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Updated: Jul 11, 2025

Intraoperative Gastroscopy for Tumor Localization in Laparoscopic Surgery for Gastric Adenocarcinoma
Published on: August 9, 2016
Identification of complications requiring interventions after gastrointestinal cancer surgery from real-world data:
Hiromitsu Kinoshita1, Tatsuto Nishigori1,2, Susumu Kunisawa3
1Department of Surgery, Graduate School of Medicine Kyoto University Kyoto Japan.
Background:
Recently, real-world data have been recognized to have a significant role for research and quality improvement worldwide. The decision on the existence or nonexistence of postoperative complications is complex in clinical practice. This multicenter validation study aimed to evaluate the accuracy of identification of patients who underwent gastrointestinal (GI) cancer surgery and extraction of postoperative complications from Japanese administrative claims data.
Methods:
We compared data extracted from both the Diagnosis Procedure Combination (DPC) and chart review of patients who underwent GI cancer surgery from April 2016 to March 2019. Using data of 658 patients at Kyoto University Hospital, we developed algorithms for the extraction of patients and postoperative complications requiring interventions, which included an invasive procedure, reoperation, mechanical ventilation, hemodialysis, intensive care unit management, and in-hospital mortality. The accuracy of the algorithms was externally validated using the data of 1708 patients at two other hospitals.
Results:
In the overall validation set, 1694 of 1708 eligible patients were correctly extracted by DPC (sensitivity 0.992 and positive predictive value 0.992). All postoperative complications requiring interventions had a sensitivity of >0.798 and a specificity of almost 1.000. The overall sensitivity and specificity of Clavien-Dindo ≥grade IIIb complications was 1.000 and 0.995, respectively.
Conclusion:
Patients undergoing GI cancer surgery and postoperative complications requiring interventions can be accurately identified using the real-world data. This multicenter external validation study may contribute to future research on hospital quality improvement or to a large-scale comparison study among nationwide hospitals using real-world data.
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