Clinical trial NCT01318798: Development and Validation of an Enhanced Prediction Score for Postoperative Acute Renal Failure After Liver Resection
Official title: Development and Validation of an Enhanced Prediction Score for Post-operative Acute Renal Failure Following Liver Resection
Study type: OBSERVATIONAL
Overall status: COMPLETED
Conditions: Acute Renal Failure
Keywords: Development
Pre- and intra-operative predictors
Acute renal failure
Liver Surgery
Prediction score
Validation
Clinical consequences
Decision curve analysis
predictors of acute renal failure after liver resection
Lead sponsor: University of Zurich
Sponsor class: OTHER
First posted: 2011-03-18
Enrollment: 549
Sex: ALL
Minimum age (years): 18
Maximum age (years): 95
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: COHORT
Time perspective: RETROSPECTIVE
Sampling method: PROBABILITY_SAMPLE
Study population: We included consecutively patients undergoing any type of hepatic surgery for benign as well as malignant diseases between July first, 2002 and October 31, 2007 in a single tertiary care center (Swiss Hepato-Pancreato-Biliary (HPB) Centre, University Hospital of Zurich, Switzerland.

Brief summary: Post-operative acute renal failure is a severe post-operative complication and is associated with high mortality. The enhanced prediction score, including pre-as well as intra-operative predictors accurately predicted ARF following hepatic surgery. This prediction score allows early identification of patients at high risk of ARF and may support decision-making for protective kidney treatment.

Detailed description: To enhance and validate an already pre-existing score accurately predicting post-operative acute renal failure (ARF) after hepatic surgery

We will enhance a pre-existing score predicting ARF based on pre-operative as well as intra-operative predictors.

Development process: we will identify the strongest predictors of ARF in a multivariable logistic regression model followed by a stepwise backward logistic regression analysis and bootstrapping.

Validation process: we will perform an internal validation by calibrating the prediction model as well as by k-fold cross validation (c statistics) and bootstrapping. Additionally, we will calculate the discrimination by the area under the curve (AUC).

Decision curve analysis: Furthermore we will perform a decision curve analysis to evaluate the clinical consequences of both prediction scores whether a patient with increased ARF risk would post-operative benefit of a treatment on the ICU.

Eligibility criteria: Inclusion Criteria:

* \> 18 years
* scheduled for liver surgery
* benign as well as malignant diseases

Exclusion Criteria:

* liver trauma
* incomplete data sets
* pre-operative chronic renal failure requiring hemodialysis

Primary outcomes:
measure: Development of an enhanced prediction score for ARF
timeFrame: within 48 hours post-operative
Secondary outcomes:
measure: Decision curve analysis
timeFrame: within 48 hours post-operative
measure: internal validation of the enhanced prediction score
timeFrame: within 48 hours post-operative
Other outcomes:
Locations:
city: Zurich
country: Switzerland
facility: University Hospital of Zurich, Departmente of Visceral and Transplantation Surgery
Study officials:
affiliation: University Hospital Zurich, Visceral and Transplantation Surgery
name: Ksenija Slankamenac, med. pract.
role: PRINCIPAL_INVESTIGATOR
References:
citation: Slankamenac K, Breitenstein S, Held U, Beck-Schimmer B, Puhan MA, Clavien PA. Development and validation of a prediction score for postoperative acute renal failure following liver resection. Ann Surg. 2009 Nov;250(5):720-8. doi: 10.1097/SLA.0b013e3181bdd840.