Natural History of Older Adults with Impaired
Kidney Function: The InCHIANTI Study
Sandra V. Giannelli,1Christophe E. Graf,1Franc ¸ois R. Herrmann,1Jean-Pierre Michel,1
Kushang V. Patel,2Francesco Pizzarelli,3Luigi Ferrucci,4and Jack Guralnik2
The aim of this study was to assess the kidney function of an older community-dwelling population at baseline
and appraise its evolution after 3 years of follow-up in terms of chronic kidney disease (CKD) stage progression,
magnitude of glomerular filtration rate (GFR) changes, and value of serum creatinine. This was a prospective
population-based study of 676 Italian participants, aged 65 years and older. GFR was estimated using the
Cockcroft–Gault equation and the Modification of Diet in Renal Disease Study equation. Using the Cockcroft–
Gault equation. A total of 33% of participants had criteria of CKD (GFR<60mL/min) at baseline; among them,
the majority remained stable, 10% improved, and 7% progressed to more severe CKD stages at follow-up. Loss
of GFR in participants with GFR<60mL/min was significantly lower (1.4mL/min per year) than in partici-
pants with GFR?60mL/min (3.3mL/min per year) at baseline. Most participants classified with CKD stage 2
(GFR 60–89mL/min) or stage 3 (GFR 30–59mL/min) at baseline did not change stage, whereas 55% of people
with CKD stage 1 (GFR>90mL/min) at baseline worsened to stage 2 and 10% worsened to stage 3. An
abnormal high level of serum creatinine at baseline did not help to predict who might worsen at follow-up.
Older people with CKD displayed a low progression of renal disease and therefore are at higher risk for co-
morbidities related to CKD than for progression to end-stage renal disease.
noninstitutionalized U.S. population over 70 years of age, the
prevalenceofCKDstage 3(glomerularfiltrationrate [GFR]30–
was 37.8% as estimated with the Modification of Diet in Renal
Disease Study equation (MDRD).1In an Italian population
sample, the prevalence of CKD defined as GFR<60mL/min
per 1.73m2using the MDRD equation was 15% and 11% for
men and women, respectively, aged 65–74, and 34.5% and
31.6% formen andwomen,respectively, over 75yearsofage, a
prevalence close to the one found in the U.S. population.2
Older age represents a risk factor for CKD, and CKD has
been associated with higher morbidity,3,4greater health care
utilization,5–8and higher mortality.7,9In older people, level
of kidney function (KF) as well as rapid decline in KF have
been shown to be both independent risk factors for cardio-
vascular disease (CVD), new onset of CVD, and all-cause
hronic kidney disease (CKD) is an important public
health problem especially in older age. In a representative
mortality.10–12However, CKD diagnosis is less obvious in
older persons than in younger adults. Indeed, the majority
(76.3%) of the total InCHIANTI (Invecchiare in Chianti
[Aging in the Chianti Area]) Study sample over 65 years with
GFR<60mL/min had normal serum creatinine levels.13
Previous studies have shown that there is a progressive
decline in GFR with age.14,15These studies display only the
overall mean of GFR decline as if there were a progressive,
homogeneous, and irreversible decline in KF with age.
However, one study assessing the creatinine clearance of 446
community-dwelling men aged 22–97 years found that 156
(35%) subjects presented no decrease in KF.14Indeed, the
practice experience demonstrates that patients, especially
older people, are not homogeneous, and that different pat-
terns of KF history may exist.
The aim of the current study was to assess the KF of an
older community-dwelling population at baseline and ap-
praise its evolution at 3 years of follow-up in terms of CKD
stage progression, magnitude of GFR changes, and value of
1Department of Internal Medicine, Rehabilitation and Geriatrics, Geneva University Hospitals, Geneva, Switzerland.
2Laboratory of Epidemiology, Demography, and Biometry, National Institute on Aging, National Institutes of Health, Bethesda, Maryland.
3Division of Nephrology, SM Annunziata Hospital, Florence, Italy.
4Longitudinal Studies Section, Clinical Research Branch, National Institute on Aging, National Institutes of Health, Baltimore, Maryland.
Volume 14, Number 5, 2011
ª Mary Ann Liebert, Inc.
