Hasil untuk "Internal medicine"

M. Jacob, A. Lopata, M. Dasouki et al.

Rebecca Nalloor, Rebecca Nalloor, Khadijah Shanazz et al.

IntroductionOnly a subset of people who experience a traumatic event develop Post-Traumatic Stress Disorder (PTSD) suggesting that there are susceptibility factors influencing PTSD pathophysiology. While post trauma sequelae factors are extensively studied, susceptibility factors are difficult to study and therefore poorly understood. To address this gap, we previously developed an animal model - Revealing Individual Susceptibility to PTSD-like phenotype (RISP). RISP allows studying susceptibility factors by identifying, before trauma, male rats that are likely to develop a PTSD-like phenotype after trauma. Hypofunctioning prefrontal cortex (PFC) has been reported in people with PTSD, however, it is unclear if it is a susceptibility factor, sequalae factor, or both. Here we tested the hypothesis that male rats classified as Susceptible with RISP will have altered medial prefrontal cortical (mPFC) function prior to a PTSD-inducing trauma.MethodsExperiment 1: Susceptible and Resilient male rats classified with RISP performed spatial exploration and were sacrificed immediately to assess neuronal expression of plasticity-related immediate early genes (Arc and Homer1a) in the medial PFC (mPFC). Experiment 2: Cognitive performance of Susceptible and Resilient rats was evaluated on an attentional set shifting task. Experiment 3: We also analyzed pre-trauma cognitive performance scores of a small group of male military personnel some of whom developed PTSD post-trauma.ResultsExperiment 1: Susceptible rats showed altered expression of plasticity-related immediate early genes in the Prelimbic and Infralimbic subregions of the mPFC following spatial exploration. Experiment 2: Susceptible rats showed deficits in attentional set shifting task only when task demands increased. Experiment 3: Male military personnel who developed PTSD post-trauma showed pre-trauma cognitive deficits in a task involving the PFC.DiscussionSusceptible rats showed mPFC deficits both at the cellular and behavioral level before PTSD-inducing trauma. Combined with the findings from the human data, these results support the hypothesis that mPFC deficits in males exist before trauma and thus are a putative susceptibility factor for PTSD. Whether these deficits are a bona fide susceptibility factor will be determined in future studies by testing if enhancing mPFC function in susceptible individuals before trauma will confer resilience to developing PTSD. Building resilience is crucial for minimizing the number of people suffering from PTSD, given that it is difficult to treat and treatments are resource intensive and benefit only a subpopulation of people suffering from PTSD.

Arti Virkud, Jessie K. Edwards, Michele Jonsson Funk et al.

Identifying optimal medical treatments to improve survival has long been a critical goal of pharmacoepidemiology. Traditionally, we use an average treatment effect measure to compare outcomes between treatment plans. However, new methods leveraging advantages of machine learning combined with the foundational tenets of causal inference are offering an alternative to the average treatment effect. Here, we use three unique, precision medicine algorithms (random forests, residual weighted learning, efficient augmentation relaxed learning) to identify optimal treatment rules where patients receive the optimal treatment as indicated by their clinical history. First, we present a simple hypothetical example and a real-world application among heart failure patients using Medicare claims data. We next demonstrate how the optimal treatment rule improves the absolute risk in a hypothetical, three-modifier setting. Finally, we identify an optimal treatment rule that optimizes the time to outcome in a real-world heart failure setting. In both examples, we compare the average time to death under the optimized, tailored treatment rule with the average time to death under a universal treatment rule to show the benefit of precision medicine methods. The improvement under the optimal treatment rule in the real-world setting is greatest (additional ~9 days under the tailored rule) for survival time free of heart failure readmission.

Wenxuan Wang, Zizhan Ma, Zheng Wang et al.

