CClinicalTrials.gg
CompletedNCT02878317AGEDUpdated Dec 10, 2024Results posted

Skin Autofluorescence as a Risk Marker in People Receiving Dialysis.

An observational study in Chronic Kidney Disease, sponsored by University of Nottingham. Completed at 1 site in United Kingdom. Open to participants aged 18 Years and older. Per ClinicalTrials.gov, last updated 2024-12-10.

Sponsored by University of Nottingham · Observational

Study type
Observational
Model
Cohort
Time perspective
Prospective
Enrollment
81
Ages
18 Years and older
Sex
All
01

Study summary

The purpose of the present study is to investigate the association between the accumulation of advanced glycation end-products (AGE) and adverse outcomes (e.g. death) in people receiving haemodialysis and peritoneal dialysis based in Royal Derby Hospital, as well as the impact of a dietetic intervention on AGE accumulation. AGE will be measured non-invasively in the skin using a technique called skin autofluorescence (SAF).

The present study will be conducted in two parts:

Study 1: this will be a prospective study where participants will be followed-up for up to five years. The research team will measure the accumulation of AGE in the skin using a quick (less than five minutes) and painless technique called SAF. This involves placing the forearm on a piece of equipment that shines a light on the skin and measures the amount of light that is reflected back. Participants will be asked to complete nutritional and quality of life questionnaires, measurements of weight, height, arm circumference and skinfold thickness (i.e. anthropometry), simple eyesight tests and blood tests.

Study 2: observational non-randomized proof of principle study where malnourished dialysis participants will receive a dietitian supervised intensive nutritional support. Participants will be followed-up for 2 years and will receive precise oral and written instructions on how to comply with the intervention. Blood and eyesight tests, SAF measurements, anthropometry and nutritional and quality of life assessments will be conducted.

In Studies 1 and 2, approximately two teaspoons of blood will be collected to measure AGE levels and do some additional blood tests to help us investigate the effects of AGEs on the body. If the participants agree, the investigators will also store some of the blood for future research.

Read the detailed description

STUDY BACKGROUND

Chronic kidney disease (CKD) is a global public health problem and is associated with multiple adverse outcomes including reduced survival, especially in people requiring renal replacement therapy (peritoneal dialysis (PD), haemodialysis [HD] and transplantation). Multiple risk factors lead to the development and/or progression of CKD, such as obesity, hyperlipidaemia, glomerulonephritis, intercurrent infections, smoking, type 2 diabetes and hypertension, the two latter being considered as leading causes of CKD worldwide.

People on dialysis develop a variety of complications/abnormalities as a result of loss of endocrine or exocrine function of the kidneys, including anaemia, metabolic acidosis, bone and mineral disorders, fluid overload, hypertension, electrolyte disturbances and dyslipidaemia. In recent years, inflammation, oxidative stress and endothelial dysfunction (other common abnormalities in people on dialysis) have become areas of interest because of their strong relationship with higher rates of cardiovascular morbidity and mortality in people on dialysis.

Advanced glycation end-products (AGE) are uremic toxins that are markedly increased in people on dialysis. Formation of AGE starts with a non-enzymatic reaction between proteins and glucose molecules called the Maillard reaction; however, AGE are also formed more rapidly during oxidative stress with the subsequent formation of reactive carbonyl compounds like methyl glyoxal. At this point, AGE synthesis is irreversible and AGE will cross-link with tissue proteins; it seems that collagen in the skin and vascular basement membranes are especially susceptible to AGE accumulation and subsequent injury. AGE also interact with specific AGE receptors that will lead to the activation of systemic inflammation by increasing the release of cytokines and, consequently, exacerbate tissue damage. Importantly, AGE are also formed in food during cooking with dry heat at high temperatures such as in frying, grilling or roasting and about 10% of the ingested AGE is absorbed.

Skin autofluorescence (SAF) is a relatively new technique that measures the skin accumulation of AGE. It is a non-invasive, operator independent, quick (less than 5 minutes) and easy to perform technique that utilizes the fluorescent properties of AGE, like the extensively used collagen linked fluorescence (CLF) method, and has been validated with specific AGE measurements and CLF in skin biopsies. It has been reported that SAF is strongly correlated with overall and cardiovascular mortality in people with diabetes and undergoing HD. Several factors have been associated with higher SAF values in people on dialysis in cross-sectional studies, for instance, chronological age in both dialysis modalities, glucose exposure from peritoneal dialysis fluid and dialysis vintage only in people on PD and presence of diabetes in people on HD.

