Development and Validation of a Nomogram for Predicting the Long-Term Survival in Patients With Chronic Thromboembolic Pulmonary Hypertension

列线图 医学 比例危险模型 内科学 多元统计 体质指数 慢性血栓栓塞性肺高压 多元分析 队列 心脏病学 生存分析 肺动脉高压 脑利钠肽 心力衰竭 统计 数学
作者
Song Hu,Jiang-Shan Tan,Sheng Liu,Tingting Guo,Wu Song,Fu-Hua Peng,Yan Wu,Xin Gao,Lu Hua
出处
期刊:American Journal of Cardiology [Elsevier BV]
卷期号:163: 109-116 被引量:3
标识
DOI:10.1016/j.amjcard.2021.09.045
摘要

There remains a lack of prognosis models for patients with chronic thromboembolic pulmonary hypertension (CTEPH). This study aims to develop a nomogram predicting 3-, 5-, and 7-year survival in patients with CTEPH and verify the prognostic model. Patients with CTEPH diagnosed in Fuwai Hospital were enrolled consecutively between May 2013 and May 2019. Among them, 70% were randomly split into a training set and the other 30% as a validation set for external validation. Cox proportional hazards model was used to identify the potential survival-related factors which were candidate variables for the establishment of nomogram and the final model was internally validated by the bootstrap method. A total of 350 patients were included in the final analysis and the median follow-up period of the whole cohort was 51.2 months. Multivariate analysis of Cox proportional hazards regression showed body mass index, mean right atrial pressure, N-terminal pro-brain natriuretic peptide (per 500 ng/ml increase in concentration), presence of anemia, and main treatment choice were the independent risk factors of mortality. The nomogram demonstrated good discrimination with the corrected C-index of 0.82 in the training set, and the C-index of 0.80 (95% CI: 0.70 to 0.91) in the external validation set. The calibration plots also showed a good agreement between predicted and actual survival in both training and validation sets. In conclusion, we developed an easy-to-use nomogram with good apparent performance using 5 readily available variables, which may help physicians to identify CTEPH patients at high risk for poor prognosis and implement medical interventions.
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
米九完成签到,获得积分10
刚刚
严易云发布了新的文献求助10
刚刚
刚刚
Akim应助现代鸣凤采纳,获得10
2秒前
玥越发布了新的文献求助10
2秒前
祟祟发布了新的文献求助10
2秒前
3秒前
可爱的函函应助jfz采纳,获得10
3秒前
香蕉觅云应助Evaporate采纳,获得10
5秒前
科研通AI5应助YANGTIAN采纳,获得10
5秒前
科研通AI5应助ZJX采纳,获得10
6秒前
Owen应助钼yanghua采纳,获得10
7秒前
yyyrrr完成签到,获得积分10
7秒前
9秒前
羽化尘发布了新的文献求助10
9秒前
9秒前
九日完成签到,获得积分10
10秒前
拓跋问儿发布了新的文献求助10
11秒前
11秒前
AAA下水工王哥完成签到,获得积分10
11秒前
11秒前
巷陌完成签到 ,获得积分10
12秒前
13秒前
13秒前
路宝发布了新的文献求助10
14秒前
刘l发布了新的文献求助10
15秒前
HEIKU应助jackten采纳,获得10
15秒前
15秒前
莱茵发布了新的文献求助10
15秒前
16秒前
16秒前
巷陌发布了新的文献求助10
16秒前
小樊同学发布了新的文献求助10
16秒前
zj发布了新的文献求助20
16秒前
所所应助Marlo采纳,获得10
16秒前
万能图书馆应助林夕采纳,获得10
16秒前
17秒前
William_l_c发布了新的文献求助10
17秒前
共享精神应助理论界萌新采纳,获得10
18秒前
18秒前
高分求助中
Worked Bone, Antler, Ivory, and Keratinous Materials 1000
Algorithmic Mathematics in Machine Learning 500
Разработка метода ускоренного контроля качества электрохромных устройств 500
Getting Published in SSCI Journals: 200+ Questions and Answers for Absolute Beginners 300
Advances in Underwater Acoustics, Structural Acoustics, and Computational Methodologies 300
The Monocyte-to-HDL ratio (MHR) as a prognostic and diagnostic biomarker in Acute Ischemic Stroke: A systematic review with meta-analysis (P9-14.010) 240
Limes XXIII Sonderband 4 / II Proceedings of the 23rd International Congress of Roman Frontier Studies Ingolstadt 2015 200
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 物理 生物化学 纳米技术 计算机科学 化学工程 内科学 复合材料 物理化学 电极 遗传学 量子力学 基因 冶金 催化作用
热门帖子
关注 科研通微信公众号,转发送积分 3829789
求助须知:如何正确求助?哪些是违规求助? 3372428
关于积分的说明 10472164
捐赠科研通 3091946
什么是DOI,文献DOI怎么找? 1701597
邀请新用户注册赠送积分活动 818501
科研通“疑难数据库(出版商)”最低求助积分说明 770925