Ferrillo Martina, Migliario Mario, Marotta Nicola, Fortunato Francesco, Bindi Marino, Pezzotti Federica, Ammendolia Antonio, Giudice Amerigo, Foglio Bonda Pier Luigi, de Sire Alessandro
Dentistry Unit, Department of Health Sciences, University of Catanzaro "Magna Graecia", Catanzaro, Italy.
Dentistry Unit, Department of Translational Medicine, University of Eastern Piedmont, Novara, Italy.
Acta Odontol Scand. 2023 Mar;81(2):151-157. doi: 10.1080/00016357.2022.2105945. Epub 2022 Jul 29.
To evaluate the linkage underpinning different clinical conditions as painful TMD and neck pain in patients affected by primary headaches.
In this machine learning study, data from medical records of patients with headaches as migraine, tension-type headache (TTH) and other primary ones, referring to a University Hospital over a 10-year period were analysed. VAS was used to evaluate the intensity of the TMD and neck pain. Moreover, the magnetic resonance imaging was used to supplement the clinical data.
A total of 300 patients (72 male, 228 female), mean aged 37.78 ± 5.11 years, were included. Higher TMD and neck pain VAS in migraine patients were reported. The machine learning analysis focussed on type of primary headache demonstrated that a higher TMD VAS was correlated to migraine, whereas a higher neck pain VAS was correlated to TTH or migraine. Concerning the TMD type, arthrogenous and mixed TMD were correlated to mild-moderate TMD pain (depending on neck pain intensity), whereas myogenic TMD was correlated to moderate-severe TMD pain.
Machine-learning approach highlighted the complexity of diagnosis process and demonstrated that neck pain might be an influential variable on the belonging to different group of headaches in TMD patients.
评估原发性头痛患者中，疼痛性颞下颌关节紊乱病（TMD）和颈部疼痛等不同临床情况之间的联系。
在这项机器学习研究中，分析了一所大学医院10年间偏头痛、紧张型头痛（TTH）及其他原发性头痛患者的病历数据。采用视觉模拟评分法（VAS）评估TMD和颈部疼痛的强度。此外，使用磁共振成像来补充临床数据。
共纳入300例患者（男性72例，女性228例），平均年龄37.78±5.11岁。偏头痛患者的TMD和颈部疼痛VAS评分更高。针对原发性头痛类型的机器学习分析表明，较高的TMD VAS与偏头痛相关，而较高的颈部疼痛VAS与TTH或偏头痛相关。关于TMD类型，关节源性和混合型TMD与轻中度TMD疼痛相关（取决于颈部疼痛强度），而肌源性TMD与中重度TMD疼痛相关。
机器学习方法突出了诊断过程的复杂性，并表明颈部疼痛可能是TMD患者所属不同头痛组别的一个影响变量。
