Development and Validation of an Enhanced Prediction Score for Postoperative Acute Renal Failure After Liver Resection

Acute Renal Failure Clinical Trial

Official title:

Development and Validation of an Enhanced Prediction Score for Post-operative Acute Renal Failure Following Liver Resection

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT01318798
• Other study ID #: StV 33-2009
• Status: Completed
• Phase: N/A
• First received: March 16, 2011
• Last updated: February 9, 2015
• Start date: January 2010
• Est. completion date: April 2012

Study information

• Verified date: February 2015
• Source: University of Zurich
• Contact: n/a
• Is FDA regulated: No
• Health authority: Switzerland: ethic committee Zurich
• Study type: Observational

Clinical Trial 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.

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.

Recruitment information / eligibility

• Status: Completed
• Enrollment: 549
• Est. completion date: April 2012
• Est. primary completion date: April 2012
• Accepts healthy volunteers: No
• Gender: Both
• Age group: 18 Years to 95 Years

Eligibility

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

Study Design

Observational Model: Cohort, Time Perspective: Retrospective

Related Conditions & MeSH terms

• Acute Kidney Injury
• Acute Renal Failure
• Renal Insufficiency

Locations

Country	Name	City	State
Switzerland	University Hospital of Zurich, Departmente of Visceral and Transplantation Surgery	Zurich

Sponsors (1)

Lead Sponsor	Collaborator
University of Zurich

Country where clinical trial is conducted

Switzerland, 

References & Publications (1)

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.0b013e3181bdd — View Citation

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Development of an enhanced prediction score for ARF	Development of an enhanced but still simple and easy applicable score based on pre- and extended by intra-operative risk factors to predict postoperative ARF in patients scheduled for liver resection	within 48 hours post-operative	No
Secondary	Decision curve analysis	Describing a decision making model by performing a decision curve analysis for clinical consequences of the enhanced prediction score and comparing it with the pre-operative prediction score	within 48 hours post-operative	No
Secondary	internal validation of the enhanced prediction score	internal Validation: discrimination, calibration, k-fold cross validation and bootstrapping	within 48 hours post-operative	No