Metabolic, cardiopulmonary, and gait profiles of recently injured and noninjured runners

Association Between Temporal Spatial Parameters and Overuse Injury History in Runners: A Systematic Review and Meta-analysis

BACKGROUND

Temporal spatial parameters during running are measurable outside of clinical and laboratory environments using wearable technology. Data from wearable technology may be useful for injury prevention, however the association of temporal spatial parameters with overuse injury in runners remains unclear.

OBJECTIVE

To identify the association between overuse injury and temporal spatial parameters during running.

DATA SOURCES

Electronic databases were searched using keywords related to temporal spatial parameters, running, and overuse injury, and authors' personal article collections through hand search.

ELIGIBILITY CRITERIA FOR SELECTING STUDIES

Articles included in this systematic review contained original data, and analytically compared at least one temporal spatial parameter (e.g. cadence) between uninjured and retrospectively or prospectively injured groups of runners. Articles were excluded from this review if they did not meet these criteria or measured temporal spatial parameters via survey.

STUDY APPRAISAL AND SYNTHESIS METHOD

The internal validity of each article was assessed using the National Institutes of Health Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies. Meta-analyses were conducted for temporal spatial parameters if data existed from at least three separate cohorts of the same prospective or retrospective design. Data were pooled and analyzed using an inverse variance fixed-effect model.

RESULTS

Thirteen articles which tested a total of 24 temporal spatial parameters during running were included in the review. Meta-analyses were conducted on four temporal spatial parameters using data from eleven retrospective studies. Healthy runners and those with a history of overuse injury had a similar average stride time (mean difference: 0.00 s, 95% CI - 0.01 to 0.01 s), contact time (mean difference: 0.00 s, 95% CI 0.00 to 0.01 s), cadence (mean difference: 0.3 steps per minute (spm), 95% CI - 1.8 to 2.5 spm), and stride length (mean difference 0.00 m, 95% CI - 0.05 to 0.05 m) during running.

LIMITATIONS

Data pooled for meta-analyses were limited to retrospective design studies. Studies included in the systematic review had low methodological consistency.

CONCLUSION

Based on pooled results from multiple studies, stride time, contact time, cadence, and stride length averages are not distinguishable between runners either with or without a history of overuse injury. More prospective studies are required to determine the association of temporal spatial parameters with overuse injury development in runners.

SYSTEMATIC REVIEW REGISTRATION REGISTRY AND NUMBER

CRD42018112290.

Use of baseline pelvic acceleration during running for classifying response to muscle strengthening treatment in patellofemoral pain: A preliminary study

BACKGROUND

Objectively identifying patients at baseline who may not respond well to a generic muscle strengthening intervention could improve clinical practice by optimizing treatment strategies. The purpose of this study was to determine whether pelvic acceleration measures during running, and clinical and demographic variables could classify patellofemoral pain patients according to their response to a 6-week hip/core and knee exercise-based rehabilitation protocol.

METHODS

Forty-one individuals with patellofemoral pain participated in a 6-week exercise intervention program and were sub-grouped into treatment Responders (n = 28) and Non-responders (n = 13) based on self-reported pain and function measures. Baseline pelvic acceleration measures were reduced using a principal component analysis and combined with patient reported outcome measures and demographic variables in a support vector machine to retrospectively classify patient treatment response.

FINDINGS

The final classification model had 85.4% classification accuracy, which was significantly better than treatment success rate, with excellent detection rates for Responders (recall: 96.4%), but 23.1% of misclassifications among Non-responders (precision: 90.0%). Thus, it resulted in an F1-score of 0.93 and a Matthews correlation coefficient of 0.69.

INTERPRETATION

Overall, the classifier successfully separated patellofemoral pain patients into exercise-based treatment Responders and Non-responders based on a combination of three components of the pelvic accelerations. While this model requires independent validation, it has the potential for further development and to be applied in clinical practice and improve treatment strategies for patellofemoral pain.

High-Intensity Cycling Training: The Effect of Work-to-Rest Intervals on Running Performance Measures

The work-to-rest ratio during cycling-based high-intensity interval training (HIT) could be important in regulating physiological and performance adaptations. We sought to determine the effectiveness of cycling-based HIT with different work-to-rest ratios for long-distance running. Thirty-two long-distance runners (age: 39 ± 8 years; sex: 14 men, 18 women; average weekly running training volume: 25 miles) underwent baseline testing (3-km time-trial, V[Combining Dot Above]O2peak and time to exhaustion, and Wingate test) before a 2-week matched-work cycling HIT of 6 × 10-second sprints with different rest periods (30 seconds [R30], 80 seconds [R80], 120 seconds [R120], or control). Three-kilometer time trial was significantly improved in the R30 group only (3.1 ± 4.0%, p = 0.04), whereas time to exhaustion was significantly increased in the 2 groups with a lower work-to-rest ratio (R30 group 6.4 ± 6.3%, p = 0.003 vs. R80 group 4.4 ± 2.7%, p = 0.03 vs. R120 group 1.9 ± 5.0%, p = 0.2). However, improvements in average power production were significantly greater with a higher work-to-rest ratio (R30 group 0.3 ± 4.1%, p = 0.8 vs. R80 group 4.6 ± 4.2%, p = 0.03 vs. R120 group 5.3 ± 5.9%, p = 0.02), whereas peak power significantly increased only in the R80 group (8.5 ± 8.2%, p = 0.04) but not in the R30 group (4.3 ± 6.1%, p = 0.3) or in the R120 group (7.1 ± 7.9%, p = 0.09). Therefore, cycling-based HIT is an effective way to improve running performance, and the type and magnitude of adaptation is dependent on the work-to-rest ratio.