Risk factors and a predictive nomogram for hemodynamic instability during adrenalectomy for large pheochromocytomas and paragangliomas: A retrospective cohort study

列线图 医学 回顾性队列研究 队列 试验预测值 内科学 曲线下面积 外科
作者
Shijie Li,Zeyu Li,Jianyi Zheng,Xiaonan Chen
出处
期刊:Ejso [Elsevier BV]
卷期号:49 (10): 106964-106964 被引量:6
标识
DOI:10.1016/j.ejso.2023.06.016
摘要

This study aimed to investigate risk factors for intraoperative hemodynamic instability (HDI) and construct a clinical model for predicting intraoperative HDI for large pheochromocytomas and paragangliomas (PPGLs) patients.A single-center retrospective study of the clinicopathological data of patients undergoing surgery for PPGLs larger than 5 cm in diameter was conducted. A total of 215 eligible patients were enrolled in the study. Three advanced statistical methods were used to select independent risk factors in the training cohort for constructing a nomogram for predicting intraoperative HDI. The predictive performance of the model was assessed by area under the curve (AUC), positive predictive value (PPV), negative predictive value (NPV), and calibration. Decision curve analysis (DCA) and clinical impact curves (CIC) were used to assess predictive accuracy and clinical utility. The performance of the nomogram of was further internally validated.Comorbid diabetes mellitus, anemia, hypoproteinemia, 24-h urine vanillylmandelic acid and intraoperative blood transfusion (P < 0.05) were identified as independent risk factors for constructing the nomogram. In the training cohort, the AUC, PPV and NPV of the nomogram were 0.846, 91.6% and 69.2%. In the validation cohort, the AUC, PPV and NPV were 0.842, 91.8% and 63.3%. These showed good predictive power of the model. The calibration curves demonstrated an optimal consistency between the nomogram-predicted and the actual observed survival probability. DCA and CIC examination showed superior clinical relevance.The nomogram can objectively and accurately predict intraoperative HDI in patients with large PPGLs, which can help in individualized pre-treatment decision-making.
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
刚刚
整齐的伯云完成签到,获得积分10
刚刚
ZHANG完成签到,获得积分20
刚刚
1秒前
SciGPT应助乘风的法袍采纳,获得10
1秒前
2秒前
3秒前
所所应助关正卿采纳,获得10
3秒前
搞怪元彤发布了新的文献求助10
4秒前
leoan完成签到,获得积分0
6秒前
Viper完成签到,获得积分10
6秒前
7秒前
初景应助DKO253采纳,获得20
7秒前
科目三应助平淡千风采纳,获得10
8秒前
C·麦塔芬完成签到,获得积分10
8秒前
8秒前
香蕉觅云应助稀饭采纳,获得10
9秒前
10秒前
Iris99发布了新的文献求助10
10秒前
11秒前
11秒前
加壹完成签到 ,获得积分10
11秒前
倩倩小跟班完成签到,获得积分10
11秒前
11秒前
傲来雾关注了科研通微信公众号
12秒前
彭于晏应助yeoman采纳,获得10
12秒前
纳米石头完成签到,获得积分10
12秒前
00发布了新的文献求助10
12秒前
可爱的函函应助向阳采纳,获得10
13秒前
14秒前
酷波er应助整齐的伯云采纳,获得10
14秒前
终究完成签到,获得积分10
15秒前
ncyao发布了新的文献求助10
16秒前
搞怪元彤完成签到,获得积分10
16秒前
悦耳哑铃发布了新的文献求助10
17秒前
bixingyu完成签到,获得积分10
18秒前
重要的如霜应助XF采纳,获得10
18秒前
眼睛大的比巴卜完成签到,获得积分10
18秒前
姜明哲完成签到,获得积分10
18秒前
BALL完成签到,获得积分10
19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
An Introduction to Foreign Language Learning and Teaching 750
The Oxford Handbook of Digital Classical Studies 550
China Pluperfect I: Epistemology of Past and Outside in Chinese Art 520
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
The fast track to determining transfer functions of linear circuits: The student guide 500
The Analytical and Numerical Solution of Electric and Magnetic Fields 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 7621541
求助须知:如何正确求助?哪些是违规求助? 9196693
关于积分的说明 19713396
捐赠科研通 7193081
什么是DOI,文献DOI怎么找? 3272838
关于科研通互助平台的介绍 2435283
邀请新用户注册赠送积分活动 2267974