草稿与最终系统地图的更新
本数据集包含转甲状腺素蛋白心脏淀粉样变性测试系统地图的草稿与终稿更新，反映共设计工作坊的系统复杂性。
基本信息
资源简介
草稿与最终系统地图的更新
【数据集背景】
本数据集源站标题为《Updates between the draft and final systems map.》。源站首次发布：2026-01-19。
【数据内容】
源站原始描述：Background Heart failure is a clinical syndrome resulting from numerous pathological conditions. One cause of heart failure, transthyretin cardiac amyloidosis, presents insidiously with common and seemingly unrelated symptoms. New treatments for cardiac amyloidosis are available that extend and improve life. However, providers are not testing patients for transthyretin cardiac amyloidosis. We took a systems science approach to explore the system of care for transthyretin cardiac amyloidosis test…
【数据结构与技术规格】
文件数 1 个，合计 5.63 KB。Table 3.xls：application/vnd.ms-excel，5.63 KB。数据集 DOI：10.1371/journal.pone.0339063.t003。
【主题与分类】
源站学科分类：Medicine、Genetics、Biotechnology、Cancer、Infectious Diseases、Virology。主题标签：tasked workshop attendees、systems science approach、seemingly unrelated symptoms、qualitative matrix analysis、numerous pathological conditions、design workshop using、clinical syndrome resulting、system evaluation theory、transthyretin cardiac amyloidosis、system map using。
【适用方向】
影像类数据可用于医学图像分析模型（检测、分割、分类）的训练与评测，也可用于标注质量与成像参数相关性的研究。
【获取与许可】
源站页面：https://plos.figshare.com/articles/dataset/_p_Updates_between_the_draft_and_final_systems_map_p_/31089790
使用许可：CC BY 4.0（https://creativecommons.org/licenses/by/4.0/）。
规范引用：Ball, Sherry L.; Koskan, Alexis; Guzman, Jenice; Dev, Sandesh (2026). Updates between the draft and final systems map.. PLOS ONE. Dataset
下载信息
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使用方式
数据集获取（Figshare）
- 源站标题：<p>Updates between the draft and final systems map.</p>
- DOI：10.1371/journal.pone.0339063.t003
- 发布日期：2026-01-19
- 文件数：1 个
- 文件总体积：5.63 KB
- 源站页面：https://plos.figshare.com/articles/dataset/_p_Updates_between_the_draft_and_final_systems_map_p_/31089790
命令行下载
curl -L -o "Table 3.xls" "https://ndownloader.figshare.com/files/61099996"
文件清单
Table 3.xls（5.63 KB）
文件总体积 5.63 KB（源站 API 实测）。
数据说明
Background
Heart failure is a clinical syndrome resulting from numerous pathological conditions. One cause of heart failure, transthyretin cardiac amyloidosis, presents insidiously with common and seemingly unrelated symptoms. New treatments for cardiac amyloidosis are available that extend and improve life. However, providers are not testing patients for transthyretin cardiac amyloidosis. We took a systems science approach to explore the system of care for transthyretin cardiac amyloidosis testing by depicting the healthcare system from patient presentation to treatment. Our goal was to define an ideal healthcare system to improve the uptake of testing protocols and enhance patient outcomes.
Methods
We assembled clinicians, researchers, and patients to participate in a co-design workshop using the first step of System Evaluation Theory to define an ideal testing and diagnostic protocol using transthyretin cardiac amyloidosis as a case study. We tasked workshop attendees with defining the patient and clinician journey from symptom presentation to diagnosis. We generated a system map using a qualitative matrix analysis of a transcript of the workshop discussion.
Results
The matrix analysis organized input from all stakeholders, allowing for the creation of a system map that reveals the complexity of the transthyretin cardiac amyloidosis testing process and potential implementation strategies to improve the efficiency and effectiveness of the system. This methodology successfully yielded generalizable elements of a testing protocol and testable strategies to facilitate the implementation of a protocol adapted to fit local site needs.
Conclusions
The substeps outlined within System Evaluation Theory Step 1 helped identify an ideal system for testing and diagnosing transthyretin cardiac amyloidosis care that could be applied to specific settings to identify, improve, and implement protocols for other complex diseases.
许可
CC BY 4.0
引用
学术使用请引用 DOI 10.1371/journal.pone.0339063.t003（source: https://plos.figshare.com/articles/dataset/_p_Updates_between_the_draft_and_final_systems_map_p_/31089790）。
数据缺失？
依托陕西、四川两大基地，我们与超过十家三甲医院建立直接合作关系，覆盖合规授权、采集治理、专业标注、数据交付的全流程，为AI医疗团队提供即拿即用的高质量临床数据。
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