Key result
EHR-based model predicts postoperative infection after GI surgery with ~88% sensitivity.
Why the study?
Postoperative infection is a major cause of morbidity and prolonged hospitalization in patients undergoing gastrointestinal surgery, motivating the investigation of risk factors and prediction models.
Can a prediction model using electronic health records identify risk factors for postoperative infection in patients undergoing gastrointestinal surgery?
Observational (n=1,637)
No
Can a prediction model using electronic health records identify risk factors for postoperative infection in patients undergoing gastrointestinal surgery?
A GEE-based prediction model using electronic health records can identify risk factors for postoperative infection after gastrointestinal surgery, though with limited specificity.
May aid postoperative infection risk stratification after GI surgery; hypothesis-generating and requires prospective validation before clinical use.
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.
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Nakazawa et al. (2020) conducted an observational in Patients undergoing gastrointestinal surgery (n=1,637). Risk factors for postoperative infection was evaluated on Postoperative infection. A generalized estimating equation model using electronic health record data predicted postoperative infection after gastrointestinal surgery with 88.2% sensitivity and 55.1% specificity.
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