AGE accumulation is postulated as the one of the modulating factors that drives visual disorders; the increased accumulation secondary to hyperglycaemia in diabetes is thought to cause vascular basement membrane thickening and destruction of pericytes from the retinal capillary bed in diabetic retinopathy. The accumulation of AGE has also been reported to be a mechanism in the deterioration in visual acuity associated with increasing age. Separately, the accumulation of AGE in other metabolic diseases (e.g. end stage kidney disease [ESKD]) has been found to cause nerve and eye dysfunction. Ocular abnormalities and therefore visual disturbances are reported in people with ESKD but the mechanism for this has not been fully explored or understood. In animal studies, AGE accumulation is seen in the lens, cornea and vitreous humour. In humans, systemic AGE levels and visual acuity scoring have not been previously investigated.

Because of the adverse outcomes strongly associated with higher levels of SAF, several options focused on reducing the accumulation of AGE have been proposed. One of these promising interventions is the reduction of dietary AGE; it has been suggested that cooking techniques that avoid very high temperatures such as poaching, steaming, stewing and boiling can significantly reduce the AGE content of food when compared to frying, broiling, grilling and roasting; nevertheless, most of the evidence regarding dietary modifications to reduce exogenous AGE is of low quality and therefore further studies are required.

Nevertheless, analysis of baseline data from Study 1 has identified strong associations between higher SAF and malnutrition whereas no correlations were observed between higher SAF and high dietary AGE intake. Correction of malnutrition may therefore represent a more important dietary intervention to reduce accumulation of AGE in people receiving dialysis. We further reasoned that placing people with malnutrition on a restrictive diet may worsen their malnutrition and we have therefore adapted our original research plan to include an observational study to assess the impact of correcting malnutrition on SAF by providing a dietitian supervised nutritional support intervention, which essentially involves the usual/standard dietetic care/advice provided by the NHS with some additional supervision, follow-up and approved dietary supplements (also provided by the NHS), rather than a randomised trial of dietary AGE restriction.

The results from the present project will benefit people on dialysis because they may demonstrate that the correction of malnutrition decreases the SAF levels in this population. Published observational studies suggest that reduction of SAF levels will in turn be associated with a reduction in the high morbidity and mortality rates associated with chronic dialysis and, consequently, healthcare costs. Improved survival and reduced comorbidity would also be expected to improve the quality of life of people on dialysis.

DURATION OF THE STUDY

Study 1:

Participant recruitment will begin on September 2016 with an anticipated recruitment period of 12 months. Therefore, all baseline data and measurements will be collected and performed between September 2016 and September 2017. Once recruited, all participants will be followed-up for up to five years; consequently, it is expected that the study will be completed by September 2022.

Study 2:

Participant recruitment will begin in December 2017 with an anticipated recruitment period of 6 months. Therefore, all baseline data and measurements will be collected and performed between December 2017 and June 2018. Once recruited, all participants will be followed-up for 24 months; consequently, it is expected that the study will be completed by June 2020.

RECRUITMENT

Potential participants on HD and PD will be recruited from the Renal Unit of the Department of Nephrology at the Royal Derby Hospital. The initial details of the study and participant information sheet will be provided by the usual care team (which may include the researcher). Participants will then be given at least 24 hours to consider whether they wish to participate, as well as ask any questions about the study, before being re-contacted by the investigators.

INFORMED CONSENT

The process for obtaining participant informed consent will be in accordance with the Research Ethics Committee (REC) guidance, Good Clinical Practice (GCP) and any other regulatory requirements that might be introduced.

All participants will provide written informed consent. The Informed Consent Form will be signed and dated by the participant before they enter the study. The Investigator will explain the details of the study and provide a Participant Information Sheet, ensuring that the participant has sufficient time to consider participating or not. The Investigator will answer any questions that the participant has concerning study participation.

STATISTICS

To compare baseline versus final evaluations, Wilcoxon test or paired t-test will be used in the case of dimensional variables, and McNemar test in the case of categorical variables. Intergroup comparisons will be performed using Mann Whitney test or Student t test for continuous variables and χ2 test or Fisher's exact test for categorical variables. To determine the significance and strength of associations, Pearson's correlation coefficient will be used for analyses of associations between continuous variables and Spearman rank for nonparametric variables. Linear regression analysis will be used to identify determinants of AGE accumulation. Cox proportional hazards models will be used to investigate the prognostic value of the accumulation of AGE for predicting mortality. A p-value less than or equal to 0.05 will be considered to have statistical significance.

Sample size calculation of Study 1 was performed by using the software nQuery Advisor v.6.0.

Sample size Study 1:

The primary outcome for sample size determination is one-year survival in relation to increased SAF levels in people on HD and PD. With a power of 80%, a two-sided alpha of 5% and an expected hazard ratio of 3.5 and 2.0 in people on PD and HD, respectively, 100 HD and 40 PD participants will be needed.

