The prevalence of gastroesophageal reflux disease in named manometric patterns of dysmotility according to the Chicago Classification 4.0

Esophageal motility disorders (EMD) may be considered primary disorders only in the absence of gastroesophageal reflux disease (GERD). If GERD is present, treatment should be directed toward correction of the abnormal reflux. The actual prevalence of GERD in manometric dysmotility patterns according to the new Chicago Classification 4.0 (CC4) is still elusive. This study aims to evaluate the prevalence of GERD in patients with esophageal motility disorders according to the CC4. We reviewed 400 consecutive patients that underwent esophageal manometry and pH monitoring. Esophageal motility was classified according to the CC4 and GERD + was defined by a DeMeester score > 14.7. Normal motility or unclassified dysmotility was present in 290 (73%) patients, with GERD+ in 184 of them (63%). There were a total of 110 patients (27%) with named esophageal motility disorders, with GERD+ in 67 (61%). The incidence of ineffective esophageal motility was 59% (n = 65) with 69% GERD +, diffuse esophageal spasm was 40% (n = 44) with 48% GERD +, and hypercontractile esophagus was 0.01% (n = 1) with 100% GERD +. There was no correlation between the presence of GERD and the number of non-peristaltic swallows. Our results show that: (i) manometry only is not enough to select patients' treatment as >60% of patients with named esophageal motility disorders have GERD; (ii) there was no correlation between the presence of GERD and the number of non-peristaltic swallows.

Esophageal high-resolution manometry demands visual interpretation in addition to mathematical software-based analysis

PURPOSE

Esophageal high-resolution manometry (HRM) revolutionized esophageal function testing due to the intuitive colorful and agreeable-to-the-eyes plots (Clouse plots). HRM execution and interpretation is guided by the Chicago Classification. The well-established metrics for interpretation allows a reliable automatic software analysis. Analysis based on these mathematical parameters, however, ignores the valuable visual interpretation unique to human eyes and based on expertise.

METHODS

We compiled some situations where visual interpretation added useful information for HRM interpretation.

RESULTS

Visual interpretation may be useful in cases of hypomotility, premature waves, artifacts, segmental abnormalities of peristalsis, and extra-luminal non-contractile findings.

CONCLUSION

These extra findings can be reported apart from the conventional parameters.