Health-Related Quality of Life Impacts Mortality but Not Progression to End-Stage Renal Disease in Pre-Dialysis Chronic Kidney Disease: A Prospective Observational Study
Health-Related Quality of Life Impacts Mortality but Not Progression to End-Stage Renal Disease in Pre-Dialysis Chronic Kidney Disease: A Prospective Observational Study
Mark D. Jesky 0 1 2 3
Mary Dutton 0 1 2 3
Indranil Dasgupta 0 1 3
Punit Yadav 0 1 2 3
Khai Ping Ng 0 1 2 3
Anthony Fenton 0 1 2 3
Derek Kyte 0 1 3
Charles J. Ferro 0 1 2 3
Melanie Calvert 0 1 3
Paul Cockwell 0 1 2 3
Stephanie J. Stringer 0 1 2 3
0 Funding: The study is supported by JABBS Foundation (Birmingham , United Kingdom) (URL:
1 Data Availability Statement: Data are available upon request. The data restriction is enforced by the NRES Committee West Midlands - South Birmingham (contact person: Penelope Gregory , Rec Manager, NRESCommittee.westmidlands-
2 Department of Renal Medicine, University Hospitals Birmingham NHS Foundation Trust , Birmingham , United Kingdom , 2 Institute of Translational Medicine, College of Medical and Dental Sciences, University of Birmingham , Birmingham , United Kingdom , 3 Renal Unit, Heart of England NHS Foundation Trust , Birmingham , United Kingdom , 4 Institute of Cardiovascular Sciences, College of Medical and Dental Sciences, University of Birmingham , Birmingham , United Kingdom , 5 Institute of Applied Health Research, College of Medical and Dental Sciences, University of Birmingham , Birmingham , United Kingdom
3 Editor: Tatsuo Shimosawa, The University of Tokyo , JAPAN
Chronic kidney disease (CKD) is associated with reduced health-related quality of life (HRQL). However, the relationship between pre-dialysis CKD, HRQL and clinical outcomes, including mortality and progression to end-stage renal disease (ESRD) is unclear.
All 745 participants recruited into the Renal Impairment In Secondary Care study to end
March 2014 were included. Demographic, clinical and laboratory data were collected at
baseline including an assessment of HRQL using the Euroqol EQ-5D-3L. Health states
were converted into an EQ-5Dindex score using a set of weighted preferences specific to the
UK population. Multivariable Cox proportional hazards regression and competing risk analyses were undertaken to evaluate the association of HRQL with progression to ESRD or allcause mortality. Regression analyses were then performed to identify variables associated with the significant HRQL components.
Median eGFR was 25.8 ml/min/1.73 m2 (IQR 19.6±33.7ml/min) and median ACR was 33
mg/mmol (IQR 6.6±130.3 mg/mmol). Five hundred and fifty five participants (75.7%)
reported problems with one or more EQ-5D domains. When adjusted for age, gender,
comorbidity, eGFR and ACR, both reported problems with self-care [hazard ratio 2.542,
95% confidence interval 1.222±5.286, p = 0.013] and reduced EQ-5Dindex score [hazard
ratio 0.283, 95% confidence interval 0.099±0.810, p = 0.019] were significantly associated
The Queen Elizabeth Hospital Birmingham Charity
Competing Interests: Melanie Calvert has received
consultancy fees from Astellas and Ferring Pharma
outside the submitted work and has received
research funding from the Health Foundation
focused on Chronic Kidney Disease. This does not
alter our adherence to PLOS ONE policies on
sharing data and materials.
with an increase in all-cause mortality. Similar findings were observed for competing risk
analyses. Reduced HRQL was not a risk factor for progression to ESRD in multivariable
Impaired HRQL is common in the pre-dialysis CKD population. Reduced HRQL, as demon
strated by problems with self-care or a lower EQ-5Dindex score, is associated with a higher
risk for death but not ESRD. Multiple factors influence these aspects of HRQL but renal
function, as measured by eGFR and ACR, are not among them.
Chronic kidney disease (CKD) affects up to one in seven adults [1±3] and is associated with an
increased risk of all-cause and cardiovascular mortality, and end-stage renal disease (ESRD)
]. There is increasing evidence of an association between pre-dialysis CKD and impaired
health-related quality of life (HRQL) as assessed by a variety of patient reported outcome
measures (PROMs) [6±9].
