Development and validation of a prediction model for postoperative intensive care unit admission in patients with non-cardiac surgery

布里氏评分 医学 列线图 接收机工作特性 重症监护室 心脏外科 曲线下面积 逻辑回归 急诊医学 重症监护 外科 重症监护医学 内科学 统计 数学
作者
Zhikun Xu,Shihua Yao,Zhongji Jiang,Linhui Hu,Zijun Huang,Quanjun Zeng,Xueyan Liu
出处
期刊:Heart & Lung [Elsevier BV]
卷期号:62: 207-214 被引量:3
标识
DOI:10.1016/j.hrtlng.2023.08.001
摘要

Accurately forecasting patients admitted to the intensive care units (ICUs) after surgery may improve clinical outcomes and guide the allocation of expensive and limited ICU resources. However, studies on predicting postoperative ICU admission in non-cardiac surgery have been limited.To develop and validate a prediction model combining pre- and intraoperative variables to predict ICU admission after non-cardiac surgery.This study is based on data from the Vital Signs DataBase (VitalDB) database. Predictors were selected using the least absolute shrinkage and selection operator regression method and logistic regression to develop a nomogram and an online web calculator. The model was internally verified by 1000-Bootstrap resampling. Performance of model was evaluated using area under the receiver operating characteristic curve (AUC), calibration curve and Brier score. The Youden's index was used to find the optimal nomogram's probability threshold. Clinical utility was assessed by decision curve analysis.This study included 5216 non-cardiac surgery patients; of these, 812 (15.6%) required postoperative ICU admission. Potential predictors included age, ASA classification, surgical department, emergency surgery, preoperative albumin level, preoperative urea nitrogen level, intraoperative crystalloid, intraoperative transfusion, intraoperative catheterization, and surgical time. A nomogram was constructed with an AUC of 0.917 (95% CI: 0.907-0.926) and a Brier score of 0.077. The Bootstrap-adjusted AUC was 0.914; the adjusted Brier score was 0.078. The calibration curve showed good agreement between predicted and actual probabilities; and the decision curve indicated clinical usefulness. Finally, we established an online web calculator for clinical application (https://xuzhikun.shinyapps.io/postopICUadmission1/).We developed and internally validated an easy-to-use nomogram for predicting ICU admission after non-cardiac surgery.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
小佛爱学护理学完成签到,获得积分20
刚刚
1秒前
huang应助无敌小天天采纳,获得20
1秒前
桶装乐事完成签到,获得积分10
1秒前
樊小雾发布了新的文献求助10
1秒前
2秒前
仄予发布了新的文献求助10
2秒前
无敌小宽哥完成签到,获得积分10
3秒前
ss发布了新的文献求助10
3秒前
半醒发布了新的文献求助10
4秒前
852应助zeng采纳,获得10
4秒前
李健应助Gotye0829采纳,获得10
4秒前
无花果应助菲菲采纳,获得10
5秒前
5秒前
领导范儿应助小木虫采纳,获得10
5秒前
王大发布了新的文献求助20
6秒前
农大长工发布了新的文献求助10
6秒前
6秒前
bkagyin应助万金油采纳,获得10
6秒前
orixero应助万金油采纳,获得10
6秒前
7秒前
脑洞疼应助可可采纳,获得10
7秒前
Akim应助zack6119采纳,获得10
7秒前
灿澈完成签到,获得积分10
7秒前
aarrrron发布了新的文献求助10
7秒前
8秒前
8秒前
yxdeng发布了新的文献求助10
8秒前
科研通AI6.2应助achun采纳,获得10
9秒前
AC咪咪完成签到,获得积分10
9秒前
Lucas完成签到,获得积分10
10秒前
fengfengfeng完成签到,获得积分20
11秒前
顾矜应助小满采纳,获得30
11秒前
11秒前
qixiaoxue1101完成签到,获得积分10
11秒前
kkkkki完成签到,获得积分10
11秒前
SanXing三醒发布了新的文献求助10
11秒前
灿澈发布了新的文献求助30
12秒前
稳如老狗完成签到,获得积分10
12秒前
乐乐应助俞孤风采纳,获得10
12秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Principles of town planning: translating concepts to applications 1000
2016 Venous Blood Study (VBS) (Final V3.0) 510
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
The Effective Clinical Neurologist 3ed 500
The Great Hymn to Šamaš 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7702648
求助须知:如何正确求助?哪些是违规求助? 9261083
关于积分的说明 20030434
捐赠科研通 7278251
什么是DOI,文献DOI怎么找? 3294279
关于科研通互助平台的介绍 2449697
邀请新用户注册赠送积分活动 2300929