Large Language Models (LLMs) are transforming healthcare through the development of LLM-based agents that can understand, reason about, and assist with medical tasks. This survey provides a comprehensive review of LLM-based agents in medicine, examining their architectures, applications, and challenges. We analyze the key components of medical agent systems, including system profiles, clinical planning mechanisms, medical reasoning frameworks, and external capacity enhancement. The survey covers major application scenarios such as clinical decision support, medical documentation, training simulations, and healthcare service optimization. We discuss evaluation frameworks and metrics used to assess these agents' performance in healthcare settings. While LLM-based agents show promise in enhancing healthcare delivery, several challenges remain, including hallucination management, multimodal integration, implementation barriers, and ethical considerations. The survey concludes by highlighting future research directions, including advances in medical reasoning inspired by recent developments in LLM architectures, integration with physical systems, and improvements in training simulations. This work provides researchers and practitioners with a structured overview of the current state and future prospects of LLM-based agents in medicine.

Linlin Wang, Shuang Xie, Aoxue Mei et al.

Abstract Purpose Acute coronary syndromes (ACS) is a leading cause of death worldwide. Albumin and globulin are the main components of serum proteins. The albumin-to-globulin ratio (AGR) is often used to assess nutritional status. However, the clinical significance of the AGR in predicting the prognosis of patients with ACS remains unclear. Patients and methods A total of 1408 patients with ACS who underwent percutaneous coronary intervention (PCI) were consecutively enrolled between January 2016 and December 2018 at The Affiliated Hospital of Chengde Medical University. The follow-up endpoints were defined as cardiac death or recurrent acute myocardial infarction. Results A total of 1363 patients responded in the follow-up period, of whom 49 had MACEs. AGR was significantly different between the MACEs and non-MACE groups. The area under the curve for the AGR was 0.619 (P = 0.004, 95% confidence interval [CI]: 0.542–0.697). The optimal cut-off value for the AGR was determined to be 1.350 using Youden’s index. The cumulative survival rate of the low AGR group was significantly lower than that of the high AGR group, according to the Kaplan–Meier curve (log-rank P = 0.008). Multivariate Cox proportional hazards model showed age ≥ 60 years, HR:2.689 (95%CI:1.288–5.615, P = 0.008), left ventricular ejection fraction (LVEF) < 40%, HR: 3.527, (95%CI: 1.357–9.164, P = 0.010), and AGR < 1.350, HR: 2.180, (95%CI: 1.078–4.407, P = 0.030) were all independent risk factors. A restricted cubic spline showed that a decreasing AGR was correlated with increasing risk of MACEs. Conclusion AGR < 1.350 is an independent prognostic risk factor for patients with ACS undergoing PCI and may be a valuable clinical marker for identifying high-risk patients.

Li Chen, Wei Liu, Renshan Cui

Abstract Background To investigate the hope level and identify its associated factors among widowed older adults residing in long-term care facilities. Methods A cross-sectional study was conducted using convenience sampling. 228 widowed older adults meeting inclusion criteria were recruited from several long-term care facilities in Liaoning Province for face-to-face questionnaire surveys. Results The hope level average score among widowed older adults in long-term care facilities was (31.73 ± 3.31). Multiple linear regression analysis revealed that nine factors were significantly associated with hope levels: educational level, duration of widowhood, frequency of children’s visits, pension income, number of chronic diseases, frequency of participation in recreational activities, medical payment method, evaluation of the long-term care facility, and total perceived social support score. These factors collectively explained 81.4% of the variance in hope levels (Adjusted R² = 0.814, F = 96.027, P < 0.001). Conclusion Hope levels among widowed older adults in long-term care facilities were at a moderate-low level. Nursing staff and facility administrators should pay attention to the hope levels of these residents and implement targeted interventions based on the identified associated factors to enhance hope levels and consequently improve their quality of life.

Guangzhi Xiong, Qiao Jin, Zhiyong Lu et al.

While large language models (LLMs) have achieved state-of-the-art performance on a wide range of medical question answering (QA) tasks, they still face challenges with hallucinations and outdated knowledge. Retrieval-augmented generation (RAG) is a promising solution and has been widely adopted. However, a RAG system can involve multiple flexible components, and there is a lack of best practices regarding the optimal RAG setting for various medical purposes. To systematically evaluate such systems, we propose the Medical Information Retrieval-Augmented Generation Evaluation (MIRAGE), a first-of-its-kind benchmark including 7,663 questions from five medical QA datasets. Using MIRAGE, we conducted large-scale experiments with over 1.8 trillion prompt tokens on 41 combinations of different corpora, retrievers, and backbone LLMs through the MedRAG toolkit introduced in this work. Overall, MedRAG improves the accuracy of six different LLMs by up to 18% over chain-of-thought prompting, elevating the performance of GPT-3.5 and Mixtral to GPT-4-level. Our results show that the combination of various medical corpora and retrievers achieves the best performance. In addition, we discovered a log-linear scaling property and the "lost-in-the-middle" effects in medical RAG. We believe our comprehensive evaluations can serve as practical guidelines for implementing RAG systems for medicine.