HRQL can be assessed using disease specific or generic instruments. The use of different
PROMs within different populations to evaluate HRQL means that it is difficult to assess the
relevance of the results reported. Furthermore, there are limited quantifiable data on the
relationship between HRQL scores and clinical outcomes, including mortality and progression to
ESRD. Previous studies have either been small, investigating these outcomes in a Taiwanese
], or have focused on individuals of black ethnicity with hypertensive CKD in
the United States [
]. A recently published study investigated the impact of HRQL using a
kidney disease specific tool (KDQOL-36) and found that low HRQL was independently
association with CV events and death, but not CKD progression [
A systematic review of PROMs used in CKD supported the use of preference-based utility
measures, favouring the EuroQol, EQ-5D due to ease of use for patients and for the ability to
derive utility values for health economic evaluation [
To date, there have been few studies investigating the relationship between pre-dialysis
CKD and HRQL as measured by EQ-5D [6±8], and no studies examining the relationship
between EQ-5D scores and clinical outcomes. To address this we evaluated HRQL within a
large prospective cohort study of pre-dialysis CKD, where EQ-5D was collected at recruitment,
to assess the relationship between HRQL and CKD stage, and the impact of HRQL on risk of
death or progression to ESRD.
Materials and Methods
The Renal Impairment In Secondary Care (RIISC) study (NCT01722383) was approved by
South Birmingham Research Ethics Committee (reference: 10/H1207/6). Patient recruitment
commenced in October 2010, the methodology utilised has been described in detail elsewhere
In brief, RIISC is a two-centre, United Kingdom based, prospective observational cohort
study with the aim of assessing determinants of long-term outcomes in patients with high risk
CKD. Inclusion criteria comprised patients with pre-dialysis CKD who fulfilled criteria for
secondary care follow-up as defined by the UK National Institute for Health and Care
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Excellence (NICE) 2008 CKD guidelines [
] (an MDRD eGFR below 30ml/min/1.73m2 or an
eGFR 30-59ml/min/1.73m2 with either decline of 5 mls/min/1.73m2/year or 10 mls/min/
1.73m2/5 years or an urinary albumin creatinine ratio (ACR) 70 mg/mmol on three
occasions) and therefore are considered at high risk of progression to ESRD. Individuals requiring
immunosuppression for immune-mediated renal disease, or who had commenced renal
replacement therapy (RRT), were not eligible for recruitment All patients provided written
consent and the study was conducted in accordance with the Declaration of Helsinki.
The patients consented for follow-up for ten years from recruitment. Blood and urine
samples were collected and processed according to pre-defined standard operating procedures and
stored at -80ÊC until analysis [
]. Patient mortality was captured through linkage between
electronic patient records and the Office of National Statistics, which collects information on
all registered deaths in the United Kingdom. Progression to ESRD was defined as the initiation
of RRT (chronic dialysis or renal transplantation).
Reporting of the study conforms to the STROBE statement for reporting of observational
Quality of life
Data were collected from participants using the EQ-5D-3L (abbreviated to EQ-5D throughout
this manuscript). This is a validated, generic preference-based measure of health status that
comprises a 5-question multi-attribute questionnaire and a visual analogue self-rating scale
]. Respondents were asked to rate severity of their current problems (level 1 = no
problems, level 2 = some/moderate problems, level 3 = severe/extreme problems) for five
dimensions of health: mobility, self-care, usual activities, pain/discomfort, and
anxiety/depression). Health states were converted into an EQ-5Dindex score ranging from −0.594 to 1.0
(where 1 is full health and lower values indicate worse HRQL) using a set of weighted
preferences produced from the UK population [
]. The EQ VAS asks respondents to rate their own
health state relative to full health (score = 100) or worst imaginable health state (score = 0).
Socio-economic status (SES) was assessed using the Index of Multiple Deprivation (IMD
]; an individual was assigned a score and rank according to their postcode; lower
scores and ranks indicated greater deprivation. The IMD has been validated as superior to
traditional deprivation indices such as the Townsend score due to its use of multiple domains
reflective of socioeconomic deprivation [
Educational attainment was defined by established UK education milestones (no formal
qualifications, GCSE/O'Level, NVQ, A'Level, undergraduate, post-graduate). Current
employment status was subdivided into the following categories: in employment, unemployed or
retired. Individuals were then asked to state the occupation category best describing their
current or last employment.
