Prevalencia de patrones Máxilo-Mandibulares en pacientes de 8,5 a 12 años, utilizando Cefalometría de Ricketts en servicios de ortopedia universitarios

Kiru Pub Date : 2020-04-05 DOI:10.24265/kiru.2020.v17n2.04
Danela Cisneros, J. Parise, D. Morocho, B. Villarreal, A. Cruz
{"title":"Prevalencia de patrones Máxilo-Mandibulares en pacientes de 8,5 a 12 años, utilizando Cefalometría de Ricketts en servicios de ortopedia universitarios","authors":"Danela Cisneros, J. Parise, D. Morocho, B. Villarreal, A. Cruz","doi":"10.24265/kiru.2020.v17n2.04","DOIUrl":null,"url":null,"abstract":"Objetive: To determine the prevalence of the different skeletal patterns in a sample of patients aged 8.5 to 12 years old, using Ricketts cephalometric analysis. Methods: A descriptive cross-sectional study was proposed, considering a sample consisting of 40 patients aged 8.5 to 12 years treated in the Orthopaedics Department at the University Clinic of The Universidad UTE, Quito-Ecuador, between July 2015 and February 2018. Ricketts summary analysis was used to determine the skeletal pattern and establish the maxilla-mandibular relationship; measurements of maxillary convexity, maxillary depth, facial axis and facial depth were recorded. The data collected was analysed using descriptive statistics, frequency analysis, measures of central tendency and dispersion. Results: The predominant skeletal pattern was Class II (52.5%), followed by the Class I skeletal pattern (40%) and Class III (7.5%) Conclusions: The most prevalent skeletal pattern was Class II. There was not a direct relationship or association with the patient's sex.","PeriodicalId":33162,"journal":{"name":"Kiru","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Kiru","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.24265/kiru.2020.v17n2.04","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Objetive: To determine the prevalence of the different skeletal patterns in a sample of patients aged 8.5 to 12 years old, using Ricketts cephalometric analysis. Methods: A descriptive cross-sectional study was proposed, considering a sample consisting of 40 patients aged 8.5 to 12 years treated in the Orthopaedics Department at the University Clinic of The Universidad UTE, Quito-Ecuador, between July 2015 and February 2018. Ricketts summary analysis was used to determine the skeletal pattern and establish the maxilla-mandibular relationship; measurements of maxillary convexity, maxillary depth, facial axis and facial depth were recorded. The data collected was analysed using descriptive statistics, frequency analysis, measures of central tendency and dispersion. Results: The predominant skeletal pattern was Class II (52.5%), followed by the Class I skeletal pattern (40%) and Class III (7.5%) Conclusions: The most prevalent skeletal pattern was Class II. There was not a direct relationship or association with the patient's sex.
在大学骨科服务中使用Ricketts头影测量法的8.5至12岁患者的最大下颌模式患病率
目的:采用立克次体头影测量分析法,确定8.5至12岁患者不同骨骼模式的患病率。方法:提出了一项描述性横断面研究,考虑到2015年7月至2018年2月期间在厄瓜多尔基多UTE大学诊所骨科接受治疗的40名年龄在8.5至12岁之间的患者。立克次体汇总分析用于确定骨骼模式并建立上下颌关系;记录上颌骨凸度、上颌骨深度、面轴和面深度的测量结果。使用描述性统计、频率分析、中心趋势和离散度测量对收集的数据进行了分析。结果:主要的骨骼类型为II类(52.5%),其次为I类(40%)和III类(7.5%)。结论:最常见的骨骼类型是II类。与患者的性别没有直接关系或关联。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
审稿时长
16 weeks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信