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根管治疗牙垂直根折的检测:锥形束计算机断层扫描的准确性及潜在预测变量评估

detection of vertical root fractures in endodontically treated teeth: Accuracy of cone-beam computed tomography and assessment of potential predictor variables.

作者信息

Quintero-Álvarez Marcela, Bolaños-Alzate Leslie-Melissa, Villa-Machado Paula-Andrea, Restrepo-Restrepo Felipe-Augusto, Tobón-Arroyave Sergio-Iván

机构信息

Senior Resident, Graduate Endodontic Program, Faculty of Dentistry, University of Antioquia. Medellín, Colombia.

Associate Professor. Graduate Endodontic Program, Faculty of Dentistry, University of Antioquia. Medellín, Colombia.

出版信息

J Clin Exp Dent. 2021 Feb 1;13(2):e119-e131. doi: 10.4317/jced.57471. eCollection 2021 Feb.

DOI:10.4317/jced.57471
PMID:33574996
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7864364/
Abstract

BACKGROUND

This study aimed: (a) to determine the diagnostic performance of cone-beam computed tomography (CBCT) for detection of vertical root fractures (VRFs); (b) to evaluate the predictive value of diagnostic criteria regarding the definition of VRFs; and (c) to examine the robustness of the association of patient-, tooth-, and treatment-related variables with VRFs.

MATERIAL AND METHODS

130 root-filled teeth with signs/symptoms of VRFs underwent clinical and CBCT assessments. Definite diagnosis of VRF was confirmed by endodontic microsurgical (EMS) exploration. Determination of diagnostic performance of CBCT was based on standard algorithms derived from two-way contingency table analysis. Predictive value of diagnostic criteria and the association between predictor variables with VRFs were analyzed using logistic regression models.

RESULTS

VRFs were detected during EMS in 50% of the teeth. Based on the finding of fracture lines on CBCT scans, sensitivity, specificity, and accuracy were 86.2%, 13.8%, and 50%, respectively. Teeth having more than three diagnostic criteria present had significant higher odds for VRF diagnosis. After logistic regression analysis, parafunctional habits, one-canal roots, excessive root canal enlargement, and absence of intra-radicular posts remained as robust predictor variables of VRFs.

CONCLUSIONS

Although the sensitivity of CBCT for VRFs detection is high, the risk of false-positive results related to its low specificity makes that all suspected cases must be confirmed by surgical exploration. VRFs cannot be reliably diagnosed by isolated clinical signs/symptoms; instead those teeth possessing more than three diagnostic criteria might be considered practically pathognomonic. The parafunctional habits, one-canal roots, excessive root canal enlargement, and the absence of intra-radicular posts may act strongly/independently for the occurrence of VRFs in endodontically treated teeth. Cone-beam computed tomography, diagnostic accuracy, diagnostic surgery, predictor variables, root canal treatment, vertical root fracture.

摘要

背景

本研究旨在:(a)确定锥形束计算机断层扫描(CBCT)检测垂直根折(VRF)的诊断性能;(b)评估VRF定义的诊断标准的预测价值;(c)检查患者、牙齿和治疗相关变量与VRF关联的稳健性。

材料与方法

130颗有VRF体征/症状的根管充填牙接受了临床和CBCT评估。通过牙髓显微外科手术(EMS)探查确诊VRF。CBCT诊断性能的确定基于双向列联表分析得出的标准算法。使用逻辑回归模型分析诊断标准的预测价值以及预测变量与VRF之间的关联。

结果

在EMS过程中,50%的牙齿检测到VRF。基于CBCT扫描上骨折线的发现,敏感性、特异性和准确性分别为86.2%、13.8%和50%。存在超过三项诊断标准的牙齿VRF诊断的几率显著更高。经过逻辑回归分析,异常功能习惯、单根管牙根、根管过度扩大和根管内桩缺失仍然是VRF的稳健预测变量。

结论

尽管CBCT检测VRF的敏感性较高,但其低特异性导致的假阳性结果风险使得所有疑似病例都必须通过手术探查来确诊。VRF不能通过孤立的临床体征/症状可靠诊断;相反,那些具有超过三项诊断标准的牙齿可能实际上可被视为具有特征性。异常功能习惯、单根管牙根、根管过度扩大和根管内桩缺失可能对根管治疗后牙齿VRF的发生有强烈/独立的作用。锥形束计算机断层扫描、诊断准确性、诊断手术、预测变量、根管治疗、垂直根折

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ff40/7864364/e0ee55662749/jced-13-e119-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ff40/7864364/67141ffdd438/jced-13-e119-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ff40/7864364/371114b18ea6/jced-13-e119-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ff40/7864364/9f0eaeb73b17/jced-13-e119-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ff40/7864364/e0ee55662749/jced-13-e119-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ff40/7864364/67141ffdd438/jced-13-e119-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ff40/7864364/371114b18ea6/jced-13-e119-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ff40/7864364/9f0eaeb73b17/jced-13-e119-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ff40/7864364/e0ee55662749/jced-13-e119-g004.jpg

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