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Sustaining e-health innovations in a complex hospital environment: learning through evidence. 在复杂的医院环境中保持电子医疗创新:通过证据学习。
Q1 HEALTH CARE SCIENCES & SERVICES Pub Date : 2024-04-30 eCollection Date: 2024-01-01 DOI: 10.3389/fdgth.2024.1346085
Mirou Jaana, Erika MacPhee, Heather Sherrard, Mark Walker

Implementing and sustaining technological innovations in healthcare is a complex process. Commonly, innovations are abandoned due to unsuccessful attempts to sustain and scale-up post implementation. Limited information is available on what characterizes successful e-health innovations and the enabling factors that can lead to their sustainability in complex hospital environments. We present a successful implementation, sustainability and scale-up of a virtual care program consisting of three e-health applications (telemedicine, telehome monitoring, and interactive voice response) in a major cardiac care hospital in Canada. We describe their evolution and adaptation over time, present the innovative approach for their "business case" and funding that supported their implementation, and identify key factors that enabled their sustainability and success, which may inform future research and serve as a benchmark for other health care organizations. Despite resource constraints, e-health innovations can be deployed and successfully sustained in complex healthcare settings contingent key considerations: simplifying technology to make it intuitive for patients; providing significant value proposition that is research supported to influence policy changes; involving early supporters of adoption from administrative and clinical staff; engaging patients throughout the innovation cycle; and partnering with industry/technology providers.

在医疗保健领域实施和维持技术创新是一个复杂的过程。通常情况下,创新成果会因为在实施后未能成功维持和推广而被放弃。关于成功的电子医疗创新有哪些特点,以及在复杂的医院环境中实现创新的可持续性有哪些有利因素,这方面的信息十分有限。我们介绍了加拿大一家大型心脏病治疗医院成功实施、维持和推广虚拟医疗项目的情况,该项目由三种电子医疗应用(远程医疗、远程家庭监测和交互式语音应答)组成。我们描述了这些应用随时间推移而发生的演变和调整,介绍了其 "商业案例 "的创新方法和支持其实施的资金,并确定了使其得以持续和成功的关键因素,这些因素可为今后的研究提供参考,并可作为其他医疗机构的基准。尽管资源有限,但电子医疗创新仍可在复杂的医疗环境中部署并成功维持,关键考虑因素包括:简化技术,使其对患者而言更直观;提供有研究支持的重要价值主张,以影响政策变化;让行政和临床人员成为采用创新的早期支持者;让患者参与整个创新周期;以及与行业/技术提供商合作。
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引用次数: 0
Editorial: Digital mental health and wellbeing under crisis. 社论:危机下的数字心理健康与福祉
Q1 HEALTH CARE SCIENCES & SERVICES Pub Date : 2024-04-29 eCollection Date: 2024-01-01 DOI: 10.3389/fdgth.2024.1404444
Koustuv Saha, Kokil Jaidka, Jennifer Kim, Jina Suh
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引用次数: 0
Blockchain integration in healthcare: a comprehensive investigation of use cases, performance issues, and mitigation strategies. 医疗保健领域的区块链整合:对使用案例、性能问题和缓解策略的全面调查。
Q1 HEALTH CARE SCIENCES & SERVICES Pub Date : 2024-04-26 eCollection Date: 2024-01-01 DOI: 10.3389/fdgth.2024.1359858
Meenavolu S B Kasyapa, C Vanmathi

Healthcare is a critical area where blockchain technology (BT) is being heralded as a potential game-changer for facilitating secure and efficient data sharing. The purpose of this review is to examine BT applications, performance challenges, and solutions in healthcare. To begin, This review paper explores popular blockchain networks for data exchange, encompassing both public and permissioned platforms, such as Ethereum and Hyperledger Fabric. This paper analyzes the potential applications of BT's decentralized, immutable, and smart contract capabilities in healthcare settings, including secure and interoperable health data exchange, patient consent management, drug supply chain oversight, and clinical trial management. The healthcare industry might greatly benefit from the increased privacy, transparency, and accessibility that these technologies provide. Despite BT's promising medical uses, the technology is not without its drawbacks. High energy consumption, throughput, and scalability are all concerns. We wrapped up by discussing the solutions that have been implemented, including consensus processes, scalability measures like sharding, and off-chain transactions that are designed to mitigate the drawbacks.

