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Review

Nonachalasic esophageal motor disorders, from diagnosis to therapy

, &
Pages 205-216 | Received 15 Dec 2021, Accepted 22 Feb 2022, Published online: 02 Mar 2022
 

ABSTRACT

Introduction

Investigations conducted using conventional manometry and, recently, using high-resolution manometry (HRM), allowed us to explore the field of esophageal motility and understand the potential link between motor features and gastroesophageal reflux disease (GERD) pathogenesis. The management of patients with nonachalasic esophageal motor disorders is often challenging, due to the clinical heterogeneous presentation and the multifactorial nature of the mechanisms underlying symptoms.

Areas covered

Several studies, carried out using HRM, have better interpreted the esophageal motor function in patients with esophagogastric junction outflow obstruction (EGJOO), distal esophageal spasm (DES), hypertensive esophagus, and hypomotility disorders. Moreover, HRM studies have shown a direct correlation between reduced esophageal motility, disruption of the esophagogastric junction, and gastroesophageal reflux burden.

Expert opinion

Pathogenesis, clinical presentation, diagnosis, and treatment of nonachalasic esophageal motor disorders still represent a challenging area, requiring future evaluation by multicenter outcome studies carried out in a large cohort of patients and asymptomatic subjects. However, we believe that an accurate clinical, endoscopic, and HRM evaluation is, nowadays, helpful in addressing patients with nonachalasic esophageal motor disorders to optimal treatment options.

Article highlights

  • The management of patients with nonachalasic esophageal motor disorders is challenging, and therefore, these patients require a personalized management.

  • HRM is, nowadays, the gold standard in evaluating esophageal motility. The criteria used for the analysis of HRM tracings are usually calculated by specific software and are accurate and reproducible variables.

  • Supplementary tests such as upper endoscopy and radiology are able to provide further information that may improve the diagnostic approach.

  • In the coming years, new consensus of experts in this field and potentially the application of artificial intelligence to reduce the intra- and interobserver variability will be necessary.

Declaration of interests

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Reviewer disclosures

Peer reviewers in this manuscript have no relevant financial or other relationships to disclose.

Additional information

Funding

This paper was not funded.

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