Karrar R N, Craig S G, Duncan H F, Abushouk S A, Elfiel S Y, Lundy F T, Clarke M, El-Karim I A
Faculty of Dentistry, University of Khartoum, Khartoum, Sudan.
School of Medicine Dentistry and Biomedical Sciences, Queen's University Belfast, Belfast, UK.
Int Endod J. 2025 Aug;58(8):1158-1171. doi: 10.1111/iej.14254. Epub 2025 May 27.
Determine the reliability and clinical validity of the Wolters classification of pulpitis.
Prospective diagnostic accuracy study in which patients with pulpitis were included. Based on history, clinical and radiographic examination, participants were categorized into initial, mild, moderate or severe pulpitis based on Wolters classification and received treatment as suggested in the classification. The American Association of Endodontists (AAE) classification was used for comparison. Treatment outcome was evaluated at 12 months. Classification reliability was assessed by measuring the interrater agreement using Fleiss' Kappa. Construct validity was assessed by cluster analysis using an unsupervised machine learning approach. Predictive validity was determined by the association of treatment outcome with the diagnostic category. All statistical analyses were conducted using R v4.3.1; a p-value of <.05 was considered statistically significant.
Ninety-two patients were included in the study. The interrater reliability showed fair agreement for Wolters classification (Kappa (κ) = 0.593, 95% confidence interval (CI): 0.592-0.595), compared with substantial agreement (κ = 0.888, 95% CI: 0.887-0.889) for the AAE classification. Association of Wolters classification with output of unsupervised K-mode cluster analysis showed that the use of a three-category model may improve discrimination of pulpitis subdivided into mild, moderate, and severe categories. The revised classification model demonstrated 100% sensitivity and specificity for accurate discrimination between mild and severe pulpitis and 83% sensitivity and 85.7% specificity for classifying moderate pulpitis. There was no significant difference between these revised diagnostic categories considering treatment outcome, suggesting good predictive validity (p > .05). Compared with the AAE classification, the new classification in conjunction with proposed treatments resulted in preserving 87% of the pulps compared with historical treatment.
We propose that a revised Wolters classification model is suitable for determining mild, moderate, and severe pulpitis to aid in clinical management of pulpitis.
确定牙髓病Wolters分类法的可靠性和临床有效性。
对纳入的牙髓炎患者进行前瞻性诊断准确性研究。根据病史、临床和影像学检查,按照Wolters分类法将参与者分为初期、轻度、中度或重度牙髓炎,并按照分类建议进行治疗。采用美国牙髓病学家协会(AAE)分类法进行比较。在12个月时评估治疗结果。通过使用Fleiss' Kappa测量评分者间一致性来评估分类可靠性。使用无监督机器学习方法通过聚类分析评估结构效度。通过治疗结果与诊断类别之间的关联来确定预测效度。所有统计分析均使用R v4.3.1进行;p值<0.05被认为具有统计学意义。
92名患者纳入研究。与AAE分类法的高度一致性(κ = 0.888,95%置信区间(CI):0.887 - 0.889)相比,Wolters分类法的评分者间可靠性显示出一般一致性(κ = 0.593,95% CI:0.592 - 0.595)。Wolters分类法与无监督K模式聚类分析结果的关联表明,使用三类模型可能会提高对分为轻度、中度和重度类别的牙髓炎的区分能力。修订后的分类模型在准确区分轻度和重度牙髓炎方面显示出100%的敏感性和特异性,在分类中度牙髓炎方面显示出83%的敏感性和85.7%的特异性。考虑治疗结果时,这些修订后的诊断类别之间没有显著差异,表明具有良好的预测效度(p > 0.05)。与AAE分类法相比,结合建议治疗方法的新分类法与历史治疗相比,可保留87%的牙髓。
我们建议修订后的Wolters分类模型适用于确定轻度、中度和重度牙髓炎,以辅助牙髓炎的临床管理。