医疗保健是一个关键领域,区块链技术(BT)被誉为促进安全高效数据共享的潜在游戏规则改变者。本综述旨在研究区块链技术在医疗保健领域的应用、性能挑战和解决方案。首先,本文探讨了用于数据交换的流行区块链网络,包括以太坊和 Hyperledger Fabric 等公共平台和许可平台。本文分析了 BT 的去中心化、不可篡改和智能合约功能在医疗保健领域的潜在应用,包括安全和可互操作的健康数据交换、患者同意书管理、药品供应链监督和临床试验管理。医疗保健行业可能会从这些技术提供的更高的隐私性、透明度和可访问性中大大受益。尽管 BT 在医疗领域的应用前景广阔,但该技术也并非没有缺点。高能耗、吞吐量和可扩展性都是令人担忧的问题。最后,我们讨论了已经实施的解决方案,包括共识流程、分片等可扩展性措施,以及旨在减轻缺点的链外交易。
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引用次数: 0
Discussion paper: implications for the further development of the successfully in emergency medicine implemented AUD2IT-algorithm. 讨论文件:进一步发展在急诊医学中成功实施的 AUD2IT 算法的意义。
Q1 HEALTH CARE SCIENCES & SERVICES Pub Date : 2024-04-04 eCollection Date: 2024-01-01 DOI: 10.3389/fdgth.2024.1249454
Christopher Przestrzelski, Antonina Jakob, Clemens Jakob, Felix R Hoffmann

The AUD2IT-algorithm is a tool to structure the data, which is collected during an emergency treatment. The goal is on the one hand to structure the documentation of the data and on the other hand to give a standardised data structure for the report during handover of an emergency patient. AUD2IT-algorithm was developed to provide residents a documentation aid, which helps to structure the medical reports without getting lost in unimportant details or forgetting important information. The sequence of anamnesis, clinical examination, considering a differential diagnosis, technical diagnostics, interpretation and therapy is rather an academic classification than a description of the real workflow. In a real setting, most of these steps take place simultaneously. Therefore, the application of the AUD2IT-algorithm should also be carried out according to the real processes. A big advantage of the AUD2IT-algorithm is that it can be used as a structure for the entire treatment process and also is entirely usable as a handover protocol within this process to make sure, that the existing state of knowledge is ensured at each point of a team-timeout. PR-E-(AUD2IT)-algorithm makes it possible to document a treatment process that, in principle, does not have to be limited to the field of emergency medicine. Also, in the outpatient treatment the PR-E-(AUD2IT)-algorithm could be used and further developed. One example could be the preparation and allocation of needed resources at the general practitioner. The algorithm is a standardised tool that can be used by healthcare professionals of any level of training. It gives the user a sense of security in their daily work.

AUD2IT 算法是一种结构化数据的工具,用于在急诊治疗过程中收集数据。其目的一方面是对数据进行结构化记录,另一方面是为急诊病人交接过程中的报告提供标准化的数据结构。开发 AUD2IT 算法的目的是为住院医师提供记录辅助工具,帮助他们安排医疗报告的结构,避免迷失在不重要的细节中或遗忘重要信息。从病史、临床检查、鉴别诊断、技术诊断、解释到治疗的顺序是一种学术分类,而不是对实际工作流程的描述。在实际环境中,这些步骤大多是同时进行的。因此,AUD2IT 算法的应用也应根据实际流程进行。AUD2IT 算法的一大优势在于,它可以作为整个治疗流程的结构,也完全可以作为该流程中的交接协议,以确保在团队中断的每一个点上都能保证现有的知识状态。PR-E-(AUD2IT)算法可以记录治疗过程,原则上不局限于急诊医学领域。此外,PR-E-(AUD2IT)算法还可用于门诊治疗并得到进一步发展。其中一个例子可以是全科医生对所需资源的准备和分配。该算法是一种标准化工具,任何培训水平的医护人员都可以使用。它让用户在日常工作中倍感安全。
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引用次数: 0
eHealth implementation in Europe: a scoping review on legal, ethical, financial, and technological aspects. 欧洲的电子保健实施情况:法律、伦理、财务和技术方面的范围审查。
Q1 HEALTH CARE SCIENCES & SERVICES Pub Date : 2024-03-08 eCollection Date: 2024-01-01 DOI: 10.3389/fdgth.2024.1332707
Britt E Bente, Anne Van Dongen, Ruud Verdaasdonk, Lisette van Gemert-Pijnen

