Evidence map›Paper›PMID 32222127›Full record

ArticleTurkish journal of medical sciences2020

The needle electromyography findings in the neurophysiological classification of ulnar neuropathy at the elbow

Halit Fidanci, Ilker Öztürk, Ahmet Candan Köylüoğlu, Mehmet Yildiz, Şencan Buturak, Zülfikar Arlier

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Article in Turkish journal of medical sciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.0field-weighted citation impact, top 21% 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

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 17 citations in OpenAlex.

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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

6 authors.

Halit FidanciDepartment of Clinical Neurophysiology, Adana City Training & Research Hospital, Adana, TurkeyORCID 0000-0001-6573-9090
Ilker ÖztürkDepartment of Neurology, Adana City Training & Research Hospital, Adana TurkeyORCID 0000-0002-2333-9360
Ahmet Candan KöylüoğluDepartment of Neurology, Adana City Training & Research Hospital, Adana TurkeyORCID 0000-0002-0795-0610
Mehmet YildizDepartment of Neurology, Adana City Training & Research Hospital, Adana TurkeyORCID 0000-0002-0411-6794
Şencan ButurakDepartment of Neurology, Adana City Training & Research Hospital, Adana TurkeyORCID 0000-0002-7496-5628
Zülfikar ArlierDepartment of Neurology, Adana City Training & Research Hospital, Adana TurkeyORCID 0000-0003-2645-648X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background/aim: Although ulnar neuropathy at the elbow (UNE) is the second most common entrapment mononeuropathy, there are few reports on its neurophysiological classification. In this study, we tried to find out the role of needle electromyography (EMG) in the neurophysiological classification of UNE. Materials and methods: UNE patients who met the clinical and neurophysiological diagnostic criteria and healthy individuals were included in this study. Reference values of nerve conduction studies were obtained from healthy individuals. Needle EMG was performed to all UNE patients. According to the neurophysiological classification proposed by Padua, UNE patients were classified as mild, moderate, and severe. Results: Thirty-one controls and thirty-five UNE patients were included in the study. There was mild UNE in 23 patients, moderate UNE in 8, and severe UNE in 4. Abnormal needle EMG findings were present in all patients with moderate and severe UNE and in 12 patients with mild UNE. Conclusion: Abnormal needle EMG findings are seen in most of the UNE patients. Therefore, it is not practical to use needle EMG findings in the neurophysiological classification. Needle EMG abnormalities may also be present in patients with mild UNE due to axonal degeneration or motor conduction block.

Indexed as

AdolescentAdultAgedElbowElectromyographyFemaleHumansMaleMiddle AgedNeedlesSensitivity and SpecificityUlnar NeuropathiesYoung AdultNeedle electromyographyneurophysiological classificationulnar neuropathy at the elbow

Identifiers

PMID32222127
PMCPMC7379465
OpenAlexW3013700374

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.