Hasil untuk "Medicine"

N. Henderson, F. Rieder, T. Wynn

J. Acosta, G. Falcone, P. Rajpurkar et al.

M. Dash, F. Chiellini, R. Ottenbrite et al.

R. Epstein, R. Street

Patient-centered care has now made it to center stage in discussions of quality. Enshrined by the Institute of Medicine’s “quality chasm” report as 1 of 6 key elements of high-quality care,[1][1] health care institutions, health planners, congressional representatives, and hospital public

D. Moher, A. Liberati, J. Tetzlaff et al.

Editor's Note: PTJ 's Editorial Board has adopted PRISMA to help PTJ better communicate research to physical therapists. For more, read Chris Maher's [editorial][1] starting on page 870. Membership of the PRISMA Group is provided in the Acknowledgments . This article has been reprinted with permission from the Annals of Internal Medicine from Moher D, Liberati A, Tetzlaff J, Altman DG, The PRISMA Group. Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement. Ann Intern Med . Available at: . The authors jointly hold copyright of this article. This article has also been published in PLoS Medicine , BMJ , Journal of Clinical Epidemiology , and Open Medicine . Copyright © 2009 Moher et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. [1]: http://www.ptjournal.org/cgi/content/full/89/9/870

E. Von Elm, D. Altman, M. Egger et al.

Much biomedical research is observational. The reporting of such research is often inadequate, which hampers the assessment of its strengths and weaknesses and of a study's generalisability. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Initiative developed recommendations on what should be included in an accurate and complete report of an observational study. We defined the scope of the recommendations to cover three main study designs: cohort, case-control, and cross-sectional studies. We convened a 2-day workshop in September 2004, with methodologists, researchers, and journal editors to draft a checklist of items. This list was subsequently revised during several meetings of the coordinating group and in e-mail discussions with the larger group of STROBE contributors, taking into account empirical evidence and methodological considerations. The workshop and the subsequent iterative process of consultation and revision resulted in a checklist of 22 items (the STROBE Statement) that relate to the title, abstract, introduction, methods, results, and discussion sections of articles. 18 items are common to all three study designs and four are specific for cohort, case-control, or cross-sectional studies. A detailed Explanation and Elaboration document is published separately and is freely available on the Web sites of PLoS Medicine, Annals of Internal Medicine, and Epidemiology. We hope that the STROBE Statement will contribute to improving the quality of reporting of observational studies.

W. Richardson, M. Wilson, J. Nishikawa et al.

P. Croskerry

Yanqing Xie, Wenjing Zhang

IntroductionThe Consistency Evaluation Policy of Generic Drugs is a major quality-oriented regulatory reform in China’s pharmaceutical manufacturing industry. Whether and how this policy facilitates the integration of the innovation chain and the industrial chain at the enterprise level remains insufficiently examined. This study evaluates the policy effect and investigates potential mechanisms.MethodsThis study used panel data on A-share listed pharmaceutical enterprises from 2013 to 2023. Enterprises were treated as the micro-level carriers of both the innovation chain and the industrial chain, and a enterprise-level index was constructed to measure their integration. A difference-in-differences (DID) design was employed to estimate the impact of the Consistency Evaluation Policy of Generic Drugs. Mechanism analyses focused on government subsidies and market concentration, and heterogeneity was assessed by market demand and total factor productivity (TFP).ResultsThe Consistency Evaluation Policy of Generic Drugs significantly promoted the integration of the innovation chain and the industrial chain. Mechanism tests suggested that the effect operated through two channels: increased government subsidies and higher market concentration. The positive effect was stronger among enterprises facing larger market demand. Moreover, the effect was significant for enterprises with higher TFP, while it was not statistically significant for enterprises with lower TFP.DiscussionThese findings suggest that policy implementation can be strengthened by (1) improving the depth and precision of the Consistency Evaluation Policy of Generic Drugs, (2) enhancing the targeting of government subsidies and supporting an appropriate degree of industry concentration where warranted, and (3) adopting differentiated guidance to stimulate enterprise vitality through multiple measures.

Mohammad Khodadad, Ali Shiraee Kasmaee, Mahdi Astaraki et al.

Medical text embedding models are foundational to a wide array of healthcare applications, ranging from clinical decision support and biomedical information retrieval to medical question answering, yet they remain hampered by two critical shortcomings. First, most models are trained on a narrow slice of medical and biological data, beside not being up to date in terms of methodology, making them ill suited to capture the diversity of terminology and semantics encountered in practice. Second, existing evaluations are often inadequate: even widely used benchmarks fail to generalize across the full spectrum of real world medical tasks. To address these gaps, we leverage MEDTE, a GTE model extensively fine-tuned on diverse medical corpora through self-supervised contrastive learning across multiple data sources, to deliver robust medical text embeddings. Alongside this model, we propose a comprehensive benchmark suite of 51 tasks spanning classification, clustering, pair classification, and retrieval modeled on the Massive Text Embedding Benchmark (MTEB) but tailored to the nuances of medical text. Our results demonstrate that this combined approach not only establishes a robust evaluation framework but also yields embeddings that consistently outperform state of the art alternatives in different tasks.

