根据临界值将运动员分为高风险组和低风险组的局限性。临床评论。

IF 1.6 Q3 SPORT SCIENCES
International Journal of Sports Physical Therapy Pub Date : 2024-09-01 eCollection Date: 2024-01-01 DOI:10.26603/001c.122644
Justin M Losciale, Linda K Truong, Patrick Ward, Gary S Collins, Garrett S Bullock
{"title":"根据临界值将运动员分为高风险组和低风险组的局限性。临床评论。","authors":"Justin M Losciale, Linda K Truong, Patrick Ward, Gary S Collins, Garrett S Bullock","doi":"10.26603/001c.122644","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Athlete injury risk assessment and management is an important, yet challenging task for sport and exercise medicine professionals. A common approach to injury risk screening is to stratify athletes into risk groups based on their performance on a test relative to a cut-off threshold. However, one potential reason for ineffective injury prevention efforts is the over-reliance on identifying these 'at-risk' groups using arbitrary cut-offs for these tests and measures. The purpose of this commentary is to discuss the conceptual and technical issues related to the use of a cut-off in both research and clinical practice.</p><p><strong>Clinical question: </strong>How can we better assess and interpret clinical tests or measures to enable a more effective injury risk assessment in athletes?</p><p><strong>Key results: </strong>Cut-offs typically lack strong biologic plausibility to support them; and are typically derived in a data-driven manner and thus not generalizable to other samples. When a cut-off is used in analyses, information is lost, leading to potentially misleading results and less accurate injury risk prediction. Dichotomizing a continuous variable using a cut-off should be avoided. Using continuous variables on its original scale is advantageous because information is not discarded, outcome prediction accuracy is not lost, and personalized medicine can be facilitated.</p><p><strong>Clinical application: </strong>Researchers and clinicians are encouraged to analyze and interpret the results of tests and measures using continuous variables and avoid relying on singular cut-offs to guide decisions. Injury risk can be predicted more accurately when using continuous variables in their natural form. A more accurate risk prediction will facilitate personalized approaches to injury risk mitigation and may lead to a decline in injury rates.</p><p><strong>Level of evidence: </strong>5.</p>","PeriodicalId":47892,"journal":{"name":"International Journal of Sports Physical Therapy","volume":"19 9","pages":"1151-1164"},"PeriodicalIF":1.6000,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11368444/pdf/","citationCount":"0","resultStr":"{\"title\":\"Limitations of Separating Athletes into High or Low-Risk Groups based on a Cut-Off. A Clinical Commentary.\",\"authors\":\"Justin M Losciale, Linda K Truong, Patrick Ward, Gary S Collins, Garrett S Bullock\",\"doi\":\"10.26603/001c.122644\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Athlete injury risk assessment and management is an important, yet challenging task for sport and exercise medicine professionals. A common approach to injury risk screening is to stratify athletes into risk groups based on their performance on a test relative to a cut-off threshold. However, one potential reason for ineffective injury prevention efforts is the over-reliance on identifying these 'at-risk' groups using arbitrary cut-offs for these tests and measures. The purpose of this commentary is to discuss the conceptual and technical issues related to the use of a cut-off in both research and clinical practice.</p><p><strong>Clinical question: </strong>How can we better assess and interpret clinical tests or measures to enable a more effective injury risk assessment in athletes?</p><p><strong>Key results: </strong>Cut-offs typically lack strong biologic plausibility to support them; and are typically derived in a data-driven manner and thus not generalizable to other samples. When a cut-off is used in analyses, information is lost, leading to potentially misleading results and less accurate injury risk prediction. Dichotomizing a continuous variable using a cut-off should be avoided. Using continuous variables on its original scale is advantageous because information is not discarded, outcome prediction accuracy is not lost, and personalized medicine can be facilitated.</p><p><strong>Clinical application: </strong>Researchers and clinicians are encouraged to analyze and interpret the results of tests and measures using continuous variables and avoid relying on singular cut-offs to guide decisions. Injury risk can be predicted more accurately when using continuous variables in their natural form. A more accurate risk prediction will facilitate personalized approaches to injury risk mitigation and may lead to a decline in injury rates.</p><p><strong>Level of evidence: </strong>5.</p>\",\"PeriodicalId\":47892,\"journal\":{\"name\":\"International Journal of Sports Physical Therapy\",\"volume\":\"19 9\",\"pages\":\"1151-1164\"},\"PeriodicalIF\":1.6000,\"publicationDate\":\"2024-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11368444/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Sports Physical Therapy\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.26603/001c.122644\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q3\",\"JCRName\":\"SPORT SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Sports Physical Therapy","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.26603/001c.122644","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q3","JCRName":"SPORT SCIENCES","Score":null,"Total":0}
引用次数: 0

摘要

背景:运动员损伤风险评估和管理是体育运动医学专业人员的一项重要而又具有挑战性的任务。损伤风险筛查的一种常见方法是根据运动员在某项测试中的表现与临界值的比较,将运动员划分为不同的风险组别。然而,伤害预防工作效果不佳的一个潜在原因是过度依赖于使用这些测试和测量方法的任意临界值来确定这些 "高危 "群体。本评论旨在讨论在研究和临床实践中使用临界值的相关概念和技术问题:临床问题:我们如何才能更好地评估和解释临床测试或测量方法,从而对运动员进行更有效的损伤风险评估?临界值通常缺乏强有力的生物合理性支持,而且通常是以数据驱动的方式得出的,因此无法推广到其他样本。当在分析中使用临界值时,信息就会丢失,从而导致潜在的误导性结果和不太准确的损伤风险预测。应避免使用临界值对连续变量进行二分。在原始尺度上使用连续变量是有优势的,因为信息不会被丢弃,结果预测的准确性也不会降低,还能促进个性化医疗的发展:临床应用:鼓励研究人员和临床医生分析和解释使用连续变量的测试和测量结果,避免依赖单一的临界值来指导决策。使用自然形式的连续变量可以更准确地预测受伤风险。更准确的风险预测将有助于采取个性化方法来降低受伤风险,并可能导致受伤率下降:5.
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Limitations of Separating Athletes into High or Low-Risk Groups based on a Cut-Off. A Clinical Commentary.

Background: Athlete injury risk assessment and management is an important, yet challenging task for sport and exercise medicine professionals. A common approach to injury risk screening is to stratify athletes into risk groups based on their performance on a test relative to a cut-off threshold. However, one potential reason for ineffective injury prevention efforts is the over-reliance on identifying these 'at-risk' groups using arbitrary cut-offs for these tests and measures. The purpose of this commentary is to discuss the conceptual and technical issues related to the use of a cut-off in both research and clinical practice.

Clinical question: How can we better assess and interpret clinical tests or measures to enable a more effective injury risk assessment in athletes?

Key results: Cut-offs typically lack strong biologic plausibility to support them; and are typically derived in a data-driven manner and thus not generalizable to other samples. When a cut-off is used in analyses, information is lost, leading to potentially misleading results and less accurate injury risk prediction. Dichotomizing a continuous variable using a cut-off should be avoided. Using continuous variables on its original scale is advantageous because information is not discarded, outcome prediction accuracy is not lost, and personalized medicine can be facilitated.

Clinical application: Researchers and clinicians are encouraged to analyze and interpret the results of tests and measures using continuous variables and avoid relying on singular cut-offs to guide decisions. Injury risk can be predicted more accurately when using continuous variables in their natural form. A more accurate risk prediction will facilitate personalized approaches to injury risk mitigation and may lead to a decline in injury rates.

Level of evidence: 5.

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
CiteScore
2.50
自引率
5.90%
发文量
124
审稿时长
16 weeks
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信