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A Clinical Decision Support System for Predicting the Early Complications of One-Anastomosis Gastric Bypass Surgery

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Abstract

Background/Objective

One of the most effective treatments for patients with obesity, albeit with some complications, is obesity surgery. The aim of this study was to develop a clinical decision support system (CDSS) to predict the early complications of one-anastomosis gastric bypass (OAGB) surgery.

Subjects/Methods

This study was conducted in Tehran, Iran on patients who underwent OAGB surgery in 2011–2014 in five hospitals. Initially, variables affecting the OAGB early complications were identified using the literature review. Patients’ data were extracted from an existing database of obesity surgery. Then, different artificial neural networks (ANNs) (multilayer perceptron (MLP) network) were developed and evaluated for prediction of 10-day, 1-month, and 3-month complications.

Results

Factors including age, BMI, smoking status, intra-operative complications, comorbidities, laboratory tests, sonography results, and endoscopy results were considered important factors for predicting early complications of OAGB. A CDSS was developed with these variables. The accuracy, specificity, and sensitivity of the 10-day prediction system in the test data were 98.4%, 98.6%, and 98.3%, respectively. These figures for 1-month system were 96%, 93%, and 98.4% and for the 3-month system were 89.3%, 86.6%, and 91.5%, respectively.

Conclusions

Using the CDSS designed, we could accurately predict the early complications of OAGB surgery.

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Acknowledgements

This study is supported by Iran University of Medical Sciences, Tehran, Iran (IUMS/SHMIS-1395.9311304002). Additionally, we appreciate National Obesity Surgery Registry to provide data for this study.

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Authors and Affiliations

  1. Health Management and Economics Research Center, Department of Health Information Management, School of Health Management and Information Sciences, Iran University of Medical Sciences, Tehran, Iran

    Abbas Sheikhtaheri

  2. Department of Health Information Management, School of Health Management and Information Sciences, Iran University of Medical Sciences, Tehran, Iran

    Azam Orooji

  3. Minimally Invasive Surgery Research Center, Iran University of Medical Sciences, Tehran, Iran

    Abdolreza Pazouki

  4. Minimally Invasive Surgery Research Center, Iran University of Medical Sciences, Tehran, Iran

    Maryam Beitollahi

  5. Department of Health Information Management, School of Health Management and Information Sciences, Iran University of Medical Sciences, Tehran, Iran

    Maryam Beitollahi

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  1. Abbas Sheikhtaheri
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  4. Maryam Beitollahi
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Correspondence to Abbas Sheikhtaheri.

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Conflict of Interest

The authors declare that they have no conflict(s) of interest.

Informed Consent

For this type of study, formal consent is not required.

Ethical Approval

The protocol of this study was reviewed and approved by the ethics committee of Iran University of Medical Sciences, Tehran, Iran (Code: IR.IUMS.REC 1395.9311304002). All procedures performed in this study were in accordance with the ethical standards of the institutional and national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

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This study did not receive any financial support.

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Sheikhtaheri, A., Orooji, A., Pazouki, A. et al. A Clinical Decision Support System for Predicting the Early Complications of One-Anastomosis Gastric Bypass Surgery. OBES SURG 29, 2276–2286 (2019). https://doi.org/10.1007/s11695-019-03849-w

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  • DOI: https://doi.org/10.1007/s11695-019-03849-w

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