Demographic, Clinical and Laboratory Variables
Demographic factors included in the analysis comprised: age, gender, ethnicity, SES (the most
deprived IMD quintile was compared to the other four quintiles combined), educational
attainment, current employment status, smoking history, and alcohol consumption.
Clinical factors comprised comorbidity, presented by individual comorbidity (malignancy,
diabetes mellitus, chronic obstructive airways disease, cerebrovascular disease, ischaemic heart
disease and peripheral vascular disease) and Charlson Comorbidity Index (CCI) [
factors included body mass index (BMI), and blood pressure. Laboratory measurements
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comprised kidney function (MDRD eGFR corrected for ethnicity [
] and ACR),
haemoglobin, acidaemia (serum bicarbonate), serum albumin, and C-reactive protein (CRP).
Brachial blood pressure (BP) was measured using the BpTRU fully automated and validated
sphygmomanometer (BpTRU Medical Devices, Coquitlam, BC, Canada), which obtained a
series of six BP readings at one-minute intervals following a five-minute rest period. Mean BP
was derived from the average of the second to sixth BP reading. This average reading has been
reported as comparable to mean daytime BP from 24 hour ambulatory BP monitoring [
Biochemistry results from the clinical laboratory were obtained from tests performed in
accordance with the current standard of care. CRP was measured using the Full Range
C-Reactive Protein Kit on a SPA™ automated PLUS turbidimeter (The Binding Site Group Ltd,
Analyses were performed using Stata 13.1 (Statacorp, College Station, Texas, USA).
Descriptive statistics. Descriptive statistics are presented as a complete cohort. Data are
presented as mean with standard deviation (SD) or median with interquartile range (IQR)
depending on distribution. Continuous variables were compared using ANOVA (parametric
distribution) or Kruskal-Wallis (non-parametric distribution). Categorical variables were
compared using chi-squared tests. Statistical significance was defined as a two-tailed p-value
Survival Analyses. Cox proportional hazard analyses (Stata command stcox) were
performed for end-points of death and ESRD (censor date March 2014). The proportionality
assumption was assessed using log-log plots. Data are presented using hazard ratios (HR])
with 95% confidence intervals (CI), p-values and survival plots.
Individual constituents of the EQ-5D were analysed (univariable analyses). Any
components demonstrating p<0.1 were then included in multivariable analyses together with a priori
variables (age, gender, comorbidity assessed by CCI, eGFR and ACR).
Competing Risk Analyses. Survival analyses, by their nature, use time-to-event data [
In this study we investigated two events (end-points): death and progression to ESRD. Survival
analyses including Cox proportional hazard analyses treat all censored events as
`uninformative'; that is to say a patient being censored due to reaching the end of their follow up or due to
another end-point (death in the case of ESRD or vice-versa) are treated equally. As these other
events are of clinical significance and of statistical importance; someone who has died will
never reach ESRD [
]. Therefore, in order to incorporate this into analyses, we carried out
competing risk analyses according to the method described by Fine and Gray [
Regression analyses to assess the impact of demographic, clinical and laboratory
variables on HRQL. Logistic regression was performed to analyse the relationship between
problems in each of the five domains with clinical, demographic and laboratory variables using
dichotomised data (patients with moderate and severe problems in a domain were combined
and compared to those with no problems). Odds ratios with 95% CI and two-tailed p-values
Linear regression was utilised for the calculated EQ-5Dindex score and the EQ VAS
(coefficient with 95% CI and p-value). Residual plots were evaluated to determine appropriateness of
linear regression models.
Data were entered into multivariable analyses if p<0.1 and a backwards selection model
performed until remaining variables had a p<0.05. Goodness-of-fit is indicated by pseudo R2
(logistic regression) or R2 (linear regression) values.
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Fig 1. Flow diagram of the participants in the study. ESRDÐEnd-stage renal disease.
All participants recruited to end March 2014 (n = 745) were included in the study. Fig 1
indicates the number of individuals at each stage of evaluation. Baseline demographic, clinical and
laboratory data are shown in Table 1 (see S1 Table for data split by CKD stage). Median age at
recruitment was 64 years (IQR 50±76 years) and 60.8% were male. The proportion of male
participants decreased with lower CKD stage (p = 0.045). 68.1% were of white ethnicity, 20.1%
south-Asian, 9.4% black ethnicity, and 2.4% from other ethnic groups. There was a borderline
difference in ethnicity by CKD stage (p = 0.052).