Sample size Study 2 Since this is a proof of principle study, it would be reasonable to include 40 dialysis participants (either HD or PD).

ETHICS COMMITTEE AND REGULATORY APPROVALS

The study will not be initiated before the protocol, informed consent forms and participant information sheets have received approval / favourable opinion from the REC, and the respective NHS Research \& Development (R\&D) department.

PROCEDURES FOR MISSING DATA AND ADVERSE EVENTS

All SAF measurements, biochemistry, nutritional and quality of life assessments for Study 1 and 2 will be used in the statistical analysis, including data from participants who did not complete the entire study protocol.

The occurrence of an adverse event as a result of participation within this study is not expected and as such no adverse event data will be collected.

QUALITY ASSURANCE \& AUDIT

Study conduct may be subject to systems audit of the Trial Master File for inclusion of essential documents; permissions to conduct the study; Trial Delegation Log; CVs of study staff and training received; local document control procedures; consent procedures and recruitment logs; adherence to procedures defined in the protocol (e.g. inclusion / exclusion criteria, correct randomisation, timeliness of visits); AE recording and reporting; accountability of study materials and equipment calibration logs.

Monitoring of study data shall include confirmation of informed consent; source data verification; data storage and data transfer procedures; local quality control checks and procedures, back-up and disaster recovery of any local databases and validation of data manipulation.

Entries on Case Report Forms (CRFs) will be verified by inspection against the source data. A sample of CRFs (10% or as per the study risk assessment) will be checked on a regular basis for verification of all entries made. In addition the subsequent capture of the data on the study database will be checked. Where corrections are required these will carry a full audit trail and justification.

Study data and evidence of monitoring and systems audits will be made available for inspection by REC as required.

02

Conditions studied

  • Chronic Kidney Disease

Keywords

  • Glycosylation End Products, Advanced
  • Skin autofluorescence
  • Renal Dialysis
03

In context

Kidney Diseases

3,840 studies on the registry are indexed under Kidney Diseases; 500 are open to participants now.

This study's enrollment of 81 is below the median of 192 across 1,033 observational studies indexed under Kidney Diseases.

Browse Kidney Diseases studies →

Lead sponsor

University of Nottingham is the lead sponsor of 455 studies on the registry; 77 are open to participants now.

Counted across the registry records on this site, refreshed daily.

04

Who can participate

Ages eligible
18 Years and older
Sexes eligible
All
Accepts healthy volunteers
No
Sampling method
Non-probability sample

Study population

Participants undergoing HD and PD treatment.

Inclusion criteria

Haemodialysis cohort:

  • Three dialysis sessions per week for 4 hours.
  • Dialysis with biocompatible membranes.
  • Able to give informed consent.

Peritoneal Dialysis cohort:

  • Dialysis with lactate/bicarbonate-buffered solutions with different glucose concentrations as prescribed for routine clinical care.
  • Able to give informed consent.

Exclusion criteria

Exclusion Criteria:

  • Does not wish to participate.
  • Renal transplant.
  • Pregnancy or breast feeding or intending pregnancy.
  • Expected survival less than one year.
05

Study design

Observational model
Cohort
Time perspective
Prospective
Enrollment
81 participants (actual)
Patient registry
No

Groups and cohorts

  • Study 2 - Non randomised proof of principle study

    Malnourished participants received individualized nutritional advice and support formulated and delivered by experienced dietitians consisting of food fortification recommendations and oral nutritional supplementation aiming to achieve estimated nutritional requirements (i.e. energy \[30-35 kcal/kg/day\] and protein intake \[1.1-1.2 g/kg/day\]). Food fortification involved enhancing the energy and protein content of meals and snacks without increasing the portion sizes of foods. Advice was individualized according to patient needs and food preferences. Oral nutritional supplements included Fortisip Compact (2.4 kcal/ml), Fortisip (1.5 kcal/ml) and Fortijuice (1.5 kcal/ml), as well as Renapro® shot and Fresubin® 5kcal Shot.

  • Historical control group from Study 1

    Participants on dialysis with malnutrition taken from Study 1, who were seen by their usual dietitian once a month and received standard nutritional counselling.

