Evidence map›Paper›PMID 25991502›Full record

ArticleJournal of orthopaedic research : official publication of the Orthopaedic Research Society2015

Statistical modeling to characterize relationships between knee anatomy and kinematics.

Lowell M Smoger, Clare K Fitzpatrick, Chadd W Clary, Adam J Cyr, Lorin P Maletsky, Paul J Rullkoetter, Peter J Laz

Open access · bronzeAbstract read
In one paragraph

Article in Journal of orthopaedic research : official publication of the Orthopaedic Research Society, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 1 pooled it
3.3field-weighted citation impact, top 8% 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

23 citing papers in PubMed, 1 synthesis or guideline pooled it, 72 citations in OpenAlex.

  1. Pooled it
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  14. Combined Estimation of Shape and Pose for Statistical Analysis of Articulating Joints.Shape in Medical Imaging : International Workshop, ShapeMI 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4, 2020, Proceedings · 2020
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  17. Statistical shape modeling of femur shape variability in female patients with hip dysplasia.Journal of orthopaedic research : official publication of the Orthopaedic Research Society · 2019
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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

7 authors at 2 institutions in 1 country.

Lowell M SmogerCenter for Orthopaedic Biomechanics, University of Denver, Denver, Colorado.
Clare K FitzpatrickCenter for Orthopaedic Biomechanics, University of Denver, Denver, Colorado.
Chadd W ClaryCenter for Orthopaedic Biomechanics, University of Denver, Denver, Colorado.
Adam J CyrCenter for Orthopaedic Biomechanics, University of Denver, Denver, Colorado.
Lorin P MaletskyUniversity of Kansas, Lawrence, Kansas.
Paul J RullkoetterCenter for Orthopaedic Biomechanics, University of Denver, Denver, Colorado.
Peter J LazCenter for Orthopaedic Biomechanics, University of Denver, Denver, Colorado.
University of Denver · USUniversity of Kansas · US

Funding

A Multi-Scale Finite Element Musculoskeletal Modeling Framework Applied to CurrenR01EB015497 · NIBIB · UNIVERSITY OF DENVER (COLORADO SEMINARY) · PI SHELBURNE, KEVIN B · 2012 to 2015
$1.1M
NIBIB NIH HHS 1R01EB015497-01NIBIB NIH HHS R01 EB015497
6 · The paper itself

Abstract

The mechanics of the knee are complex and dependent on the shape of the articular surfaces and their relative alignment. Insight into how anatomy relates to kinematics can establish biomechanical norms, support the diagnosis and treatment of various pathologies (e.g., patellar maltracking) and inform implant design. Prior studies have used correlations to identify anatomical measures related to specific motions. The objective of this study was to describe relationships between knee anatomy and tibiofemoral (TF) and patellofemoral (PF) kinematics using a statistical shape and function modeling approach. A principal component (PC) analysis was performed on a 20-specimen dataset consisting of shape of the bone and cartilage for the femur, tibia and patella derived from imaging and six-degree-of-freedom TF and PF kinematics from cadaveric testing during a simulated squat. The PC modes characterized links between anatomy and kinematics; the first mode captured scaling and shape changes in the condylar radii and their influence on TF anterior-posterior translation, internal-external rotation, and the location of the femoral lowest point. Subsequent modes described relations in patella shape and alta/baja alignment impacting PF kinematics. The complex interactions described with the data-driven statistical approach provide insight into knee mechanics that is useful clinically and in implant design.

Indexed as

Models, StatisticalAdultAgedAged, 80 and overBiomechanical PhenomenaHumansKnee JointMaleMiddle Agedjoint mechanicskinematicsknee anatomyprincipal component analysisstatistical shape modeling

Identifiers

PMID25991502
PMCPMC4591110
OpenAlexW1720657599

What OpenQuestion holds

Textmetadata
LicenceTDM
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.