46.3% of participants were in the most deprived quintile nationally (IMD 2010). No
difference in SES was seen when analysed by CKD stage for IMD score (p = 0.517) or comparing the
percentage in the most deprived quintile (p = 0.351). Comorbidity was common and increased
with advancing CKD stage, both as assessed by individual comorbidities and the CCI
(p = 0.007; age adjusted CCI p<0.001).
Table 2 illustrates the study population by Kidney Disease Improving Global Outcomes
(KDIGO) classification [
]. Median eGFR was 25.8 ml/min/1.73 m2 (IQR 19.6±33.7ml/min)
and Median ACR was 33 mg/mmol (IQR 6.6±130.3 mg/mmol).
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Cohort (n = 745)
Cohort (n = 745)
Complete HRQL data were available for 733 participants (98.4%). Proportions of individuals
reporting problems with each of the five domains are shown in Fig 2. One hundred and
seventy eight participants (24.3%) reported no problems within any domain. Problems with one,
two, three, four and five domains were reported by 136 (18.6%), 129 (17.6%), 153 (20.9%), 91
(12.4%) and 46 (6.3%) participants, respectively.
Associations between HRQL and CKD
As illustrated in Fig 2, statistically significant differences between CKD stages were seen in the
mobility (p = 0.001) and usual activity (p = 0.002) domains, with more problems reported with
a worse CKD stage. No significant difference was found between CKD stages and the other
Only a small number of participants described problems in the unable/severe category,
therefore data were dichotomised to combine the respondents who reported moderate
problems with those in the severe or unable category.
Fig 2. Reported HRQL Problems by EQ-5D domain. Data presented as whole cohort (All) and catagorised by CKD stage (determined
by MDRD eGFR). * p-value for chi-squared test comparing CKD stage to reported problems for each EQ-5D-3L domain.
Health related quality of life for the EQ VAS and calculated EQ-5Dindex score are shown in
Table 3. The EQ-5Dindex score decreased (worsened) with more advanced CKD stage
(p = 0.017). No significant difference was seen between CKD stage and the EQ VAS.
Association between HRQL and Clinical end-points
Death. By March 24th 2014, 46 (6.2%) participants had died. Univariable cox regression
analysis demonstrated that reported problems with mobility, self-care (Fig 3), usual, lower
EQ5Dindex score, and lower EQ VAS, were all associated with an increased risk of death. Table 4
indicates univariable cox regression analyses for a priori variables and EQ-5D components.
In multivariable analysis, each significant EQ-5D variable was combined with age, gender,
comorbidity assessed by CCI, eGFR and ACR. Self-care (HR 2.542, 95% CI 1.222±5.286,
EQ-5D Index Score
Visual Analogue Scale
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Fig 3. Cox Proportional Hazards Regression for reported problems with self-care and death. Univariable Analyses.
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Fig 4. Cox Proportional Hazards Regression for reported problems with self-care and death. Multivariable Analyses.
Covariates included age, gender, Comorbidity (assessed by Charlson Comorbidity Index) and renal function (eGFR and ACR).
p = 0.013, Fig 4, Table 5) and the EQ-5Dindex score (HR 0.283, 95% CI 0.099±0.810, p = 0.019,
Table 5) were independently associated with an increased risk of death. Fourteen out of 102
(13.7%) participants who reported problems with self-care died compared to 32/641 (5.0%)
participants who reported no problems (chi-squared p = 0.001).
To adjust the HR associated for death for the competing end-point of ESRD, a competing
risk analysis was performed. Problems with self-care (sub-distribution hazard ratio [SHR]
2.608, 95% CI 1.260±5.597, p = 0.01) and a lower EQ-5Dindex score (SHR 0.317, 95% CI 0.105±
0.958, p = 0.042) remained significant in the multivariable analysis with age, gender,
comorbidity, eGFR and ACR (Table 5).
These analyses also identify increasing age, comorbidity and higher ACR as being
associated with death. Estimated GFR was not significant; however a creatinine greater than
265 μmol/L (3mg/dL) scores 2 points in the CCI. Reanalysing the data for the CCI without the
renal disease points results in eGFR demonstrating significance in Cox regression but not
competing risk analyses (see S2 Table).
