• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

2型糖尿病患者围手术期护理的数字决策支持:行动呼吁

Digital Decision Support for Perioperative Care of Patients With Type 2 Diabetes: A Call to Action.

作者信息

Cai Jianwen, Li Peiyi, Li Weimin, Hao Xuechao, Li Sheyu, Zhu Tao

机构信息

Department of Anesthesiology, West China Hospital of Sichuan University, No. 17 Section 3 Renmin South Road, Chengdu, 610000, China, 86 18681357952.

Laboratory of Anesthesia and Critical Care Medicine, West China Hospital of Sichuan University, Chengdu, China.

出版信息

JMIR Diabetes. 2025 Apr 8;10:e70475. doi: 10.2196/70475.

DOI:10.2196/70475
PMID:40198903
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11999379/
Abstract

Type 2 diabetes mellitus affects over 500 million people globally, with 10%-20% requiring surgery. Patients with diabetes are at increased risk for perioperative complications, including prolonged hospital stays and higher mortality, primarily due to perioperative hyperglycemia. Managing blood glucose during the perioperative period is challenging, and conventional monitoring is often inadequate to detect rapid fluctuations. Clinical decision support systems (CDSS) are emerging tools to improve perioperative diabetes management by providing real-time glucose data and medication recommendations. This viewpoint examines the role of CDSS in perioperative diabetes care, highlighting their benefits and limitations. CDSS can help manage blood glucose more effectively, preventing both hyperglycemia and hypoglycemia. However, technical and integration challenges, along with clinician acceptance, remain significant barriers.

摘要

全球有超过5亿人患有2型糖尿病,其中10%-20%的患者需要进行手术。糖尿病患者围手术期并发症的风险增加,包括住院时间延长和死亡率升高,主要原因是围手术期高血糖。围手术期血糖管理具有挑战性,传统监测往往不足以检测快速波动。临床决策支持系统(CDSS)是一种新兴工具,通过提供实时血糖数据和用药建议来改善围手术期糖尿病管理。本文观点探讨了CDSS在围手术期糖尿病护理中的作用,强调了其益处和局限性。CDSS有助于更有效地管理血糖,预防高血糖和低血糖。然而,技术和整合挑战以及临床医生的接受度仍然是重大障碍。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d3ba/11999379/70076519a465/diabetes-v10-e70475-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d3ba/11999379/70076519a465/diabetes-v10-e70475-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d3ba/11999379/70076519a465/diabetes-v10-e70475-g001.jpg

相似文献

1
Digital Decision Support for Perioperative Care of Patients With Type 2 Diabetes: A Call to Action.2型糖尿病患者围手术期护理的数字决策支持:行动呼吁
JMIR Diabetes. 2025 Apr 8;10:e70475. doi: 10.2196/70475.
2
Just another tool in their repertoire: uncovering insights into public and patient perspectives on clinicians' use of machine learning in perioperative care.这只是他们全部技能中的另一种工具:揭示公众和患者对于临床医生在围手术期护理中使用机器学习的看法。
J Am Med Inform Assoc. 2025 Jan 1;32(1):150-162. doi: 10.1093/jamia/ocae257.
3
Managing Patients Undergoing Orthopedic Surgery to Improve Glycemic Outcomes.管理接受骨科手术的患者以改善血糖结局。
Curr Diab Rep. 2022 Jan 6;21(12):68. doi: 10.1007/s11892-021-01434-z.
4
Review of electronic decision-support tools for diabetes care: a viable option for low- and middle-income countries?糖尿病护理电子决策支持工具综述:低收入和中等收入国家的可行选择?
J Diabetes Sci Technol. 2011 May 1;5(3):553-70. doi: 10.1177/193229681100500310.
5
Expectations and Requirements of Surgical Staff for an AI-Supported Clinical Decision Support System for Older Patients: Qualitative Study.外科医护人员对用于老年患者的人工智能支持临床决策支持系统的期望与要求:定性研究
JMIR Aging. 2024 Dec 17;7:e57899. doi: 10.2196/57899.
6
Decision-support tools via mobile devices to improve quality of care in primary healthcare settings.移动设备决策支持工具改善基层医疗服务质量。
Cochrane Database Syst Rev. 2021 Jul 27;7(7):CD012944. doi: 10.1002/14651858.CD012944.pub2.
7
Digital tracking, provider decision support systems, and targeted client communication via mobile devices to improve primary health care.通过数字追踪、医疗服务提供者决策支持系统以及借助移动设备与目标客户进行沟通,以改善初级卫生保健。
Cochrane Database Syst Rev. 2025 Apr 7;4(4):CD012925. doi: 10.1002/14651858.CD012925.pub2.
8
The effects of computerised decision support systems on nursing and allied health professional performance and patient outcomes: a systematic review and user contextualisation.计算机化决策支持系统对护理及相关健康专业人员绩效和患者结局的影响:一项系统综述与用户情境化分析
Health Soc Care Deliv Res. 2024 Oct;12(40):1-93. doi: 10.3310/GRNM5147.
9
Management of Individuals With Diabetes at High Risk for Hypoglycemia: An Endocrine Society Clinical Practice Guideline.《低血糖高危糖尿病患者管理:内分泌学会临床实践指南》。
J Clin Endocrinol Metab. 2023 Feb 15;108(3):529-562. doi: 10.1210/clinem/dgac596.
10
User-Oriented Requirements for Artificial Intelligence-Based Clinical Decision Support Systems in Sepsis: Protocol for a Multimethod Research Project.脓毒症中基于人工智能的临床决策支持系统的面向用户需求:多方法研究项目方案
JMIR Res Protoc. 2025 Jan 30;14:e62704. doi: 10.2196/62704.

