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首页> 外文期刊>Journal of oral rehabilitation >Dental attrition models predicting temporomandibular joint disease or masticatory muscle pain versus asymptomatic controls.
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Dental attrition models predicting temporomandibular joint disease or masticatory muscle pain versus asymptomatic controls.

机译:牙齿磨损模型可预测颞下颌关节疾病或咀嚼性肌肉疼痛与无症状对照的关系。

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AIMS: To determine whether patients with temporomandibular joint disease or masticatory muscle pain can be usefully differentiated from asymptomatic controls using multifactorial classification tree models of attrition severity and/or rates. METHODS: Measures of attrition severity and rates in patients diagnosed with disc displacement (n = 52), osteoarthrosis (n = 74), or masticatory muscle pain only (n = 43) were compared against those in asymptomatic controls (n = 132). Cross-validated classification tree models were tested for fit with sensitivity, specificity, accuracy and log likelihood accountability. RESULTS: The model for identifying asymptomatic controls only required the three measures of attrition severity (anterior, mediotrusive and laterotrusive posterior) to be differentiated from the patients with a 74.2 +/- 3.8% cross-validation accuracy. This compared with cross-validation accuracies of 69.7 +/- 3.7% for differentiating disc displacement using anterior and laterotrusive attrition severity, 68.7 +/- 3.9% for differentiating disc displacement using anterior and laterotrusive attrition rates, 70.9 +/- 3.3% for differentiating osteoarthrosis using anterior attrition severity and rates, 94.6 +/- 2.1% for differentiating myofascial pain using mediotrusive and laterotrusive attrition severity, and 92.0 +/- 2.1% for differentiating myofascial pain using mediotrusive and anterior attrition rates. The myofascial pain models exceeded the > or =75% sensitivity and > or =90% specificity thresholds recommended for diagnostic tests, and the asymptomatic control model approached these thresholds. CONCLUSION: Multifactorial models using attrition severity and rates may differentiate masticatory muscle pain patients from asymptomatic controls, and have some predictive value for differentiating intracapsular temporomandibular disorder patients as well.
机译:目的:使用磨损严重程度和/或发生率的多因素分类树模型,确定是否可以有效地将颞下颌关节疾病或咀嚼肌疼痛患者与无症状对照区分开。方法:将被诊断为椎间盘移位(n = 52),骨关节炎(n = 74)或仅咀嚼肌疼痛(n = 43)的患者的磨损严重程度和比率与无症状对照组(n = 132)进行了比较。对交叉验证的分类树模型进行了敏感性,特异性,准确性和对数可能性问责制的拟合测试。结果:用于识别无症状对照的模型仅需要将三种磨损严重程度(前,中间和后屈)与患者进行区分,交叉验证的准确性为74.2 +/- 3.8%。与之相比,使用前向和后向磨损的严重程度来鉴别椎间盘移位的交叉验证准确性为69.7 +/- 3.7%,使用前向和远向进行磨损率来鉴别椎间盘移位的交叉验证准确度为68.7 +/- 3.9%,对于前向和后向磨损的鉴别率则为70.9 +/- 3.3%骨关节炎使用前减重程度和比率,中度和迟发性减重程度可区分肌筋膜疼痛为94.6 +/- 2.1%,可使用中度和前减重率区分肌筋膜疼痛为92.0 +/- 2.1%。肌筋膜疼痛模型超过了诊断测试建议的≥75%敏感性阈值和≥90%的特异性阈值,而无症状对照模型接近这些阈值。结论:采用磨损严重程度和速率的多因素模型可以将咀嚼性肌肉疼痛患者与无症状对照区分开,并且对于区分囊内颞下颌疾病患者也具有一定的预测价值。

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