Evidence map›Paper›PMID 33615524›Full record

ArticleJournal of orthopaedic research : official publication of the Orthopaedic Research Society2021

Multivariate functional principal component analysis identifies waveform features of gait biomechanics related to early-to-moderate hip osteoarthritis.

Koren E Roach, Valentina Pedoia, Jinhee J Lee, Tijana Popovic, Thomas M Link, Sharmila Majumdar, Richard B Souza

Open access · greenAbstract read
In one paragraph

Article in Journal of orthopaedic research : official publication of the Orthopaedic Research Society, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
0.4field-weighted citation impact, top 34% 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

9 citing papers in PubMed, 13 citations in OpenAlex.

  1. Observational
  2. Article
  3. The functional gait deviation index.Journal of applied statistics · 2026
    Article
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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 1 institution in 1 country.

Koren E RoachDepartment of Radiology and Biomedical Imaging, Musculoskeletal Quantitative Imaging Research, University of California, San Francisco, California, USA.ORCID 0000-0003-0897-9340
Valentina PedoiaDepartment of Radiology and Biomedical Imaging, Musculoskeletal Quantitative Imaging Research, University of California, San Francisco, California, USA.
Jinhee J LeeDepartment of Radiology and Biomedical Imaging, Musculoskeletal Quantitative Imaging Research, University of California, San Francisco, California, USA.
Tijana PopovicDepartment of Radiology and Biomedical Imaging, Musculoskeletal Quantitative Imaging Research, University of California, San Francisco, California, USA.
Thomas M LinkDepartment of Radiology and Biomedical Imaging, Musculoskeletal Quantitative Imaging Research, University of California, San Francisco, California, USA.
Sharmila MajumdarDepartment of Radiology and Biomedical Imaging, Musculoskeletal Quantitative Imaging Research, University of California, San Francisco, California, USA.
Richard B SouzaDepartment of Radiology and Biomedical Imaging, Musculoskeletal Quantitative Imaging Research, University of California, San Francisco, California, USA.
QB3 · US

Funding

Structural, Biochemical and Functional Connectivity in Osteoarthritis using Quantitative Magnetic Resonance Imaging and Skeletal BiomechanicsR01AR069006 · NIAMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI MAJUMDAR, SHARMILA, SOUZA, RICHARD BRIAN · 2016 to 2025
$7.2M
Mentoring Biomechanics Research in OsteoarthritisK24AR072133 · NIAMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Richard Brian Souza · 2018 to 2026
$1.5M
Multidimensional MRI-based Non-Euclidean Deep Learning to Study OsteoarthritisR00AR070902 · NIAMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI PEDOIA, VALENTINA · 2018 to 2020
$747k
NIAMS NIH HHS K24 AR072133NIAMS NIH HHS R00 AR070902NIAMS NIH HHS R01 AR069006
6 · The paper itself

Abstract

Clinicians often examine movement patterns to design hip osteoarthritis (OA) interventions, yet traditional biomechanical analyses only report a single timepoint. Multivariate principal component analysis (MFPCA) analyzes the entire waveform (i.e., movement pattern), which clinicians observe to direct treatment. This study investigated hip OA indicators, by (1) employing MFPCA to characterize variance across the hip, knee, and ankle angles in healthy and early-to-moderate hip OA participants; and (2) investigating relationships between these waveform features and hip cartilage health. Bilateral hip magnetic resonance images from 72 participants with Kellgren-Lawrence grades ranging from 0 to 3 were used to calculate mean T

Indexed as

Cartilage, ArticularOsteoarthritis, HipOsteoarthritis, KneeBiomechanical PhenomenaGaitHumansMagnetic Resonance ImagingPrincipal Component Analysisgait biomechanicship osteoarthritismagnetic resonance imagingmultivariate functional principal component analysisT 1ρ and T 2 relaxation times

Identifiers

PMID33615524
PMCPMC8180534
OpenAlexW3113162785

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.