Evidence map›Paper›PMID 24762234›Full record

Observational studyJournal of athletic training

A predictive model to estimate knee-abduction moment: implications for development of a clinically applicable patellofemoral pain screening tool in female athletes.

Gregory D Myer, Kevin R Ford, Kim D Barber Foss, Mitchell J Rauh, Mark V Paterno, Timothy E Hewett

Open access · bronzeAbstract readObservational Study
In one paragraph

Observational study in Journal of athletic training. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
3.1field-weighted citation impact, top 9% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed, 1 synthesis or guideline pooled it, 25 citations in OpenAlex.

  1. Pooled it
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  9. SPORTSMETRICS™ TRAINING IMPROVES POWER AND LANDING IN HIGH SCHOOL ROWERS.International journal of sports physical therapy · 2016
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 5 institutions in 1 country.

Gregory D MyerSports Medicine Biodynamics Center and Human Performance Laboratory, Cincinnati Children's Hospital Medical Center, OH.
Kevin R Ford
Kim D Barber Foss
Mitchell J Rauh
Mark V Paterno
Timothy E Hewett
Cincinnati Children's Hospital Medical Center · USRocky Mountain University of Health Professions · USSan Diego State University · USThe Micheli Center for Sports Injury Prevention · USUniversity of Cincinnati Medical Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

contextProspective measures of high external knee-abduction moment (KAM) during landing identify female athletes at increased risk of patellofemoral pain (PFP). A clinically applicable screening protocol is needed.

objectiveTo identify biomechanical laboratory measures that would accurately quantify KAM loads during landing that predict increased risk of PFP in female athletes and clinical correlates to laboratory-based measures of increased KAM status for use in a clinical PFP injury-risk prediction algorithm. We hypothesized that we could identify clinical correlates that combine to accurately determine increased KAM associated with an increased risk of developing PFP.

designDescriptive laboratory study.

settingBiomechanical laboratory. PATIENTS OR OTHER

participantsAdolescent female basketball and soccer players (n = 698) from a single-county public school district. MAIN OUTCOME MEASURE(S): We conducted tests of anthropometrics, maturation, laxity, flexibility, strength, and landing biomechanics before each competitive season. Pearson correlation and linear and logistic regression modeling were used to examine high KAM (>15.4 Nm) compared with normal KAM as a surrogate for PFP injury risk.

resultsThe multivariable logistic regression model that used the variables peak knee-abduction angle, center-of-mass height, and hip rotational moment excursion predicted KAM associated with PFP risk (>15.4 NM of KAM) with 92% sensitivity and 74% specificity and a C statistic of 0.93. The multivariate linear regression model that included the same predictors accounted for 70% of the variance in KAM. We identified clinical correlates to laboratory measures that combined to predict high KAM with 92% sensitivity and 47% specificity. The clinical prediction algorithm, including knee-valgus motion (odds ratio [OR] = 1.46, 95% confidence interval [CI] = 1.31, 1.63), center-of-mass height (OR = 1.21, 95% CI = 1.15, 1.26), and hamstrings strength/body fat percentage (OR = 1.80, 95% CI = 1.02, 3.16) predicted high KAM with a C statistic of 0.80.

conclusionsClinical correlates to laboratory-measured biomechanics associated with an increased risk of PFP yielded a highly sensitive model to predict increased KAM status. This screening algorithm consisting of a standard camcorder, physician scale for mass, and handheld dynamometer may be used to identify athletes at increased risk of PFP.

Indexed as

Models, StatisticalAdolescentAdultAlgorithmsArthralgiaBasketballBiomechanical PhenomenaFemaleHipHumansKnee JointLogistic ModelsMass ScreeningModels, BiologicalMovementPain Measurementassessment toolshigh-risk biomechanicsknee injury preventionpatellofemoral risk factorstargeted neuromuscular training

Identifiers

PMID24762234
PMCPMC4080601
OpenAlexW2067359535

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.