06

What researchers measure

Primary outcomes

  1. Skin Autofluorescence Levels at 6 Months

    Skin autolfuorescence (SAF) was measured after 6 months of intensive dietetic advice and nutritional support with a validated Autofluorescence Reader (AGE) Standard Unit (SU), version 2.4.3. The AGE Reader SU directs an ultraviolet excitation light through an illumination window of approximately 1 cm2 on a skin area of the volar surface of the forearm at approximately 10 cm below the elbow. The AGE Reader then measures the amount of emitted light that is reflected back from the skin using a spectrometer and a 200-µm glass fiber. SAF is calculated as the ratio between emission and excitation and is expressed as arbitrary units (AU). Three measurements were conducted and the mean value of these was used for statistical analysis. The reference value of SAF for the age group of 60-70 years is 2.5±0.6 AU.

    Time frame: 6 months

Secondary outcomes

  1. Energy Intake at 6 Months.

    Energy (calorie) intake after 6 months of intensive dietetic advice and nutritional support.

    Time frame: 6 months

  2. Nutritional Status at 6 Months

    The 7-point scale Subjective Global Assessment (SGA, gold standard for nutritional status assessment in the dialysis population) was used to evaluate nutritional status at 6 months after intensive dietetic advice and nutritional support. The SGA score ranges from 1-7. Nutritional status can be classified into normal nutritional status (scores of 6 or 7), mild-moderate malnutrition (scores of 3-5), or severe malnutrition (scores of 1 or 2).

    Time frame: 6 months

  3. Dietary Advanced Glycation End-products (AGE) Intake at 6 Months

    Dietary AGE intake after 6 months of intensive dietetic advice and nutritional support

    Time frame: 6 months

  4. Protein Intake at 6 Months.

    Protein intake after 6 months of intensive dietetic advice and nutritional support.

    Time frame: 6 months

  5. Serum Albumin Levels at 6 Months

    Serum albumin levels after 6 months of intensive dietetic advice and nutritional support.

    Time frame: 6 months

  6. Handgrip Strength at 6 Months

    Handgrip strength after 6 months of intensive dietetic advice and nutritional support.

    Time frame: 6 months

Other outcomes

  1. Health-related Quality of Life, Short Form-36 Physical Component Score

    The Short Form-36 (SF-36) physical component score (PCS) was calculated after 6 months of intensive dietetic advice and nutritional support according to well-defined guidelines as follows: 1) recoding of 10 questions of the SF-36 survey; 2) calculation of raw scores for each of the eight health state domains of the SF-36 survey; 3) transformation of raw scores into a 0-100 scale; 4) standardisation of the transformed scales using a z-score transformation and the means and standard deviations from the general United Kingdom (UK) population; 5) calculation of the PCS by multiplying each scale z-score by their respective physical factor score coefficient and summing the eight products; and 6) the resulting sum is multiplied by 10 and added to 50 to linearly transform the PCS to the T-score metric, which has a mean of 50 and a standard deviation of 10 for the general UK population. A PCS above or below 50 is therefore indicative of better or worse physical health, respectively.

    Time frame: 6 months

  2. Health-related Quality of Life, Short Form-36 Mental Component Score

    The Short Form-36 (SF-36) mental component score (MCS) was calculated after 6 months of intensive dietetic advice and nutritional support according to well-defined guidelines as follows: 1) recoding of 10 questions of the SF-36 survey; 2) calculation of raw scores for each of the eight health state domains of the SF-36 survey; 3) transformation of raw scores into a 0-100 scale; 4) standardisation of the transformed scales using a z-score transformation and the means and standard deviations from the general United Kingdom (UK) population; 5) calculation of the MCS by multiplying each scale z-score by their respective mental factor score coefficient and summing the eight products; and 6) the resulting sum is multiplied by 10 and added to 50 to linearly transform the MCS to the T-score metric, which has a mean of 50 and a standard deviation of 10 for the general UK population. A MCS score above or below 50 is therefore indicative of better or worse mental health, respectively.

    Time frame: 6 months

  3. Health-related Quality of Life, European QoL-5 Dimensions (EQ5D) Health State Score (HSS)

    EQ5D HSS after 6 months of intensive dietetic advice and nutritional support. The HSS ranges from -0.285 (for the worst health state) to 1 (for the best health state).

    Time frame: 6 months

  4. Health-related Quality of Life, European QoL-5 Dimensions (EQ5D) Visual Analogue Score (VAS)

    EQ5D VAS after 6 months of intensive dietetic advice and support. The VAS uses a thermometer-like scale numbered from 0 to 100 to grade the current health status of individuals; the higher the VAS the better the health state.

    Time frame: 6 months

  5. Deaths/All-cause Mortality

    The total number of deaths during follow up was recorded at 6 months.

    Time frame: 6 months

07

Results

Posted Dec 10, 2024
Limitations and caveats
This was a single-centre proof of principle study. The number of participants was small and the follow-up period was relatively short. The results observed in this study may not be applicable to populations with dark skin colour (who were excluded from our study) because skin autofluorescence measurements cannot be performed in persons with darker skin colour because of the high absorption of the excitation light.

