Evidence map›Paper›PMID 33136207›Full record

ReviewSports medicine - open2020

Biomechanical Determinants of Knee Joint Loads Associated with Increased Anterior Cruciate Ligament Loading During Cutting: A Systematic Review and Technical Framework.

Thomas A Donelon, Thomas Dos'Santos, Guy Pitchers, Mathew Brown, Paul A Jones

Open access · goldAbstract readReview
In one paragraph

Review in Sports medicine - open, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 57 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
57citing papers in PubMed, 5 pooled it
8.2field-weighted citation impact, top 2% 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

57 citing papers in PubMed, 5 syntheses or guidelines pooled it, 108 citations in OpenAlex.

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  17. Reliability of a Novel Qualitative Assessment Tool for Evaluating a Run Plant Task.International journal of sports physical therapy · 2026
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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

5 authors at 3 institutions in 1 country.

Thomas A DonelonRoom Af87, Section of Sport and Exercise Sciences, School of Human and Life Sciences, Canterbury Christ Church University, North Holmes Road, Canterbury, Kent, CT1 1QU, UK. Thomas.Donelon@canterbury.ac.uk.ORCID http://orcid.org/0000-0001-8813-2195
Thomas Dos'SantosDepartment of Sport and Exercise Science, Manchester Metropolitan University, Bonsall Street, Manchester, M15 6GX, UK.
Guy PitchersRoom Af87, Section of Sport and Exercise Sciences, School of Human and Life Sciences, Canterbury Christ Church University, North Holmes Road, Canterbury, Kent, CT1 1QU, UK.
Mathew BrownRoom Af87, Section of Sport and Exercise Sciences, School of Human and Life Sciences, Canterbury Christ Church University, North Holmes Road, Canterbury, Kent, CT1 1QU, UK.
Paul A JonesSchool of Health Sciences, University of Salford, C702 Allerton Building, Salford, M6 6PU, UK.
Canterbury Christ Church University · GBManchester Metropolitan University · GBUniversity of Salford · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCutting actions are associated with non-contact ACL injuries in multidirectional sports due to the propensity to generate large multiplanar knee joint loads (KJLs) that have the capacity to increase ACL loading and strain. Numerous studies have investigated the biomechanical determinants of KJLs in cutting tasks. The aim of this systematic review was to comprehensively review the literature regarding biomechanical determinants of KJLs during cutting, in order to develop a cutting technical framework alongside training recommendations for practitioners regarding KJL mitigation.

methodsDatabases (SPORTDiscus, Web of Science and PubMed) were systematically searched using a combination of the following terms: "Biomechanical determinants", or "Knee abduction moment", or "Technical determinants", or "Knee loading", or "Knee loads", or "Mechanical determinants", or "ACL strain", or "Knee adduction moment", or "Anterior tibial shear", or "Knee internal rotation moment", or "Knee valgus moment" AND "Change of direction", or "Cutting manoeuvre", or "Run and cut", or "Run-and-cut", or "Sidestepping", or "Side-stepping", or "Shuttle run". Inclusion criteria were as follows: studies examining a cutting task < 110° with a preceding approach run that examined biomechanical determinants of KJLs using three-dimensional motion analysis.

resultsThe search returned 6404 possibly eligible articles, and 6 identified through other sources. Following duplicate removal, 4421 titles and abstracts were screened, leaving 246 full texts to be screened for inclusion. Twenty-three full texts were deemed eligible for inclusion and identified numerous determinants of KJLs; 11 trunk, 11 hip, 7 knee, 3 multiplanar KJLs, 5 foot/ankle and 7 identifying ground reaction forces (GRFs) as determinants of KJLs.

conclusionUsing the framework developed from the results, cutting KJLs can be mitigated through the following: reducing lateral foot-plant distances, thus lowering hip abduction and orientating the foot closer to neutral with a mid-foot or forefoot placement strategy; minimising knee valgus and hip internal rotation angles and motion at initial contact (IC) and weight acceptance (WA); avoiding and limiting lateral trunk flexion and attempt to maintain an upright trunk position or trunk lean into the intended direction; and finally, reducing GRF magnitude during WA, potentially by attenuation through increased knee flexion and emphasising a greater proportion of braking during the penultimate foot contact (PFC).

Indexed as

ACLInjury-Performance ConflictKnee joint loadsSidesteppingTechnical Framework

Identifiers

PMID33136207
PMCPMC7606399
OpenAlexW3094794124

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.