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Preoperative nomogram to predict posthepatectomy liver failure
Author(s) -
Dhir Mashaal,
Samson Kaeli K.,
Yepuri Natesh,
Yanala Ujwal R.,
Smith Lynette M.,
Are Chandrakanth
Publication year - 2021
Publication title -
journal of surgical oncology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.201
H-Index - 111
eISSN - 1096-9098
pISSN - 0022-4790
DOI - 10.1002/jso.26463
Subject(s) - nomogram , medicine , hepatectomy , liver failure , surgery , neoadjuvant therapy , proportional hazards model , cohort , resection , cancer , breast cancer
Background and Objectives Posthepatectomy liver failure (PHLF) is associated with significant morbidity and mortality. However, it is often difficult to predict the risk of PHLF in an individual patient. We aimed to develop a preoperative nomogram to predict PHLF and allow better risk stratification before surgery. Methods Data for patients undergoing a partial or major hepatectomy were extracted from the hepatectomy‐specific NSQIP database for years 2014–2016. Data set from 2017 was used for validation. Patients with Grade B/C liver failure were compared with patients with no liver failure. Results A total of 10 808 patients from 2014–2016 data set were included. Of these, 316 patients (2.9%) developed Grade B/C PHLF. In the multivariable model consisting of preoperative variables, the following were predictive of Grade B/C PHLF (all p < 0.05): male gender, biliary stent, neoadjuvant therapy, viral hepatitis B or C, concurrent resections, biliary reconstruction, low sodium, and low albumin (model c statistic‐0.78). This model was used to construct a nomogram. In the 2017 validation cohort of 4367 patients the nomogram again demonstrated good c‐statistic (0.78). Conclusions Our nomogram provides patient‐specific probabilities for PHLF, and is easy to use. This is a valuable tool that can be utilized for preoperative patient counseling and selection.