Mat Lazin Muhamamd Amirul, Wan Zainon Wan Nazlee, Humayun Arsalan, Madawana Ashwini M, Hassan Akram, Zhang Yu, Awang Nawi Mohamad Arif
Department of Oral Medicine, School of Dental Sciences, Universiti Sains Malaysia (USM), Kota Bharu, MYS.
Department of Family Medicine, School of Dental Sciences, Universiti Sains Malaysia (USM), Kota Bharu, MYS.
Cureus. 2024 Jul 16;16(7):e64641. doi: 10.7759/cureus.64641. eCollection 2024 Jul.
Introduction Tooth sensitivity, or dentin hypersensitivity (DH), is characterized by sharp, sudden pain in response to stimuli such as cold, heat, sweet, or acidic foods and drinks. In Malaysia, there is limited understanding of the epidemiological aspects of tooth sensitivity, necessitating focused research. The condition results from the exposure of dentinal tubules transmitting stimuli to nerves within the pulp, with contributing factors including gingival recession, enamel erosion, and periodontal disease. This study aims to investigate the factors associated with tooth sensitivity among patients at the Hospital Universiti Sains Malaysia (USM) using advanced statistical methods. Methods This study employed a computational research design to develop an ordinal regression and bootstrap methodology using the RStudio software (Posit PBC, Boston, MA) to analyze secondary data from the Hospital Universiti Sains Malaysia. Six variables were analyzed: tooth wear severity, patient's age, gender, smoking status, alcohol status, and type of toothbrush. The study was conducted in three phases: 1) the development of an ordinal regression model, 2) the development of algorithms for ordinal regression and bootstrap method, and 3) validation using tooth sensitivity data. Results The analysis revealed that the replication with 1000 samples provided the most precise estimates with small standard errors (SE) and consistently significant effects across variables. Tooth sensitivity was influenced by age, toothpaste type, toothbrush type, and brushing frequency. Conclusion The study highlights the importance of considering multiple variables such as age, toothpaste type, toothbrush type, and brushing frequency in understanding tooth sensitivity. The combined ordinal regression and bootstrap technique significantly improved the model's accuracy, providing valuable insights for dental health professionals. These findings underscore the need for specific guidelines on oral hygiene practices to manage and reduce the risk of tooth sensitivity.
引言
牙齿敏感，即牙本质过敏症（DH），其特征是对冷、热、甜或酸性食物及饮料等刺激产生尖锐、突然的疼痛。在马来西亚，对牙齿敏感的流行病学方面了解有限，因此有必要进行针对性研究。这种情况是由于牙本质小管暴露，将刺激传递至牙髓内的神经，其促成因素包括牙龈退缩、牙釉质侵蚀和牙周疾病。本研究旨在使用先进的统计方法调查马来西亚理科大学医院（USM）患者中与牙齿敏感相关的因素。
方法
本研究采用计算研究设计，使用RStudio软件（Posit PBC，马萨诸塞州波士顿）开发有序回归和自助法方法，以分析来自马来西亚理科大学医院的二次数据。分析了六个变量：牙齿磨损严重程度、患者年龄、性别、吸烟状况、饮酒状况和牙刷类型。该研究分三个阶段进行：1）开发有序回归模型；2）开发有序回归和自助法算法；3）使用牙齿敏感数据进行验证。
结果
分析表明，1000个样本的重复抽样提供了最精确的估计，标准误差（SE）小，且各变量的效应始终显著。牙齿敏感受年龄、牙膏类型、牙刷类型和刷牙频率影响。
结论
该研究强调了在理解牙齿敏感时考虑年龄、牙膏类型、牙刷类型和刷牙频率等多个变量的重要性。有序回归和自助法相结合的技术显著提高了模型的准确性，为牙科保健专业人员提供了有价值的见解。这些发现强调了需要制定关于口腔卫生习惯的具体指南，以管理和降低牙齿敏感的风险。
