shifts and higher-order interactions more clearly revealed model weaknesses. Penalized and projection-based approaches-ridge, lasso, elastic net, partial least squares (PLS), and principal components regression (PCR)-consistently achieved strong RMSE and DIR performance. Flexible learners excelled only under strong signals and sufficient sample sizes. Results highlight robust linear/projection defaults and the necessity of rigorous external validation.

Junying Chen, Zhenyang Cai, Zhiheng Liu et al.

Despite the success of large language models (LLMs) in various domains, their potential in Traditional Chinese Medicine (TCM) remains largely underexplored due to two critical barriers: (1) the scarcity of high-quality TCM data and (2) the inherently multimodal nature of TCM diagnostics, which involve looking, listening, smelling, and pulse-taking. These sensory-rich modalities are beyond the scope of conventional LLMs. To address these challenges, we present ShizhenGPT, the first multimodal LLM tailored for TCM. To overcome data scarcity, we curate the largest TCM dataset to date, comprising 100GB+ of text and 200GB+ of multimodal data, including 1.2M images, 200 hours of audio, and physiological signals. ShizhenGPT is pretrained and instruction-tuned to achieve deep TCM knowledge and multimodal reasoning. For evaluation, we collect recent national TCM qualification exams and build a visual benchmark for Medicinal Recognition and Visual Diagnosis. Experiments demonstrate that ShizhenGPT outperforms comparable-scale LLMs and competes with larger proprietary models. Moreover, it leads in TCM visual understanding among existing multimodal LLMs and demonstrates unified perception across modalities like sound, pulse, smell, and vision, paving the way toward holistic multimodal perception and diagnosis in TCM. Datasets, models, and code are publicly available. We hope this work will inspire further exploration in this field.

Mahmoud Alwakeel, Aditya Nagori, An-Kwok Ian Wong et al.

Large Language Models have been tested on medical student-level questions, but their performance in specialized fields like Critical Care Medicine (CCM) is less explored. This study evaluated Meta-Llama 3.1 models (8B and 70B parameters) on 871 CCM questions. Llama3.1:70B outperformed 8B by 30%, with 60% average accuracy. Performance varied across domains, highest in Research (68.4%) and lowest in Renal (47.9%), highlighting the need for broader future work to improve models across various subspecialty domains.

Yuhao Sun, Albert Tenesa, John Vines

Precision Medicine (PM) transforms the traditional "one-drug-fits-all" paradigm by customising treatments based on individual characteristics, and is an emerging topic for HCI research on digital health. A key element of PM, the Polygenic Risk Score (PRS), uses genetic data to predict an individual's disease risk. Despite its potential, PRS faces barriers to adoption, such as data inclusivity, psychological impact, and public trust. We conducted a mixed-methods study to explore how people perceive PRS, formed of surveys (n=254) and interviews (n=11) with UK-based participants. The interviews were supplemented by interactive storyboards with the ContraVision technique to provoke deeper reflection and discussion. We identified ten key barriers and five themes to PRS adoption and proposed design implications for a responsible PRS framework. To address the complexities of PRS and enhance broader PM practices, we introduce the term Human-Precision Medicine Interaction (HPMI), which integrates, adapts, and extends HCI approaches to better meet these challenges.

Alice Tang, Maria Wei, Anna Haemel et al.

Recent advances in artificial intelligence (AI) and multimodal data collection are revolutionizing dermatology. Generative AI and machine learning approaches offer opportunities to enhance the diagnosis and treatment of inflammatory skin diseases, including atopic dermatitis, psoriasis, hidradenitis suppurativa, and autoimmune connective tissue disease. This review examines the current landscape of AI applications for inflammatory skin diseases and explores how generative AI and machine learning methods can advance the field through deep phenotyping, disease heterogeneity characterization, drug development, personalized medicine, and clinical care. We discuss the promises and challenges of these technologies and present a vision for their integration into clinical practice.