Background: The evolution of eHealth development has shifted from standalone tools to comprehensive digital health environments, fostering data exchange among diverse stakeholders and systems. Nevertheless, existing research and implementation frameworks have primarily emphasized technological and organizational aspects of eHealth implementation, overlooking the intricate legal, ethical, and financial considerations. It is essential to discover what legal, ethical, financial, and technological challenges should be considered to ensure successful and sustainable implementation of eHealth.

Objective: This review aims to provide insights into barriers and facilitators of legal, ethical, financial, and technological aspects for successful implementation of complex eHealth technologies, which impacts multiple levels and multiple stakeholders.

Methods: A scoping review was conducted by querying PubMed, Scopus, Web of Science, and ACM Digital Library (2018-2023) for studies describing the implementation process of eHealth technologies that facilitate data exchange. Studies solely reporting clinical outcomes or conducted outside Europe were excluded. Two independent reviewers selected the studies. A conceptual framework was constructed through axial and inductive coding, extracting data from literature on legal, ethical, financial, and technological aspects of eHealth implementation. This framework guided systematic extraction and interpretation.

Results: The search resulted in 7.308 studies that were screened for eligibility, of which 35 (0.48%) were included. Legal barriers revolve around data confidentiality and security, necessitating clear regulatory guidelines. Ethical barriers span consent, responsibility, liability, and validation complexities, necessitating robust frameworks. Financial barriers stem from inadequate funding, requiring (commercial) partnerships and business models. Technological issues include interoperability, integration, and malfunctioning, necessitating strategies for enhancing data reliability, improving accessibility, and aligning eHealth technology with existing systems for smoother integration.

Conclusions: This research highlights the multifaceted nature of eHealth implementation, encompassing legal, ethical, financial, and technological considerations. Collaborative stakeholder engagement is paramount for effective decision-making and aligns with the transition from standalone eHealth tools to integrated digital health environments. Identifying suitable stakeholders and recognizing their stakes and values enriches implementation strategies with expertise and guidance across all aspects. Future research should explore the timing of these considerations and practical solutions for regulatory compliance, funding, navigation of responsibility and liability, and business models for reimbursement strategies.

背景:电子医疗的发展已从独立的工具转变为全面的数字医疗环境,促进了不同利益相关者和系统之间的数据交换。然而,现有的研究和实施框架主要强调电子医疗实施的技术和组织方面,而忽略了错综复杂的法律、伦理和财务方面的考虑。有必要了解应考虑哪些法律、伦理、财务和技术挑战,以确保电子医疗的成功和可持续实施:本综述旨在深入探讨法律、伦理、财务和技术方面的障碍和促进因素,以便成功实施复杂的电子医疗技术,这将对多个层面和多个利益相关者产生影响:通过查询 PubMed、Scopus、Web of Science 和 ACM 数字图书馆(2018-2023 年),对描述促进数据交换的电子健康技术实施过程的研究进行了范围界定。仅报告临床结果或在欧洲以外进行的研究被排除在外。两位独立审稿人对研究进行了筛选。通过轴向编码和归纳编码,从有关电子医疗实施的法律、伦理、财务和技术方面的文献中提取数据,构建了一个概念框架。该框架为系统性提取和解释提供了指导:通过检索,筛选出 7308 项研究符合条件,其中 35 项(0.48%)被纳入。法律障碍围绕数据的保密性和安全性,需要明确的监管准则。伦理障碍涉及同意、责任、义务和验证的复杂性,因此需要强有力的框架。资金障碍源于资金不足,需要(商业)伙伴关系和业务模式。技术问题包括互操作性、集成和故障,因此需要制定战略来提高数据可靠性、改善可访问性,并使电子健康技术与现有系统保持一致,以实现更顺畅的集成:本研究强调了电子医疗实施的多面性,包括法律、道德、财务和技术方面的考虑。利益相关者的合作参与对于有效决策至关重要,并与从独立的电子医疗工具向集成的数字医疗环境过渡相一致。确定合适的利益相关者并认识到他们的利害关系和价值观,可以丰富实施策略,为其提供各方面的专业知识和指导。未来的研究应探讨这些考虑因素的时间安排,以及监管合规、资金、责任和义务的引导以及报销策略的商业模式等方面的实用解决方案。
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引用次数: 0
Toward mechanistic medical digital twins: some use cases in immunology. 迈向机理医学数字双胞胎:免疫学中的一些用例。
IF 3.2 Q1 HEALTH CARE SCIENCES & SERVICES Pub Date : 2024-03-07 eCollection Date: 2024-01-01 DOI: 10.3389/fdgth.2024.1349595
Reinhard Laubenbacher, Fred Adler, Gary An, Filippo Castiglione, Stephen Eubank, Luis L Fonseca, James Glazier, Tomas Helikar, Marti Jett-Tilton, Denise Kirschner, Paul Macklin, Borna Mehrad, Beth Moore, Virginia Pasour, Ilya Shmulevich, Amber Smith, Isabel Voigt, Thomas E Yankeelov, Tjalf Ziemssen

