列线图
可视化
急性肾损伤
败血症
医学
计算机科学
重症监护医学
数据科学
数据挖掘
内科学
作者
Jing Li,Ruibin Meng,Luheng Guo,Linlin Gu,Cuiping Hao,Meng Shi
出处
期刊:PubMed
[National Institutes of Health]
日期:2024-10-01
卷期号:36 (10): 1069-1074
标识
DOI:10.3760/cma.j.cn121430-20240102-00003
摘要
Female, hypertension, vasopressin usage, and SCr are the main risk factors for sAKI in patients with sepsis. The sAKI predictive model constructed based on these factors can help clinical doctors identifying high-risk patients as early as possible, and intervene in a timely manner to provide preventive effects. Compared with the common static nomogram, online dynamic nomogram can make predictive models clearer, more intuitive, and easier.
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