Saiqing Chen, Chunxia Zhang, Yueting Yu

BackgroundHeart failure (HF) represents the terminal phase of multiple cardiovascular conditions and is associated with significant morbidity and mortality rates. Arachidonic acid (AA), an essential fatty acid, plays a crucial role in modulating cardiovascular function under both normal and disease states. The purpose of this research was to examine how AA is related to HF, providing new perspective for individualized treatment.MethodsTranscriptomic datasets were retrieved from the Gene Expression Omnibus (GEO) database. The raw data were consolidated to identify differentially expressed genes (DEGs) and subsequently subjected to bioinformatics analysis. Gene ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed. Signature genes were identified through Least Absolute Shrinkage and Selection Operator (LASSO) regression, Support Vector Machine-Recursive Feature Elimination (SVM-RFE), and Random Forest (RF) algorithms. Receiver Operating Characteristic (ROC) curves were generated for gene evaluation, and a nomogram was developed. An analysis of immune cell infiltration was conducted using Single Sample Gene Set Enrichment Analysis (ssGSEA), and Gene Set Enrichment Analysis (GSEA) was conducted to determine important pathways. Subsequently, we also performed drug sensitivity evaluation. Finally, the expression levels of the identified signature genes in HF samples were confirmed using qRT-PCR analysis.ResultsFour characteristic genes demonstrating favorable performance in the ROC analysis. The comprehensive nomogram developed in this study exhibited enhanced clinical utility. In addition, notable variations in immune cell infiltration levels were detected, and GSEA highlighted key biological pathways.ConclusionThis investigation demonstrated a strong association between arachidonic acid-associated gene expression and heightened risk of HF, offering novel perspectives on the disease's underlying pathological processes and providing potential insights for personalized management of HF.

Sanchita Chakraborty, S.R. Rao, Abhijit Poddar

Mpox virus (MPXV) is the only pathogen that triggered two Public Health Emergency of International Concern (PHEIC) declarations, first in July 2022 and then again in August 2024. The 2022 outbreak was attributed primarily to clade IIb MPXV, specifically lineage B.1. However, the 2024 global outbreak was largely due to the emergence of clade Ib MPXV, which was first identified in the Sud Kivu region of the Democratic Republic of the Congo in 2023. During this period, the transmission route of MPXV transitioned from primarily zoonotic spillovers to sustained human-to-human transmission, disproportionately affecting vulnerable groups such as men-who-have-sex-with-men, immunocompromised individuals and marginalized populations with limited access to healthcare. This shift has been driven by critical mutations in genes associated with viral fitness, immune evasion and transmission dynamics. Moreover, these changes correspond with atypical and often milder yet more transmissible clinical presentations, complicating the detection and management of cases. Despite these challenges, health system preparedness has remained uneven. High-income countries leverage existing infrastructure to facilitate rapid responses through proactive policies and financial commitments. However, many low- and middle-income countries struggle with delayed case detection, limited surge capacity, community unawareness and fragmented outbreak governance. Although diagnostics, vaccines and antivirals have advanced, issues such as accessibility, affordability and distribution have persisted, hindering global solidarity efforts. This narrative review integrates evidence on the evolution of MPXV clades, clinical heterogeneity, and public health responses. Furthermore, by learning from past outbreaks, this review proposes actionable, time-sensitive recommendations to strengthen surveillance, ensure equitable deployment of countermeasures, secure supply chains and embed One Health approaches for increased resilience.

In-Gyu Lee, Jun-Young Oh, Hee-Jung Yu et al.

Recently, with increasing interest in pet healthcare, the demand for computer-aided diagnosis (CAD) systems in veterinary medicine has increased. The development of veterinary CAD has stagnated due to a lack of sufficient radiology data. To overcome the challenge, we propose a generative active learning framework based on a variational autoencoder. This approach aims to alleviate the scarcity of reliable data for CAD systems in veterinary medicine. This study utilizes datasets comprising cardiomegaly radiograph data. After removing annotations and standardizing images, we employed a framework for data augmentation, which consists of a data generation phase and a query phase for filtering the generated data. The experimental results revealed that as the data generated through this framework was added to the training data of the generative model, the frechet inception distance consistently decreased from 84.14 to 50.75 on the radiograph. Subsequently, when the generated data were incorporated into the training of the classification model, the false positive of the confusion matrix also improved from 0.16 to 0.66 on the radiograph. The proposed framework has the potential to address the challenges of data scarcity in medical CAD, contributing to its advancement.

Manlio De Domenico, Luca Allegri, Guido Caldarelli et al.

