Hasan A Uysal, Turan Poyraz, Halil Gulluoglu, Fethi Idiman, Egemen Idiman
{"title":"儿童多发性硬化症患者Lhermitte体征的人工智能模型：一项随访研究","authors":"Hasan A Uysal, Turan Poyraz, Halil Gulluoglu, Fethi Idiman, Egemen Idiman","doi":"10.17219/acem/196466","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Lhermitte's sign (LS) is an important clinical marker for patients with multiple sclerosis (MS). Research on pediatric-onset MS (POMS) and LS is limited. To date, there has been no research conducted on the clinical and artificial intelligence (AI)-based radiological correlation of LS.</p><p><strong>Objectives: </strong>This follow-up study aims to investigate the relationship between LS and clinical findings according to AI-based radiological characteristics of patients with POMS.</p><p><strong>Material and methods: </strong>Basic descriptive statistics of patients with POMS according to sociodemographic, clinical and radiological findings were collected. Variables were evaluated at a 95% confidence level (95% CI), and a value of p < 0.05 was accepted as statistically significant. The LS in patients with MS was classified according to its presence in the past and at the time of the study screening: group A: absent; group B: positive in the past but absent at screening; group C: present both in the past and at the screening; group D: absent in the past but present at the screening. In addition, patients were grouped according to the duration of their MS, with the following classifications: <10 years and at least 10 years.</p><p><strong>Results: </strong>A total of 1,298 records were identified in the database search. Ninety-two patients who met the inclusion criteria were included in the study. The frequency of upper cervical lesions (C1-4 vertebral segmental levels) was higher in group B and C than in group A (p = 0.017). Among patients with an MS duration of 10-years, C1-4 lesions were least frequent in group A.</p><p><strong>Conclusions: </strong>Spinal imaging with AI-based programs can be used at least as much as brain magnetic resonance imaging (MRI) for early diagnosis, prognosis and treatment response. We have for the first time investigated LS in a large sample of patients with POMS. It is, however, recommended to conduct further multicenter studies to more specifically identify LS in patients with POMS.</p>","PeriodicalId":7306,"journal":{"name":"Advances in Clinical and Experimental Medicine","volume":" ","pages":"165-177"},"PeriodicalIF":2.1000,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An artificial intelligence model for Lhermitte's sign in patients with pediatric-onset multiple sclerosis: A follow-up study.\",\"authors\":\"Hasan A Uysal, Turan Poyraz, Halil Gulluoglu, Fethi Idiman, Egemen Idiman\",\"doi\":\"10.17219/acem/196466\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Lhermitte's sign (LS) is an important clinical marker for patients with multiple sclerosis (MS). Research on pediatric-onset MS (POMS) and LS is limited. To date, there has been no research conducted on the clinical and artificial intelligence (AI)-based radiological correlation of LS.</p><p><strong>Objectives: </strong>This follow-up study aims to investigate the relationship between LS and clinical findings according to AI-based radiological characteristics of patients with POMS.</p><p><strong>Material and methods: </strong>Basic descriptive statistics of patients with POMS according to sociodemographic, clinical and radiological findings were collected. Variables were evaluated at a 95% confidence level (95% CI), and a value of p < 0.05 was accepted as statistically significant. The LS in patients with MS was classified according to its presence in the past and at the time of the study screening: group A: absent; group B: positive in the past but absent at screening; group C: present both in the past and at the screening; group D: absent in the past but present at the screening. In addition, patients were grouped according to the duration of their MS, with the following classifications: <10 years and at least 10 years.</p><p><strong>Results: </strong>A total of 1,298 records were identified in the database search. Ninety-two patients who met the inclusion criteria were included in the study. The frequency of upper cervical lesions (C1-4 vertebral segmental levels) was higher in group B and C than in group A (p = 0.017). Among patients with an MS duration of 10-years, C1-4 lesions were least frequent in group A.</p><p><strong>Conclusions: </strong>Spinal imaging with AI-based programs can be used at least as much as brain magnetic resonance imaging (MRI) for early diagnosis, prognosis and treatment response. We have for the first time investigated LS in a large sample of patients with POMS. It is, however, recommended to conduct further multicenter studies to more specifically identify LS in patients with POMS.</p>\",\"PeriodicalId\":7306,\"journal\":{\"name\":\"Advances in Clinical and Experimental Medicine\",\"volume\":\" \",\"pages\":\"165-177\"},\"PeriodicalIF\":2.1000,\"publicationDate\":\"2025-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Advances in Clinical and Experimental Medicine\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.17219/acem/196466\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"MEDICINE, RESEARCH & EXPERIMENTAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Clinical and Experimental Medicine","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.17219/acem/196466","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MEDICINE, RESEARCH & EXPERIMENTAL","Score":null,"Total":0}
An artificial intelligence model for Lhermitte's sign in patients with pediatric-onset multiple sclerosis: A follow-up study.