End-Stage Renal Disease. Seventy-eight participants (10.5%) had reached ESRD by the
censor date. Lower EQ VAS score was the only component of the EQ-5D associated with an
increased HR for progression to ESRD (Table 6). Significance was lost when age, gender,
comorbidity, eGFR and ACR were included in a multivariable analysis. Similarly, competing
risk analysis indicated an association with a lower VAS and ESRD in univariable but not
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Identi®ed problem with self care
Age (per 10 year increase)
Gender (female as reference)
Charlson Comorbidity Index
eGFR (per 5ml/min increase)
ACR (per 10mg/mmol rise)
EQ-5D index score
Age (per 10 year increase)
Gender (female as reference)
Charlson Comorbidity Index
eGFR (per 5ml/min increase)
ACR (per 10mg/mmol rise)
The impact of demographic, clinical and laboratory variables on HRQL
The analyses above demonstrate the two HRQL factors associated with death in the survival
analyses were problems with self-care and a lower EQ-5Dindex score. In order to explore factors
predictive of these two elements, further exploratory analyses were performed for self-care
(logistic regression) and the EQ-5Dindex score (linear regression).
Self-care. Table 7 shows the factors that were associated with (p<0.1) reported problems
Ethnicity classified as other or not stated, people who were not currently working, higher
BMI, higher bicarbonate concentration, and higher CRP were statistically significantly
associated with reported problems with self-care in multivariable analysis (Table 7). This model
explained 16.5% of variability with self-care (pseudo R2 0.165). Of note, age and renal function
did not influence this aspect of HRQL.
EQ-5Dindex score. Table 8 shows factors (p<0.1) associated with a higher EQ-5D score
(i.e. better HRQL).
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Multivariable analysis found the following variables remained associated with better
HRQL: male gender; currently in employment; not smoking in comparison to current
smoking; lower BMI; less comorbidity; and lower CRP (Table 8). This linear regression model
explained 20.8% of the variability in HRQL as assessed by the EQ-5Dindex score (adjusted R2
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0.208). Again age and renal function were not associated with this assessment of overall
The relationship between pre-dialysis CKD, HRQL and clinical outcomes is an important
aspect of nephrology practice. Our study, conducted in a cohort of people with advanced and/
or progressive CKD, demonstrated that reported problems with HRQL, as measured by the
EQ-5D, were common; only 24.3% of participants reported no problem in any EQ-5D
Impaired HRQL was a risk factor for death; problems with self-care and overall HRQL,
assessed by the EQ-5Dindex score, were associated with an increased HR for death when
analysed with age, gender, comorbidity, eGFR and ACR. This association was present in both cox
proportional hazard regression and competing risk regression (with ESRD as the competing
risk). No element of HRQL was independently associated with risk of progression to ESRD.
Until recently, previous studies investigating HRQL in patients with pre-dialysis CKD had
focused on specific populations (Taiwanese [
] or individuals of black ethnicity with
hypertensive CKD in the United States [
]). Whilst the generalizability of these studies to a
multiethnic United Kingdom CKD population is questionable, both studies identified an association
with HRQL and death in similarity to our study. However, the association with HRQL and
CKD progression was conflicting; Tsai and colleagues identified an association [
] but Porter
and colleagues only noted an association in a composite of death and CKD progression [
A combined analysis of the Chronic Renal Insufficiency Cohort and Hispanic Chronic
Renal Insufficiency Cohort has recently been published [
]. 3837 patients (of a total of 3939
enrolled) completed the disease specific KDQOL-36 questionnaire. Consistent with our study,
they found that low HRQL was independently associated with a higher risk of death but not
CKD progression in several KDQOL-36 subscales (physical component summary, mental
component subscale, effects and symptoms). The KDQOL-36 questionnaire is a detailed
HRQL survey based on a chronic disease core, with added items relevant to patients with
kidney disease [
]. Compared to the EQ-5D, it is more time consuming to complete, has some
components that apply more to those undergoing RRT than the pre-dialysis population, and
its utility in health economic evaluations is not as established.
