Division of Gastroenterology and Hepatology, Medical College of Wisconsin, Wisconsin, USA.
Curr Opin Otolaryngol Head Neck Surg. 2023 Dec 1;31(6):374-381. doi: 10.1097/MOO.0000000000000936. Epub 2023 Oct 4.
Addressing dysphagia is vital due to its prevalence and impact on healthcare expenditure. While high resolution manometry (HRM) effectively evaluates esophageal dysphagia, its role in oropharyngeal dysphagia and upper esophageal sphincter (UES) dysfunction remains debated. The fourth iteration of the Chicago classification (CC) offers an algorithmic approach for diagnosing abnormal motor patterns via HRM. This review assesses the CC's impact on dysphagia management.
The Chicago classification version 4.0 emphasizes auxiliary and provocative techniques when the algorithm falls short of a conclusive diagnosis. It introduces stricter criteria for previously ambiguous conditions like ineffective motility and esophagogastric junction outflow obstruction. This version also introduces the concept of conclusive and inconclusive classifications based on symptoms, provocation maneuvers, and supportive testing minimizing ambiguity.
The Chicago classification v4.0 remains a useful tool for the diagnosis of well characterized esophageal motility disorders. However, major limitations include reliance on HRM and a focus on distal esophagus contractile characteristics without considering proximal esophagus or upper esophageal sphincter, both of which can sometimes be the only evident abnormality in patients with dysphagia. Despite efforts to reduce ambiguity, diagnostic challenges persist. These limitations can be addressed in future updates.
由于吞咽困难的普遍性及其对医疗支出的影响，解决吞咽困难问题至关重要。高分辨率测压（HRM）可有效评估食管吞咽困难，但在口咽吞咽困难和上食管括约肌（UES）功能障碍中的作用仍存在争议。芝加哥分类第 4 版（CC）提供了一种通过 HRM 诊断异常运动模式的算法方法。本综述评估了 CC 对吞咽困难管理的影响。
芝加哥分类版本 4.0 强调在算法诊断不明确时使用辅助和激发技术。它为以前模棱两可的情况（如无效运动和食管胃连接部流出梗阻）引入了更严格的标准。该版本还引入了基于症状、激发操作和支持性测试的明确和不明确分类的概念，最大限度地减少了歧义。
芝加哥分类 v4.0 仍然是诊断特征明确的食管动力障碍的有用工具。然而，主要限制包括对 HRM 的依赖以及对远端食管收缩特性的关注，而不考虑近端食管或上食管括约肌，在吞咽困难患者中，这些部位有时是唯一明显的异常部位。尽管努力减少歧义，但诊断挑战仍然存在。这些限制可以在未来的更新中得到解决。
