Evidence map›Paper›PMID 37292477›Full record

ArticleArXiv2023

Development and Stability Analysis of Carpal Kinematic Metrics from 4D Magnetic Resonance Imaging.

Azadeh Sharafi, Andrew S Nencka, Kevin M Koch

Open access · greenAbstract readPreprint
In one paragraph

Article in ArXiv, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.6field-weighted citation impact, top 39% 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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Azadeh Sharafi
Andrew S Nencka
Kevin M Koch
Medical College of Wisconsin · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionWrist instability remains a common health concern. The potential of dynamic Magnetic Resonance Imaging (MRI) in assessing carpal dynamics associated with this condition is a field of ongoing research. This study contributes to this line of inquiry by developing MRI-derived carpal kinematic metrics and investigating their stability.

methodsA previously described 4D MRI approach for tracking the movements of carpal bones in the wrist was deployed in this study. A panel of 120 metrics characterizing radial/ulnar deviation and flexion extension movements was constructed by fitting low order polynomial models of scaphoid and lunate degrees of freedom against that of the capitate. Intraclass Correlation Coefficients were utilized to analyze intra- and inter-subject stability within a mixed cohort of 49 subjects, including 20 with and 29 without a history of wrist injury.

resultsA comparable degree of stability across the two different wrist movements. Out of the total 120 derived metrics, distinct subsets demonstrated high stability within each type of movement. Among asymptomatic subjects, 16 out of 17 metrics with high intra-subject stability also showed high inter-subject stability. Interestingly, some quadratic term metrics, although relatively unstable within asymptomatic subjects, showed increased stability within this group, hinting at potential differentiation in their behavior across different cohorts.

conclusionThis study showed the developing potential of dynamic MRI to characterize complex carpal bone dynamics. Stability analyses of the derived kinematic metrics showed encouraging differences between cohorts with and without a history of wrist injury. Although these broad metric stability variations highlight the potential utility of this approach for analysis of carpal instability, further studies are necessary to better characterize these observations.

Identifiers

PMID37292477
PMCPMC10246087
OpenAlexW4379966167

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.