Portillo-Ortíz Nadia Karina, Sigala-González Luis Raúl, Ramos-Moctezuma Iván René, Bermúdez Bencomo Brenda Lizeth, Gomez Salgado Brissa Aylin, Ovalle Arias Fátima Cristal, Leal-Berumen Irene, Berumen-Nafarrate Edmundo
Faculty of Medicine and Biomedical Sciences, Universidad Autónoma de Chihuahua (UACH), Chihuahua 31125, Mexico.
Star Medica Chihuahua Hospital, Perif. de la Juventud 6103, Fracc. El Saucito, Chihuahua 31110, Mexico.
Diagnostics (Basel). 2024 Dec 25;15(1):19. doi: 10.3390/diagnostics15010019.
: This international multicenter study aimed to assess the effectiveness of the Pivot-Shift Meter (PSM) mobile application in diagnosing and classifying anterior cruciate ligament (ACL) injuries, emphasizing the need for standardization to improve diagnostic precision and treatment outcomes. : ACL evaluations were conducted by eight experienced orthopedic surgeons across five Latin American countries (Bolivia, Chile, Colombia, Ecuador, and Mexico). The PSM app utilized smartphone gyroscopes and accelerometers to standardize the pivot-shift test. Data analysis from 224 control tests and 399 standardized tests included non-parametric statistical methods, such as the Mann-Whitney U test for group comparisons and chi-square tests for categorical associations, alongside neural network modeling for injury grade classification. : Statistical analysis demonstrated significant differences between standardized and control tests, confirming the effectiveness of the standardization. The neural network model achieved high classification accuracy (94.7%), with precision, recall, and F1 scores exceeding 90%. Receiver Operating Characteristic (ROC) analysis yielded an area under the curve of 0.80, indicating reliable diagnostic accuracy. : The PSM mobile application, combined with standardized pivot-shift techniques, is a reliable tool for diagnosing and classifying ACL injuries. Its high performance in predicting injury grades makes it a valuable addition to clinical practice for enhancing diagnostic precision and informing treatment planning.
这项国际多中心研究旨在评估枢轴移位测量仪（PSM）移动应用程序在诊断和分类前交叉韧带（ACL）损伤方面的有效性，强调需要标准化以提高诊断精度和治疗效果。ACL评估由来自五个拉丁美洲国家（玻利维亚、智利、哥伦比亚、厄瓜多尔和墨西哥）的八位经验丰富的骨科医生进行。PSM应用程序利用智能手机陀螺仪和加速度计对枢轴移位试验进行标准化。对224次对照试验和399次标准化试验的数据分析包括非参数统计方法，如用于组间比较的曼-惠特尼U检验和用于分类关联的卡方检验，以及用于损伤分级分类的神经网络建模。统计分析表明标准化试验和对照试验之间存在显著差异，证实了标准化的有效性。神经网络模型实现了较高的分类准确率（94.7%），精确率、召回率和F1分数均超过90%。受试者操作特征（ROC）分析得出曲线下面积为0.80，表明诊断准确性可靠。PSM移动应用程序与标准化的枢轴移位技术相结合，是诊断和分类ACL损伤的可靠工具。它在预测损伤分级方面的高性能使其成为临床实践中提高诊断精度和为治疗计划提供信息的有价值补充。
