Evidence map›Paper›PMID 34669175›Full record

ReviewSports medicine (Auckland, N.Z.)2022

Effects of and Response to Mechanical Loading on the Knee.

David S Logerstedt, Jay R Ebert, Toran D MacLeod, Bryan C Heiderscheit, Tim J Gabbett, Brian J Eckenrode

Abstract readReview
PubMed Publisher
In one paragraph

Review in Sports medicine (Auckland, N.Z.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 61 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
61citing papers in PubMed, 5 pooled it
11.5field-weighted citation impact, top 1% 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

61 citing papers in PubMed, 5 syntheses or guidelines pooled it, 109 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. TNFα-Related Chondrocyte Inflammation Models: A Systematic Review.International journal of molecular sciences · 2024
    Pooled it
  4. Pooled it
  5. Pooled it
  6. Review
  7. Article
  8. Article
  9. Review
  10. Comparing kinematic and kinetic demands on the knee joint during selected physiotherapy exercises and activities of daily living.Technology and health care : official journal of the European Society for Engineering and Medicine · 2026
    Article
  11. Observational
  12. Article
  13. Review
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Review

1 more citing papers are in PubMed but not listed here.

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 6 institutions in 2 countries.

David S LogerstedtDepartment of Physical Therapy, University of the Sciences in Philadelphia, Philadelphia, PA, USA. d.logerstedt@usciences.edu.ORCID http://orcid.org/0000-0001-8977-013X
Jay R EbertSchool of Human Sciences (Exercise and Sport Science), University of Western Australia, Perth, WA, Australia.
Toran D MacLeodDepartment of Physical Therapy, Sacramento State University, Sacramento, CA, USA.
Bryan C HeiderscheitOrthopedics and Rehabilitation, University of Wisconsin-Madison, Madison, WI, USA.
Tim J GabbettGabbett Performance Solutions, Brisbane, QLD, Australia.
Brian J EckenrodeDepartment of Physical Therapy, Arcadia University, Glenside, PA, USA.
Arcadia University · USCalifornia State University, Sacramento · USThe University of Western Australia · AUUniversity of Southern Queensland · AUUniversity of the Sciences · USUniversity of Wisconsin–Madison · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mechanical loading to the knee joint results in a differential response based on the local capacity of the tissues (ligament, tendon, meniscus, cartilage, and bone) and how those tissues subsequently adapt to that load at the molecular and cellular level. Participation in cutting, pivoting, and jumping sports predisposes the knee to the risk of injury. In this narrative review, we describe different mechanisms of loading that can result in excessive loads to the knee, leading to ligamentous, musculotendinous, meniscal, and chondral injuries or maladaptations. Following injury (or surgery) to structures around the knee, the primary goal of rehabilitation is to maximize the patient's response to exercise at the current level of function, while minimizing the risk of re-injury to the healing tissue. Clinicians should have a clear understanding of the specific injured tissue(s), and rehabilitation should be driven by knowledge of tissue-healing constraints, knee complex and lower extremity biomechanics, neuromuscular physiology, task-specific activities involving weight-bearing and non-weight-bearing conditions, and training principles. We provide a practical application for prescribing loading progressions of exercises, functional activities, and mobility tasks based on their mechanical load profile to knee-specific structures during the rehabilitation process. Various loading interventions can be used by clinicians to produce physical stress to address body function, physical impairments, activity limitations, and participation restrictions. By modifying the mechanical load elements, clinicians can alter the tissue adaptations, facilitate motor learning, and resolve corresponding physical impairments. Providing different loads that create variable tensile, compressive, and shear deformation on the tissue through mechanotransduction and specificity can promote the appropriate stress adaptations to increase tissue capacity and injury tolerance. Tools for monitoring rehabilitation training loads to the knee are proposed to assess the reactivity of the knee joint to mechanical loading to monitor excessive mechanical loads and facilitate optimal rehabilitation.

Indexed as

Knee InjuriesMechanotransduction, CellularBiomechanical PhenomenaHumansKneeKnee JointWeight-Bearing

Identifiers

PMID34669175
OpenAlexW3205446507

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.