To explore further the factors that influence the components of HRQL associated with
death (self-care and the EQ-5Dindex score), we assessed the relationship between these
components and demographic, clinical and laboratory variables utilizing regression analysis. Not
being currently employed, whether young and not working or retired, conveyed the highest
HR associated with impaired HRQL. Other significant factors for a lower HRQL included
higher BMI, a higher CRP, and multimorbidity. Further research is warranted.
Interestingly, we did not identify an association between these aspects of HRQL and SES,
increasing age of the participants or renal function, as measured by eGFR or ACR. This lack of
association between HRQL and renal function, is a finding variably supported by previous
7, 31, 32
As we, and others, have demonstrated, reported problems with HRQL are common in this
] and we have found an association between impaired HRQL and death. It is
therefore important to consider what strategies could be used to improve HRQL; improving
HRQL will not only improve patient well-being but may convey a survival advantage. Previous
studies have demonstrated that optimisation of haemoglobin, psychological interventions and
physical exercise may be of benefit [33±35]. However, the majority of these studies have
focused on patients who have reached ESRD rather than pre-dialysis CKD. Therefore, the
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transferability of these, or of interventions instigated for other chronic disease states, requires
In this study of patients with pre-dialysis CKD, problems with self-care and the EQ-5Dindex
] were both of prognostic significance; in clinical practice problems with self-care
may be the more useful HRQL screening question to identify patients with CKD at an
increased risk of death. This could then direct social care resources towards these patients and
ensure that appropriate time is allocated so that patients are adequately supported when
counselled about their higher mortality risk. It may also enable identification of a high-risk group
where interventions to improve outcomes can be studied.
Strengths and Weaknesses
The major strength of this study is the use of a prospectively recruited, socio-economically and
ethnically diverse cohort of patients with advanced and/or progressive pre-dialysis dependent
CKD. Detailed demographic and clinical data were collected at initial recruitment and the
participants were tracked longitudinally to record outcomes, including death and ESRD. HRQL
was assessed by the EQ-5D tool, which is recommended as the preference based measure for
HRQL evaluation in CKD [
]. Survival analyses were performed using both Cox proportional
hazard analyses and competing risk analyses. The latter is important, though rarely used, as it
enabled the competing risk of ESRD to be taken into account when assessing death and vice
versa: both end-points are (separately) of key interest to patients, their families and clinicians
A weakness, as with all observational studies, is that we have assessed association rather
than causation. Whilst the analyses for factors associated with an increased risk of death
included baseline renal function and progression to ESRD (in competing risk analyses), we did
not include any other measure of CKD progression. In addition, whilst we collected
considerable demographic and clinical information, we did not complete any formal assessment of
frailty, depression or nutritional status of the participants. These factors have been associated
with impairment of HRQL [9, 37±42].
In summary, we have demonstrated that impaired HRQL is common in a diverse pre-dialysis
CKD population and that impaired HRQL, as demonstrated by problems with self-care or a
lower EQ-5Dindex score, is associated with a higher risk for death but not ESRD. Multiple
factors influence these aspects of impaired HRQL but renal function, as measured by eGFR and
ACR, are not among them.
Further studies are recommended to evaluate interventions that may improve HRQL
within the pre-dialysis CKD population and to investigate whether any improvements in
HRQL are associated with a survival advantage.
S1 Table. Demographic, clinical and laboratory data subdivided by Kidney Disease
Improving Global Outcomes (KDIGO) eGFR classification.
S2 Table. Multivariable Survival Analyses for death.
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The authors would like to acknowledge the support of the staff in the renal outpatients
department at University Hospital Birmingham and Heartlands Hospital, the research and
development department at University Hospital Birmingham, the recruiting RIISC study team and the
individuals who participated in the study.
Conceptualization: MDJ MD CJF PC SJS.
Data curation: MDJ AF CJF PC SJS.
Formal analysis: MDJ AF CJF MC PC SJS.
Funding acquisition: PC.
Investigation: MDJ MD ID PY KPN AF CJF PC SJS.
Methodology: MDJ DK CJF MC PC SJS.
Project administration: MDJ PC SJS.
Resources: MDJ MD ID PY KPN AF CJF PC SJS.
Supervision: PC SJS.
Visualization: MDJ PC SJS.
Writing ± original draft: MDJ PC SJS.
Writing ± review & editing: MDJ MD ID PY KPN AF DK CJF MC PC SJS.
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