本文引用的文献

1
Worldwide trends in diabetes prevalence and treatment from 1990 to 2022: a pooled analysis of 1108 population-representative studies with 141 million participants.全球糖尿病患病率和治疗趋势 1990 年至 2022 年:基于 14100 万参与者的 1108 项人群代表性研究的汇总分析。
Lancet. 2024 Nov 23;404(10467):2077-2093. doi: 10.1016/S0140-6736(24)02317-1. Epub 2024 Nov 13.
2
Association between multimorbidity and postoperative mortality in patients undergoing major surgery: a prospective study in 29 countries across Europe.多病症与接受大型手术的患者术后死亡率之间的关联:欧洲 29 个国家的前瞻性研究。
Anaesthesia. 2024 Sep;79(9):945-956. doi: 10.1111/anae.16324. Epub 2024 May 27.
3
Outcomes of clinical decision support systems in real-world perioperative care: a systematic review and meta-analysis.
临床决策支持系统在现实围手术期护理中的效果:一项系统评价和荟萃分析。
Int J Surg. 2024 Dec 1;110(12):8057-8072. doi: 10.1097/JS9.0000000000001821.
4
American Association of Clinical Endocrinology Consensus Statement: Comprehensive Type 2 Diabetes Management Algorithm - 2023 Update.美国临床内分泌学会共识声明:全面 2 型糖尿病管理算法-2023 年更新。
Endocr Pract. 2023 May;29(5):305-340. doi: 10.1016/j.eprac.2023.02.001.
5
[Ontologies Applied in Clinical Decision Support Systems for Diabetes].[应用于糖尿病临床决策支持系统的本体论]
Sichuan Da Xue Xue Bao Yi Xue Ban. 2023 Jan;54(1):208-216. doi: 10.12182/20220860201.
6
Barriers and enablers to implementing and using clinical decision support systems for chronic diseases: a qualitative systematic review and meta-aggregation.实施和使用慢性病临床决策支持系统的障碍与促进因素:一项定性系统评价与元聚合分析
Implement Sci Commun. 2022 Jul 28;3(1):81. doi: 10.1186/s43058-022-00326-x.
7
Diabetes mellitus and perioperative outcomes: a scoping review of the literature.糖尿病与围手术期结局:文献综述
Br J Anaesth. 2022 May;128(5):817-828. doi: 10.1016/j.bja.2022.02.013. Epub 2022 Mar 14.
8
The Perioperative Human Digital Twin.围手术期人体数字孪生模型
Anesth Analg. 2022 Apr 1;134(4):885-892. doi: 10.1213/ANE.0000000000005916.
9
Guidelines and quality criteria for artificial intelligence-based prediction models in healthcare: a scoping review.医疗保健中基于人工智能的预测模型的指南和质量标准:一项范围综述
NPJ Digit Med. 2022 Jan 10;5(1):2. doi: 10.1038/s41746-021-00549-7.
10
Unbox the black-box for the medical explainable AI via multi-modal and multi-centre data fusion: A mini-review, two showcases and beyond.通过多模态和多中心数据融合开启医学可解释人工智能的黑匣子:一篇综述、两个案例展示及其他
Inf Fusion. 2022 Jan;77:29-52. doi: 10.1016/j.inffus.2021.07.016.