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Open AccessArticle

Prediction of Postoperative Infection for Patients Undergoing Gastrointestinal Surgery: Findings from Electronic Health Records

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Department of Medical Informatics and Statistics, Niigata University Graduate School of Medical and Dental Sciences, and Division of Pharmacy, Niigata University Medical and Dental Hospital, Niigata 951-8520, Japan
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Department of Medical Informatics, Niigata University Medical and Dental Hospital, and Division of Digestive and General Surgery, Niigata University Graduate School of Medical and Dental Sciences, Niigata 951-8520, Japan
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Division of Pharmacy, Niigata University Medical and Dental Hospital, Niigata 951-8520, Japan
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Division of Digestive and General Surgery, Niigata University Graduate School of Medical and Dental Sciences, Niigata 951-8520, Japan
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Department of Medical Informatics, Niigata University Medical and Dental Hospital, Niigata 951-8520, Japan
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Author to whom correspondence should be addressed.
Gastroenterol. Insights 2020, 11(2), 36-46; https://doi.org/10.3390/gastroent11020007
Received: 25 October 2020 / Revised: 16 November 2020 / Accepted: 17 November 2020 / Published: 19 November 2020
(This article belongs to the Section Gastrointestinal Disease)
Introduction: Postoperative infection is a major cause of morbidity and prolonged hospitalization in patients undergoing gastrointestinal surgery. This observational study aimed to investigate the risk factors associated with postoperative infection and to develop a prediction model for postoperative infections that occur after gastrointestinal surgery. Methods: The study population comprised 1637 patients who underwent gastrointestinal surgery at Niigata University Medical and Dental Hospital between June 2013 and May 2017. Observational data from 1883 surgical procedures were used in the statistical analyses (including 198 patients who underwent several operations). Results: The generalized estimating equation (GEE) was used to detect significant risk factors, including older age, history of smoking, body temperature greater than 38 °C, non-endoscopic surgical procedures, surgery in the thoracic or lower gastrointestinal tract, and use of medical nutritional products during surgery. The sensitivity and specificity of the GEE model were 88.2% and 55.1%, respectively. Conclusion: This study established a predictable GEE model, incorporating the data of patients who were hospitalized several times into a prediction analysis, even though the sensitivity was not sufficiently high. The GEE model, which is considered clinically useful, can be constructed using a variety of variables, including those obtained from electronic health records. View Full-Text
Keywords: gastrointestinal surgery; postoperative infection; generalized estimating equation; surgical site infection gastrointestinal surgery; postoperative infection; generalized estimating equation; surgical site infection
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MDPI and ACS Style

Nakazawa, K.; Ishikawa, T.; Toyama, A.; Wakai, T.; Akazawa, K. Prediction of Postoperative Infection for Patients Undergoing Gastrointestinal Surgery: Findings from Electronic Health Records. Gastroenterol. Insights 2020, 11, 36-46. https://doi.org/10.3390/gastroent11020007

AMA Style

Nakazawa K, Ishikawa T, Toyama A, Wakai T, Akazawa K. Prediction of Postoperative Infection for Patients Undergoing Gastrointestinal Surgery: Findings from Electronic Health Records. Gastroenterology Insights. 2020; 11(2):36-46. https://doi.org/10.3390/gastroent11020007

Chicago/Turabian Style

Nakazawa, Kyoko; Ishikawa, Takashi; Toyama, Akira; Wakai, Toshifumi; Akazawa, Kohei. 2020. "Prediction of Postoperative Infection for Patients Undergoing Gastrointestinal Surgery: Findings from Electronic Health Records" Gastroenterol. Insights 11, no. 2: 36-46. https://doi.org/10.3390/gastroent11020007

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