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临床试验/NCT06635668
NCT06635668招募中不适用

Baseline ACL Injury Risk Screening and Normative Data

Sanford Health1 个研究点 分布在 1 个国家目标入组 5,000 人开始时间: 2022年7月19日最近更新:
适应症

试验速览

阶段
不适用
状态
招募中
入组人数
5,000
试验地点
1
主要终点
Incidence of injury

研究概览

简要总结

This is a prospective, observational cohort study aimed at establishing a database of normative biomechanics for healthy athletes and surveying these athletes for 12 months following baseline testing for the occurrence of new musculoskeletal injuries, with a particular emphasis on ACL injuries.

详细描述

This study is a prospective, observational cohort study aimed at establishing a database of normative biomechanics data for healthy athletes. The primary focus is on quantifying muscle strength, movement patterns, and biomechanics in relation to the risk of musculoskeletal injuries, particularly ACL injuries. The study will also explore the relationship between these biomechanical factors and the occurrence of new injuries over a 12 month follow-up period.

The research will involve a large sample size of athletes within the Sanford Health service area, including those participating in organized sports at middle schools, high schools, and universities. Advanced marker less three-dimensional motion capture technology will be employed to gather high-fidelity biomechanical data. This will allow for the development of sophisticated algorithms to assess individual injury risk and facilitate targeted interventions aimed at reducing the likelihood of ACL injuries.

Participants will undergo an injury risk screen, which is a standard component of the athletic camps sponsored by Sanford Sports and Sanford Orthopedics and Sports Medicine. This screen includes assessments of muscle strength and movement biomechanics, along with the collection of demographic and sports participation data. Participants will then receive a follow-up surveys at six and twelve months to report any new injuries.

The study is designed to provide essential normative data, which is currently lacking, particularly for tests used in the assessment of ACLR patients. This data will enhance clinicians' ability to evaluate a patient's readiness for return to sport by comparing their performance to robust normative values. Additionally, the study will collect data on other risk factors, such as a history of concussions, to better understand the interplay between these factors and biomechanics in ACL injury risk.

By establishing this comprehensive database, the study aims to improve patient care by informing ACL and ACLR treatment and return-to-play guidelines, ultimately reducing the risk of ACL re-injury in athletes.

研究设计

研究类型
Observational
观察模型
Cohort
时间视角
Prospective

入排标准

年龄范围
10 Years 至 65 Years(Child, Adult, Older Adult)
性别
All
接受健康志愿者

入选标准

  • Healthy athletes participating in formal, organized, competitive sports between the ages of 10 and 65 years old

排除标准

  • Athletes who are injured at the time of consent and pregnant individuals

结局指标

主要结局

Incidence of injury

时间窗: 12 months from baseline

The primary outcome measure will assess the incidence of ACL injuries among participants. This metric will be determined by responses to a follow-up survey administered at 6 and 12 months post-injury risk screen. Participants will be asked whether they sustained an injury that prevented them from participating in their sport or activity for 10 or more consecutive days. The measure will capture any new ACL injuries occurring within the specified follow-up period.

Incidence of injury

时间窗: 6 and 12 months from baseline

The primary outcome measure will assess the incidence of ACL injuries among participants. This metric will be determined by responses to follow-up surveys administered at 6 and 12 months post-injury risk screen. Participants will be asked whether they sustained an injury that prevented them from participating in their sport or activity for 10 or more consecutive days. The measure will capture any new ACL injuries occurring within the specified follow-up period.

次要结局

未报告次要终点

研究者

申办方类型
Other
责任方
Sponsor

研究点 (1)

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