老年髋部骨折患者术前深静脉血栓形成的风险预测模型:系统回顾与元分析》。

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS ACS Applied Bio Materials Pub Date : 2024-01-01 DOI:10.1177/10760296241285565
Huali Guo, Kuankuan Xu, Fangfang Deng, Qingqing Chen, Jie Liang, Kun Zhang
{"title":"老年髋部骨折患者术前深静脉血栓形成的风险预测模型:系统回顾与元分析》。","authors":"Huali Guo, Kuankuan Xu, Fangfang Deng, Qingqing Chen, Jie Liang, Kun Zhang","doi":"10.1177/10760296241285565","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>To systematically assess the risk prediction models for preoperative deep vein thrombosis in older patients with hip fractures.</p><p><strong>Method: </strong>We searched four databases for literature through November 17, 2023. We included patients aged ≥60 with hip fractures and considered English-language case-control or cohort studies that focused on developing and/or validating risk prediction models for DVT in this population. Excluded were studies that solely analyzed risk factors without constructing a prediction model, had fewer than 2 predictive variables, or were not available in full-text or were duplicate publications. The Predictive Model Bias Risk Assessment tool was utilized to evaluate risk of bias. The area under the curve (AUC) values were meta-analyzed using R Studio software. The I<sup>2</sup> index and Cochrane q test were employed to assess heterogeneity. Additionally, sensitivity analysis was performed by systematically removing individual studies to explore the sources of heterogeneity.</p><p><strong>Results: </strong>A total of 1880 studies were gathered. Out of these, seven studies were included, encompassing 8 models. The most commonly utilized factors in the models were D-dimer and the time from injury to admission. The pooled AUC value for the validation of 8 models was 0.84 (95% confidence interval: 0.80-0.87), indicating robust model performance.</p><p><strong>Conclusion: </strong>Current risk prediction models for preoperative DVT in elderly hip fracture patients are still in the developmental phase. Future research should focus on developing new models with larger sample sizes, robust study designs, and multicenter external validation.</p>","PeriodicalId":2,"journal":{"name":"ACS Applied Bio Materials","volume":null,"pages":null},"PeriodicalIF":4.6000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11425752/pdf/","citationCount":"0","resultStr":"{\"title\":\"Risk Prediction Models for Preoperative Deep Vein Thrombosis in Older Patients with Hip Fracture: A Systematic Review and Meta-Analysis.\",\"authors\":\"Huali Guo, Kuankuan Xu, Fangfang Deng, Qingqing Chen, Jie Liang, Kun Zhang\",\"doi\":\"10.1177/10760296241285565\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>To systematically assess the risk prediction models for preoperative deep vein thrombosis in older patients with hip fractures.</p><p><strong>Method: </strong>We searched four databases for literature through November 17, 2023. We included patients aged ≥60 with hip fractures and considered English-language case-control or cohort studies that focused on developing and/or validating risk prediction models for DVT in this population. Excluded were studies that solely analyzed risk factors without constructing a prediction model, had fewer than 2 predictive variables, or were not available in full-text or were duplicate publications. The Predictive Model Bias Risk Assessment tool was utilized to evaluate risk of bias. The area under the curve (AUC) values were meta-analyzed using R Studio software. The I<sup>2</sup> index and Cochrane q test were employed to assess heterogeneity. Additionally, sensitivity analysis was performed by systematically removing individual studies to explore the sources of heterogeneity.</p><p><strong>Results: </strong>A total of 1880 studies were gathered. Out of these, seven studies were included, encompassing 8 models. The most commonly utilized factors in the models were D-dimer and the time from injury to admission. The pooled AUC value for the validation of 8 models was 0.84 (95% confidence interval: 0.80-0.87), indicating robust model performance.</p><p><strong>Conclusion: </strong>Current risk prediction models for preoperative DVT in elderly hip fracture patients are still in the developmental phase. Future research should focus on developing new models with larger sample sizes, robust study designs, and multicenter external validation.</p>\",\"PeriodicalId\":2,\"journal\":{\"name\":\"ACS Applied Bio Materials\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.6000,\"publicationDate\":\"2024-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11425752/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS Applied Bio Materials\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1177/10760296241285565\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MATERIALS SCIENCE, BIOMATERIALS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Bio Materials","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1177/10760296241285565","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, BIOMATERIALS","Score":null,"Total":0}
引用次数: 0

摘要

目的:系统评估老年髋部骨折患者术前深静脉血栓形成的风险预测模型:系统评估老年髋部骨折患者术前深静脉血栓形成的风险预测模型:我们检索了四个数据库中截至 2023 年 11 月 17 日的文献。我们纳入了年龄≥60岁的髋部骨折患者,并考虑了侧重于开发和/或验证该人群深静脉血栓风险预测模型的英文病例对照或队列研究。仅分析风险因素而未构建预测模型的研究、预测变量少于 2 个的研究、未提供全文的研究或重复发表的研究均排除在外。预测模型偏倚风险评估工具用于评估偏倚风险。使用 R Studio 软件对曲线下面积(AUC)值进行元分析。采用 I2 指数和 Cochrane q 检验来评估异质性。此外,还通过系统性地删除个别研究来进行敏感性分析,以探索异质性的来源:结果:共收集到 1880 项研究。结果:共收集到 1880 项研究,其中有 7 项研究被纳入,包含 8 个模型。模型中最常用的因素是 D-二聚体和从受伤到入院的时间。8个模型验证的集合AUC值为0.84(95%置信区间:0.80-0.87),表明模型性能良好:结论:目前针对老年髋部骨折患者术前深静脉血栓的风险预测模型仍处于开发阶段。未来的研究应重点开发样本量更大、研究设计更稳健、经多中心外部验证的新模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
Risk Prediction Models for Preoperative Deep Vein Thrombosis in Older Patients with Hip Fracture: A Systematic Review and Meta-Analysis.

Objective: To systematically assess the risk prediction models for preoperative deep vein thrombosis in older patients with hip fractures.

Method: We searched four databases for literature through November 17, 2023. We included patients aged ≥60 with hip fractures and considered English-language case-control or cohort studies that focused on developing and/or validating risk prediction models for DVT in this population. Excluded were studies that solely analyzed risk factors without constructing a prediction model, had fewer than 2 predictive variables, or were not available in full-text or were duplicate publications. The Predictive Model Bias Risk Assessment tool was utilized to evaluate risk of bias. The area under the curve (AUC) values were meta-analyzed using R Studio software. The I2 index and Cochrane q test were employed to assess heterogeneity. Additionally, sensitivity analysis was performed by systematically removing individual studies to explore the sources of heterogeneity.

Results: A total of 1880 studies were gathered. Out of these, seven studies were included, encompassing 8 models. The most commonly utilized factors in the models were D-dimer and the time from injury to admission. The pooled AUC value for the validation of 8 models was 0.84 (95% confidence interval: 0.80-0.87), indicating robust model performance.

Conclusion: Current risk prediction models for preoperative DVT in elderly hip fracture patients are still in the developmental phase. Future research should focus on developing new models with larger sample sizes, robust study designs, and multicenter external validation.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
期刊最新文献
A Systematic Review of Sleep Disturbance in Idiopathic Intracranial Hypertension. Advancing Patient Education in Idiopathic Intracranial Hypertension: The Promise of Large Language Models. Anti-Myelin-Associated Glycoprotein Neuropathy: Recent Developments. Approach to Managing the Initial Presentation of Multiple Sclerosis: A Worldwide Practice Survey. Association Between LACE+ Index Risk Category and 90-Day Mortality After Stroke.
×
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