The adoption of digital twins (DTs) in precision medicine is increasingly viable, propelled by extensive data collection and advancements in artificial intelligence (AI), alongside traditional biomedical methodologies. However, the reliance on black-box predictive models, which utilize large datasets, presents limitations that could impede the broader application of DTs in clinical settings. We argue that hypothesis-driven generative models, particularly multiscale modeling, are essential for boosting the clinical accuracy and relevance of DTs, thereby making a significant impact on healthcare innovation. This paper explores the transformative potential of DTs in healthcare, emphasizing their capability to simulate complex, interdependent biological processes across multiple scales. By integrating generative models with extensive datasets, we propose a scenario-based modeling approach that enables the exploration of diverse therapeutic strategies, thus supporting dynamic clinical decision-making. This method not only leverages advancements in data science and big data for improving disease treatment and prevention but also incorporates insights from complex systems and network science, quantitative biology, and digital medicine, promising substantial advancements in patient care.

Davide Belluomo, Tiziana Calamoneri, Giacomo Paesani et al.

We present a new unified graph-based representation of medical data, combining genetic information and medical records of patients with medical knowledge via a unique knowledge graph. This approach allows us to infer meaningful information and explanations that would be unavailable by looking at each data set separately. The systematic use of different databases, managed throughout the built knowledge graph, gives new insights toward a better understanding of oncology medicine. Indeed, we reduce some useful medical tasks to well-known problems in theoretical computer science for which efficient algorithms exist.

Ben-Gang Zhou, Ming-Wen Guo, Li-Juan Zhang et al.

Background: The efficacy of the 14-day esomeprazole–amoxicillin (EA) dual therapy in eradicating Helicobacter pylori ( H. pylori ) has been widely discussed previously. Vonoprazan, a novel potassium-competitive acid blocker, presents rapid, potent, and long-lasting acid inhibitory effects compared to esomeprazole. However, there is currently a scarcity of direct comparisons between the 10-day vonoprazan–amoxicillin (VA) and the 14-day EA dual therapy for H. pylori eradication. Objectives: This study aimed to compare the efficacy and safety of the 10-day VA and the 14-day EA dual therapy for H. pylori first-line eradication. Design: This study was a prospective, multicenter, open-label, randomized controlled trial. Methods: The study was conducted at 10 hospitals in China. In total, 570 newly diagnosed H. pylori -infected patients were recruited from April 2023 to February 2024. These patients were randomly assigned to either the 10-day VA group (vonoprazan 20 mg twice daily + amoxicillin 1000 mg three times daily) or the 14-day EA group (esomeprazole 20 mg four times daily + amoxicillin 750 mg four times daily). The primary outcome was the eradication rate, with secondary outcomes including adverse events and compliance. Results: The 10-day VA regimen outperformed the 14-day EA regimen in terms of eradication rates in intention-to-treat (ITT) analysis (85.4% vs 76.7%, p  = 0.008), modified ITT analysis (90.7% vs 84.8%, p  = 0.036), and per-protocol (PP) analysis (91.1% versus 85.5%, p  = 0.047). The non-inferiority p -values in all three analyses were less than 0.001. No statistically significant difference was observed in the incidence of adverse events between the two groups (9.1% vs 11.7%, p  = 0.308). The 10-day VA regimen demonstrated higher compliance compared to the 14-day EA regimen ( p  = 0.006). Conclusion: The 10-day VA dual therapy showed a satisfactory eradication rate of 91.1% (PP analysis), demonstrating good safety and better compliance compared to the 14-day EA dual therapy as the first-line eradication. Trial registration: This trial was registered in the Chinese Clinical Trial Registry (registration number: ChiCTR2300070475) on April 12, 2023.

Paulo Ricardo Martins-Filho, Francy Waltília Cruz Araújo, Luiz Carlos Santos-Júnior et al.