Jonathan Brady, Vijay Chandiramani, Michelle Chatwin et al.

This report relates to a study group hosted by the EPSRC funded network, Integrating data-driven BIOphysical models into REspiratory MEdicine (BIOREME), and supported by SofTMech and Innovate UK, Business Connect. The BIOREME network hosts events, including this study group, to bring together multi-disciplinary researchers, clinicians, companies and charities to catalyse research in the applications of mathematical modelling for respiratory medicine. The goal of this study group was to provide an interface between companies, clinicians, and mathematicians to develop mathematical tools to the problems presented. The study group was held at The University of Glasgow on the 17 - 21 June 2024 and was attended by 16 participants from 8 different institutions. Below details the technical report of one of the challenges and the methods developed by the team of researchers who worked on this challenge.

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.

Clara Barfod Parellada, Leigh C. Ward, Anne Mette Skovgaard et al.

Objective: Body composition takes a key position in monitoring obesity risk in children. Bioelectrical impedance analysis (BIA) offers a promising, non-invasive method, suitable for field use and young children. However, existing BIA protocols are not tailored to this age group, leaving a knowledge gap on procedures feasible and acceptable to children, parents, and health professionals. This study aimed to develop and assess the feasibility of implementing a standardised protocol for BIA measurements in young children. Methods: The settings of community health nurses (CHNs) in Denmark were used to develop a standardised protocol for BIA measurements of two-year-old children (January 2022–March 2025). Feasibility was evaluated in a community-based sample of 72 children, evaluating suitability, practicality, adaptation, resources, and acceptability. Results: The BIA protocol was developed through an iterative process exploring the children's reactions and cooperation during assessments. The final protocol was tested on 70 children (mean age 24.21 ± 1.21 months). A total of 50 children (71 %) completed the BIA measurements. CHNs reported the procedures as feasible, though challenges included child cooperation, equipment availability, and technical difficulties. Most parents (96 %) found procedures acceptable, and 79 % perceived their child accepted them. Conclusions: This first study to develop and test a standardised BIA protocol tailored young children, demonstrates feasibility in home settings and high acceptability among parents, children, and CHNs. Although no normative BIA data exists for young children, our findings support the potential for integrating body composition monitoring into community-based early obesity prevention programmes, conditioning developmentally appropriate assessment and training health professionals.

Alex Ferreira da Silva, Franciele Jesus Lima, Alyne Riani Moreira et al.

Aberrant Rho-associated kinase function could be associated with increased bone fragility. Since cigarette smoke (CS) exposure promotes the increase in bone fragility due to changes in bone tissue components, this study aimed to investigate how CS exposure could modulate the Rho kinase-associated bone structural changes. Mice were assigned to four groups: control; smoke; control with Rho kinase inhibitor administration; and smoke with a Rho kinase inhibitor. Bone samples were obtained to assess bone histomorphometry analysis, type I collagen composition, and MEPE expression in trabeculae. We observed that CS exposure induced decreased trabecular and osteoid thickness. A concomitant increase in the osteoclastic and erosion surfaces and a decrease in the mineralization surface were observed. Additionally, CS exposure decreased the type I collagen and MEPE expression. Rho kinase inhibitor administration recovered the bone mineralization and the collagen type I deposition. Conclusions: CS exposure increases Rho kinase activity in bone cells, leading to structural changes. The administration of a Rho GTPases inhibitor partially reverses these effects, likely due to the recovery in osteoblast activity.

Keya Ghosh, Tahia Ahmed Logno, Tridip Das et al.

Isolation of zoonotic Campylobacter species has been standardized through the ISO 10272:2017 protocol. However, application of the protocol in a LMIC country failed to isolate Campylobacter due to extended-spectrum beta-lactamase (ESBL) producing Escherichia coli overgrowth during the Campylobacter selective enrichment phase. The aim of the study was to identify the contaminants and explore ways to mitigate them. A set of 25 non-Campylobacter contaminants isolated from chicken cecal samples grown on modified charcoal-cefoperazone-deoxycholate agar (mCCDA) during Campylobacter isolation were included. All isolates were screened for species identification and the presence of selected ESBL producing genes. Minimum inhibitory concentrations of tazobactam were measured using a microbroth dilution technique. The Campylobacter isolation protocol was then modified to inhibit the contaminants by adding the required tazobactam supplement to Preston broth or to mCCDA. All contaminants were found to be E. coli carrying at least one of the ESBL-producing genes blaTEM, blaCTX or blaSHV. The MIC of tazobactam sodium for ESBL-producing E. coli strains grown in Preston broth was at least 128 mg/L. Preston broth supplemented with tazobactam at 128 mg/L inhibited the growth of ESBL-producing E. coli but did not inhibit the growth of C. jejuni or C. coli. Interestingly, mCCDA plates supplemented with tazobactam at a much lower concentration of 4 mg/L could also prevent growth of ESBL-producing E. coli even without broth enrichment, increasing the efficiency of isolation of Campylobacter. Direct inoculation of cecal materials to mCCDA supplemented with tazobactam at 4 mg/L was recommended as the most cost-effective way to conduct Campylobacter surveillance targeting the cecal matrix instead of directly following ISO 10272:2017 protocol.

