Mohammed Al-Shehri, Theerthika Dillibabu, Belinda Nicolau, Marco Magalhaes, Nicholas Makhoul, Faleh Tamimi, Peter Chauvin, Sreenath Madathil
{"title":"口腔黏膜病变临床诊断算法的现状:范围综述。","authors":"Mohammed Al-Shehri, Theerthika Dillibabu, Belinda Nicolau, Marco Magalhaes, Nicholas Makhoul, Faleh Tamimi, Peter Chauvin, Sreenath Madathil","doi":"10.1111/odi.15388","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Diagnosing oral lesions remains challenging for many dentists. Despite the availability of diagnostic algorithms, there is a dearth of comprehensive evidence synthesis and a discussion on their clinical and pedagogical applicability.</p><p><strong>Methods: </strong>A scoping review was conducted to identify: (1) algorithms or flow diagrams that help clinicians to diagnose oral lesions in a clinical setting without additional software; (2) publications in English; (3) all age groups; (4) algorithms for oral lesions of soft tissue only. We excluded those that are: (1) black-box; (2) required additional tests; (3) older versions; (4) for non-mucosal lesions, and (5) intended for self-screening. A keyword and MeSH term search was performed across three peer-reviewed publication databases and gray literature.</p><p><strong>Results: </strong>Seventeen algorithms from 15 peer-reviewed manuscripts and 1 online course were identified. Most studies did not mention how the algorithms were developed, and none had been validated in a clinical setting. The algorithms often focused on one or two types of lesions and were incomplete in differential diagnoses.</p><p><strong>Conclusion: </strong>Few clinical diagnostic algorithms for oral lesions are available in the literature. Notably, there are no validated and comprehensive clinical diagnostic algorithms for oral mucosal lesions.</p>","PeriodicalId":19615,"journal":{"name":"Oral diseases","volume":" ","pages":""},"PeriodicalIF":2.9000,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The Current State of Clinical Diagnostic Algorithms for Mucosal Oral Lesions: A Scoping Review.\",\"authors\":\"Mohammed Al-Shehri, Theerthika Dillibabu, Belinda Nicolau, Marco Magalhaes, Nicholas Makhoul, Faleh Tamimi, Peter Chauvin, Sreenath Madathil\",\"doi\":\"10.1111/odi.15388\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Diagnosing oral lesions remains challenging for many dentists. Despite the availability of diagnostic algorithms, there is a dearth of comprehensive evidence synthesis and a discussion on their clinical and pedagogical applicability.</p><p><strong>Methods: </strong>A scoping review was conducted to identify: (1) algorithms or flow diagrams that help clinicians to diagnose oral lesions in a clinical setting without additional software; (2) publications in English; (3) all age groups; (4) algorithms for oral lesions of soft tissue only. We excluded those that are: (1) black-box; (2) required additional tests; (3) older versions; (4) for non-mucosal lesions, and (5) intended for self-screening. A keyword and MeSH term search was performed across three peer-reviewed publication databases and gray literature.</p><p><strong>Results: </strong>Seventeen algorithms from 15 peer-reviewed manuscripts and 1 online course were identified. Most studies did not mention how the algorithms were developed, and none had been validated in a clinical setting. The algorithms often focused on one or two types of lesions and were incomplete in differential diagnoses.</p><p><strong>Conclusion: </strong>Few clinical diagnostic algorithms for oral lesions are available in the literature. Notably, there are no validated and comprehensive clinical diagnostic algorithms for oral mucosal lesions.</p>\",\"PeriodicalId\":19615,\"journal\":{\"name\":\"Oral diseases\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":2.9000,\"publicationDate\":\"2025-06-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Oral diseases\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1111/odi.15388\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"DENTISTRY, ORAL SURGERY & MEDICINE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Oral diseases","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1111/odi.15388","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"DENTISTRY, ORAL SURGERY & MEDICINE","Score":null,"Total":0}
The Current State of Clinical Diagnostic Algorithms for Mucosal Oral Lesions: A Scoping Review.
Background: Diagnosing oral lesions remains challenging for many dentists. Despite the availability of diagnostic algorithms, there is a dearth of comprehensive evidence synthesis and a discussion on their clinical and pedagogical applicability.
Methods: A scoping review was conducted to identify: (1) algorithms or flow diagrams that help clinicians to diagnose oral lesions in a clinical setting without additional software; (2) publications in English; (3) all age groups; (4) algorithms for oral lesions of soft tissue only. We excluded those that are: (1) black-box; (2) required additional tests; (3) older versions; (4) for non-mucosal lesions, and (5) intended for self-screening. A keyword and MeSH term search was performed across three peer-reviewed publication databases and gray literature.
Results: Seventeen algorithms from 15 peer-reviewed manuscripts and 1 online course were identified. Most studies did not mention how the algorithms were developed, and none had been validated in a clinical setting. The algorithms often focused on one or two types of lesions and were incomplete in differential diagnoses.
Conclusion: Few clinical diagnostic algorithms for oral lesions are available in the literature. Notably, there are no validated and comprehensive clinical diagnostic algorithms for oral mucosal lesions.
期刊介绍:
Oral Diseases is a multidisciplinary and international journal with a focus on head and neck disorders, edited by leaders in the field, Professor Giovanni Lodi (Editor-in-Chief, Milan, Italy), Professor Stefano Petti (Deputy Editor, Rome, Italy) and Associate Professor Gulshan Sunavala-Dossabhoy (Deputy Editor, Shreveport, LA, USA). The journal is pre-eminent in oral medicine. Oral Diseases specifically strives to link often-isolated areas of dentistry and medicine through broad-based scholarship that includes well-designed and controlled clinical research, analytical epidemiology, and the translation of basic science in pre-clinical studies. The journal typically publishes articles relevant to many related medical specialties including especially dermatology, gastroenterology, hematology, immunology, infectious diseases, neuropsychiatry, oncology and otolaryngology. The essential requirement is that all submitted research is hypothesis-driven, with significant positive and negative results both welcomed. Equal publication emphasis is placed on etiology, pathogenesis, diagnosis, prevention and treatment.