Oleksandr Bilokon, Nataliya Bilokon, Paul Bilokon

AIAltMed is a cutting-edge platform designed for drug discovery and repurposing. It utilizes Tanimoto similarity to identify structurally similar non-medicinal compounds to known medicinal ones. This preprint introduces AIAltMed, discusses the concept of `AI-driven alternative medicine,' evaluates Tanimoto similarity's advantages and limitations, and details the system's architecture. Furthermore, it explores the benefits of extending the system to include PubChem and outlines a corresponding implementation strategy.

Guoxing Yang, Jianyu Shi, Zan Wang et al.

Pre-training and fine-tuning have emerged as a promising paradigm across various natural language processing (NLP) tasks. The effectiveness of pretrained large language models (LLM) has witnessed further enhancement, holding potential for applications in the field of medicine, particularly in the context of Traditional Chinese Medicine (TCM). However, the application of these general models to specific domains often yields suboptimal results, primarily due to challenges like lack of domain knowledge, unique objectives, and computational efficiency. Furthermore, their effectiveness in specialized domains, such as Traditional Chinese Medicine, requires comprehensive evaluation. To address the above issues, we propose a novel domain specific TCMDA (TCM Domain Adaptation) approach, efficient pre-training with domain-specific corpus. Specifically, we first construct a large TCM-specific corpus, TCM-Corpus-1B, by identifying domain keywords and retreving from general corpus. Then, our TCMDA leverages the LoRA which freezes the pretrained model's weights and uses rank decomposition matrices to efficiently train specific dense layers for pre-training and fine-tuning, efficiently aligning the model with TCM-related tasks, namely TCM-GPT-7B. We further conducted extensive experiments on two TCM tasks, including TCM examination and TCM diagnosis. TCM-GPT-7B archived the best performance across both datasets, outperforming other models by relative increments of 17% and 12% in accuracy, respectively. To the best of our knowledge, our study represents the pioneering validation of domain adaptation of a large language model with 7 billion parameters in TCM domain. We will release both TCMCorpus-1B and TCM-GPT-7B model once accepted to facilitate interdisciplinary development in TCM and NLP, serving as the foundation for further study.

Jeanette Zanker, Daniela Hüser, Adrien Savy et al.

Viral vectors have become important tools for basic research and clinical gene therapy over the past years. However, in vitro testing of vector-derived transgene function can be challenging when specific post-translational modifications are needed for biological activity. Similarly, neuropeptide precursors need to be processed to yield mature neuropeptides. SH-SY5Y is a human neuroblastoma cell line commonly used due to its ability to differentiate into specific neuronal subtypes. In this study, we evaluate the suitability of SH-SY5Y cells in a potency assay for neuropeptide-expressing adeno-associated virus (AAV) vectors. We looked at the impact of neuronal differentiation and compared single-stranded (ss) AAV and self-complementary (sc) AAV transduction at increasing MOIs, RNA transcription kinetics, as well as protein expression and mature neuropeptide production. SH-SY5Y cells proved highly transducible with AAV1 already at low MOIs in the undifferentiated state and even better after neuronal differentiation. Readouts were GFP or neuropeptide mRNA expression. Production of mature neuropeptides was poor in undifferentiated cells. By contrast, differentiated cells produced and sequestered mature neuropeptides into the medium in a MOI-dependent manner.

Eun Kyoung Kim, Hong-Mi Choi, Jong-Hwan Lee et al.

