Evidence map›Paper›PMID 28574361›Full record

ArticleIEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society2017

Electrical Impedance Myography for Evaluating Paretic Muscle Changes After Stroke.

Xiaoyan Li, Le Li, Henry Shin, Sheng Li, Ping Zhou

Abstract read
In one paragraph

Article in IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Review
  2. Reliability of bioimpedance spectroscopy in the upper trapezius muscle.Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology · 2026
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  6. Review
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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.

Xiaoyan Li
Le Li
Henry Shin
Sheng Li
Ping Zhou

Funding

High Density Surface EMG Assessment of Motor Unit Alterations after StrokeR01NS080839 · NINDS · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI ZHOU, PING · 2014 to 2017
$1.3M
NINDS NIH HHS R01 NS080839
6 · The paper itself

Abstract

Electrical impedance myography (EIM) was used to assess the paretic muscle intrinsic electrical properties post stroke. Twenty-seven subjects with chronic hemiparesis participated in this study. Muscle impedance was measured by applying high-frequency, low-intensity alternating current to biceps brachii muscles. Major EIM parameters, resistance ( ), reactance ( ), phase angle ( ), and electrical anisotropy ratios (AR) of the three parameters, were examined at 50 kHz. Statistical analysis demonstrated significant reduction of reactance, phase angle, AR of resistance, and AR of reactance in the paretic muscle compared with the contralateral side (Paretic X: , contralateral X: , and p < 0.001; Paretic : , contralateral : 14.5 ± 0.82°, and p < 0.001; Paretic AR of R: 0.969 ± 0.013, contralateral AR of R: 1.008 ± 0.011, and p < 0.02; and Paretic AR of X: 0.981 ± 0.066, contralateral AR of X: 1.114 ± 0.041, and p < 0.02). Correlation analysis, however, did not show any significant relationship between EIM parameters and clinical assessments. Findings of this paper indicated significant changes in the muscular intrinsic electrical properties after stroke, possibly related to structural modifications induced by loss of muscle fibers or fat infiltration as well as changes in the quality of cell membranes post stroke.

Indexed as

Electric ImpedanceAdultAgedAlgorithmsAnisotropyElectromyographyFemaleHumansMaleMiddle AgedMuscle, SkeletalParesisReproducibility of ResultsStroke

Identifiers

PMID28574361
PMCPMC6734926

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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.