Relationship of Subtalar Joint Range of Motion to Ankle Injuries in NBA G League and Collegiate Basketball Players

Introduction

Lateral ankle sprains are the most frequent orthopaedic injury (13.2%) and second most common cause of missed games in the National Basketball Association (NBA) with incidence of 3.4-5.1/1000 exposures.^3,5 These injuries can result in significant morbidity, residual symptoms, and functional instability, emphasizing importance of ankle sprains in basketball athletes.

Prevention of these injuries can only be successful after determination of risk factors. Prior studies have reported numerous risk factors; however, studies examining the correlation of ankle range of motion (ROM) and injuries in basketball players failed to account for subtalar joint complex (STJ) motion.^3,6,8

We sought to prospectively determine whether ROM of the ankle STJ was correlated with the incidence of ankle injuries in basketball players and to identify an at-risk population that may benefit from participation in an ankle injury prevention program. We hypothesized that increased STJ ROM would predispose to ankle injuries.

Methods

Funding for this prospective cohort study was provided by a merit-based research grant from the J Robert Gladden Orthopaedic Society. This study was approved by the Institutional Review Board and the NBA Team Physicians Research Committee. Patient data were collected during preseason examination of NBA G-League (Maine Red Claws) or Men’s Division I and III collegiate (Tufts University or Merrimack College) basketball players between 2017 and 2019. Patient demographics are presented in Table 1. Patients were excluded if they had ligamentous laxity, required a rigid ankle brace, or sustained an ankle injury outside of basketball-related activity. In keeping with established protocols, each player was evaluated anew each season and treated as a discrete subject. ¹⁰

OPEN IN VIEWER

Table 1.

Player Demographics.

Risk Factor for Ankle Injury	Injured	Noninjured	P value
Age, y, mean	21.3	21.3	.906
Height, in., mean	76.4	76.4	.959
Weight, lb, mean	203	202	.522
History of previous ankle injury, % (n/n)	11.1 (7/63)	16.3 (14/86)	.37
Bony abnormality on radiograph, % (n/n)	12.7 (15/118)	19.4 (6/31)	.344
History of previous ankle surgery, %	14.5	0	.415
Pregame ankle taping, % (n/n)	15.9 (17/107)	9.5 (4/42)	.315
Backcourt player, % (n/n)	13.2 (7/53)	14.6 (14/96)	.817
Collegiate athlete, % (n/n)	11.3 (7/62)	16.1 (14/87)	.406

Researchers were trained on standardized use of bubble goniometers. Intraclass correlation coefficients (ICCs) of intra- and interrater reliability ranged between good and excellent at 0.92, 0.75, 0.90, and 0.73 for subtalar inversion, eversion, dorsiflexion, and plantarflexion, respectively. Bilateral passive talocrural joint motion and STJ motion were measured using standardized goniometer placement (Figure 1). Anterior drawer, talar tilt, and talocrural joint laxity tests were triply measured and averaged. Subtalar eversion and inversion were added to assess total STJ range of motion for each patient and defined as combination motion (CM). To assess for the discrepancy between subtalar inversion and eversion, these values were subtracted (degrees of inversion – degrees of eversion) to calculate the subtalar difference (SD). We defined the ratio of CM to SD as the subtalar mobility index (SMI) (SMI = CM/SD). However, using SD alone, one is unable to differentiate between hypermobility or rigidity within the subtalar joint when inversion and eversion were similar. For this reason, we assessed CM to identify patients with increased subtalar mobility in conjunction with SD. SMI, which is the proportion of CM to SD, therefore can be used as a proxy for these measurements.

OPEN IN VIEWER

Figure 1a.

(A) Measurement of talocrural joint dorsiflexion and plantarflexion: patient positioned prone in 90 degrees knee flexion. Goniometer placed with fulcrum aligned with lateral malleolus, stationary arm midline along fibular axis, and moving arm parallel to fifth metatarsal. (B) Measurement of subtalar eversion and inversion: patient prone with tibia stabilized in sagittal plane, midfoot locked. Goniometer placed at midpoint between malleoli with stationary arm at midline of the leg and moving arm at midline of calcaneus.

All players underwent preseason 3-view bilateral ankle radiographs to measure static talar tilt angle and medial and lateral clear space widening. Radiographs were screened for potential confounders (os subfibulare, idiopathic cavovarus, and osseous collation).^2,4

Courtside athletic trainers diagnosed and recorded all ankle injuries during the season. ⁸ Statistical analysis was performed using SPSS-V26.0 (IBM Corporation, Armonk, NY). Continuous variables underwent descriptive analysis. Intra- and inter-rater reliability ICC for ankle plantarflexion, dorsiflexion, subtalar eversion, and inversion were calculated.

Demographic and sport-specific predictors were first assessed by χ² analysis. CM, SD, and SMI were tested for association with ankle injuries and receiver operating characteristic curve analysis was used to calculate predictive outcome thresholds for these biomechanical predictors. Binary logistic regressions were used to estimate odds ratios for predictors that were significant under χ² analysis. These tests were conducted independently in bivariate fashion (P = .05).

Results

A total of 74 players (43 collegiate, 31 professional) with mean age 21.3 ± 2.2 years met inclusion criteria, totaling 103 player-seasons from 2017-2019. Twenty-one ankle injuries occurred in 19 players with 10 405 player exposures (incidence: 2.11/1000) requiring a mean 5.4 days of rehabilitation before return to play. Cumulatively, players missed 113 days of playing time.