Participant flow

Study 1: Participant recruitment began in September 2016. All baseline data and measurements were collected and performed between September 2016 and August 2017. Once recruited, all participants were followed-up for up to five years. Study 2: Participant recruitment began in December 2017. All baseline data and measurements were collected and performed between December 2017 and June 2018. Once recruited, all participants were followed-up for up to 24 months.

Participant flow — Overall Study
MilestoneStudy 2 - Non Randomised Proof of Principle StudyHistorical Control Group From Study 1
Started3249
Completed2849
Not completed40

Outcome measures

PrimarySkin Autofluorescence Levels at 6 Months

Skin autolfuorescence (SAF) was measured after 6 months of intensive dietetic advice and nutritional support with a validated Autofluorescence Reader (AGE) Standard Unit (SU), version 2.4.3. The AGE Reader SU directs an ultraviolet excitation light through an illumination window of approximately 1 cm2 on a skin area of the volar surface of the forearm at approximately 10 cm below the elbow. The AGE Reader then measures the amount of emitted light that is reflected back from the skin using a spectrometer and a 200-µm glass fiber. SAF is calculated as the ratio between emission and excitation and is expressed as arbitrary units (AU). Three measurements were conducted and the mean value of these was used for statistical analysis. The reference value of SAF for the age group of 60-70 years is 2.5±0.6 AU.

Time frame:
6 months
Reported as:
Mean · Arbitrary units
Skin Autofluorescence Levels at 6 Months
Arbitrary unitsStudy 2 - Non Randomised Proof of Principle StudyHistorical Control Group From Study 1
Skin Autofluorescence Levels at 6 Months3.7 ± 0.73.8 ± 1.2
SecondaryEnergy Intake at 6 Months.

Energy (calorie) intake after 6 months of intensive dietetic advice and nutritional support.

Time frame:
6 months
Reported as:
Median · Kcal/kg/day
Energy Intake at 6 Months.
Kcal/kg/dayStudy 2 - Non Randomised Proof of Principle StudyHistorical Control Group From Study 1
Energy Intake at 6 Months.30.1 (24.9 to 35.9)18.9 (15.1 to 26.9)
SecondaryNutritional Status at 6 Months

The 7-point scale Subjective Global Assessment (SGA, gold standard for nutritional status assessment in the dialysis population) was used to evaluate nutritional status at 6 months after intensive dietetic advice and nutritional support. The SGA score ranges from 1-7. Nutritional status can be classified into normal nutritional status (scores of 6 or 7), mild-moderate malnutrition (scores of 3-5), or severe malnutrition (scores of 1 or 2).

Time frame:
6 months
Reported as:
Median · score on a scale
Nutritional Status at 6 Months
score on a scaleStudy 2 - Non Randomised Proof of Principle StudyHistorical Control Group From Study 1
Nutritional Status at 6 Months5.0 (5.0 to 6.0)5.0 (3.0 to 7.0)
SecondaryDietary Advanced Glycation End-products (AGE) Intake at 6 Months

Dietary AGE intake after 6 months of intensive dietetic advice and nutritional support

Time frame:
6 months
Reported as:
Median · Kilounits/day
Dietary Advanced Glycation End-products (AGE) Intake at 6 Months
Kilounits/dayStudy 2 - Non Randomised Proof of Principle StudyHistorical Control Group From Study 1
Dietary Advanced Glycation End-products (AGE) Intake at 6 Months19074 (13372 to 27340)14697 (9427 to 19071)
SecondaryProtein Intake at 6 Months.

Protein intake after 6 months of intensive dietetic advice and nutritional support.

Time frame:
6 months
Reported as:
Median · g/kg/day
Protein Intake at 6 Months.
g/kg/dayStudy 2 - Non Randomised Proof of Principle StudyHistorical Control Group From Study 1
Protein Intake at 6 Months.1.1 (0.8 to 1.2)0.8 (0.6 to 1.0)
SecondarySerum Albumin Levels at 6 Months

Serum albumin levels after 6 months of intensive dietetic advice and nutritional support.

Time frame:
6 months
Reported as:
Median · g/L
Serum Albumin Levels at 6 Months
g/LStudy 2 - Non Randomised Proof of Principle StudyHistorical Control Group From Study 1
Serum Albumin Levels at 6 Months31.5 (30.0 to 34.0)31.0 (27.0 to 34.5)
SecondaryHandgrip Strength at 6 Months

Handgrip strength after 6 months of intensive dietetic advice and nutritional support.

