A predictive model for patients with median arcuate ligament syndrome

A predictive model for patients with median arcuate ligament syndrome 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 http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Surgical Endoscopy Springer Journals

A predictive model for patients with median arcuate ligament syndrome

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Publisher
Springer US
Copyright
Copyright © 2018 by Springer Science+Business Media, LLC, part of Springer Nature
Subject
Medicine & Public Health; Surgery; Gynecology; Gastroenterology; Hepatology; Proctology; Abdominal Surgery
ISSN
0930-2794
eISSN
1432-2218
D.O.I.
10.1007/s00464-018-6240-y
Publisher site
See Article on Publisher Site

Abstract

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

Journal

Surgical EndoscopySpringer Journals

Published: May 29, 2018

References

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