Background: Lhermitte's sign (LS) is an important clinical marker for patients with multiple sclerosis (MS). Research on pediatric-onset MS (POMS) and LS is limited. To date, there has been no research conducted on the clinical and artificial intelligence (AI)-based radiological correlation of LS.
Objectives: This follow-up study aims to investigate the relationship between LS and clinical findings according to AI-based radiological characteristics of patients with POMS.
Material and methods: Basic descriptive statistics of patients with POMS according to sociodemographic, clinical and radiological findings were collected. Variables were evaluated at a 95% confidence level (95% CI), and a value of p < 0.05 was accepted as statistically significant. The LS in patients with MS was classified according to its presence in the past and at the time of the study screening: group A: absent; group B: positive in the past but absent at screening; group C: present both in the past and at the screening; group D: absent in the past but present at the screening. In addition, patients were grouped according to the duration of their MS, with the following classifications: <10 years and at least 10 years.
Results: A total of 1,298 records were identified in the database search. Ninety-two patients who met the inclusion criteria were included in the study. The frequency of upper cervical lesions (C1-4 vertebral segmental levels) was higher in group B and C than in group A (p = 0.017). Among patients with an MS duration of 10-years, C1-4 lesions were least frequent in group A.
Conclusions: Spinal imaging with AI-based programs can be used at least as much as brain magnetic resonance imaging (MRI) for early diagnosis, prognosis and treatment response. We have for the first time investigated LS in a large sample of patients with POMS. It is, however, recommended to conduct further multicenter studies to more specifically identify LS in patients with POMS.
期刊介绍：
Advances in Clinical and Experimental Medicine has been published by the Wroclaw Medical University since 1992. Establishing the medical journal was the idea of Prof. Bogumił Halawa, Chair of the Department of Cardiology, and was fully supported by the Rector of Wroclaw Medical University, Prof. Zbigniew Knapik. Prof. Halawa was also the first editor-in-chief, between 1992-1997. The journal, then entitled "Postępy Medycyny Klinicznej i Doświadczalnej", appeared quarterly.
Prof. Leszek Paradowski was editor-in-chief from 1997-1999. In 1998 he initiated alterations in the profile and cover design of the journal which were accepted by the Editorial Board. The title was changed to Advances in Clinical and Experimental Medicine. Articles in English were welcomed. A number of outstanding representatives of medical science from Poland and abroad were invited to participate in the newly established International Editorial Staff.
Prof. Antonina Harłozińska-Szmyrka was editor-in-chief in years 2000-2005, in years 2006-2007 once again prof. Leszek Paradowski and prof. Maria Podolak-Dawidziak was editor-in-chief in years 2008-2016. Since 2017 the editor-in chief is prof. Maciej Bagłaj.
Since July 2005, original papers have been published only in English. Case reports are no longer accepted. The manuscripts are reviewed by two independent reviewers and a statistical reviewer, and English texts are proofread by a native speaker.
The journal has been indexed in several databases: Scopus, Ulrich’sTM International Periodicals Directory, Index Copernicus and since 2007 in Thomson Reuters databases: Science Citation Index Expanded i Journal Citation Reports/Science Edition.
In 2010 the journal obtained Impact Factor which is now 1.179 pts. Articles published in the journal are worth 15 points among Polish journals according to the Polish Committee for Scientific Research and 169.43 points according to the Index Copernicus.
Since November 7, 2012, Advances in Clinical and Experimental Medicine has been indexed and included in National Library of Medicine’s MEDLINE database. English abstracts printed in the journal are included and searchable using PubMed http://www.ncbi.nlm.nih.gov/pubmed.
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