Evidence map›Paper›PMID 31074634›Full record

ArticleJournal of athletic training2019

Bilateral Strength Asymmetries and Unilateral Strength Imbalance: Predicting Ankle Injury When Considered With Higher Body Mass in US Special Forces

Shawn R Eagle, Marijn Kessels, Caleb D Johnson, Branco Nijst, Mita Lovalekar, Kellen Krajewski, Shawn D Flanagan, Bradley C Nindl, Chris Connaboy

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Article in Journal of athletic training, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

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8citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Shawn R EagleNeuromuscular Research Laboratory, University of Pittsburgh, PA.
Marijn KesselsFaculty of Health, Medicine and Life Sciences, Maastricht University, the Netherlands.
Caleb D JohnsonNeuromuscular Research Laboratory, University of Pittsburgh, PA.
Branco NijstFaculty of Health, Medicine and Life Sciences, Maastricht University, the Netherlands.
Mita LovalekarNeuromuscular Research Laboratory, University of Pittsburgh, PA.
Kellen KrajewskiNeuromuscular Research Laboratory, University of Pittsburgh, PA.
Shawn D FlanaganNeuromuscular Research Laboratory, University of Pittsburgh, PA.
Bradley C NindlNeuromuscular Research Laboratory, University of Pittsburgh, PA.
Chris ConnaboyNeuromuscular Research Laboratory, University of Pittsburgh, PA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

contextAnkle injury is one of the most common conditions in athletics and military activities. Strength asymmetry (SA) and imbalance may represent a risk factor for injury, but past investigations have produced ambiguous conclusions. Perhaps one explanation for this ambiguity is the fact that these authors used univariate models to predict injury.

objectiveTo evaluate the predictive utility of SA and imbalance calculations for ankle injury in univariate and multivariate prediction models.

designProspective cohort study.

settingLaboratory. PATIENTS OR OTHER

participantsA total of 140 male US Air Force Special Forces. MAIN OUTCOME MEASURE(S): Baseline testing consisted of body composition, isometric strength, and aerobic and anaerobic capacity. A clinician conducted medical chart reviews 365 days posttesting to document the incidence of ankle injury. Strength asymmetries were calculated based on the equations most prevalent in the literature along with known physiological predictors of injury in the military: age, height, weight, body composition, and aerobic capacity. Simple logistic regression was conducted using each predictor, and backward stepwise logistic regression was conducted with each equation method and the physiological predictors entered initially into the model.

resultsStrength asymmetry or imbalance or both, as a univariate predictor, was not able to predict ankle injury 365 days posttesting. Body mass (

conclusionsAs a univariate predictor, SA did not predict ankle injury. However, SA contributed significantly to predicting ankle injury in a multivariate model using body mass. Interpreting SA and imbalance in the presence of other physiological variables can help elucidate the risk of ankle injury.

Indexed as

Ankle InjuriesAthletic InjuriesMilitary PersonnelAdultBody Mass IndexFemaleHumansIncidenceMaleMuscle StrengthPostural BalancePredictive Value of TestsProspective StudiesSportsUnited Statesmilitary athletesrehabilitationsymmetry

Identifiers

PMID31074634
PMCPMC6602377

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.