BackgroundDue to increased needs to reduce non-fatal as well as fatal cardiac events, preoperative echocardiography remains part of routine clinical practice in many hospitals. Data on the role of preoperative echocardiography in low-risk non-cardiac surgery (NCS) other than ambulatory surgeries do not exist. We aimed to investigate the role of preoperative echocardiography in predicting postoperative adverse cardiovascular events (CVEs) in asymptomatic patients undergoing low-risk NCS.MethodsThe study population was derived from a retrospective cohort of 1,264 patients who underwent elective low-risk surgery at three tertiary hospitals from June 1, 2021, to June 30, 2021. Breast, distal bone, thyroid, and transurethral surgeries were included. Preoperative examination data including electrocardiography, chest radiography, and echocardiography were collected. The primary outcome was a composite of postoperative adverse CVEs including all-cause death, myocardial infarction, cerebrovascular events, newly diagnosed or acutely decompensated heart failure (HF), lethal arrhythmia such as sustained ventricular tachycardia/fibrillation, and new-onset atrial fibrillation within 30 days after the index surgery.ResultsPreoperative echocardiography was performed in 503 patients (39.8%), most frequently in patients with breast surgery (73.5%), followed by transurethral (37.7%), distal bone (21.6%), and thyroid surgeries (11.9%). Abnormal findings were observed in 5.0% of patients with preoperative echocardiography. Postoperative adverse CVEs occurred in 10 (0.79%) patients. Although a history of previous HF was an independent predictor of postoperative CVE occurrence (adjusted odds ratio, aOR: 17.98; 95% confidence interval, CI: 1.21–266.71, P = 0.036), preoperative echocardiography did not significantly predict CVE in multivariate analysis (P = 0.097). However, in patients who underwent preoperative echocardiography, the presence of abnormal echocardiographic findings was independently associated with development of CVE after NCS (aOR: 23.93; 95% CI: 1.2.28–250.76, P = 0.008). In particular, the presence of wall motion abnormality was a strong predictor of postoperative adverse CVE.ConclusionIn real-world clinical practice, preoperative echocardiography was performed in substantial number of patients with potential cardiac risk even in low-risk NCS, and abnormal findings were independently associated with postoperative CVE. Future studies should identify patients undergoing low-risk NCS for whom preoperative echocardiography would be helpful to predict adverse CVE.

Satheesh Kumar, Guei-Sheung Liu

JunBo Wu, Nathaniel Comfort

Public health is the most recent of the biomedical sciences to be seduced by the trendy moniker "precision." Advocates for "precision public health" (PPH) call for a data-driven, computational approach to public health, leveraging swaths of genomic "big data" to inform public health decision-making. Yet, like precision medicine, PPH oversells the value of genomic data to determine health outcomes, but on a population-level. A large historical literature has shown that over-emphasizing heredity tends to disproportionately harm underserved minorities and disadvantaged communities. By comparing and contrasting PPH with an earlier attempt at using big data and genetics, in the Progressive era (1890-1920), we highlight some potential risks of a genotype-driven preventive public health. We conclude by suggesting that such risks may be avoided by prioritizing data integration across many levels of analysis, from the molecular to the social.

Michael Gilmartin, MD, Jack Collins, MD, Sabina Mason, BSc (Hons), LLB et al.

OBJECTIVES:. Patients discharged from the ICU post-COVID-19 pneumonitis may experience long-term morbidity related to their critical illness, the treatment for this and the ICU environment. The aim of this study was to characterize the cognitive, psychologic, and physical consequences of COVID-19 in patients admitted to the ICU and discharged alive. DESIGN:. Prospective cohort study. SETTING:. Post-intensive care syndrome (PICS) follow-up clinic at Tallaght University Hospital, a tertiary referral center with a 16-bed mixed medical-surgical ICU, including critical care physicians, a psychologist, a physiotherapist, and a research nurse. PATIENTS:. Patients who had been admitted to the ICU in our tertiary referral center with COVID-19 pneumonitis 6 months earlier. INTERVENTIONS:. None. MEASUREMENTS AND MAIN RESULTS:. A total of 22 patients attended the 6-month PICS follow-up clinic following admission to ICU with COVID-19 pneumonitis. Mean grip strength was low at the 6-month follow-up at 24.1 pounds (sd 9.8) with a minimally active median metabolic equivalent (MET) of 970 METs/wk (interquartile range, 0–7,794 METs/wk). Only 59% of patients were independent with regard to their activities of daily living. Eight of 14 patients (57%) had returned to work by 6 months post-ICU discharge. Their mean Intensive Care Psychological Assessment Tool (IPAT) score was 6.6 (sd 4.6) with a Post-Traumatic Stress Disorder Checklist for Diagnostic and Statistical Manual of Mental Disorders-5th Edition (PCL-5) score of 21.1 (sd 17.5) and a mean Montreal Cognitive Assessment (MoCA) score of 24 (sd 8.4); suggestive of mild cognitive impairment. In a multivariable regression model, only Acute Physiology and Chronic Health Evaluation II score was significantly independently associated with MoCA score as a cognitive PICS outcome (beta-coefficient, –1.6; se, 0.6; p = 0.04). None of the predictor variables were significantly independently associated with IPAT and PCL-5 as psychologic outcomes, nor with International Physical Activity Questionnaire-Short Form as a physical PICS outcome. CONCLUSIONS:. In this single-center prospective cohort study, we found that patients have a high burden of physical and psychologic impairment at 6 months following ICU discharge post-COVID-19 pneumonitis; in many cases requiring specialist referrals for long-term input. We advocate for increased resources for this much needed follow-up multidisciplinary intervention for an ever-growing population of patients.

