Suppr超能文献

机器学习预测围手术期 SARS-CoV-2 感染患者手术死亡率:COVIDSurg 死亡率评分。

Machine learning risk prediction of mortality for patients undergoing surgery with perioperative SARS-CoV-2: the COVIDSurg mortality score.

出版信息

Br J Surg. 2021 Nov 11;108(11):1274-1292. doi: 10.1093/bjs/znab183.

Abstract

To support the global restart of elective surgery, data from an international prospective cohort study of 8492 patients (69 countries) was analysed using artificial intelligence (machine learning techniques) to develop a predictive score for mortality in surgical patients with SARS-CoV-2. We found that patient rather than operation factors were the best predictors and used these to create the COVIDsurg Mortality Score (https://covidsurgrisk.app). Our data demonstrates that it is safe to restart a wide range of surgical services for selected patients.

摘要

为了支持全球选择性手术的重启,我们利用人工智能(机器学习技术)分析了一项针对 8492 名患者(来自 69 个国家)的国际前瞻性队列研究的数据,以开发一种针对 SARS-CoV-2 感染手术患者死亡率的预测评分。我们发现,患者因素而非手术因素是最佳预测因素,我们利用这些因素创建了 COVIDsurg Mortality Score(https://covidsurgrisk.app)。我们的数据表明,对于选定的患者,重启广泛的手术服务是安全的。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ca2/10364925/5d127054ff3d/znab183f1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验