Zheng-Gui Du1, Yong-Gang Wei1, Ke-Fei Chen1, Bo Li1. 1. Zheng-Gui Du, Yong-Gang Wei, Ke-Fei Chen, Bo Li, Department of Liver Surgery, Liver Transplantation Center, West China Hospital, Sichuan University, Chengdu 610041, Sichuan Province, China.
Abstract
AIM: To establish a reliable definition of postoperative liver failure (PLF) and allow the prediction of outcomes after hepatectomy. METHODS: The clinical data of 478 consecutive patients who underwent hepatectomy were retrospectively analyzed. The examined prognostic factors included the ratio of total bilirubin (TBIL) on postoperative day (POD) X to TBIL on POD 1 (TBIL-r1) and the ratio of the international normalized ratio (INR) on POD X to the INR on POD 1 (INR-r1) for PODs 3, 5 and 7. Student's t test, the χ(2) test, logistic regression, survival analysis and receiver operating curve analysis were used to evaluate risk factors and establish the definition of postoperative liver failure (PLF). RESULTS: Fourteen patients (2.9%) died of liver failure within 3 mo of surgery. Significant differences were found between patients who died of liver failure and the remaining patients in terms of TBIL-r1 and INR-r1 on PODs 3, 5 and 7. The combination of TBIL-r1 and INR-r1 on POD 5 showed strong predictive power for liver failure-related death (sensitivity 92.9% and specificity 90.1%). The hepatic damage score (HDs), which was derived from TBIL-r1 and INR-r1, was used to define the degree of metabolic functional impairment after resection as mild (HDs = 0), reversible hepatic "dysfunction" (HDs = 1) or fatal hepatic failure (HDs = 2). Furthermore, the indocyanine green retention rate at 15 min (ICG-R15) and the number of resected segments (RSs) were identified as independent predictors of the HDs. A linear relationship was found between ICG-R15 and RSs in the HDs = 2 group. The regression equation was: RSs = -0.168 × ICG-R15 + 5.625 (r (2) = 0.613, F = 14.257, P = 0.004). CONCLUSION: PLF can be defined by the HDs, which accurately predicts liver failure-related death after liver resection. Furthermore, the ICG-R15 and RSs can be used as selection criteria for hepatectomy.
AIM: To establish a reliable definition of postoperative liver failure (PLF) and allow the prediction of outcomes after hepatectomy. METHODS: The clinical data of 478 consecutive patients who underwent hepatectomy were retrospectively analyzed. The examined prognostic factors included the ratio of total bilirubin (TBIL) on postoperative day (POD) X to TBIL on POD 1 (TBIL-r1) and the ratio of the international normalized ratio (INR) on POD X to the INR on POD 1 (INR-r1) for PODs 3, 5 and 7. Student's t test, the χ(2) test, logistic regression, survival analysis and receiver operating curve analysis were used to evaluate risk factors and establish the definition of postoperative liver failure (PLF). RESULTS: Fourteen patients (2.9%) died of liver failure within 3 mo of surgery. Significant differences were found between patients who died of liver failure and the remaining patients in terms of TBIL-r1 and INR-r1 on PODs 3, 5 and 7. The combination of TBIL-r1 and INR-r1 on POD 5 showed strong predictive power for liver failure-related death (sensitivity 92.9% and specificity 90.1%). The hepatic damage score (HDs), which was derived from TBIL-r1 and INR-r1, was used to define the degree of metabolic functional impairment after resection as mild (HDs = 0), reversible hepatic "dysfunction" (HDs = 1) or fatal hepatic failure (HDs = 2). Furthermore, the indocyanine green retention rate at 15 min (ICG-R15) and the number of resected segments (RSs) were identified as independent predictors of the HDs. A linear relationship was found between ICG-R15 and RSs in the HDs = 2 group. The regression equation was: RSs = -0.168 × ICG-R15 + 5.625 (r (2) = 0.613, F = 14.257, P = 0.004). CONCLUSION: PLF can be defined by the HDs, which accurately predicts liver failure-related death after liver resection. Furthermore, the ICG-R15 and RSs can be used as selection criteria for hepatectomy.
Authors: Michael A Choti; James V Sitzmann; Marcelo F Tiburi; Wuthi Sumetchotimetha; Ram Rangsin; Richard D Schulick; Keith D Lillemoe; Charles J Yeo; John L Cameron Journal: Ann Surg Date: 2002-06 Impact factor: 12.969
Authors: J Belghiti; J M Regimbeau; F Durand; A R Kianmanesh; F Dondero; B Terris; A Sauvanet; O Farges; F Degos Journal: Hepatogastroenterology Date: 2002 Jan-Feb
Authors: William R Jarnagin; Mithat Gonen; Yuman Fong; Ronald P DeMatteo; Leah Ben-Porat; Sarah Little; Carlos Corvera; Sharon Weber; Leslie H Blumgart Journal: Ann Surg Date: 2002-10 Impact factor: 12.969
Authors: David A Kooby; Yuman Fong; Arief Suriawinata; Mithat Gonen; Peter J Allen; David S Klimstra; Ronald P DeMatteo; Michael D'Angelica; Leslie H Blumgart; William R Jarnagin Journal: J Gastrointest Surg Date: 2003-12 Impact factor: 3.267
Authors: Dongbo Wu; Enqiang Chen; Tao Liang; Menglan Wang; Bin Chen; Bai Lang; Hong Tang Journal: Medicine (Baltimore) Date: 2017-08 Impact factor: 1.889
Authors: T Bluth; R Teichmann; T Kiss; I Bobek; J Canet; G Cinnella; L De Baerdemaeker; C Gregoretti; G Hedenstierna; S N Hemmes; M Hiesmayr; M W Hollmann; S Jaber; J G Laffey; M J Licker; K Markstaller; I Matot; G Müller; G H Mills; J P Mulier; C Putensen; R Rossaint; J Schmitt; M Senturk; A Serpa Neto; P Severgnini; J Sprung; M F Vidal Melo; H Wrigge; M J Schultz; P Pelosi; M Gama de Abreu Journal: Trials Date: 2017-04-28 Impact factor: 2.279
Authors: Ken Min Chin; John Carson Allen; Jin Yao Teo; Juinn Huar Kam; Ek Khoon Tan; Yexin Koh; Kim Poh Brian Goh; Peng Chung Cheow; Prema Raj; Kah Hoe Pierce Chow; Yaw Fui Alexander Chung; London Lucien Ooi; Chung Yip Chan; Ser Yee Lee Journal: Ann Hepatobiliary Pancreat Surg Date: 2018-08-31