Endoscopic Prediction of Achalasia: Putting the CART Before the CARS

Abstract

Background and aims: Endoscopy can detect features indicative of esophageal dysmotility, but standardized approaches for diagnosing achalasia based on these findings remain limited. Recently, the CARS score was developed to address this gap. This study aimed to evaluate the diagnostic utility of endoscopy in identifying achalasia, using the STARD framework and current reference standards.

Methods: Adult patients with esophageal symptoms were prospectively enrolled from 2018 to 2023 and evaluated using endoscopy, esophageal manometry, FLIP panometry, and barium esophagram. The CARS score was assigned to endoscopic videos by two raters blinded to other clinical details. The diagnostic accuracy of the CARS score for predicting achalasia, based on Chicago Classification v4.0, was assessed through two interpretation methods: binary cutoffs for the total score and a classification tree model.

Results: 316 patients were included: 115 patients with achalasia (36%), 113 with normal motility (36%), and 88 with other manometric findings (28%). A CARS score ≥ 4 demonstrated 72% sensitivity and 99% specificity for achalasia, while a score ≥ 3 had 83% sensitivity and 96% specificity. The optimal classification tree had three levels (resistance score at the top, followed by anatomy and content scores, with hernia presence at the bottom) and had a sensitivity of 90% and a specificity 92% for achalasia.

Conclusion: Endoscopy can accurately identify achalasia with high specificity using the CARS score. While motility testing to confirm an achalasia diagnosis remains essential prior to therapy, a high CARS score may help in the early identification of achalasia, especially in settings where motility testing is not readily available.

Keywords: achalasia; dysphagia; endoscopy; esophageal motility.

FIGURE 1

Standards for Reporting of Diagnostic Accuracy (STARD) flow chart of the 316 patients enrolled in the study. The endoscopic CARS scoring system served as the index test, with HRM and FLIP/TBE used as reference standards. EGD, esophagogastroduodenoscopy; EGJOO, esophagogastric junction outflow obstruction; EOE, eosinophilic esophagitis; HRM, high‐resolution manometry; TBE, timed barium esophagram.

FIGURE 2

CARS score by Chicago Classification v4.0 motility group. DES, distal esophageal spasm; EGJOO, esophagogastric junction outflow obstruction; IEM, ineffective esophageal motility. The bars represent the mean and error bars 95% confidence intervals. Pairwise comparisons were performed using the Kruskal–Wallis test. (A) Total CARS score by CCv4.0 diagnosis. (B) CARS score components by CCv4.0 diagnosis.

FIGURE 3

Distribution of maximum EGJ diameter by CARS resistance score. Boxplots show the distribution of maximum EGJ diameter for each CARS resistance score. The central line represents the median, boxes the interquartile range, and whiskers extend to 1.5 times the interquartile range. Pairwise comparisons are performed using the Mann–Whitney U test. Significance levels: * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001. EGJ, esophagogastric junction.

FIGURE 4

CART model. This tree was constructed using a training set of 236 patients (75% of the total dataset). Start at the top and follow the path through subsequent nodes until you reach the bottom. Each “leaf” at the bottom of the tree represents a classification. Inside each leaf, the proportion of correctly classified patients within that class is shown.