■使用当前常用的人体测量指数数据描述青春期前尿道下裂的解剖异常,并预测术后诊断分类。
■选取2021年4月至2022年9月在四川省人民医院初治的青春期前尿道下裂患儿。我们记录了他们术前的阴囊距离,肛门生殖器距离,2D:4D手指比率,术后尿道下裂分类。受试者工作特征曲线用于单变量分析训练集中尿道下裂分类的每个指标的诊断预测值。二元逻辑回归,随机森林,并构建了支持向量机模型。此外,我们还前瞻性地收集了2022年10月至2023年9月的数据作为测试集,以验证构建的机器学习模型。
■本研究包括389例,远端有50个,167中轴,和172例近端病例。在验证集中,二进制LR的灵敏度,射频,支持向量机是17%,17%和0%用于识别远端类型,61%,55%和64%用于识别中轴类型,56%,60%和48%用于识别近端类型,分别。三分类RF和SVM模型的灵敏度分别为17%和17%的远端类型,中轴型为64%和73%,近端类型为60%和60%,分别。在测试集中,二进制LR的灵敏度,RF和SVM为6%,0%和0%用于识别远端类型,64%,55%和66%用于识别中轴类型,48%,62%和39%用于识别近端类型,分别。三分类RF和SVM模型对远端类型的灵敏度分别为12%和0%,中轴型为57%和77%,近端类型为65%和53%,分别。与二元分类模型相比,三分类模型对远端类型的敏感性没有提高.
■肛门生殖距离和阴囊距离对中段和近端尿道下裂具有良好的预测价值,其中AGD2,具有更高的测试效率和稳定性,建议作为首选的肛门生殖器距离指标。2D:4D手指比率(RadioL,RadioR)对尿道下裂分类的预测价值不大。
UNASSIGNED: To describe the anatomical abnormalities of hypospadias before puberty using current commonly used anthropometric index data and predict postoperative diagnostic classification.
UNASSIGNED: Children with hypospadias before puberty who were initially treated at Sichuan Provincial People\'s Hospital from April 2021 to September 2022 were selected. We recorded their preoperative penoscrotal distance, anogenital distance, 2D:4D finger ratio, and postoperative hypospadias classification. The receiver operating character curve was used for univariate analysis of the diagnostic predictive value of each index for hypospadias classification in the training set. Binary logistic regression, random forest, and support vector machine models were constructed. In addition, we also prospectively collected data from October 2022 to September 2023 as a test set to verify the constructed machine learning models.
UNASSIGNED: This study included 389 cases, with 50 distal, 167 midshaft, and 172 proximal cases. In the validation set, the sensitivity of the binary LR, RF, and SVM was 17%, 17% and 0% for identifying the distal type, 61%, 55% and 64% for identifying the midshaft type, and 56%, 60% and 48% for identifying the proximal type, respectively. The sensitivity of the three-classification RF and SVM models was 17% and 17% for distal type, 64% and 73% for midshaft type, 60% and 60% for proximal type, respectively. In the Testing set, the sensitivity of the binary LR, RF and SVM was 6%, 0% and 0% for identifying the distal type, 64%, 55% and 66% for identifying the midshaft type, and 48%, 62% and 39% for identifying the proximal type, respectively. The sensitivity of the three-classification RF and SVM models was 12% and 0% for distal type, 57% and 77% for midshaft type, and 65% and 53% for proximal type, respectively. Compared with binary classification models, the sensitivity of the three-classification models for distal type was not improved.
UNASSIGNED: Anogenital distance and penoscrotal distance have a favorable predictive value for midshaft and proximal hypospadias, among which AGD2, with higher test efficiency and stability, is recommended as the preferred anogenital distance indicator. The 2D:4D finger ratio (RadioL, RadioR) has little predictive value for hypospadias classification.