A fundamental challenge for personalized medicine is to capture enough of the complexity of an individual patient to determine an optimal way to keep them healthy or restore their health. This will require personalized computational models of sufficient resolution and with enough mechanistic information to provide actionable information to the clinician. Such personalized models are increasingly referred to as medical digital twins. Digital twin technology for health applications is still in its infancy, and extensive research and development is required. This article focuses on several projects in different stages of development that can lead to specific-and practical-medical digital twins or digital twin modeling platforms. It emerged from a two-day forum on problems related to medical digital twins, particularly those involving an immune system component. Open access video recordings of the forum discussions are available.

个性化医疗面临的一个基本挑战是,如何充分捕捉个体患者的复杂性,以确定保持其健康或恢复其健康的最佳方法。这就要求个性化计算模型具有足够的分辨率和足够的机理信息,以便为临床医生提供可操作的信息。这种个性化模型越来越多地被称为医学数字孪生。用于医疗应用的数字孪生技术仍处于起步阶段,需要进行广泛的研究和开发。本文重点介绍几个处于不同开发阶段的项目,这些项目可以开发出具体实用的医疗数字孪生或数字孪生建模平台。本文是为期两天的医学数字孪生相关问题论坛的成果,尤其是那些涉及免疫系统的问题。论坛讨论的视频录像可公开获取。
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引用次数: 0
Enhancing patient outcomes: the role of clinical utility in guiding healthcare providers in curating radiology AI applications. 提高患者疗效:临床实用性在指导医疗服务提供者策划放射学人工智能应用中的作用。
Q1 HEALTH CARE SCIENCES & SERVICES Pub Date : 2024-03-07 eCollection Date: 2024-01-01 DOI: 10.3389/fdgth.2024.1359383
Franziska Lobig, Jacob Graham, Apeksha Damania, Brian Sattin, Joana Reis, Prateek Bharadwaj

With advancements in artificial intelligence (AI) dominating the headlines, diagnostic imaging radiology is no exception to the accelerating role that AI is playing in today's technology landscape. The number of AI-driven radiology diagnostic imaging applications (digital diagnostics) that are both commercially available and in-development is rapidly expanding as are the potential benefits these tools can deliver for patients and providers alike. Healthcare providers seeking to harness the potential benefits of digital diagnostics may consider evaluating these tools and their corresponding use cases in a systematic and structured manner to ensure optimal capital deployment, resource utilization, and, ultimately, patient outcomes-or clinical utility. We propose several guiding themes when using clinical utility to curate digital diagnostics.