Anna Efverman PhD

Background: Expectations may modify outcomes. However, studies often fail to measure expectations. This raises the need for a brief valid and reliable expectancy measure. Objectives: To study treatment expectations in individuals entering acupuncture or rest, validity and test re-test reliability of a single-item expectancy measure graded on a category scale, a Numeric Rating Scale (NRS) and a Visual Analog Scale (VAS), and to identify psychometric differences between the scales. Method: In this methodology study, treatment expectations were measured in 363 participants before they received acupuncture (genuine traditional penetrating or non-penetrating telescopic sham acupuncture, n = 239, 98%, responded) or a control treatment involving just rest (n = 120, 100%, responded), aimed to improve level of relaxation. A treatment expectancy measure, graded on a five-grade category scale, an eight-grade NRS and a 100 mm VAS, was tested for test re-test reliability. Level of expectation and relaxation was measured at baseline, pre- and post-therapy (n = 729 expectancy measurements). Results: The participants scheduled for acupuncture or rest believed moderately (Inter Quartile Range, IQR, moderately-much) and much (IQR moderately-much) the treatment to be effective. The Intra-Class Correlation coefficient versus Kappa coefficient between test and re-test was .868/.868 for the category scale, .820/.820 for the NRS, and .856/.854 for the VAS. The middle step “Believe moderately the treatment to be effective” was equivalent with median 4 (IQR, 3-4) on NRS and median 52 mm (IQR 42-52) on VAS. The response rates were 708 (97%) on the category scale, 707 (97%) on the NRS, and 703 (96%) on the VAS. All three scales discriminated that pre-therapy expectations were more positive in the individuals who reported an improvement in relaxation level ( P < .001-.003). The VAS presented higher responsiveness to detect expectancy changes over time (71% increased expectation), compared to the NRS (52% increased) and the category scale (12% increased), P < .001. Conclusions: Individuals entering acupuncture, or a control intervention, presented positive treatment expectations, and the expectancy measure presented satisfactory reliability, validity, high response rates, sensitiveness, and responsiveness. Integrative cancer therapy researchers who want to control for expectancy-related bias in clinical trials should consider measuring expectation using the single-item expectancy measure.

Gabriella Iannuzzo, Geetank Kamboj, Parinita Barman et al.

Background and aims: Cardiovascular diseases (CVD) pose a significant global health burden. Lowering low-density lipoprotein-cholesterol is the primary therapeutic aim for preventing primary and secondary CVD events. While statins are the standard treatments, their limitations, such as side effects and intolerance in certain patient groups, necessitate exploration of alternative lipid-lowering therapies (LLTs). We systematically reviewed randomised controlled trials (RCTs) evaluating cardiovascular outcomes associated with non-statin LLTs (bempedoic acid, alirocumab, evolocumab, ezetimibe, and inclisiran) in adults with CVD or high cardiovascular risk. Methods: EMBASE, Medline, Cochrane Library, and clinical trial registries were systematically searched for eligible studies, from inception until February 08, 2023. Two reviewers independently screened the studies, with discrepancies resolved by a third reviewer. Data extraction and validation were conducted, and the risk of bias was assessed using the Cochrane Risk-of-Bias tool-2 for RCTs. Results: The search strategy yielded 2104 citations. Post screening for eligibility, nine unique trials/studies (84 publications) were identified. Among these, one trial each was identified for bempedoic acid and alirocumab, three for evolocumab, and four for ezetimibe. No published literature documenting the cardiovascular outcomes of inclisiran was identified. Only one trial (CLEAR Outcomes) included statin-intolerant patients at baseline. Most studies evaluated a 3-component, 4-component, or 5-component major adverse cardiovascular events composite as an outcome along with individual components. The quality of the included trials was found to be fair-to-good. Conclusions: The systematic review findings emphasise the significance of considering non-statin LLTs as viable treatment options for individuals with CVD or high cardiovascular risk who cannot tolerate or achieve optimal lipid control with statin therapy alone.

S. Mangione, L. Nieman

Vahid Reza Nafisi, Roshanak Ghods

Persian Medicine (PM) uses wrist temperature/humidity and pulse to determine a person's health status and temperament. However, the diagnosis may depend on the physician's interpretation, hindering the combination of PM with modern medical methods. This study proposes a system for measuring pulse signals and temperament detection based on PM. The system uses recorded thermal distribution, a temperament questionnaire, and a customized pulse measurement device. The collected data can be sent to a physician via a telecare system for interpretation and prescription of medications. The system was clinically implemented for patient care, assessed the temperaments of 34 participants, and recorded thermal images of the wrist, back of the hand, and entire face. The study suggests that a customized device for measuring pulse waves and other criteria based on PM can be incorporated into a telemedicine system, reducing the dependency on PM specialists for diagnosis.

