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Updated: Jun 22, 2026

Modified Laparoscopic Anatomic Hepatectomy: Two-Surgeon Technique Combined with the Simple Extracorporeal Pringle Maneuver

Modified Laparoscopic Anatomic Hepatectomy: Two-Surgeon Technique Combined with the Simple Extracorporeal Pringle Maneuver

Published on: June 16, 2023

Avoiding futile damage control laparotomy.

Nicolas Kairinos¹, Philip M Hayes, Andrew J Nicol

¹Trauma Centre, Dept of Surgery, Groote Schuur Hospital and University of Cape Town, Cape Town, South Africa. nickykairinos@gmail.com

|July 3, 2009

Summary

This summary is machine-generated.

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This study validates an equation predicting mortality in damage control surgery (DCS) patients. The equation accurately identifies unsalvageable patients, aiding resource allocation during mass casualty events.

Area of Science:

Trauma Surgery
Surgical Outcomes
Predictive Modeling in Medicine

Background:

Patient age, lowest pre-operative pH, and lowest core temperature are key mortality predictors in damage control surgery (DCS).
A prior equation using these factors predicted non-survivors with 100% positive predictive value but only 25% sensitivity.
This study aimed to validate the predictive accuracy of this established equation on a new patient cohort.

Purpose of the Study:

To validate a previously developed predictive equation for mortality in patients undergoing DCS.
To assess the positive predictive value and sensitivity of the equation in a distinct patient cohort.
To determine the equation's utility in identifying futile surgical cases.

Main Methods:

A retrospective validation study analyzed 73 patients undergoing DCS between 1998 and 2001.

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Last Updated: Jun 22, 2026

Modified Laparoscopic Anatomic Hepatectomy: Two-Surgeon Technique Combined with the Simple Extracorporeal Pringle Maneuver

Modified Laparoscopic Anatomic Hepatectomy: Two-Surgeon Technique Combined with the Simple Extracorporeal Pringle Maneuver

Published on: June 16, 2023

Lowest pre-operative pH, lowest core temperature, and patient age were recorded.

The established equation was applied to predict "unsalvageable" patients, with outcomes compared to actual results.

Main Results:

The equation correctly identified 8 "unsalvageable" patients, all of whom died (100% positive predictive value).
Sensitivity was 24%, with 25 of the "potentially salvageable" group also dying.
Combined data from the original and validation cohorts (145 patients) showed 53 deaths, with 13 predicted as unsalvageable.

Conclusions:

The predictive equation demonstrated consistent positive predictive value and sensitivity.
The equation can aid in identifying futile surgical interventions when resources are strained.
This tool supports efficient surgical triage in mass casualty incidents by highlighting patients unlikely to survive.