Time frame:
6 months
Reported as:
Median · kg
Handgrip Strength at 6 Months
kgStudy 2 - Non Randomised Proof of Principle StudyHistorical Control Group From Study 1
Handgrip Strength at 6 Months16.7 (10.6 to 24.7)18.3 (12.4 to 26.3)
Other pre-specifiedHealth-related Quality of Life, Short Form-36 Physical Component Score

The Short Form-36 (SF-36) physical component score (PCS) was calculated after 6 months of intensive dietetic advice and nutritional support according to well-defined guidelines as follows: 1) recoding of 10 questions of the SF-36 survey; 2) calculation of raw scores for each of the eight health state domains of the SF-36 survey; 3) transformation of raw scores into a 0-100 scale; 4) standardisation of the transformed scales using a z-score transformation and the means and standard deviations from the general United Kingdom (UK) population; 5) calculation of the PCS by multiplying each scale z-score by their respective physical factor score coefficient and summing the eight products; and 6) the resulting sum is multiplied by 10 and added to 50 to linearly transform the PCS to the T-score metric, which has a mean of 50 and a standard deviation of 10 for the general UK population. A PCS above or below 50 is therefore indicative of better or worse physical health, respectively.

Time frame:
6 months
Reported as:
Median · score on a scale
Health-related Quality of Life, Short Form-36 Physical Component Score
score on a scaleStudy 2 - Non Randomised Proof of Principle StudyHistorical Control Group From Study 1
Health-related Quality of Life, Short Form-36 Physical Component Score17.2 (8.1 to 26.9)15.9 (10.4 to 22.8)
Other pre-specifiedHealth-related Quality of Life, Short Form-36 Mental Component Score

The Short Form-36 (SF-36) mental component score (MCS) was calculated after 6 months of intensive dietetic advice and nutritional support according to well-defined guidelines as follows: 1) recoding of 10 questions of the SF-36 survey; 2) calculation of raw scores for each of the eight health state domains of the SF-36 survey; 3) transformation of raw scores into a 0-100 scale; 4) standardisation of the transformed scales using a z-score transformation and the means and standard deviations from the general United Kingdom (UK) population; 5) calculation of the MCS by multiplying each scale z-score by their respective mental factor score coefficient and summing the eight products; and 6) the resulting sum is multiplied by 10 and added to 50 to linearly transform the MCS to the T-score metric, which has a mean of 50 and a standard deviation of 10 for the general UK population. A MCS score above or below 50 is therefore indicative of better or worse mental health, respectively.

Time frame:
6 months
Reported as:
Median · score on a scale
Health-related Quality of Life, Short Form-36 Mental Component Score
score on a scaleStudy 2 - Non Randomised Proof of Principle StudyHistorical Control Group From Study 1
Health-related Quality of Life, Short Form-36 Mental Component Score47.5 (38.5 to 57.3)41.6 (30.6 to 49.9)
Other pre-specifiedHealth-related Quality of Life, European QoL-5 Dimensions (EQ5D) Health State Score (HSS)

EQ5D HSS after 6 months of intensive dietetic advice and nutritional support. The HSS ranges from -0.285 (for the worst health state) to 1 (for the best health state).

Time frame:
6 months
Reported as:
Median · score on a scale
Health-related Quality of Life, European QoL-5 Dimensions (EQ5D) Health State Score (HSS)
score on a scaleStudy 2 - Non Randomised Proof of Principle StudyHistorical Control Group From Study 1
Health-related Quality of Life, European QoL-5 Dimensions (EQ5D) Health State Score (HSS)0.485 (0.297 to 0.741)0.470 (0.198 to 0.699)
Other pre-specifiedHealth-related Quality of Life, European QoL-5 Dimensions (EQ5D) Visual Analogue Score (VAS)

EQ5D VAS after 6 months of intensive dietetic advice and support. The VAS uses a thermometer-like scale numbered from 0 to 100 to grade the current health status of individuals; the higher the VAS the better the health state.

Time frame:
6 months
Reported as:
Median · score on a scale
Health-related Quality of Life, European QoL-5 Dimensions (EQ5D) Visual Analogue Score (VAS)
score on a scaleStudy 2 - Non Randomised Proof of Principle StudyHistorical Control Group From Study 1
Health-related Quality of Life, European QoL-5 Dimensions (EQ5D) Visual Analogue Score (VAS)45 (27 to 60)50 (25 to 69)
Other pre-specifiedDeaths/All-cause Mortality

The total number of deaths during follow up was recorded at 6 months.

