Evidence map›Paper›PMID 27922760›Full record

ArticleDiabetes technology & therapeutics2016

NerveCheck for the Detection of Sensory Loss and Neuropathic Pain in Diabetes.

Georgios Ponirakis, Maria N Odriozola, Samantha Odriozola, Ioannis N Petropoulos, Shazli Azmi, Maryam Ferdousi, Hassan Fadavi, Uazman Alam, Andrew Marshall, Maria Jeziorska and 7 more

Open access · hybridAbstract readControlled Clinical Trial
In one paragraph

Article in Diabetes technology & therapeutics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
0.8field-weighted citation impact, top 24% 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

12 citing papers in PubMed, 1 synthesis or guideline pooled it, 22 citations in OpenAlex.

  1. Pooled it
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  4. Article
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  12. Observational
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

17 authors at 1 institution in 1 country.

Georgios Ponirakis1 Research Division, Weill Cornell Medicine-Qatar , Qatar Foundation, Education City, Doha, Qatar .
Maria N Odriozola3 Department of Electronics Engineering, Phi Med Europe Barcelona , Barcelona, Spain .
Samantha Odriozola3 Department of Electronics Engineering, Phi Med Europe Barcelona , Barcelona, Spain .
Ioannis N Petropoulos1 Research Division, Weill Cornell Medicine-Qatar , Qatar Foundation, Education City, Doha, Qatar .
Shazli Azmi2 Institute of Cardiovascular Sciences, Faculty of Biology, Medicine and Health, University of Manchester and Central Manchester NHS Foundation Trust , Manchester Academic Health Science Centre, Manchester, United Kingdom .
Maryam Ferdousi2 Institute of Cardiovascular Sciences, Faculty of Biology, Medicine and Health, University of Manchester and Central Manchester NHS Foundation Trust , Manchester Academic Health Science Centre, Manchester, United Kingdom .
Hassan Fadavi2 Institute of Cardiovascular Sciences, Faculty of Biology, Medicine and Health, University of Manchester and Central Manchester NHS Foundation Trust , Manchester Academic Health Science Centre, Manchester, United Kingdom .
Uazman Alam2 Institute of Cardiovascular Sciences, Faculty of Biology, Medicine and Health, University of Manchester and Central Manchester NHS Foundation Trust , Manchester Academic Health Science Centre, Manchester, United Kingdom .
Andrew Marshall2 Institute of Cardiovascular Sciences, Faculty of Biology, Medicine and Health, University of Manchester and Central Manchester NHS Foundation Trust , Manchester Academic Health Science Centre, Manchester, United Kingdom .
Maria Jeziorska2 Institute of Cardiovascular Sciences, Faculty of Biology, Medicine and Health, University of Manchester and Central Manchester NHS Foundation Trust , Manchester Academic Health Science Centre, Manchester, United Kingdom .
Anthony Miro3 Department of Electronics Engineering, Phi Med Europe Barcelona , Barcelona, Spain .
Ahmad Kheyami2 Institute of Cardiovascular Sciences, Faculty of Biology, Medicine and Health, University of Manchester and Central Manchester NHS Foundation Trust , Manchester Academic Health Science Centre, Manchester, United Kingdom .
Mitra Tavakoli2 Institute of Cardiovascular Sciences, Faculty of Biology, Medicine and Health, University of Manchester and Central Manchester NHS Foundation Trust , Manchester Academic Health Science Centre, Manchester, United Kingdom .
Ahmed Al-Ahmar2 Institute of Cardiovascular Sciences, Faculty of Biology, Medicine and Health, University of Manchester and Central Manchester NHS Foundation Trust , Manchester Academic Health Science Centre, Manchester, United Kingdom .
Maria B Odriozola3 Department of Electronics Engineering, Phi Med Europe Barcelona , Barcelona, Spain .
Ariel Odriozola4 ICEN, Catalonian Institute of Endocrinology and Nutrition , Medical Centre, Barcelona, Spain .
Rayaz A Malik1 Research Division, Weill Cornell Medicine-Qatar , Qatar Foundation, Education City, Doha, Qatar .
Weill Cornell Medical College in Qatar · QA

Funding

NON-INVASIVE SURROGATE MARKERS FOR DIABETIC NEUROPATHYR01NS046259 · NINDS · UNIVERSITY OF MANCHESTER · PI BOULTON, ANDREW JM · 2002 to 2004
$771k
NINDS NIH HHS R01 NS046259
6 · The paper itself

Abstract

backgroundAccurate and economic detection of nerve damage in diabetes is key to more widespread diagnosis of patients with diabetic peripheral neuropathy (DPN) and painful diabetic neuropathy. This study examined the diagnostic performance of NerveCheck, an inexpensive ($500) quantitative sensory testing (QST) device.

methodsOne hundred forty-four subjects (74 with and 70 without diabetes) underwent assessment with NerveCheck, neuropathy disability score (NDS), nerve conduction studies (NCS), intraepidermal and corneal nerve fiber density (IENFD and CNFD), and McGill questionnaire for neuropathic pain.

resultsOf the 74 subjects with diabetes, 41 were diagnosed with DPN based on the NDS. The NerveCheck scores for vibration perception threshold (VPT), cold perception threshold (CPT), and warm perception threshold (WPT) were significantly lower (P ≤ 0.0001) in diabetic patients with DPN compared to patients without DPN. The diagnostic accuracy of VPT was high with reference to NCS (area under the curve [AUC]: 82%-84%) and moderate for IENFD, CNFD, and neuropathic pain (AUC: 60%-76%). The diagnostic accuracy of CPT and WPT was moderate with reference to NCS, IENFD, and CNFD (AUC: 69%-78%) and low for neuropathic pain (AUC: 63%-65%).

conclusionsNerveCheck is a low-cost QST device with good diagnostic utility for identifying sensory deficits, comparable to established tests of large and small fiber neuropathy and for the severity of neuropathic pain.

Indexed as

AdultAgedDiabetic NeuropathiesDiagnostic Techniques, NeurologicalHumansMiddle AgedNeuralgiaSensation DisordersDiabetic peripheral neuropathyDiagnostic deviceNerveCheckQuantitative sensory testing

Identifiers

PMID27922760
PMCPMC5178001
OpenAlexW2560492779

What OpenQuestion holds

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LicenceCC BY-NC
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.