Loyola University Medical Center, Maywood, IL 60153, USA.
J Pediatr Urol. 2013 Aug;9(4):498-502. doi: 10.1016/j.jpurol.2012.07.019. Epub 2012 Sep 12.
Training in urology relies largely on the traditional methods of clinical immersion and the use of reference texts. Computer enhanced visual learning (CEVL) is an on-line learning tool that may effectively supplement these methods. We evaluate the role of CEVL in establishing the endoscopic diagnosis of posterior urethral valves (PUV).
This study compares test scores of PUV diagnosis made by pediatric urologists and fellows in pediatric urology training programs while watching pediatric cystourethroscopy videos before and after viewing the CEVL learning module. The CEVL module used illustrations and video clips to highlight criteria important in diagnosing PUV. Data was analyzed for improvement in test scores (Chi square).
There were 112 study subjects enrolled. An improvement in the post-test scores was observed (p < 0.001). When independently analyzing cases with PUV, an improvement in diagnosis was also observed (p < 0.005). While a trend toward improvement was observed in correctly diagnosing normal urethras, this was not statistically significant.
Overall, there was an improvement observed after viewing the CEVL module. This was most notable in cases where PUV was present. The CEVL module is an effective supplement for enhancing the endoscopic diagnosis of PUV.
泌尿科的培训在很大程度上依赖于临床浸润的传统方法和参考文本的使用。计算机增强视觉学习（CEVL）是一种在线学习工具，可以有效地补充这些方法。我们评估了 CELV 在建立后尿道瓣膜（PUV）内镜诊断中的作用。
本研究比较了观看小儿膀胱尿道镜检查录像前后，小儿泌尿科医生和小儿泌尿科培训项目中的研究员在观看 CELV 学习模块后对 PUV 诊断的测试分数。CEVL 模块使用插图和视频剪辑来突出诊断 PUV 的重要标准。对测试分数的提高进行了数据分析（卡方检验）。
共有 112 名研究对象被纳入研究。观察到后测分数的提高（p < 0.001）。当独立分析存在 PUV 的病例时，也观察到诊断的改善（p < 0.005）。虽然正确诊断正常尿道的趋势有所改善，但这并不具有统计学意义。
总的来说，观看 CELV 模块后观察到了改善。在存在 PUV 的情况下，这种改善最为明显。CELV 模块是增强 PUV 内镜诊断的有效补充。
