Literature DB >> 19855257

Perioperative mortality for management of hepatic neoplasm: a simple risk score.

Jessica P Simons1, Joshua S Hill, Sing Chau Ng, Shimul A Shah, Zheng Zhou, Giles F Whalen, Jennifer F Tseng.   

Abstract

OBJECTIVES: To develop a population-based risk score for stratifying patients by risk of in-hospital mortality following procedural intervention for hepatic neoplasm.
BACKGROUND: There has been growing support for the value of surgical management of hepatic neoplastic disease, both primary and metastatic. Advances in surgical and ablative technologies have contributed to a decrease in the mortality associated with these procedures. However, multiple patient-, disease- and treatment-related factors can contribute to perioperative morbidity and mortality.
METHODS: Using the Nationwide Inpatient Sample from 1998 to 2005, a retrospective cohort of patient-discharges for hepatic procedures with a concurrent diagnosis of hepatic primary or metastatic neoplasm to the liver was assembled. Procedures were categorized as lobectomy, wedge resection, or enucleation/ablation. Logistic regression and bootstrap methods were used to create an integer score for estimating the risk of in-hospital mortality using patient demographics, comorbidities, procedure type, tumor type, and hospital characteristics. A randomly selected sample of 80% of the cohort was used to create the risk score. Testing was conducted in the remaining 20% validation-set.
RESULTS: In total, 12,969 patient-discharges were identified. Overall in-hospital mortality was 3.45%. Predictive characteristics incorporated into the model included: age, sex, Charlson comorbidity score, procedure type, hospital type, and type of neoplasm. Integer values were assigned to these, and used to calculate an additive score. Five clinically relevant groups were assembled to stratify risk, with a 36-fold gradient in mortality. Rates in the groups were as follows: 0.9%, 2.5%, 6.8%, 17.6%, and 35.9%. In the derivation set, as well as in the validation set, the simple score discriminated well, with c-statistics of 0.76 and 0.70, respectively.
CONCLUSIONS: An integer-based risk score can be used to predict in-hospital mortality after hepatic procedure for neoplasm, and may be useful for preoperative risk stratification and patient counseling.

Entities:  

Mesh:

Year:  2009        PMID: 19855257     DOI: 10.1097/SLA.0b013e3181bc9c2f

Source DB:  PubMed          Journal:  Ann Surg        ISSN: 0003-4932            Impact factor:   12.969


  13 in total

1.  External validation of a pre-operative nomogram predicting peri-operative mortality risk after liver resections for malignancy.

Authors:  Mashaal Dhir; Srinevas K Reddy; Lynette M Smith; Fred Ullrich; James Wallis Marsh; Allan Tsung; David A Geller; Chandrakanth Are
Journal:  HPB (Oxford)       Date:  2011-09-16       Impact factor: 3.647

2.  Preoperative hepatitis B virus DNA level is a risk factor for postoperative liver failure in patients who underwent partial hepatectomy for hepatitis B-related hepatocellular carcinoma.

Authors:  Gang Huang; Wan Yee Lau; Feng Shen; Ze-Ya Pan; Si-Yuan Fu; Yun Yang; Wei-Ping Zhou; Meng-Chao Wu
Journal:  World J Surg       Date:  2014-09       Impact factor: 3.352

Review 3.  Acute renal injury after partial hepatectomy.

Authors:  Luis Alberto Batista Peres; Luis Cesar Bredt; Raphael Flavio Fachini Cipriani
Journal:  World J Hepatol       Date:  2016-07-28

4.  Central hepatectomy for centrally located malignant liver tumors: A systematic review.

Authors:  Ser Yee Lee
Journal:  World J Hepatol       Date:  2014-05-27

5.  Risk stratification for distal pancreatectomy utilizing ACS-NSQIP: preoperative factors predict morbidity and mortality.

Authors:  Kaitlyn Jane Kelly; David Yu Greenblatt; Yin Wan; Robert J Rettammel; Emily Winslow; Clifford S Cho; Sharon M Weber
Journal:  J Gastrointest Surg       Date:  2010-12-15       Impact factor: 3.452

6.  Inpatient mortality after orthopaedic surgery.

Authors:  Mariano E Menendez; Valentin Neuhaus; David Ring
Journal:  Int Orthop       Date:  2015-02-25       Impact factor: 3.075

7.  Pre-operative nomogram to predict risk of peri-operative mortality following liver resections for malignancy.

Authors:  Mashaal Dhir; Lynette M Smith; Fred Ullrich; Premila D Leiphrakpam; Quan P Ly; Aaron R Sasson; Chandrakanth Are
Journal:  J Gastrointest Surg       Date:  2010-09-08       Impact factor: 3.452

8.  Improving the quality of liver resection: a systematic review and critical analysis of the available prognostic models.

Authors:  Chetana Lim; Cornelius H Dejong; Oliver Farges
Journal:  HPB (Oxford)       Date:  2014-10-17       Impact factor: 3.647

9.  Predicting major complications after laparoscopic cholecystectomy: a simple risk score.

Authors:  Melissa M Murphy; Shimul A Shah; Jessica P Simons; Nicholas G Csikesz; Theodore P McDade; Andreea Bodnari; Sing-Chau Ng; Zheng Zhou; Jennifer F Tseng
Journal:  J Gastrointest Surg       Date:  2009-08-12       Impact factor: 3.452

10.  A novel preoperative predictive model of 90-day mortality after liver resection for huge hepatocellular carcinoma.

Authors:  Yue Yin; Jian-Wen Cheng; Fei-Yu Chen; Xu-Xiao Chen; Xin Zhang; Ao Huang; De-Zhen Guo; Yu-Peng Wang; Ya Cao; Jia Fan; Jian Zhou; Xin-Rong Yang
Journal:  Ann Transl Med       Date:  2021-05
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.