Krishnan Venkatesan

Objective: The Kulkarni Technique of one-sided dissection with penile invagination allows for single-stage management of panurethral stricture. In this accompanying video, we demonstrate and discuss the use of this technique in urethral reconstruction. Patient and surgical procedure: The patient is a 60-year-old male with a history of stricture treated in the remote past with posterior auricular graft. His-stricture eventually recurred, and he was self-calibrating weekly for 15 years before presenting to us with obstructive lower urinary tract symptoms and recurrent urinary tract infections. Investigation with urethrography revealed an approximately 10 cm urethral stricture extending from the proximal bulbar urethra to mid-penile urethra. No evidence of lichen sclerosus was evident on physical examination.A perineal incision was made, and one-sided dissection carried out on the patient's left-side, dividing the bulbocavernosus muscle to access the urethra dorsally. This dissection was extended towards midline to rotate the urethra off to one side, leaving the right-side neurovascular attachments intact. Once the penis was invaginated, the dissection was extended proximally and distally beyond the extents of the urethral stricture.The urethra was then opened dorsally through the length of stricture and two oral mucosa grafts were quilted onto the adjacent tunica albuginea. The urethral edges are then sewn to the edges of the graft, de-rotating the urethra back into its orthotopic position. A catheter is inserted prior to completion of this urethral closure. The bulbocavernosus muscle edges are reapproximated and the bulbar incision is closed in multiple layers. Results: This patient had an uneventful recovery and a peri‑catheter urethrogram approximately 3 weeks after surgery demonstrated no extravasation, so the catheter was removed. The patient continues to do well with no evidence of recurrence at 3 years follow-up. Previously reported outcomes suggest this is a safe, reproducible, and durably effective technique. Conclusion: The Kulkarni Technique offers a minimally invasive, single stage approach to pan-urethral stricture. It allows for avoidance of a penile incision and minimization of impact on the neurovascular support structures of the anterior urethra.

Yanpeng Feng, Zhiyuan Chen, Yi Xu et al.

IκBζ (encoded by NFKBIZ) is the most recently identified IkappaB family protein. As an atypical member of the IkappaB protein family, NFKBIZ has been the focus of recent studies because of its role in inflammation. Specifically, it is a key gene in the regulation of a variety of inflammatory factors in the NF-KB pathway, thereby affecting the progression of related diseases. In recent years, investigations into NFKBIZ have led to greater understanding of this gene. In this review, we summarize the induction of NFKBIZ and then elucidate its transcription, translation, molecular mechanism and physiological function. Finally, the roles played by NFKBIZ in psoriasis, cancer, kidney injury, autoimmune diseases and other diseases are described. NFKBIZ functions are universal and bidirectional, and therefore, this gene may exert a great influence on the regulation of inflammation and inflammation-related diseases.

Sharli Paphitis, Fatima Akilu, Natasha Chilambo et al.

Background Despite theoretical support for including mental health and psychosocial support (MHPSS) with peacebuilding, few programmes in conflict-affected regions fully integrate these approaches. Aims To describe and assess preliminary outcomes of the Counselling on Wheels programme delivered by the NEEM Foundation in the Borno State of North-East Nigeria. Method We first describe the components of the Counselling on Wheels programme, including education and advocacy for peace and social cohesion through community peacebuilding partnerships and activities, and an MHPSS intervention open to all adults, delivered in groups of eight to ten people. We then conducted secondary analysis of data from 1550 adults who took part in the MHPSS intervention, who provided data at baseline and 1–2 weeks after the final group session. Vulnerability to violent extremism was assessed with a locally developed 80-item scale. Symptoms of common mental disorders were assessed with the Depression, Anxiety and Stress Scale (DASS-21) and Post-Traumatic Stress Disorder Scale (PTSD-8). Data were analysed through a mixed-effect linear regression model, accounting for clustering by community and adjusted for age and gender. Results After taking part in group MHPSS, scores fell for depression (−5.8, 95% CI −6.7 to −5.0), stress (−5.5, 95% CI −6.3 to −4.6), post-traumatic stress disorder (−2.9, 95% CI −3.4 to −2.4) and vulnerability to violent extremism (−44.6, 95% CI −50.6 to −38.6). Conclusions The Counselling on Wheels programme shows promise as a model for integrating MHPSS with community peacebuilding activities in this conflict-affected region of Africa.