人工智能(AI)的发展占据了各大媒体的头条,放射诊断成像技术也不例外,人工智能在当今的技术领域正扮演着越来越重要的角色。人工智能驱动的放射诊断成像应用(数字诊断)的数量正在迅速增加,这些应用既有商业化的,也有正在开发中的,而这些工具能为患者和医疗服务提供者带来的潜在益处也在迅速扩大。医疗服务提供商在寻求利用数字诊断学的潜在优势时,可以考虑以系统化和结构化的方式评估这些工具及其相应的用例,以确保最佳的资本部署、资源利用,并最终实现患者的治疗效果或临床效用。在利用临床效用来策划数字诊断时,我们提出了几个指导性主题。
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引用次数: 0
Smart hospital: achieving interoperability and raw data collection from medical devices in clinical routine. 智能医院:实现临床常规医疗设备的互操作性和原始数据收集。
Q1 HEALTH CARE SCIENCES & SERVICES Pub Date : 2024-03-06 eCollection Date: 2024-01-01 DOI: 10.3389/fdgth.2024.1341475
Eimo Martens, Hans-Ulrich Haase, Giulio Mastella, Andreas Henkel, Christoph Spinner, Franziska Hahn, Congyu Zou, Augusto Fava Sanches, Julia Allescher, Daniel Heid, Elena Strauss, Melanie-Maria Maier, Mark Lachmann, Georg Schmidt, Dominik Westphal, Tobias Haufe, David Federle, Daniel Rueckert, Martin Boeker, Matthias Becker, Karl-Ludwig Laugwitz, Alexander Steger, Alexander Müller

Introduction: Today, modern technology is used to diagnose and treat cardiovascular disease. These medical devices provide exact measures and raw data such as imaging data or biosignals. So far, the Broad Integration of These Health Data into Hospital Information Technology Structures-Especially in Germany-is Lacking, and if data integration takes place, only non-Evaluable Findings are Usually Integrated into the Hospital Information Technology Structures. A Comprehensive Integration of raw Data and Structured Medical Information has not yet Been Established. The aim of this project was to design and implement an interoperable database (cardio-vascular-information-system, CVIS) for the automated integration of al medical device data (parameters and raw data) in cardio-vascular medicine.

Methods: The CVIS serves as a data integration and preparation system at the interface between the various devices and the hospital IT infrastructure. In our project, we were able to establish a database with integration of proprietary device interfaces, which could be integrated into the electronic health record (EHR) with various HL7 and web interfaces.

Results: In the period between 1.7.2020 and 30.6.2022, the data integrated into this database were evaluated. During this time, 114,858 patients were automatically included in the database and medical data of 50,295 of them were entered. For technical examinations, more than 4.5 million readings (an average of 28.5 per examination) and 684,696 image data and raw signals (28,935 ECG files, 655,761 structured reports, 91,113 x-ray objects, 559,648 ultrasound objects in 54 different examination types, 5,000 endoscopy objects) were integrated into the database. Over 10.2 million bidirectional HL7 messages (approximately 14,000/day) were successfully processed. 98,458 documents were transferred to the central document management system, 55,154 materials (average 7.77 per order) were recorded and stored in the database, 21,196 diagnoses and 50,353 services/OPS were recorded and transferred. On average, 3.3 examinations per patient were recorded; in addition, there are an average of 13 laboratory examinations.

Discussion: Fully automated data integration from medical devices including the raw data is feasible and already creates a comprehensive database for multimodal modern analysis approaches in a short time. This is the basis for national and international projects by extracting research data using FHIR.