Omar Vázquez-Estrada, Anays Acevedo-Barrera, Alexander Nahmad-Rohen et al.

Light's internal reflectivity near a critical angle is very sensitive to the angle of incidence and the optical properties of the external medium near the interface. Novel applications in biology and medicine of subcritical internal reflection are being pursued. In many practical situations the refractive index of the external medium may vary with respect to its bulk value due to different physical phenomena at surfaces. Thus, there is a pressing need to understand the effects of a refractive-index gradient at a surface for near-critical-angle reflection. In this work we investigate theoretically the reflectivity near the critical angle at an interface with glass assuming the external medium has a continuous depth-dependent refractive index. We present graphs of the internal reflectivity as a function of the angle of incidence, which exhibit the effects of a refractive-index gradient at the interface. We analyse the behaviour of the reflectivity curves before total internal reflection is achieved. Our results provide insight into how one can recognise the existence of a refractive-index gradient at the interface and shed light on the viability of characterising it.

G Jignesh Chowdary, Suganya G, Premalatha M et al.

With the advancements in computer technology, there is a rapid development of intelligent systems to understand the complex relationships in data to make predictions and classifications. Artificail Intelligence based framework is rapidly revolutionizing the healthcare industry. These intelligent systems are built with machine learning and deep learning based robust models for early diagnosis of diseases and demonstrates a promising supplementary diagnostic method for frontline clinical doctors and surgeons. Machine Learning and Deep Learning based systems can streamline and simplify the steps involved in diagnosis of diseases from clinical and image-based data, thus providing significant clinician support and workflow optimization. They mimic human cognition and are even capable of diagnosing diseases that cannot be diagnosed with human intelligence. This paper focuses on the survey of machine learning and deep learning applications in across 16 medical specialties, namely Dental medicine, Haematology, Surgery, Cardiology, Pulmonology, Orthopedics, Radiology, Oncology, General medicine, Psychiatry, Endocrinology, Neurology, Dermatology, Hepatology, Nephrology, Ophthalmology, and Drug discovery. In this paper along with the survey, we discuss the advancements of medical practices with these systems and also the impact of these systems on medical professionals.