Time frame:
6 months
Reported as:
Number · participants
Deaths/All-cause Mortality
participantsStudy 2 - Non Randomised Proof of Principle StudyHistorical Control Group From Study 1
Deaths/All-cause Mortality35

Adverse events

Collected over The occurrence of an adverse event as a result of participation within this study was not expected and as such no adverse event data was collected.. Non-serious events are listed at a 0% frequency threshold.

Adverse event summary by group
GroupDeathsSeriousOther
Study 2———
Historical Control Group———

Baseline characteristics

Age, Continuous
Age, Continuous(years)Study 2Historical Control Group - Study 1Total
Median65 (56 to 74)63 (53 to 75)64 (54.5 to 74.5)
Sex: Female, Male
Sex: Female, Male(Participants)Study 2Historical Control Group - Study 1Total
Female142640
Male142337
Race (NIH/OMB)
Race (NIH/OMB)(Participants)Study 2Historical Control Group - Study 1Total
American Indian or Alaska Native000
Asian000
Native Hawaiian or Other Pacific Islander000
Black or African American000
White244367
More than one race4610
Unknown or Not Reported000
Serum albumin
Serum albumin(g/L)Study 2Historical Control Group - Study 1Total
Median30.0 (26.0 to 33.0)32.0 (27.0 to 34.0)31.0 (26.5 to 33.5)
Dietary AGE intake
Dietary AGE intake(Kilounits/day)Study 2Historical Control Group - Study 1Total
Median13823 (10840 to 20441)11940 (8787 to 15833)12882 (9814 to 18137)
Energy intake
Energy intake(kcal/kg/day)Study 2Historical Control Group - Study 1Total
Median20.9 (16.6 to 27.3)17.9 (13.5 to 21.7)19.4 (15.1 to 24.5)
Protein intake
Protein intake(g/kg/day)Study 2Historical Control Group - Study 1Total
Median0.7 (0.6 to 1.1)0.8 (0.6 to 1.0)0.75 (0.6 to 1.05)
Skin autofluorescence
Skin autofluorescence(Arbitrary units)Study 2Historical Control Group - Study 1Total
Mean3.8 ± 0.73.5 ± 0.93.7 ± 0.8

1 further baseline measures are reported on the registry.

08

Study locations

1 site
  • Derby Hospitals NHS Foundation Trust
    Derby, Derbyshire DE22 3NE, United Kingdom
09

