Evidence map›Paper›PMID 28351803›Full record

ArticleJournal of neuroscience methods2017

Establishing a reliable gait evaluation method for rodent studies.

Huanwen Chen, Jian Du, Yifan Zhang, Kevin Barnes, Xiaofeng Jia

Abstract readEvaluation StudyValidation Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of neuroscience methods, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing 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

23 citing papers in PubMed.

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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

5 authors.

Huanwen ChenDepartment of Neurosurgery, University of Maryland School of Medicine, Baltimore, MD 21201, USA.
Jian DuDepartment of Neurosurgery, University of Maryland School of Medicine, Baltimore, MD 21201, USA.
Yifan ZhangDepartment of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
Kevin BarnesDepartment of Neurosurgery, University of Maryland School of Medicine, Baltimore, MD 21201, USA.
Xiaofeng JiaDepartment of Neurosurgery, University of Maryland School of Medicine, Baltimore, MD 21201, USA; Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Department of Orthopedics, University of Maryland School of Medicine, Baltimore, MD 21201, USA; Department of Anatomy and Neurobiology, University of Maryland School of Medicine, Baltimore, MD 21201, USA; Department of Anesthesiology and Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA. Electronic address: xjia@som.umaryland.edu.

Funding

Brain Monitoring and Therapeutic Hypothermia after Cardiac ArrestR01HL118084 · NHLBI · UNIVERSITY OF MARYLAND BALTIMORE · PI JIA, XIAOFENG · 2013 to 2018
$1.9M
NHLBI NIH HHS R01 HL118084
6 · The paper itself

Abstract

backgroundCatWalk is one of the most popular tools for evaluating gait recovery in preclinical research, however, there is currently no consensus on which of the many gait parameters captured by CatWalk can reliably model recovery. There are conflicting interpretations of results, along with many common but seldom reported problems such as heel walking and poor compliance. NEW

methodWe developed a systematic manual classification method that overcomes common problems such as heel walking and poor compliance. By correcting automation errors and removing inconsistent gait cycles, we isolated stretches of recordings that are more reliable for analysis. Recovery outcome was also assessed by quantitative histomorphometric analysis of myelinated axons.

resultsWhile 40-60% of runs were erroneously classified without manual intervention, we corrected all errors with our new method, and showed that Stand Time, Duty Cycle, and Swing Speed are able to track significant differences over time and between experimental groups (all p<0.05). The usability of print area and intensity parameters requires further validation beyond the capabilities of CatWalk. COMPARISON WITH EXISTING METHOD(S): There is currently no strategy that addresses problems such as heel walking and poor compliance, and therefore no standard set of parameters that researchers can rely on to report their findings.

conclusionManual classification is a crucial step to generate reliable CatWalk data, and Stand Time, Duty Cycle, and Swing Speed are suitable parameters for evaluating gait recovery. Static parameters such as print area and intensity should be used with extreme caution.

Indexed as

GaitAnimalsImage Interpretation, Computer-AssistedLameness, AnimalPhysical ExaminationRatsRats, NudeReproducibility of ResultsSensitivity and SpecificitySoftwareWhole Body ImagingCatWalkFunctional recoveryGaitHeel walkingPeripheral nerveRat

Identifiers

PMID28351803
PMCPMC5461654

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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.