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. 2024 Apr 16;8(5):896-916.
doi: 10.1002/ags3.12803. eCollection 2024 Sep.

Risk model for morbidity and mortality following liver surgery based on a national Japanese database

Tatsuya Orimo  1   2 , Shinya Hirakawa  3   4 , Akinobu Taketomi  1   2 , Hisateru Tachimori  3   4 , Taro Oshikiri  2 , Hiroaki Miyata  4   5 , Yoshihiro Kakeji  2 , Ken Shirabe  6
Affiliations

Risk model for morbidity and mortality following liver surgery based on a national Japanese database

Tatsuya Orimo et al. Ann Gastroenterol Surg. .

Abstract

Aim: We evaluated the morbidity and mortality associated with liver surgery in Japan and developed a risk model for liver resection using information from a national database.

Methods: We retrospectively reviewed 73 861 Japanese patients who underwent hepatectomy between 2014 and 2019, using information from the National Clinical Database (NCD) registrations. The primary endpoints were 30 days and in-hospital mortality, and the secondary endpoints were postoperative complications. Logistic regression risk models for postoperative morbidity and mortality after hepatectomy were constructed based on preoperative clinical parameters and types of liver resection, and validated using a bootstrapping method.

Results: The 30-day and in-hospital mortality rates were 0.9% and 1.7%, respectively. Trisectionectomy, hepatectomy for gallbladder cancer, hepatectomy for perihilar cholangiocarcinoma, and poor activities of daily living were statistically significant risk factors with high odds ratios for both postoperative morbidity and mortality. Internal validations indicated that the c-indices for 30-day and in-hospital mortality were 0.824 and 0.839, respectively.

Conclusions: We developed a risk model for liver resection by using a national surgical database that can predict morbidity and mortality based on preoperative factors.

Keywords: hepatectomy; liver resection; morbidity; mortality; risk model.

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Conflict of interest statement

Hiroaki Miyata is affiliated with the Department of Healthcare Quality Assessment at the University of Tokyo. The department is a social collaboration department supported by grants from the National Clinical Database, Johnson & Johnson K.K, Nipro Corporation, and Intuitive Surgical Sàrl. Shinya Hirakawa and Hisateru Tachimori belong to an endowed course of Keio University funded by Takeda Pharmaceutical Company Limited and belong to the Department of Healthcare Quality Assessment at the University of Tokyo that accepts financial support from National Clinical Database, Johnson & Johnson K.K., Nipro Corporation, and Intuitive Surgical Sàrl. But Dr Miyata, Dr Hirakawa, and Dr Tachimori have no conflicts of interest regarding this research. The other authors declare no conflicts of interest regarding this research. Dr. Yoshihiro Kakeji and Dr. Ken Shirabe are editorial members of Annals of Gastroenterological Surgery.

Figures

FIGURE 1
FIGURE 1
Study population flow chart.
FIGURE 2
FIGURE 2
Calibration curves of the risk model showing the predicted vs. actual probability for 30‐day mortality, in‐hospital mortality, reoperation, surgical site infection (organ space), bile leakage, pneumonia, renal failure, postoperative blood transfusion, and sepsis.
FIGURE 3
FIGURE 3
(A) Average number of cases per facility in each year. (B) 30‐day mortality rates by facility size. (C) In‐hospital mortality rates by facility size.
See this image and copyright information in PMC

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