Malin Backlund, Per Venge, Lillemor Berntson

Abstract Background The inflammatory process in juvenile idiopathic arthritis (JIA) involves both the innate and the adaptive immune system. The turnover and activity of neutrophil granulocytes may be reflected by proteins secreted from primary or secondary granules and from the cytoplasm of sequestered cells. Our primary aim was to compare the levels of the secondary neutrophil granule protein human neutrophil lipocalin (HNL), in JIA patients and controls, and to explore a possible priming of neutrophils through parallel analyses in plasma and serum. A secondary aim was to relate the levels of HNL to two other well-studied leukocyte proteins, S100A8/A9 and myeloperoxidase (MPO), as well as to clinical aspects of JIA. Methods The concentrations of the three biomarkers in serum, two of them also in plasma, were measured using enzyme-linked immunosorbent assay in 37 children with JIA without medical treatment, in high disease activity based on juvenile arthritis disease activity score 27 (JADAS27), 32 children on medical treatment, mainly in lower disease activity, and 16 healthy children. We assessed for differences between two groups using the Mann-Whitney U test, and used the Kruskal-Wallis test for multiple group comparisons. Spearman rank correlation, linear and multiple regression analyses were used for evaluation of associations between biomarker concentrations and clinical scores. Results The concentrations of HNL and MPO in serum were significantly increased in children with JIA (p < 0.001, p = 0.002) compared with healthy children, but we found no difference in the plasma levels of HNL and MPO between children with JIA and controls. The serum concentrations of MPO and HNL were unaffected by medical treatment, but S100A8/A9 was reduced by medical treatment and correlated with JADAS27 in both univariate (r = 0.58, p < 0.001) and multivariate (r = 0.59, p < 0.001) analyses. Conclusions Neutrophil granulocytes in children with JIA are primed to release primary and secondary granule proteins, without relation to medical treatment, whereas signs of increased turnover and sequestration of neutrophil granulocytes are reduced by treatment. Levels of neutrophil-originating proteins in serum most likely reflect underlying disease activities of JIA.

R. García-Ramos, D. Santos-García, A. Alonso-Cánovas et al.

Introduction: Many diseases associated with hyperkinetic movement disorders manifest in women of childbearing age. It is important to understand the risks of these diseases during pregnancy, and the potential risks of treatment for the fetus. Objectives: This study aims to define the clinical characteristics and the factors affecting the lives of women of childbearing age with dystonia, chorea, Tourette syndrome, tremor, and restless legs syndrome, and to establish guidelines for management of pregnancy and breastfeeding in these patients. Results: This consensus document was developed through an exhaustive literature search and a discussion of the content by a group of movement disorder experts from the Spanish Society of Neurology. Conclusions: We must evaluate the risks and benefits of treatment in all women with hyperkinetic movement disorders, whether pre-existing or with onset during pregnancy, and aim to reduce effective doses as much as possible or to administer drugs only when necessary. In hereditary diseases, families should be offered genetic counselling. It is important to recognise movement disorders triggered during pregnancy, such as certain types of chorea and restless legs syndrome. Resumen: Introducción: Muchas enfermedades que cursan con trastornos del movimiento hipercinético debutan o afectan a mujeres en edad fértil. Es importante conocer los riesgos que tienen las mujeres con estas enfermedades durante el embarazo así como los posibles efectos de los tratamientos sobre el feto. Objetivos: Definir las características clínicas y los factores que condicionan la vida de la mujer en edad fértil con distonía, corea, síndrome de Tourette, temblor y síndrome de piernas inquietas. Definir una guía de actuación y manejo del embarazo y lactancia en las pacientes con esta enfermedad. Desarrollo: Este documento de consenso se ha realizado mediante una búsqueda bibliográfica exhaustiva y discusión de los contenidos llevadas a cabo por un grupo de expertos en trastornos del movimiento de la Sociedad Española de Neurología (SEN). Conclusiones: En todas las mujeres que padecen o debutan con trastornos del movimiento hipercinéticos se debe valorar el riesgo-beneficio de los tratamientos, reducir al máximo la dosis eficaz o administrarlo de forma puntual en los casos en que sea posible. En aquellas patologías de causa hereditaria es importante un consejo genético para las familias. Es importante reconocer los trastornos del movimiento desencadenados durante el embarazo como determinadas coreas y el síndrome de piernas inquietas.

N. T. Bagraev, L. E. Klyachkin, A. M. Malyarenko et al.

A spectrometer based on silicon nanosandwiches (SNS) is proposed for problems of personalized medicine. SNS structures exhibit properties of terahertz (THz) emitter and receiver of the THz response of biological tissue. Measurements of the current-voltage curves of the SNS structure make it possible to analyze the spectral composition of the THz response of biological tissue and determine relative contributions of various proteins and amino acids contained in the structure of DNA oligonucleotides and the corresponding compounds. Evident advantages of the proposed method are related to the fact that the THz response can be directly obtained from living biological tissue and, hence, used for express analysis of the DNA oligonucleotides. Tests of several control groups show that the further analysis of the specific features of the spectral peaks of the SNS current-voltage curves is of interest for methods of personalized diagnostics and treatment.