A new risk calculation model for complications of hepatectomy in adults over 75

IF 2 3区 医学 Q2 ANESTHESIOLOGY Perioperative Medicine Pub Date : 2024-02-26 DOI:10.1186/s13741-024-00366-y
Lining Xu, Weiyu Wang, Yingying Xu
{"title":"A new risk calculation model for complications of hepatectomy in adults over 75","authors":"Lining Xu, Weiyu Wang, Yingying Xu","doi":"10.1186/s13741-024-00366-y","DOIUrl":null,"url":null,"abstract":"Owing to poor organ function reserve, older adults have a high risk of postoperative complications. However, there is no well-established system for assessing the risk of complications after hepatectomy in older adults. This study aimed to design a risk assessment tool to predict the risk of complications after hepatectomy in adults older than 75 years. A total of 326 patients were identified. A logistic regression equation was used to create the Risk Assessment System of Hepatectomy in Adults (RASHA) for the prediction of complications (Clavien‒Dindo classification ≥ II). Multivariate correlation analysis revealed that comorbidity (≥ 5 kinds of disease or < 5 kinds of disease, odds ratio [OR] = 5.552, P < 0.001), fatigue (yes or no, OR = 4.630, P = 0.009), Child‒Pugh (B or A, OR = 4.211, P = 0.004), number of liver segments to be removed (≥ 3 or ≤ 2, OR = 4.101, P = 0.001), and adjacent organ resection (yes or no, OR = 1.523, P = 0.010) were independent risk factors for postoperative complications after hepatectomy in older persons (aged ≥ 75 years). A binomial logistic regression model was established to evaluate the RASHA score (including the RASHA scale and RASHA formula). The area under the curve (AUC) for the RASHA scale was 0.916, and the cut-off value was 12.5. The AUC for the RASHA formula was 0.801, and the cut-off value was 0.2106. RASHA can be used to effectively predict the postoperative complications of hepatectomy through perioperative variables in adults older than 75 years. The Research Registry: researchregistry8531. https://www.researchregistry.com/browse-the-registry#home/registrationdetails/63901824ae49230021a5a0cf/ .","PeriodicalId":19764,"journal":{"name":"Perioperative Medicine","volume":"12 1","pages":""},"PeriodicalIF":2.0000,"publicationDate":"2024-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Perioperative Medicine","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s13741-024-00366-y","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ANESTHESIOLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

Owing to poor organ function reserve, older adults have a high risk of postoperative complications. However, there is no well-established system for assessing the risk of complications after hepatectomy in older adults. This study aimed to design a risk assessment tool to predict the risk of complications after hepatectomy in adults older than 75 years. A total of 326 patients were identified. A logistic regression equation was used to create the Risk Assessment System of Hepatectomy in Adults (RASHA) for the prediction of complications (Clavien‒Dindo classification ≥ II). Multivariate correlation analysis revealed that comorbidity (≥ 5 kinds of disease or < 5 kinds of disease, odds ratio [OR] = 5.552, P < 0.001), fatigue (yes or no, OR = 4.630, P = 0.009), Child‒Pugh (B or A, OR = 4.211, P = 0.004), number of liver segments to be removed (≥ 3 or ≤ 2, OR = 4.101, P = 0.001), and adjacent organ resection (yes or no, OR = 1.523, P = 0.010) were independent risk factors for postoperative complications after hepatectomy in older persons (aged ≥ 75 years). A binomial logistic regression model was established to evaluate the RASHA score (including the RASHA scale and RASHA formula). The area under the curve (AUC) for the RASHA scale was 0.916, and the cut-off value was 12.5. The AUC for the RASHA formula was 0.801, and the cut-off value was 0.2106. RASHA can be used to effectively predict the postoperative complications of hepatectomy through perioperative variables in adults older than 75 years. The Research Registry: researchregistry8531. https://www.researchregistry.com/browse-the-registry#home/registrationdetails/63901824ae49230021a5a0cf/ .
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
75 岁以上成年人肝切除术并发症的新风险计算模型
由于器官功能储备较差,老年人术后出现并发症的风险很高。然而,目前还没有一套完善的系统来评估老年人肝切除术后并发症的风险。本研究旨在设计一种风险评估工具,用于预测 75 岁以上老年人肝切除术后并发症的风险。共确定了 326 名患者。采用逻辑回归方程建立了成人肝切除术风险评估系统(RASHA),用于预测并发症(Clavien-Dindo分级≥ II)。多变量相关分析显示,合并症(≥ 5 种疾病或< 5 种疾病,几率比 [OR] = 5.552,P < 0.001)、疲劳(是或否,OR = 4.630,P = 0.009)、Child-Pugh(B 或 A,OR = 4.211,P = 0.004)、切除肝段数(≥ 3 或 ≤ 2,OR = 4.101,P = 0.001)和邻近器官切除(是或否,OR = 1.523,P = 0.010)是老年人(年龄≥ 75 岁)肝切除术后并发症的独立危险因素。建立了一个二项式逻辑回归模型来评估 RASHA 评分(包括 RASHA 量表和 RASHA 公式)。RASHA 量表的曲线下面积(AUC)为 0.916,临界值为 12.5。RASHA 公式的曲线下面积为 0.801,临界值为 0.2106。RASHA可用于通过围手术期变量有效预测75岁以上成人肝切除术的术后并发症。研究注册表:researchregistry8531. https://www.researchregistry.com/browse-the-registry#home/registrationdetails/63901824ae49230021a5a0cf/ 。
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
自引率
3.80%
发文量
55
审稿时长
10 weeks
期刊最新文献
The performance of ChatGPT in day surgery and pre-anesthesia risk assessment: a case-control study of 150 simulated patient presentations. Correction: The impact of preoperative stroke on 1-year mortality and days at home alive after major surgery: an observational cohort study. The use of complementary and alternative medicine among surgical patients: a cross-sectional study. Chronic post-surgical pain after total knee arthroplasty: a narrative review. Advances in the multimodal management of perioperative hypothermia: approaches from traditional Chinese and Western medicine.
×
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