简介如今,现代技术已被用于诊断和治疗心血管疾病。这些医疗设备可提供精确的测量数据和原始数据,如成像数据或生物信号。到目前为止,这些健康数据还没有被广泛整合到医院信息技术结构中(尤其是在德国),即使进行了数据整合,通常也只是将无价值的结果整合到医院信息技术结构中。原始数据和结构化医疗信息的全面整合尚未建立。本项目旨在设计和实施一个可互操作的数据库(心血管信息系统,CVIS),用于自动整合心血管医学中所有医疗设备数据(参数和原始数据):方法:CVIS 是各种设备与医院 IT 基础设施之间的数据集成和准备系统。在我们的项目中,我们建立了一个集成了专有设备接口的数据库,该数据库可通过各种 HL7 和网络接口集成到电子病历(EHR)中:在 2020 年 7 月 1 日至 2022 年 6 月 30 日期间,我们对整合到该数据库中的数据进行了评估。在此期间,共有 114 858 名患者被自动纳入数据库,其中 50 295 人的医疗数据已被输入。在技术检查方面,超过 450 万个读数(平均每个检查 28.5 个读数)、684,696 个图像数据和原始信号(28,935 个心电图文件、655,761 个结构化报告、91,113 个 X 光对象、54 种不同检查类型中的 559,648 个超声波对象、5,000 个内窥镜检查对象)被纳入数据库。成功处理了 1020 多万条双向 HL7 信息(每天约 14000 条)。98,458 份文件被传送到中央文件管理系统,55,154 份材料(平均每份订单 7.77 份)被记录并储存在数据库中,21,196 项诊断和 50,353 项服务/OPS 被记录并传送。平均每个病人记录了 3.3 次检查;此外,平均还有 13 次实验室检查:讨论:医疗设备的全自动数据整合(包括原始数据)是可行的,并且已经在短时间内为多模式现代分析方法创建了一个全面的数据库。这是通过使用 FHIR 提取研究数据开展国内和国际项目的基础。
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引用次数: 0
Digital loneliness-changes of social recognition through AI companions. 数字孤独--通过人工智能伴侣改变社会认知。
Q1 HEALTH CARE SCIENCES & SERVICES Pub Date : 2024-03-05 eCollection Date: 2024-01-01 DOI: 10.3389/fdgth.2024.1281037
Kerrin Artemis Jacobs

Inherent to the experience of loneliness is a significant change of meaningful relatedness that (usually negatively) affects a person's relationship to self and others. This paper goes beyond a purely subjective-phenomenological description of individual suffering by emphasizing loneliness as a symptomatic expression of distortions of social recognition relations. Where there is loneliness, a recognition relation has changed. Most societies face an increase in loneliness among all groups of their population, and this sheds light on the reproduction conditions of social integration and inclusion. These functions are essential lifeworldly components of social cohesion and wellbeing. This study asks whether "social" AI promotes these societal success goals of social integration of lonely people. The increasing tendency to regard AI Companions (AICs) as reproducers of adequate recognition is critically discussed with this review. My skepticism requires further justification, especially as a large portion of sociopolitical prevention efforts aim to fight an increase of loneliness primarily with digital strategies. I will argue that AICs rather reproduce than sustainably reduce the pathodynamics of loneliness: loneliness gets simply "digitized."

孤独感的内在体验是有意义的关系发生了重大变化,这种变化(通常是负面的)影响了一个人与自我和他人的关系。本文超越了对个人痛苦的纯主观现象学描述,强调孤独是社会认可关系扭曲的症状表现。哪里存在孤独,哪里的认可关系就发生了变化。大多数社会的所有人群都面临着孤独感增加的问题,这揭示了社会融合和包容的再生产条件。这些功能是社会凝聚力和福祉的基本生活世界组成部分。本研究提出的问题是,"社交 "人工智能是否能促进孤独者融入社会的这些社会成功目标。越来越多的人倾向于将人工智能伴侣(AIC)视为充分认可的再现者,本评论对此进行了批判性讨论。我的怀疑需要更多的理由,尤其是社会政治预防工作的很大一部分都旨在主要通过数字战略来对抗孤独感的增加。我将论证,"AIC "与其说是可持续地减少孤独的病理动力,不如说是在复制孤独:孤独被简单地 "数字化 "了。
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引用次数: 0
Unlocking the potential of telehealth in Africa for HIV: opportunities, challenges, and pathways to equitable healthcare delivery. 释放非洲远程保健在防治艾滋病毒方面的潜力:机遇、挑战和公平提供保健服务的途径。
Q1 HEALTH CARE SCIENCES & SERVICES Pub Date : 2024-03-04 eCollection Date: 2024-01-01 DOI: 10.3389/fdgth.2024.1278223
Diego F Cuadros, Qian Huang, Thulile Mathenjwa, Dickman Gareta, Chayanika Devi, Godfrey Musuka
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引用次数: 0
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