References and documents

Publications

  • Arsov S, Graaff R, van Oeveren W, Stegmayr B, Sikole A, Rakhorst G, Smit AJ. Advanced glycation end-products and skin autofluorescence in end-stage renal disease: a review. Clin Chem Lab Med. 2014 Jan 1;52(1):11-20. doi: 10.1515/cclm-2012-0832. PubMed 23612551 ↗
  • Darlene, A., Dartt Reza, D. and D'Amore, P. (2011) Immunology, inflammation and diseases of the eye. Elsevier Press: pp. 287-288.
  • Graaff R, Arsov S, Ramsauer B, Koetsier M, Sundvall N, Engels GE, Sikole A, Lundberg L, Rakhorst G, Stegmayr B. Skin and plasma autofluorescence during hemodialysis: a pilot study. Artif Organs. 2014 Jun;38(6):515-8. doi: 10.1111/aor.12205. Epub 2013 Oct 29. PubMed 24164288 ↗
  • Hartog JW, Voors AA, Schalkwijk CG, Scheijen J, Smilde TD, Damman K, Bakker SJ, Smit AJ, van Veldhuisen DJ. Clinical and prognostic value of advanced glycation end-products in chronic heart failure. Eur Heart J. 2007 Dec;28(23):2879-85. doi: 10.1093/eurheartj/ehm486. Epub 2007 Nov 5. PubMed 17986469 ↗
  • Ishibashi T, Murata T, Hangai M, Nagai R, Horiuchi S, Lopez PF, Hinton DR, Ryan SJ. Advanced glycation end products in age-related macular degeneration. Arch Ophthalmol. 1998 Dec;116(12):1629-32. doi: 10.1001/archopht.116.12.1629. PubMed 9869793 ↗
  • Junaid Nazar CM, Kindratt TB, Ahmad SM, Ahmed M, Anderson J. Barriers to the successful practice of chronic kidney diseases at the primary health care level; a systematic review. J Renal Inj Prev. 2014 Jul 1;3(3):61-7. doi: 10.12861/jrip.2014.20. eCollection 2014. PubMed 25340171 ↗
  • Kandarakis SA, Piperi C, Topouzis F, Papavassiliou AG. Emerging role of advanced glycation-end products (AGEs) in the pathobiology of eye diseases. Prog Retin Eye Res. 2014 Sep;42:85-102. doi: 10.1016/j.preteyeres.2014.05.002. Epub 2014 Jun 4. PubMed 24905859 ↗
  • Kellow NJ, Savige GS. Dietary advanced glycation end-product restriction for the attenuation of insulin resistance, oxidative stress and endothelial dysfunction: a systematic review. Eur J Clin Nutr. 2013 Mar;67(3):239-48. doi: 10.1038/ejcn.2012.220. Epub 2013 Jan 30. PubMed 23361161 ↗
  • Kidney Disease: Improving Global Outcomes (KDIGO) CKD Work Group (2013). KDIGO 2012 Clinical practice guideline for the evaluation and management of chronic kidney disease. Kidney Int 4(Suppl. 3): pp. 1-150.
  • Kimura H, Tanaka K, Kanno M, Watanabe K, Hayashi Y, Asahi K, Suzuki H, Sato K, Sakaue M, Terawaki H, Nakayama M, Miyata T, Watanabe T. Skin autofluorescence predicts cardiovascular mortality in patients on chronic hemodialysis. Ther Apher Dial. 2014 Oct;18(5):461-7. doi: 10.1111/1744-9987.12160. Epub 2014 Jan 24. PubMed 24456287 ↗
  • McIntyre NJ, Chesterton LJ, John SG, Jefferies HJ, Burton JO, Taal MW, Fluck RJ, McIntyre CW. Tissue-advanced glycation end product concentration in dialysis patients. Clin J Am Soc Nephrol. 2010 Jan;5(1):51-5. doi: 10.2215/CJN.05350709. Epub 2009 Nov 5. PubMed 19965551 ↗
  • Nongnuch A, Davenport A. The effect of vegetarian diet on skin autofluorescence measurements in haemodialysis patients. Br J Nutr. 2015 Apr 14;113(7):1040-3. doi: 10.1017/S0007114515000379. Epub 2015 Mar 12. PubMed 25761438 ↗
  • Oleniuc M, Schiller A, Secara I, Onofriescu M, Hogas S, Apetrii M, Siriopol D, Covic A. Evaluation of advanced glycation end products accumulation, using skin autofluorescence, in CKD and dialysis patients. Int Urol Nephrol. 2012 Oct;44(5):1441-9. doi: 10.1007/s11255-011-0097-5. Epub 2011 Dec 10. PubMed 22160646 ↗
  • Siriopol D, Hogas S, Veisa G, Mititiuc I, Volovat C, Apetrii M, Onofriescu M, Busila I, Oleniuc M, Covic A. Tissue advanced glycation end products (AGEs), measured by skin autofluorescence, predict mortality in peritoneal dialysis. Int Urol Nephrol. 2015 Mar;47(3):563-9. doi: 10.1007/s11255-014-0870-3. Epub 2014 Nov 26. PubMed 25425437 ↗
  • Smit AJ, Gerrits EG. Skin autofluorescence as a measure of advanced glycation endproduct deposition: a novel risk marker in chronic kidney disease. Curr Opin Nephrol Hypertens. 2010 Nov;19(6):527-33. doi: 10.1097/MNH.0b013e32833e9259. PubMed 20844429 ↗
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  • Singh VP, Bali A, Singh N, Jaggi AS. Advanced glycation end products and diabetic complications. Korean J Physiol Pharmacol. 2014 Feb;18(1):1-14. doi: 10.4196/kjpp.2014.18.1.1. Epub 2014 Feb 13. PubMed 24634591 ↗
  • Zhang QL, Rothenbacher D. Prevalence of chronic kidney disease in population-based studies: systematic review. BMC Public Health. 2008 Apr 11;8:117. doi: 10.1186/1471-2458-8-117. PubMed 18405348 ↗
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Study documents

  • Protocol and statistical analysis plan · Oct 4, 2017

Documents are hosted by the registry — open the source record to download them.

Individual participant data

Plan to share: No

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Updates

Tracking since Sep 25, 2026
No changes since tracking began. The registry record was last updated on Dec 10, 2024, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
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Registry details

Key details

Study ID
NCT02878317
Lead sponsor
University of Nottingham
Collaborators
University Hospitals of Derby and Burton NHS Foundation Trust
Responsible party
Sponsor
First posted
Aug 25, 2016
Start date
Sep 21, 2016
Primary completion
Mar 31, 2022
Completion
Mar 31, 2022
Results posted
Dec 10, 2024
Last update
Dec 10, 2024

Study contacts

Maarten Taal, Doctor
study director · University Hospitals of Derby and Burton NHS Foundation Trust

Oversight

Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

Not currently enrolling

This study is completed, as verified in Jun 2024. You cannot join it, but the record below documents what was studied.

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