Evidence map›Paper›PMID 29276707›Full record

ArticleFrontiers in bioengineering and biotechnology2017

Reliability and Minimal Detectable Change Values for Predictions of Knee Forces during Gait and Stair Ascent Derived from the FreeBody Musculoskeletal Model of the Lower Limb.

Phil D B Price, Conor Gissane, Daniel J Cleather

Abstract read
In one paragraph

Article in Frontiers in bioengineering and biotechnology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
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

6 citing papers in PubMed.

  1. Article
  2. The Reliability and Validity of Gluteal Endurance Measures (GEMs).International journal of sports physical therapy · 2021
    Article
  3. Article
  4. Knee Forces During Landing in Men and Women.Journal of human kinetics · 2019
    Article
  5. Deep Learning for Musculoskeletal Force Prediction.Annals of biomedical engineering · 2019
    Article
  6. Article
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

3 authors.

Phil D B PriceSchool of Sport, Health and Applied Sciences, St. Mary's University, Twickenham, United Kingdom.
Conor GissaneSchool of Sport, Health and Applied Sciences, St. Mary's University, Twickenham, United Kingdom.
Daniel J CleatherSchool of Sport, Health and Applied Sciences, St. Mary's University, Twickenham, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

FreeBody is a musculoskeletal model of the lower limb used to calculate predictions of muscle and joint contact forces. The validation of FreeBody has been described in a number of publications; however, its reliability has yet to be established. The purpose of this study was, therefore, to establish the test-retest reliability of FreeBody in a population of healthy adults in order to add support to previous and future research using FreeBody that demonstrates differences between cohorts after an intervention. We hypothesized that test-retest estimations of knee contact forces from FreeBody would demonstrate a high intra-class correlation. Kinematic and kinetic data from nine older participants (4 men: mean age = 63 ± 11 years; 5 women: mean age = 49 ± 4 years) performing level walking and stair ascent was collected on consecutive days and then analyzed using FreeBody. There was a good level of intra-session agreement between the waveforms for the individual trials of each activity during testing session 1 (

Indexed as

KAMknee osteoarthritismedial tibiofemoral joint load sharemusculoskeletal modelingpatellofemoral jointpeak knee adduction momenttibiofemoral jointvalidation

Identifiers

PMID29276707
PMCPMC5727024

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.