Chronic Kidney Disease Mineral and Bone DisorderNCT02697578
Artificial Intelligence: a New Alternative to Analyse CKD-MBD in Hemodialysis
An observational study of Chronic Kidney Disease Mineral and Bone Disorder, run by Maimónides Biomedical Research Institute of Córdoba at 1 site in Spain.
Trial summary
The regulation of calcium, phosphate and parathyroid hormone in hemodialysis is complex and each parameter is not independently regulated. Simultaneous modification in these three parameters are the result of abnormal mineral metabolism and the treatment used. Read more about this study
- Who is it for?
- Ages 18 to 90 years
- Conditions the study is for
- Chronic Kidney Disease Mineral and Bone Disorder
- How many people
- 197 participants
- Where
- 1 siteSpain
- Study dates
- 1 Feb 2016to 19 Dec 2018
- 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 to 90 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: Incident hemodialysis patients
Who may be able to join
- Incident hemodialysis patients
- Non acute renal failure
Who cannot join
- Previous treatment with cinacalcet
- Neoplasia
- Previous parathyrodectomy
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Artificial Intelligence: to Analyse CKD-MBD in Hemodialysis and Cardiovascular Risk
The regulation of calcium, phosphate and parathyroid hormone in hemodialysis is complex and each parameter is not independently regulated. Simultaneous modification in these three parameters are the result of abnormal mineral metabolism and the treatment used. The specific objective of this work is an accurate and exhaustive analysis and description of the complex relationships between clinically relevant parameters in chronic kidney disease metabolism bone disease. In order to achieve these objectives we have used a machine learning approach Random Forest able to extract useful knowledge from a large database. The analysis of the complex interactions between the different parameters needs an advance mathematical approach such as Random Forest . The second aim of this study is to determine whether calcium, phosphate and parathyroid hormone, Fibroblast growth factor 23 and calcitriol are long-term associated with demographic features, mortality, co-morbidity and the therapy prescribed. We will analyze in a prospective study on incident patients, whether the use of this new model may predict the cardiovascular risk..
Read the detailed description
In hemodialysis patients, deviations of serum concentration of calcium, phosphate or parathyroid hormone from the values recommended by KDIGO are associated to a negative outcome. The regulation of calcium, phosphate and parathyroid hormone is complex and each parameter is not independently regulated. In hemodialysis patient's simultaneous modification in these three parameters are the result of abnormal mineral metabolism and the treatment used to correct these abnormalities that usually produce changes in more than one parameter. The specific objective of this work is an accurate and exhaustive analysis and description of the complex relationships between clinically relevant parameters in chronic kidney disease metabolism bone disease. In order to achieve these objectives we have used a machine learning approach Random Forest able to extract useful knowledge from a large database. The analysis of the complex interactions between the different parameters needs an advance mathematical approach such as Random Forest . The second aim of this study is to determine whether calcium, phosphate and parathyroid hormone, Fibroblast growth factor 23 and calcitriol are long-term associated with demographic features, mortality, co-morbidity and the therapy prescribed. Compare the predictions obtained with conventional statistical analysis versus the new model analysis based on artificial intelligence. Our preliminary results suggest that there are interactions between some parameters that are strong enough to question whether the evaluation of a given therapy can be based in the measurement of one single parameter. Subsequently, we will analyze in a prospective study on incident patients, whether the use of this new model may predict the cardiovascular risk and reduce the therapy cost.
- Medical subject headings
- Chronic Kidney Disease-Mineral and Bone Disorder
What is being measured
The primary outcome is the main question the study is designed to answer.
Change from Baseline Fibroblast growth factor 23 (pg/ml) at 24 months
Prospective analysis of fibroblast growth factor in a cohort of incident hemodialysis patients
Measured: Baseline, 24 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted3 Mar 2016 (estimated)
- Study start1 Feb 2016
- Primary completion19 Dec 2018
- Study completion19 Dec 2018
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Chronic Kidney Disease Mineral and Bone DisorderStudies of the same condition, open and under way.
