Literature DB >> 26298028

Thirty-day mortality leads to underestimation of postoperative death after liver resection: A novel method to define the acute postoperative period.

Tobias S Schiergens1, Maximilian Dörsch1, Laura Mittermeier2, Katharina Brand2, Helmut Küchenhoff2, Serene M L Lee1, Hao Feng1, Karl-Walter Jauch1, Jens Werner1, Wolfgang E Thasler3.   

Abstract

BACKGROUND: Postoperative mortality commonly is defined as death occurring within 30 days of surgery or during hospitalization. After resection for liver malignancies, this definition may result in underreporting, because mortality caused by postoperative complications can be delayed as the result of improved critical care. The aim of this study was to estimate statistically the acute postoperative period (APP) after partial hepatectomy and to compare mortality within this phase to standard timestamps.
METHODS: From a prospective database, 784 patients undergoing resection for primary and secondary hepatic malignancies between 2003 and 2013 were reviewed. For estimation of APP, a novel statistical method applying tests for a constant postoperative hazard was implemented. Multivariable mortality analysis was performed.
RESULTS: The APP was determined to last for 80 postoperative days (95% confidence interval 40-100 days). Within this period, 55 patients died (7.0%; 80-day mortality). In comparison, 30-day mortality (N = 32, 4.0%) and in-hospital death (N = 39, 5.0%) were relevantly less. No patient died between postoperative days 80 and 90. The causes of mortality within 30 days and from days 30-80 did not greatly differ, especially regarding posthepatectomy liver failure (44% vs 39%, P = .787). Septic complications, however, tended to cause late deaths more frequently (43% vs 25%, P = .255). Comorbidities (Charlson comorbidity index ≥ 3; P = .046), increased preoperative alanine aminotransferase activity (P = .030), and major liver resection (P = .035) were independent risk factors of 80-day mortality.
CONCLUSION: After liver resection for primary and secondary malignancies, 90-day rather than 30-day or in-hospital mortality should be used to avoid underreporting of deaths.
Copyright © 2015 Elsevier Inc. All rights reserved.

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Year:  2015        PMID: 26298028     DOI: 10.1016/j.surg.2015.07.019

Source DB:  PubMed          Journal:  Surgery        ISSN: 0039-6060            Impact factor:   3.982


  8 in total

1.  Nonparametric change point estimation for survival distributions with a partially constant hazard rate.

Authors:  Alessandra R Brazzale; Helmut Küchenhoff; Stefanie Krügel; Tobias S Schiergens; Heiko Trentzsch; Wolfgang Hartl
Journal:  Lifetime Data Anal       Date:  2018-04-05       Impact factor: 1.588

2.  Intrahepatic fibrin(ogen) deposition drives liver regeneration after partial hepatectomy in mice and humans.

Authors:  Dafna Groeneveld; David Pereyra; Zwanida Veldhuis; Jelle Adelmeijer; Petra Ottens; Anna K Kopec; Patrick Starlinger; Ton Lisman; James P Luyendyk
Journal:  Blood       Date:  2019-01-17       Impact factor: 22.113

3.  Contributing factors to severe complications after liver resection: an aggregate root cause analysis in 105 consecutive patients.

Authors:  Kholoud Houssaini; Oumayma Lahnaoui; Amine Souadka; Mohamed-Anass Majbar; Abdelilah Ghanam; Brahim El Ahmadi; Zakaria Belkhadir; Leila Amrani; Raouf Mohsine; Amine Benkabbou
Journal:  Patient Saf Surg       Date:  2020-09-29

4.  The 3-60 criteria challenge established predictors of postoperative mortality and enable timely therapeutic intervention after liver resection.

Authors:  Georg P Gyoeri; David Pereyra; Eva Braunwarth; Markus Ammann; Philipp Jonas; Florian Offensperger; Florian Klinglmueller; Ruth Baumgartner; Sandra Holzer; Michael Gnant; Friedrich Laengle; Stefan Staettner; Thomas Gruenberger; Patrick Starlinger
Journal:  Hepatobiliary Surg Nutr       Date:  2019-04       Impact factor: 7.293

5.  Early prediction of postoperative liver dysfunction and clinical outcome using antithrombin III-activity.

Authors:  David Pereyra; Florian Offensperger; Florian Klinglmueller; Stefanie Haegele; Lukas Oehlberger; Thomas Gruenberger; Christine Brostjan; Patrick Starlinger
Journal:  PLoS One       Date:  2017-04-13       Impact factor: 3.240

6.  Implementation of the Management of Anticoagulation in the Periprocedural Period App Into an Electronic Health Record: A Prospective Cohort Study.

Authors:  Alex C Spyropoulos; Dimitrios Giannis; Jessica Cohen; Suja John; Anne Myrka; Damian Inlall; Michael Qiu; Saydi Akgul; Roger J Hyman; Jason J Wang
Journal:  Clin Appl Thromb Hemost       Date:  2020 Jan-Dec       Impact factor: 2.389

7.  Predicting Postoperative Liver Dysfunction Based on Blood-Derived MicroRNA Signatures.

Authors:  Patrick Starlinger; Hubert Hackl; David Pereyra; Susanna Skalicky; Elisabeth Geiger; Michaela Finsterbusch; Dietmar Tamandl; Christine Brostjan; Thomas Grünberger; Matthias Hackl; Alice Assinger
Journal:  Hepatology       Date:  2019-04-10       Impact factor: 17.425

8.  A novel machine learning algorithm to predict disease free survival after resection of hepatocellular carcinoma.

Authors:  Markus Bo Schoenberg; Julian Nikolaus Bucher; Dominik Koch; Nikolaus Börner; Sebastian Hesse; Enrico Narciso De Toni; Max Seidensticker; Martin Kurt Angele; Christoph Klein; Alexandr V Bazhin; Jens Werner; Markus Otto Guba
Journal:  Ann Transl Med       Date:  2020-04
  8 in total

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