Prediction of anterior cruciate ligament injury in basketball players using machine learning

ISRCTN	ISRCTN18009799
DOI	https://doi.org/10.1186/ISRCTN18009799
ClinicalTrials.gov (NCT)	Nil known
Clinical Trials Information System (CTIS)	Nil known
Protocol serial number	USM/JEPeM/22040199
Sponsor	Hospital Universiti Sains Malaysia
Funder	Investigator initiated and funded

Submission date: 22/08/2024
Registration date: 22/08/2024
Last edited: 21/10/2025

Recruitment status: No longer recruiting
Overall study status: Completed
Condition category: Musculoskeletal Diseases

Prospectively registered

Protocol

Statistical analysis plan

Results

Individual participant data

Plain English summary of protocol

Background and study aims
This study aims to find out what factors increase the risk of ACL (anterior cruciate ligament) injuries in young adult basketball players. The ACL is a crucial ligament in the knee, and injuries to it can be serious and often require surgery. The researchers also want to see if machine learning, a type of computer technology, can accurately predict who might get injured. By doing this, they hope to identify important risk factors specific to male basketball players, which could help in creating better injury prevention strategies.

Who can participate?
To participate in this study, you must be:
1. Male
2. At least 18 years old
3. Exercising at least 8 hours per week
4. Playing basketball for at least 3 years
5. Not having a knee injury based on a specific test called the Lachman’s test

What does the study involve?
If you join the study, you will undergo several tests to measure factors related to ACL injuries. After the tests, you will be followed for 12 months to see if you sustain an ACL injury during that time. Your data will help in developing and validating a machine learning model to predict ACL injuries in basketball players.

What are the possible benefits and risks of participating?
By participating, you could help advance understanding of ACL injuries in basketball players and contribute to better injury prevention strategies in the future. There may be minimal risks associated with the physical tests, but these will be conducted by trained professionals to ensure your safety.

Where is the study run from?
The study is being conducted at Hospital Universiti Sains Malaysia

When is the study starting and how long is it expected to run for?
October 2021 to April 2024

Who is funding the study?
Investigator initiated and funded

Who is the main contact?
Guo-Long-fei (guolongfei0422@student.usm.my)
Dr Shazlin Binti Shaharudin (shazlin@usm.my).

Contact information

Prof Shazlin Shaharudin
Principal investigator

School of Health Sciences,Universiti Sains Malaysia,16150 Kubang Kerian
Kelantan
150000
Malaysia

ORCID ID	0000-0001-5583-7631
Phone	+60 9-767 7578
Email	shazlin@usm.my

Dr Longfei Guo
Public, Scientific

Building 7, Wenxingyuan, Qianbeitun Road
Taiyuan
30000
China

ORCID ID	0009-0005-2098-2413
Phone	+86 15536887299
Email	guolongfei0422@student.usm.my

Study information

Primary study design	Observational
Study design	Single-center observational cohort study
Secondary study design	Cohort study
Study type	Participant information sheet
Scientific title	Prediction of anterior cruciate ligament (ACL) injuries in basketball players using machine learning algorithms: a prospective study
Study acronym	B-ACL-ML
Study objectives	1. Athlete's profile, Physical function, basketball-specific skills, biomechanics and electromyography are related to ACL injury risk among basketball athletes. 2. The predictive model is valid in distinguishing between male basketball players with and without ACL injuries.
Ethics approval(s)	Approved 01/09/2022, Jawatankuasa Etika Penyelidikan Manusia Universiti Sains Malaysia (Universiti Sains Malaysia 16150 Kubang Kerian, Kelantan., Kelantan, 15000, Malaysia; +60 9-7673000; jepem@usm.my), ref: USM/JEPeM/22040199
Health condition(s) or problem(s) studied	Prevention of anterior cruciate ligament (ACL) injury in male basketball players
Intervention	In this study, 104 young adult basketball players volunteer to participate. The athletes' profiles, physical functions, basketball-specific skills, biomechanics, and electromyography (EMG) of seven muscles, including the quadriceps, hamstrings, and gastrocnemius, are measured during unanticipated side-cutting maneuvers. After a 12-month follow-up, these data will be compared between those who sustain injuries and those who remain injury-free.
Intervention type	Behavioural
Primary outcome measure(s)	Measured at baseline and 12 months: 1. The athlete's profile (height, weight, age, level of play, playing position), basketball training record, and self-reported injury history for each participant were recorded 2. Balance testing and joint mobility testing were conducted using YBT and FMS, with a duration of half an hour 3. Biomechanical and synchronized electromyography (EMG) experiments were performed, lasting for two hours 4. Trunk testing was conducted using DLH, strength testing was performed with 1-RM weighted squat and deadlift, explosive strength was assessed using countermovement jump (CMJ), squat jump (SJ), and drop jump (DJ), and agility testing was carried out with the Lane Agility Test lasting for two hours
Key secondary outcome measure(s)	There are no secondary outcome measures
Completion date	03/04/2024

Eligibility

Participant type(s)	Healthy volunteer
Age group	Adult
Lower age limit	18 Years
Upper age limit	30 Years
Sex	Male
Target sample size at registration	120
Total final enrolment	114
Key inclusion criteria	1. Male 2. Age over 18 years 3. Exercising ≥8 hours per week, 4. Having played basketball for at least 3 years 5. Having a negative Lachman's knee examination
Key exclusion criteria	1. Exercise-related or neurological disorders 2. Recent hip or knee surgery or trauma 3. Incomplete data not being analyzed
Date of first enrolment	02/09/2022
Date of final enrolment	04/04/2023

Locations

Countries of recruitment

China

Study participating centres

Taiyuan University of Technology High Performance Sports Centre

No.18, Xinminyuan Road, Wanbailin District
Taiyuan
030024
China

Xinzhou Normal University

No.1, Dunqi East Street
Xinzhou
034000
China

Results and Publications

Individual participant data (IPD) Intention to share	No
IPD sharing plan summary	Data sharing statement to be made available at a later date
IPD sharing plan	Individual participant data will not be provided due to privacy concerns

Study outputs

Output type	Details	Date created	Date added	Peer reviewed?	Patient-facing?
Results article		14/10/2025	21/10/2025	Yes	No
Participant information sheet	Participant information sheet	11/11/2025	11/11/2025	No	Yes

Editorial Notes

21/10/2025: Publication reference added.
22/08/2024: Trial's existence confirmed by Jawatankuasa Etika Penyelidikan Manusia Universiti Sains Malaysia.