| Literature DB >> 33429801 |
Saud F Alsubaie1, Walid Kamal Abdelbasset1,2, Abdulaziz A Alkathiry3, Waleed M Alshehri4, Mohammed M Azyabi1, Basil B Alanazi1, Abdulaziz A Alomereni5, Faisal Y Asiri6.
Abstract
ABSTRACT: Anterior cruciate ligament (ACL) injury is one of the most common knee injuries that leads to many consequences such as early osteoarthritis and knee joint instability.To explore the association of the types of ACL tear (complete and partial) and side of injury (dominant vs nondominate) with types of playing surfaces, sports, shoes, and mechanism of injuries as well as to determine whether higher levels of fatigue and physical fitness are risk factors for complete ACL tear.This cross-sectional study used a questionnaire to collect information from young male adults with a confirmed ACL injury who were attending rehabilitation programs. The outcomes of interest were patterns of ACL injury, levels of fatigue before the injury on a 0 to 10 scale, and levels of physical fitness (hours per week). Mann-Whitney U and Kruskal Wallis tests were used to assess the differences between groups, while the odds ratios were calculated to evaluate risk factors for complete ACL tear.One hundred thirteen young male adults with a confirmed ACL injury were enrolled. Most of the reported ACL injuries in this study were complete tear (80.5%) and occurred more frequently in the dominant leg (74.6%) due to noncontact mechanism (63.6%). More ACL injuries happened while playing soccer (97.2%) on artificial turf (53.3%). The level of fatigue before ACL injury was significantly higher in partial ACL tear injuries compared to complete ACL tear injuries (P = .014). For every 1-point increase in the level of fatigue on a 0-10 scale, there was a 25% reduction in complete ACL injury risk (P = .023).The pattern of ACL types of tear and side of injury varies in different playing surfaces and mechanisms of injuries. Higher levels of fatigue seem to be associated with a partial tear of the ACL and reduction of a complete ACL tear risk factor.Entities:
Mesh:
Year: 2021 PMID: 33429801 PMCID: PMC7793338 DOI: 10.1097/MD.0000000000024171
Source DB: PubMed Journal: Medicine (Baltimore) ISSN: 0025-7974 Impact factor: 1.817
Demographic data and clinical characteristics of the Participants.
| Characteristics | Values |
| Age, mean ± SD (years) | 32.2 ± 7.8 |
| Weight, mean ± SD (kg) | 77.2 ± 14 |
| Height, mean ± SD (cm) | 171 ± 7 |
| Body Mass Index, mean ± SD (Kg/m2) | 26.4 ± 4 |
| Education (years) | 14.7 ± 2.3 |
| Physical fitness (hours per week) | 3.3 ± 1.7 |
| Level of fatigue prior to injury (maximum score = 10) | 5.1 ± 2.5 |
| ACL reconstruction (%) | |
| - Yes | 77 (70) |
| - No | 33 (30) |
| - Missing data | 3 |
| Smoking (%) | |
| - Smokers | 30 (28.6) |
| - Non smokers | 75 (71.4) |
| - Missing data | 8 |
| Type of tear (%) | |
| - Complete tear | 91 (80.5) |
| - Partial tear | 22 (19.5) |
| Side of injury (%) | |
| - Dominant side | 62 (74.6) |
| - Non dominant side | 21 (25.4) |
| - Missing data | 30 |
| Type of sport (%) | |
| - Soccer | 105 (97.2) |
| - Others | 3 (2.8) |
| - Missing data | 5 |
| Type of playing surfaces (%) | |
| - Artificial turf | 56 (53.3) |
| - Natural grass | 29 (27.6) |
| - Sand playground | 20 (19) |
| - Missing data | 8 |
| Type of shoes (%) | |
| - Sports shoes suitable for the type of sport | 97 (88.2) |
| - Sports shoes are not suitable for the type of sport | 6 (5.5) |
| - Non-athletic shoes | 3 (2.7) |
| - Without shoes | 4 (3.6) |
| - Missing data | 3 |
| Mechanism of injury (%) | |
| - Pivoting (noncontact) | 51 (47.7) |
| - Jumping and landing (noncontact) | 17 (15.9) |
| - Player-to-player contact (contact) | 28 (26.1) |
| - Direct hit to the knee (contact) | 11 (10.3) |
| - Missing data | 5 |
Figure 1Distribution of ACL tears types and side of injury.
Figure 2Distribution of ACL injuries in different playing surfaces.
Figure 3Frequency of different mechanism of injuries in relation to the distribution of types of ACL injury (part A), the side of injury (part B), and the type of playing field (part C).
Impact of fatigue and physical fitness on different types of ACL tears, side of injury, and mechanism of injuries.
| Variables | Fatigue level (0–10) | Physical fitness (hours per week) | ||
| Type of tear | ||||
| - Complete | 4.76 ± 2.5 | 0.014∗ | 3.23 ± 1.7 | .355 |
| - Partial | 6.35 ± 1.9 | 3.7 ± 1.7 | ||
| Side of injury | ||||
| - Dominant | 4.84 ± 2.6 | 0.888 | 3.48 ± 1.7 | .406 |
| - Non-dominant | 5.1 ± 2.0 | 3.1 ± 1.7 | ||
| Mechanism of injury | ||||
| - Pivoting | 4.83 ± 2.23 | 0.785 | 3.31 ± 1.72 | .869 |
| - Jumping and landing | 5.19 ± 2.73 | 3.40 ± 1.87 | ||
| - Player to-player contact | 5.33 ± 2.53 | 3.31 ± 1.57 | ||
| - Direct hit to the knee | 4.83 ± 3.97 | 2.85 ± 1.69 | ||
Participant demographics and clinical measures (N = 113).
| Complete Tear | Partial Tear | Odds ratio (95% CI) | |||
| Age (years) | 32.2 (7.8) | 32.1 (8.1) | .945 | 1.01 (0.94–1.06) | .944 |
| Height (cm) | 170.8 (7.0) | 172.2 (5.1) | .393 | 0.97 (0.90–1.04) | .389 |
| Weight (Kg) | 76.3 (10.7) | 81.2 (22.6) | .142 | 0.98 (0.94–1.01) | .158 |
| Body Mass Index | 26.2 (3.7) | 27.2 (6.8) | .338 | 0.95 (0.86–1.05) | .341 |
| Education (yrs) | 14.9 (2.3) | 13.9 (2.3) | .097 | 1.18 (0.97–1.45) | .102 |
| Fatigue Level (0–10) | 4.8 (2.5) | 6.4 (1.9) | .014∗ | 0.75 (0.58–0.96) | .023∗ |
| Physical Fitness (hours per week) | 3.2 (1.7) | 3.7 (1.7) | .342 | 0.85 (0.61–1.19) | .341 |