| 李孝熠,朱毅,李聪慧.从“预康复”到“预测性康复”的研究——基于CiteSpace的可视化分析[J].中国康复,2021,36(2):67-71 |
| 从“预康复”到“预测性康复”的研究——基于CiteSpace的可视化分析 |
| Innovation from Prehabilitation to Predictive Rehabilitation: A Visualization Analysis Based on CiteSpace |
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| DOI： |
| 中文关键词: 预康复 CiteSpace 可视化分析 大数据分析 预测性康复 |
| 英文关键词: prehabilitation CiteSpace visual analysis data analysis predictive rehabilitation |
| 基金项目:国家自然科学基金项目（81860875） |
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| 摘要点击次数: 7231 |
| 全文下载次数: 8807 |
| 中文摘要: |
| 目的：对2010～2019年的预康复相关文献进行计量学分析，构建知识图谱，揭示预康复相关领域的研究热点和趋势，为康复治疗提供预测方法。方法：以Web of Science（WOS）核心合集数据库为数据来源，通过CiteSpace对预康复相关文献进行分析，采用引文分析方法以及信息可视化技术，绘制学科、关键词等可视化图谱。结果：共检索到3117篇文献，年度发文量呈总体上升态势。可视化图谱显示，预康复研究涉及众多的学科领域，与外科学、骨科学、肿瘤学和工程学等密切相关。该领域的研究热点包括康复、物理疗法、生活质量等；研究趋势则主要集中在“多中心化”和“术前评估”等方面。结论：本文揭示了预康复的发展趋势和研究热点，验证了可视化软件在预康复研究中的有效性，也为预康复的风险因素管理和并发症处置提供了新思路。国内外大数据与预测性研究的广泛应用，提示我们还可将大数据分析与预康复进一步结合，构建预测模型，进行有效的风险因素预判，从而采取预测性干预，实现从“预康复”到“预测性康复”的转变。 |
| 英文摘要: |
| Objective: To make a quantitative analysis of literature related to prehabilitation between 2010 and 2019, draw knowledge maps, reveal research hotspots and trends in prehabilitation fields, and provide a prediction method for rehabilitation treatment. Methods: Web of Science Core Collection database was taken as the data source, and the visual atlas of disciplines and keywords was drawn by using citation analysis method and information visualization technology. Results: A total of 3,117 articles were retrieved, and the annual number of articles was on the rise. The visual atlas shows that prehabilitation research involves many disciplines and fields, which are closely related to surgery, orthopedics, oncology and more. Research hotspots include rehabilitation, physical therapy, quality of life, etc. The research trend mainly focuses on “multicentric” and “preoperative evaluation”. Conclusion: This paper reveals the frontier and hotspot of prehabilitation research, verifies the effectiveness of visual software in prehabilitation research, and provides a new idea for risk factor management and complication management of prehabilitation. It suggests that we can further use big data analysis to build a model, and take predictive intervention according to the risk factors of patients, so as to realize the transformation from “prehabilitation” to “predictive rehabilitation”. |
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