Nomograms for Predicting High Hospitalization Costs and Prolonged Stay among Hospitalized Patients with pAECOPD.

IF 2.1 4区 医学 Q3 RESPIRATORY SYSTEM Canadian respiratory journal Pub Date : 2024-09-06 DOI:10.1155/2024/2639080
Nafeisa Dilixiati,Mengyu Lian,Ziliang Hou,Jie Song,Jingjing Yang,Ruiyan Lin,Jinxiang Wang
{"title":"Nomograms for Predicting High Hospitalization Costs and Prolonged Stay among Hospitalized Patients with pAECOPD.","authors":"Nafeisa Dilixiati,Mengyu Lian,Ziliang Hou,Jie Song,Jingjing Yang,Ruiyan Lin,Jinxiang Wang","doi":"10.1155/2024/2639080","DOIUrl":null,"url":null,"abstract":"This study aimed to develop nomograms to predict high hospitalization costs and prolonged stays in hospitalized acute exacerbations of chronic obstructive pulmonary disease (AECOPD) patients with community-acquired pneumonia (CAP), also known as pAECOPD. A total of 635 patients with pAECOPD were included in this observational study and divided into training and testing sets. Variables were initially screened using univariate analysis, and then further selected using a backward stepwise regression. Multivariable logistic regression was performed to establish nomograms. The predictive performance of the model was evaluated using the receiver operating characteristic (ROC) curve, area under the curve (AUC), calibration curve, and decision curve analysis (DCA) in both the training and testing sets. Finally, the logistic regression analysis showed that elevated white blood cell count (WBC>10 × 109 cells/l), hypoalbuminemia, pulmonary encephalopathy, respiratory failure, diabetes, and respiratory intensive care unit (RICU) admissions were risk factors for predicting high hospitalization costs in pAECOPD patients. The AUC value was 0.756 (95% CI: 0.699-0.812) in the training set and 0.792 (95% CI: 0.718-0.867) in the testing set. The calibration plot and DCA curve indicated the model had good predictive performance. Furthermore, decreased total protein, pulmonary encephalopathy, reflux esophagitis, and RICU admissions were risk factors for predicting prolonged stays in pAECOPD patients. The AUC value was 0.629 (95% CI: 0.575-0.682) in the training set and 0.620 (95% CI: 0.539-0.701) in the testing set. The calibration plot and DCA curve indicated the model had good predictive performance. We developed and validated two nomograms for predicting high hospitalization costs and prolonged stay, respectively, among hospitalized patients with pAECOPD. This trial is registered with ChiCTR2000039959.","PeriodicalId":9416,"journal":{"name":"Canadian respiratory journal","volume":null,"pages":null},"PeriodicalIF":2.1000,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Canadian respiratory journal","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1155/2024/2639080","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"RESPIRATORY SYSTEM","Score":null,"Total":0}
引用次数: 0

Abstract

This study aimed to develop nomograms to predict high hospitalization costs and prolonged stays in hospitalized acute exacerbations of chronic obstructive pulmonary disease (AECOPD) patients with community-acquired pneumonia (CAP), also known as pAECOPD. A total of 635 patients with pAECOPD were included in this observational study and divided into training and testing sets. Variables were initially screened using univariate analysis, and then further selected using a backward stepwise regression. Multivariable logistic regression was performed to establish nomograms. The predictive performance of the model was evaluated using the receiver operating characteristic (ROC) curve, area under the curve (AUC), calibration curve, and decision curve analysis (DCA) in both the training and testing sets. Finally, the logistic regression analysis showed that elevated white blood cell count (WBC>10 × 109 cells/l), hypoalbuminemia, pulmonary encephalopathy, respiratory failure, diabetes, and respiratory intensive care unit (RICU) admissions were risk factors for predicting high hospitalization costs in pAECOPD patients. The AUC value was 0.756 (95% CI: 0.699-0.812) in the training set and 0.792 (95% CI: 0.718-0.867) in the testing set. The calibration plot and DCA curve indicated the model had good predictive performance. Furthermore, decreased total protein, pulmonary encephalopathy, reflux esophagitis, and RICU admissions were risk factors for predicting prolonged stays in pAECOPD patients. The AUC value was 0.629 (95% CI: 0.575-0.682) in the training set and 0.620 (95% CI: 0.539-0.701) in the testing set. The calibration plot and DCA curve indicated the model had good predictive performance. We developed and validated two nomograms for predicting high hospitalization costs and prolonged stay, respectively, among hospitalized patients with pAECOPD. This trial is registered with ChiCTR2000039959.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
预测 pAECOPD 住院患者住院费用高昂和住院时间延长的提名图。
本研究旨在开发提名图,以预测慢性阻塞性肺疾病(AECOPD)急性加重并伴有社区获得性肺炎(CAP)(又称 pAECOPD)的住院患者的高住院费用和延长住院时间。这项观察性研究共纳入了 635 名 pAECOPD 患者,并将其分为训练集和测试集。首先使用单变量分析筛选变量,然后使用后向逐步回归法进一步筛选变量。采用多变量逻辑回归建立提名图。在训练集和测试集中,使用接收者操作特征曲线(ROC)、曲线下面积(AUC)、校准曲线和决策曲线分析(DCA)对模型的预测性能进行了评估。最后,逻辑回归分析表明,白细胞计数升高(WBC>10 × 109 cells/l)、低白蛋白血症、肺性脑病、呼吸衰竭、糖尿病和入住呼吸重症监护室(RICU)是预测 pAECOPD 患者住院费用高的风险因素。训练集的 AUC 值为 0.756(95% CI:0.699-0.812),测试集的 AUC 值为 0.792(95% CI:0.718-0.867)。校准图和 DCA 曲线表明该模型具有良好的预测性能。此外,总蛋白减少、肺性脑病、反流性食管炎和入住 RICU 是预测 pAECOPD 患者住院时间延长的风险因素。训练集的 AUC 值为 0.629(95% CI:0.575-0.682),测试集的 AUC 值为 0.620(95% CI:0.539-0.701)。校准图和 DCA 曲线表明该模型具有良好的预测性能。我们开发并验证了两个提名图,分别用于预测 pAECOPD 住院患者的高住院费用和延长住院时间。本试验的注册号为 ChiCTR2000039959。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Canadian respiratory journal
Canadian respiratory journal 医学-呼吸系统
CiteScore
4.20
自引率
0.00%
发文量
61
审稿时长
6-12 weeks
期刊介绍: Canadian Respiratory Journal is a peer-reviewed, Open Access journal that aims to provide a multidisciplinary forum for research in all areas of respiratory medicine. The journal publishes original research articles, review articles, and clinical studies related to asthma, allergy, COPD, non-invasive ventilation, therapeutic intervention, lung cancer, airway and lung infections, as well as any other respiratory diseases.
期刊最新文献
Clinical Analysis of 32 Cases of Subglottic Benign Airway Stenosis Treated With Montgomery T Silicone Stent. Nomograms for Predicting High Hospitalization Costs and Prolonged Stay among Hospitalized Patients with pAECOPD. Gentiopicroside Ameliorates Sepsis-Induced Acute Lung Injury via Inhibiting Inflammatory Response. Development of Prone Position Ventilation Device and Study on the Application Effect of Combined Life Support Technology in Critically Ill Patients. IL-17 Mildly Rescued the Impaired Proliferation of Alveolar Epithelial Cells Induced by LCN2 Overexpression.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1