Critical IllnessNCT03954275
Detailed Assessment of Augmented Renal Clearance in a Large Mixed Intensive Care Unit Population
An observational study of Critical Illness and Augmented Renal Clearance, run by Universitaire Ziekenhuizen KU Leuven at 1 site in Belgium.
Trial summary
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. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Critical Illness, Augmented Renal Clearance
- How many people
- 10,000 participants
- Where
- 1 siteBelgium
- Study dates
- 1 Oct 2018to Sep 2019
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
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
Who may be able to join
- Having at least one 24h creatinine clearance measurement available
Who cannot join
- Any form of renal replacement therapy
Trial locations and contacts
1 site in 1 country.
Belgium1 site, 1 recruiting
- Recruiting
UZLeuven
Leuven, 3000
Matthias Gijsen, PharmD
Isabel Spriet, PharmD PhD
About this study
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.
Read the 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.
- Conditions
- Critical Illness, Augmented Renal Clearance
- Being tested
- no intervention
- Medical subject headings
- Critical Illness
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
no interventionOther
no intervention
| Study group | Role | What they receive |
|---|---|---|
| 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. Receives: Other: no intervention |
What is being measured
The primary outcome is the main question the study is designed to answer.
ARC incidence per day
Incidence of ARC per 100 ICU days
Measured: 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)
Measured: 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)
Measured: Retrospective analysis between January 2013 and December 2015
ARC daily prevalence
Daily prevalence of ARC (% of ARC days per ICU admission day)
Measured: 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.
Measured: 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.
Measured: 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).
Measured: 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.
Measured: 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.
Measured: Retrospective analysis between January 2013 and December 2015
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted17 May 2019
- Study start1 Oct 2018
- Primary completionAug 2019 (estimated)
- Study completionSep 2019 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for Critical IllnessStudies of the same condition, open and under way.
- More trials run by Universitaire Ziekenhuizen KU LeuvenThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Retrospective
- Enrolment
- 10,000 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Universitaire Ziekenhuizen KU Leuven
- Sponsor type
- University, hospital or other
- Collaborators
- University Hospital, Ghent, University Hospital, Antwerp
- Responsible party
- Principal investigator, Matthias Gijsen, Universitaire Ziekenhuizen KU Leuven
- Investigators
- Isabel Spriet, PhD, Study director, Universitaire Ziekenhuizen KU Leuven
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT03954275
- Sponsor's protocol ID
- S61364
- Status last verified
- May 2019
- First submitted
- 3 May 2019
- Last updated
- 17 May 2019
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided: To be discussed
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.
PubMed 33048900
Study at a glance
From the registry record, last updated by the sponsor on 17 May 2019. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Detailed Assessment of Augmented Renal Clearance in a Large Mixed Intensive Care Unit Population
- ClinicalTrials.gov ID
- NCT03954275
- Acronym / sponsor ID
- S61364
- Conditions
- Critical Illness, Augmented Renal Clearance
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 10,000 participants (estimated)
- Lead sponsor
- Universitaire Ziekenhuizen KU LeuvenUniversity, hospital or other
- Collaborators
- University Hospital, Ghent, University Hospital, Antwerp
- Study start
- 1 Oct 2018 (actual)
- Primary completion
- Aug 2019 (estimated)
- Study completion
- Sep 2019 (estimated)
- First posted
- 17 May 2019 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
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 design
- Observational model
- Cohort
- Time perspective
- Retrospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Critically ill patients with a CrCl24h | – | Other: no interventionPatients admitted to any intensive care unit (surgical, medical or cardiac) and having at least one 24h creatinine clearance measurement available. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- 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
Key inclusion criteria (1 listed)
- Having at least one 24h creatinine clearance measurement available
Key exclusion criteria (1 listed)
- Any form of renal replacement therapy
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| no interventionno intervention | Other | Critically ill patients with a CrCl24h |
Primary outcome
ARC incidence per day
Time frame: Retrospective analysis between January 2013 and December 2015
Incidence of ARC per 100 ICU days
ARC incidence per admission
Time frame: Retrospective analysis between January 2013 and December 2015
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)
Duration and course of ARC episodes
Time frame: Retrospective analysis between January 2013 and December 2015
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)
ARC daily prevalence
Time frame: Retrospective analysis between January 2013 and December 2015
Daily prevalence of ARC (% of ARC days per ICU admission day)
Logistic regression with ARC as dependent variable
Time frame: Retrospective analysis between January 2013 and December 2015
Risk factors associated with ARC will be identified through logistic regression analysis on demographic and clinical data.
Predictive algorithm for ARC
Time frame: Retrospective analysis between January 2013 and December 2015
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.
Most precise formula using Bland-Altman agreement analysis
Time frame: Retrospective analysis between January 2013 and December 2015
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).
Performance of the best cutoff for ARC using ROC curve analysis
Time frame: Retrospective analysis between January 2013 and December 2015
Performance of the best cutoff for ARC using ROC curve analysis on the most precise formula estimating renal function.
Exploration of clinical impact of ARC via surrogate markers
Time frame: Retrospective analysis between January 2013 and December 2015
Vancomycin and aminoglycoside (amikacin \& gentamycin) serum concentrations will be used as surrogate markers to evaluate potential clinical impact of ARC.
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 17 May 2019.
- Derived from this study: PubMed 33048900Gijsen 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.
- Individual participant dataSharing planned: Undecided. To be discussed
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Isabel Spriet, PhD study director
Universitaire Ziekenhuizen KU Leuven
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Critical Illness and Augmented Renal Clearance, run by Universitaire Ziekenhuizen KU Leuven at 1 site in Belgium.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 1 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 17 May 2019. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Belgium. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact Matthias Gijsen, PharmD (16 340087 ext. 0032, matthias.gijsen@uzleuven.be), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
ARC incidence per day (time frame: Retrospective analysis between January 2013 and December 2015). The study lists 9 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT03954275, which also lists 1 linked publication.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 17 May 2019.