Direct measures of ankle, subtalar, or combined motion were not associated with risk of injury, rejecting our original hypothesis that increased STJ ROM would predispose to ankle injuries. However, we did find that players with an SD <6 degrees demonstrated higher injury rates versus players without this risk factor (26.1% vs 8.7%, P = .005), and SMI >3.75 was also predictive of injury (23.7% vs 10.8%, P = .049). Although CM was not predictive of injury, we found that players with both a CM >16 degrees and an SD >6 degrees had significantly higher injury rates than their counterparts (27.6% vs 10.8%, P = .020). This was also demonstrated in players with CM >16 degrees and an SMI >3.75 (26.7% vs 10.9%, P = .027). Passive ankle ROM measurements for injured vs uninjured players are presented in Table 2.

OPEN IN VIEWER

Table 2.

Results of Independent Samples t Testing Comparing ROM of Injured vs Noninjured Players: Risk of Ankle Injury by ROM. ^a

ROM Measurement	Injured	Noninjured	P Value
Dorsiflexion	13.7 (5.0)	13.9 (5.2)	.878
Plantarflexion	43.5 (12.8)	40.7 (11.7)	.322
Inversion	13.0 (4.7)	14.8 (4.6)	.099
Eversion	6.5 (2.7)	6.0 (3.1)	.533

Abbreviation: ROM, range of motion.

a

Values are expressed in degrees; values in parentheses are standard deviations.

Binary logistic regression analysis demonstrated that players with an SD <6 degrees were 3.69 times more likely to sustain an ankle injury than those with an SD ≥6 degrees (P = .007). Players with a CM >16 degrees and an SD <6 degrees had 3.14 times higher odds of injury (P = .025). A CM >16 degrees and an SMI >3.75 conferred 2.97 times higher injury risk (P = .032) (Table 3).

OPEN IN VIEWER

Table 3.

Odds Ratio of Ankle Injury by PROM and Predictor: Risk of Ankle Injury by STJ Motion.

Parameter	OR of Injury	95% CI	P Value
Dorsiflexion	1.007	0.920-1.102	.877
Plantarflexion	0.981	0.944-1.019	.321
Inversion	1.094	0.983-1.218	.101
Eversion	0.954	0.823-1.106	.531
CM	1.041	0.960-1.129	.335
SD < 6*	3.686	1.427-9.523	.007
CM > 16 and SD < 6*	3.136	1.157-8.500	.025
SMI > 3.75*	2.965	1.098-8.006	.032
CM > 16 and SMI > 3.75	2.56	0.982-6.675	.054

Abbreviations: CM, combination motion; OR, odds ratio; PROM, patient reported outcome measures; SD, subtalar difference; SMI, subtalar mobility index; STJ, subtalar joint.

*

Statistically significant.

Chi-square analysis found ankle injuries had no significant association with player position (P = .82), prior ankle injury (P = .37), shoe-type (P = .611), prophylactic pregame taping (P = .32), radiographic abnormalities (P = .34), or previous ankle surgery (P = .415).

Discussion

This prospective study rejected our original hypothesis that increased STJ ROM would predispose to ankle injuries. However, we did find an increased risk of ankle injury in players with decreased difference between inversion and eversion. By using the predictive subtalar mobility thresholds found in this study, we aim to alert clinicians to at-risk players.

No prior studies have investigated the STJ in basketball players; however, structural STJ hypermobility in nonathletes is a known risk factor for lateral ankle sprains and chronic instability.^1,2,7,9 Our findings suggest that injuries resulting in destabilization of the STJ may predispose to ankle injury and may warrant additional investigation with advanced imaging and close clinical follow-up. ⁹

SD proved to be the only individual threshold that was also identified as a risk factor. However, using SD alone, one is unable to differentiate between STJ hypermobility or rigidity when inversion and eversion were similar. Therefore, we recommend assessing CM to identify patients with increased subtalar mobility in conjunction with SD. SMI (proportion of CM to SD) can be used as a proxy for these measurements. We found that an SMI threshold of >3.75 approached significance but greater overall subtalar mobility (CM > 16 degrees) in combination with SMI >3.75 increases the risk of ankle injury by nearly 3 times.

Previous studies have reported multiple risk factors for ankle injuries in basketball players.^6,8 We found no significant differences in injury patterns when comparing collegiate vs professional basketball players (11.3% vs 16.1%, P = .406), history of previous ankle injury (16.3% vs 11.1%, P = .37) or prior ankle surgery (0% vs 14.5%, P = .415), nor based on shoe characteristics (P = .611). In contrast to prior studies, our data demonstrated no difference in injury rates with prophylactic taping (9.5% vs 15.9%, P = .315). ³

The present study has weaknesses. Goniometers possess a standard of measurement error, and some talocrural joint motion contributed to measured STJ values. ¹ Additionally, although we did not identify any osseous coalitions on plain radiographs, it is possible that players with rigid ankles had fibrous coalitions not evident on radiographs. We defined an athlete exposure to include any game or practice. Similar to other injury prevention studies, this method of data collection allowed comprehensive data capture of ankle injuries and should be regarded as a strength of the study. Incidence of injury was relatively scarce in this population during the period studied. We intentionally omitted a power analysis given that a post hoc analysis may falsely provide reassurances about the probability of type II error.

Supplemental Material