Yifan Yang, Qiao Jin, Furong Huang et al.

The integration of Large Language Models (LLMs) into healthcare applications offers promising advancements in medical diagnostics, treatment recommendations, and patient care. However, the susceptibility of LLMs to adversarial attacks poses a significant threat, potentially leading to harmful outcomes in delicate medical contexts. This study investigates the vulnerability of LLMs to two types of adversarial attacks in three medical tasks. Utilizing real-world patient data, we demonstrate that both open-source and proprietary LLMs are susceptible to manipulation across multiple tasks. This research further reveals that domain-specific tasks demand more adversarial data in model fine-tuning than general domain tasks for effective attack execution, especially for more capable models. We discover that while integrating adversarial data does not markedly degrade overall model performance on medical benchmarks, it does lead to noticeable shifts in fine-tuned model weights, suggesting a potential pathway for detecting and countering model attacks. This research highlights the urgent need for robust security measures and the development of defensive mechanisms to safeguard LLMs in medical applications, to ensure their safe and effective deployment in healthcare settings.

Pengcheng Qiu, Chaoyi Wu, Xiaoman Zhang et al.

The development of open-source, multilingual medical language models can benefit a wide, linguistically diverse audience from different regions. To promote this domain, we present contributions from the following: First, we construct a multilingual medical corpus, containing approximately 25.5B tokens encompassing 6 main languages, termed as MMedC, enabling auto-regressive domain adaptation for general LLMs; Second, to monitor the development of multilingual medical LLMs, we propose a multilingual medical multi-choice question-answering benchmark with rationale, termed as MMedBench; Third, we have assessed a number of open-source large language models (LLMs) on our benchmark, along with those further auto-regressive trained on MMedC. Our final model, MMed-Llama 3, with only 8B parameters, achieves superior performance compared to all other open-source models on both MMedBench and English benchmarks, even rivaling GPT-4. In conclusion, in this work, we present a large-scale corpus, a benchmark and a series of models to support the development of multilingual medical LLMs.

Nikita Neveditsin, Pawan Lingras, Vijay Mago

This paper explores the advancements and applications of language models in healthcare, focusing on their clinical use cases. It examines the evolution from early encoder-based systems requiring extensive fine-tuning to state-of-the-art large language and multimodal models capable of integrating text and visual data through in-context learning. The analysis emphasizes locally deployable models, which enhance data privacy and operational autonomy, and their applications in tasks such as text generation, classification, information extraction, and conversational systems. The paper also highlights a structured organization of tasks and a tiered ethical approach, providing a valuable resource for researchers and practitioners, while discussing key challenges related to ethics, evaluation, and implementation.

Soaad Hossain, James Rasalingam, Arhum Waheed et al.

With the growing interest in using AI and machine learning (ML) in medicine, there is an increasing number of literature covering the application and ethics of using AI and ML in areas of medicine such as clinical psychiatry. The problem is that there is little literature covering the economic aspects associated with using ML in clinical psychiatry. This study addresses this gap by specifically studying the economic implications of using ML in clinical psychiatry. In this paper, we evaluate the economic implications of using ML in clinical psychiatry through using three problem-oriented case studies, literature on economics, socioeconomic and medical AI, and two types of health economic evaluations. In addition, we provide details on fairness, legal, ethics and other considerations for ML in clinical psychiatry.

Ghadeer O. Ghosheh, Jin Li, Tingting Zhu

With the widespread of machine learning models for healthcare applications, there is increased interest in building applications for personalized medicine. Despite the plethora of proposed research for personalized medicine, very few focus on representing missingness and learning from the missingness patterns in time-series Electronic Health Records (EHR) data. The lack of focus on missingness representation in an individualized way limits the full utilization of machine learning applications towards true personalization. In this brief communication, we highlight new insights into patterns of missingness with real-world examples and implications of missingness in EHRs. The insights in this work aim to bridge the gap between theoretical assumptions and practical observations in real-world EHRs. We hope this work will open new doors for exploring directions for better representation in predictive modelling for true personalization.