Detailed Assessment of Augmented Renal Clearance in a Large Mixed Intensive Care Unit Population

This multi-center retrospective cohort study presents a detailed assessment of augmented renal clearance (ARC) in a mixed population of adult critically ill patients. Epidemiology of ARC will be studied in detail in a very heterogeneous population. Risk factors for ARC will be identified and a predictive scoring system for ARC ready to use in clinical practice will be constructed and validated. Performance of estimators of kidney function will be measured and a cutoff for ARC will be determined for the best estimator. Finally clinical impact of ARC will be explored using vancomycine and aminoglycosides levels as surrogate marker.

Study Overview

• Status: Unknown
• Conditions: Critical Illness; Augmented Renal Clearance
• Intervention / Treatment: Other: no intervention

Detailed Description

Augmented renal clearance will be assessed in detail in a very large and heterogeneous adult critically ill population. Analysis will be conducted retrospectively on a multi-center database collected by the M@tric research group. M@tric collects data from all intensive care units (surgical, medical, cardiac) in 3 Belgian University Hospitals (Leuven, Ghent, Antwerp).

Anonymised admission, demographic, clinical and laboratory data collected from 2013 until the present will be retrieved from the M@tric database. These data will then be coded and analysed in R statistical software. ARC will be defined based on a 24h creatinine clearance (CrCl24h) >=130ml/min/1.73m².

Epidemiology and risk factors for ARC will be studied in order to confirm and clarify past studies which have mostly been done in rather small and specific subsets of patients. A predictive algorithm for ARC will be trained and subsequently validated for use in clinical practice. Moreover this algorithm will be compared to existing scoring systems, which have not yet found their way into clinical practice. This algorithm will provide the ability to anticipate ARC on the intensive care unit. Also use of formulae estimating renal function will be evaluated in this population. These estimators will be compared to the CrCl24h, which is considered the golden standard in clinical practice. A cutoff for the best estimating formula in order to detect ARC will be calculated. Finally the impact of ARC on serum levels of hydrophilic molecules likes vancomycine and aminoglycosides will be studied. As this research follows a retrospective design these levels will be used a surrogate marker for clinical impact. This will potentially point out some opportunities for future research on the clinical impact of ARC.

• Study Type: Observational
• Enrollment (Anticipated): 10000

Contacts and Locations

• Study Contact: Name: Matthias Gijsen, PharmD; Phone Number: 0032 16 340087; Email: matthias.gijsen@uzleuven.be
• Study Contact Backup: Name: Isabel Spriet, PhD; Phone Number: 0032 16 341262; Email: isabel.spriet@uzleuven.be

Study Locations

• Belgium
  • Leuven, Belgium, 3000
    • Recruiting
    • UZLeuven
    • Contact: Matthias Gijsen, PharmD
    • Contact: Isabel Spriet, PharmD PhD

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years and older (Adult, Older Adult)
• Accepts Healthy Volunteers: No
• Genders Eligible for Study: All

• Sampling Method: Probability Sample

Study Population

Patients admitted at any intensive care unit (surgical, medical, cardiac) from the 3 participating centra (Leuven University Hospitals, Ghent University Hospital, Antwerp University Hospital) between 2013 and present

Description

Inclusion Criteria:

• Having at least one 24h creatinine clearance measurement available

Exclusion Criteria:

• Any form of renal replacement therapy

Study Plan

How is the study designed?

Number of groups / cohorts

1

Cohorts and Interventions

Group / Cohort	Intervention / Treatment
Critically ill patients with a CrCl24h; Patients admitted to any intensive care unit (surgical, medical or cardiac) and having at least one 24h creatinine clearance measurement available.	Other: no intervention; no intervention

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
ARC incidence per day	Incidence of ARC per 100 ICU days	Retrospective analysis between January 2013 and December 2015
ARC incidence per admission	Incidence of ARC in % of ICU admissions: with ARC incidence defined as at least once, min. 50% of the measurements, 100% of the measurements during ICU admission)	Retrospective analysis between January 2013 and December 2015
Duration and course of ARC episodes	ARC episodes: number of episodes (count), length of the episodes (days) and both combined to obtain relative contribution to ARC as a % ((count*length)/total ARC days)	Retrospective analysis between January 2013 and December 2015
ARC daily prevalence	Daily prevalence of ARC (% of ARC days per ICU admission day)	Retrospective analysis between January 2013 and December 2015
Logistic regression with ARC as dependent variable	Risk factors associated with ARC will be identified through logistic regression analysis on demographic and clinical data.	Retrospective analysis between January 2013 and December 2015
Predictive algorithm for ARC	An algorithm predicting ARC on the next day(s) will be created using a backward selection logistic regression model on the risk factors associated with ARC detected in this study and/or in previously published studies.	Retrospective analysis between January 2013 and December 2015
Most precise formula using Bland-Altman agreement analysis	Bland-Altman agreement analysis between CrCl24h and 3 commonly used serum creatinine based formulae estimating renal function (CKD-EPI, C&G, MDRD) will be used to identify the formula with the best precision (SD of the bias).	Retrospective analysis between January 2013 and December 2015
Performance of the best cutoff for ARC using ROC curve analysis	Performance of the best cutoff for ARC using ROC curve analysis on the most precise formula estimating renal function.	Retrospective analysis between January 2013 and December 2015
Exploration of clinical impact of ARC via surrogate markers	Vancomycin and aminoglycoside (amikacin & gentamycin) serum concentrations will be used as surrogate markers to evaluate potential clinical impact of ARC.	Retrospective analysis between January 2013 and December 2015

Collaborators and Investigators

• Sponsor: Universitaire Ziekenhuizen KU Leuven
• Collaborators: University Hospital, Ghent; University Hospital, Antwerp
• Investigators: Study Director: Isabel Spriet, PhD, Universitaire Ziekenhuizen KU Leuven

Publications and helpful links

General Publications

• Gijsen M, Huang CY, Flechet M, Van Daele R, Declercq P, Debaveye Y, Meersseman P, Meyfroidt G, Wauters J, Spriet I. Development and External Validation of an Online Clinical Prediction Model for Augmented Renal Clearance in Adult Mixed Critically Ill Patients: The Augmented Renal Clearance Predictor. Crit Care Med. 2020 Dec;48(12):e1260-e1268. doi: 10.1097/CCM.0000000000004667.

Study record dates

Study Major Dates

• Study Start (Actual): October 1, 2018
• Primary Completion (Anticipated): August 1, 2019
• Study Completion (Anticipated): September 1, 2019

Study Registration Dates

• First Submitted: May 3, 2019
• First Submitted That Met QC Criteria: May 15, 2019
• First Posted (Actual): May 17, 2019

Study Record Updates

• Last Update Posted (Actual): May 17, 2019
• Last Update Submitted That Met QC Criteria: May 15, 2019
• Last Verified: May 1, 2019

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Pathologic Processes; Disease Attributes; Critical Illness
• Other Study ID Numbers: S61364

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: UNDECIDED
• IPD Plan Description: To be discussed

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No