Evidence map›Paper›PMID 35410142›Full record

ArticleBMC neurology2022

Corneal confocal microscopy in the evaluation of immune-related motor neuron disease syndrome.

Lin Jiao, Yuanjin Zhang, Haikun Wang, Dongsheng Fan

Open access · goldAbstract read
In one paragraph

Article in BMC neurology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
1.2field-weighted citation impact, top 22% 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

6 citing papers in PubMed, 1 synthesis or guideline pooled it, 6 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Observational
  6. Article
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

4 authors at 2 institutions in 1 country.

Lin JiaoDepartment of Neurology, Peking University Third Hospital, Beijing, China.
Yuanjin ZhangDepartment of Neurology, Peking University Third Hospital, Beijing, China.
Haikun WangDepartment of Ophthalmology, Peking University Third Hospital, Beijing, China.
Dongsheng FanDepartment of Neurology, Peking University Third Hospital, Beijing, China. dsfan2010@aliyun.com.
Peking University Third Hospital · CNPeking University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTo investigate the sensitivity and specificity of corneal confocal microscopy (CCM) in the diagnosis of immune-related motor neuron disease syndrome and evaluation of the response to immunosuppressive therapy.

methodsSeventy-two patients with clinical manifestations of motor neuron disease (MND) were analysed. According to whether they had concomitant rheumatic immune disease or rheumatic immune antibody abnormalities, they were divided into an MND group (33 patients) and an immune-related MND syndrome group (39 patients). Another 10 healthy adults were selected as the control group. All individuals were examined by CCM.

resultsFor Langerhans cell(LC) density, the area under the receiver operating characteristic(ROC)curve was 0.8, the best cut-off was 67.7 cells/mm2, the sensitivity was 79.5%, and the specificity was 72.7%. For inferior whorl length (IWL), the area under the ROC curve was 0.674, the best cut-off was 17.41 mm/mm

conclusionThe LC density and IWL are ideal for distinguishing MND from immune-related MND syndrome. The LC density reflects the immunotherapy response sensitively.

Indexed as

Diabetic NeuropathiesMotor Neuron DiseaseAdultCorneaHumansMicroscopy, ConfocalROC CurveSyndromeCorneal confocal microscopyImmunityInferior whorl lengthLangerhans cellMotor neuron disease

Identifiers

PMID35410142
PMCPMC8996532
OpenAlexW4223466761

What OpenQuestion holds

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LicenceCC BY
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.