- 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
- Prospective
- Enrolment
- 197 participants (actual)
Sponsor and investigators
- Lead sponsor
- Maimónides Biomedical Research Institute of Córdoba
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- Alejandro Martín Malo, MD, Principal investigator, Andalusian Public Health System
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT02697578
- Sponsor's protocol ID
- PI-0311-2014
- Status last verified
- Dec 2018
- First submitted
- 23 Feb 2016
- Last updated
- 21 Dec 2018
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 21 Dec 2018. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Artificial Intelligence: to Analyse CKD-MBD in Hemodialysis and Cardiovascular Risk
- ClinicalTrials.gov ID
- NCT02697578
- Acronym / sponsor ID
- PI-0311-2014
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 197 participants (actual)
- Lead sponsor
- Maimónides Biomedical Research Institute of CórdobaUniversity, hospital or other
- Study start
- 1 Feb 2016 (actual)
- Primary completion
- 19 Dec 2018 (actual)
- Study completion
- 19 Dec 2018 (actual)
- First posted
- 3 Mar 2016 (estimated)
- 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.
The regulation of calcium, phosphate and parathyroid hormone in hemodialysis is complex and each parameter is not independently regulated. Simultaneous modification in these three parameters are the result of abnormal mineral metabolism and the treatment used. The specific objective of this work is an accurate and exhaustive analysis and description of the complex relationships between clinically relevant parameters in chronic kidney disease metabolism bone disease. In order to achieve these objectives we have used a machine learning approach Random Forest able to extract useful knowledge from a large database. The analysis of the complex interactions between the different parameters needs an advance mathematical approach such as Random Forest . The second aim of this study is to determine whether calcium, phosphate and parathyroid hormone, Fibroblast growth factor 23 and calcitriol are long-term associated with demographic features, mortality, co-morbidity and the therapy prescribed. We will analyze in a prospective study on incident patients, whether the use of this new model may predict the cardiovascular risk..
Detailed description
In hemodialysis patients, deviations of serum concentration of calcium, phosphate or parathyroid hormone from the values recommended by KDIGO are associated to a negative outcome. The regulation of calcium, phosphate and parathyroid hormone is complex and each parameter is not independently regulated. In hemodialysis patient's simultaneous modification in these three parameters are the result of abnormal mineral metabolism and the treatment used to correct these abnormalities that usually produce changes in more than one parameter. The specific objective of this work is an accurate and exhaustive analysis and description of the complex relationships between clinically relevant parameters in chronic kidney disease metabolism bone disease. In order to achieve these objectives we have used a machine learning approach Random Forest able to extract useful knowledge from a large database. The analysis of the complex interactions between the different parameters needs an advance mathematical approach such as Random Forest . The second aim of this study is to determine whether calcium, phosphate and parathyroid hormone, Fibroblast growth factor 23 and calcitriol are long-term associated with demographic features, mortality, co-morbidity and the therapy prescribed. Compare the predictions obtained with conventional statistical analysis versus the new model analysis based on artificial intelligence. Our preliminary results suggest that there are interactions between some parameters that are strong enough to question whether the evaluation of a given therapy can be based in the measurement of one single parameter. Subsequently, we will analyze in a prospective study on incident patients, whether the use of this new model may predict the cardiovascular risk and reduce the therapy cost.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
Who may qualify
- Ages
- 18 to 90 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Incident hemodialysis patients
Key inclusion criteria (2 listed)
- Incident hemodialysis patients
- Non acute renal failure
Key exclusion criteria (3 listed)
- Previous treatment with cinacalcet
- Neoplasia
- Previous parathyrodectomy
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Change from Baseline Fibroblast growth factor 23 (pg/ml) at 24 months
Time frame: Baseline, 24 months
Prospective analysis of fibroblast growth factor in a cohort of incident hemodialysis patients
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 21 Dec 2018.
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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.
Alejandro Martín Malo, MD principal investigator
Andalusian Public Health System
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 Chronic Kidney Disease Mineral and Bone Disorder, run by Maimónides Biomedical Research Institute of Córdoba at 1 site in Spain.
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 2 inclusion and 3 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: finished, as of the sponsor's last update on 21 Dec 2018. 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 Spain. 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?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Change from Baseline Fibroblast growth factor 23 (pg/ml) at 24 months (time frame: Baseline, 24 months). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
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 21 Dec 2018.