Background Due to the rarity of median arcuate ligament (MAL) syndrome, patient selection for surgery remains difficult. This study provides a predictive model to optimize patient selection and predict outcomes following a MAL release. Methods Prospective data from patients undergoing a MAL release included demographics, radiologic studies, and SF-36 questionnaires. Successful postoperative changes in SF-36 was defined as an improvement > 10% in the total SF-36 score. A logistic regression model was used to develop a clinically applicable table to predict surgical outcomes. Celiac artery (CA) blood flow velocities were compared pre- and postoperatively and Pearson correlations were examined between velocities and SF-36 score changes. Results 42 patients underwent a laparoscopic MAL release with a mean follow-up of 28.5 ± 18.8 months. Postoperatively, all eight SF-36 scales improved significantly. The logistic regression model for predicting surgical benefit was significant (p = 0.0244) with a strong association between predictors and outcome (R = 0.36). Age and baseline CA expiratory velocity were significant predictors of improvement and predicted clinical improvement. There were significant differences between pre- and postoperative CA velocities. Postoperatively, the bodily pain scale showed the most significant increase (64%, p < 0.0001). A table was developed using age and preoperative
Surgical Endoscopy – Springer Journals
Published: May 29, 2018
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