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  • 标题:Alveolar Osteitis Following Tooth Extraction: Systematic Review and Google Trends Analysis Instigated by the First Upper Premolar Case Reported from Iraq
  • 本地全文:下载
  • 作者:Ahmed Al-Imam ; Amer Al-Khazraji
  • 期刊名称:Modern Applied Science
  • 印刷版ISSN:1913-1844
  • 电子版ISSN:1913-1852
  • 出版年度:2019
  • 卷号:13
  • 期号:3
  • 页码:1-12
  • DOI:10.5539/mas.v13n3p1
  • 语种:English
  • 出版社:Canadian Center of Science and Education
  • 摘要:Introduction: Alveolar osteitis is a painful condition that may occur following permanent teeth extraction due to the failure of formation of a blood clot or its dislodgement before the complete healing of the wound.We aim to provide a systematic review and trends analytic on the epidemiology and the digital epidemiology as well as the management of alveolar osteitis and to seek any available data in connection with alveolar osteitis following upper premolar tooth extraction.Methods: This study represents a combinatory of literature review, analytics of Google Trends, and the first documented case from Iraq of alveolar osteitis following extraction of the maxillary first premolar.Three literature databases were explored, using Boolean operators, including NCBI-PubMed, Elsevier, and the Cochrane Library.Google Trends database was examined to assess the digital epidemiology.Results:The total number of hits was 54417.There was an overall deficit of literature concerning the condition in connection with the extraction of maxillary premolars.The digital epidemiology was limited to twenty-two countries including three countries from the Middle East accounting for 13.63% of the total geographic mapping while Iraq was absent.Conclusion:Our exceptional case report instigated a systematic analytic of a trends database and the literature.The analysis confirmed the inadequacy of studies from the Middle East.Future studies should deploy the use of machine learning algorithms for a rigour statistical inference based on data from online and offline big data repositories of public health records.
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