Study design and population
This study used baseline and 3 years of follow-up data
from the InCHIANTI Study, a longitudinal population-based
study of people living in Greve in Chianti and Bagno a Ri-
poli, in the Tuscany region of Italy. This study was planned
by the Laboratory of Clinical Epidemiology of the Italian
National Research Council on Aging (INRCA, Florence,
Italy) in collaboration with the Laboratory of Epidemiology,
Demography, and Biometry at the National Institute on
Aging. Data were collected between September, 1998 and
March 2000 for baseline and between November, 2001 and
November, 2003 for follow-up. The INRCA ethics committee
approved the InCHIANTI Study protocol, which met the
criteria outlined in the Declaration of Helsinki. All subjects
agreed to participate in the study and provided informed
Figure 1 shows the different recruitment steps from the
total InCHIANTI Study population to the analytic sample
size. The InCHIANTI Study included 1,453 people who were
randomly selected using a multistage stratified sampling
method; they agreed to participate in the study and provided
written informed consent. Participants below 65 years
(n¼298), with missing values of serum creatinine and/or
weight at baseline (n¼176) or follow-up (n¼146), and par-
ticipants missing at follow-up (n¼157) were excluded,
leading to a total sample size of 676 participants.
Excluded people 65 years and over, were older, predom-
inantly women, and displayed lower GFR, years of educa-
tion, score on the Mini-Mental State Examination (MMSE)
and had worse physical performance and more co-morbidities.
Excluded people due to missing values at follow-up or loss
to follow-up (303 participants) displayed a mean GFR of
57.7mL/min (GFR?60mL/min in 43%; GFR 30–59 in 51%;
GFR 15–29 in 6%). Causes of death, defined using Interna-
tional Classification of Diseases (ICD)-9 code, were mainly
due to circulatory system disease (51%), neoplasm (28%),
respiratory system disease (7%), nervous system disease
(4%), senility (3%), and other diseases (7%). No participants
died due to end-stage CKD.
Participants underwent a first interview at home during
which sociodemographic data were collected and cognitive
performance was assessed using the MMSE.16The number of
years the subject attended school was used to define edu-
cation. During a second appointment at the study clinic,
participants who fasted at least 8hr underwent a peripheral
blood collection. The clinical examination occurred during a
third visit and was carried out by trained geriatricians and
physical therapists. The presence and severity of co-
morbidities found during the examination were verified us-
ing standard algorithms based on medical history, drug
treatments, symptoms and signs, medical documents, and
hospital discharge records.17Weight and height were mea-
sured with participants wearing light clothes and no shoes,
and used to compute body mass index (BMI) as (weight
[kg]/(height [m])2). Blood pressure was first assessed on
both arms with the patient supine for at least 5min. Then
measurements were repeated two times on the arm with the
highest value of systolic blood pressure (SBP), and the mean
of these two values was used to define SBP. Physical function
was assessed using the Short Physical Performance Battery.18
Laboratory measures and kidney function assessment
Serum creatinine was detected by kinetic-colorimetric as-
say based on a modified Jaffe method using a commercial
enzymatic kit (Roche Diagnostics, GmbH, Mannheim, Ger-
many) and Roche-Hitachi Analyzer in the same central lab-
oratory at baseline and follow-up. The analytical sensitivity
(lower detection limit) was 0.1mg/dL, with intraassay and
interassay coefficients of variation of 0.7% and 2.3%, re-
spectively. Serum creatinine was used to estimate the GFR
and to stratify the population between normal and abnormal
serum creatinine using previously established cutoffs for
adults [abnormal values: men,>1.3mg/dL(>114.9mmol/
Both the Cockroft–Gault (CG) and MDRD equations have
been proposed as good estimates of GFR in an adult popu-
lation by the Kidney Disease Outcome Quality Initiative of
the National Kidney Foundation (NKF-K/DOQI).4However,
it has been shown that in older populations, and when using
the serum creatinine assay not calibrated to the new criterion
standard, the CG equation constantly underestimates the
true GFR20–25compared to the MDRD equation, which dis-
played less consistent results, with both underestima-
tion20,21,25and overestimation22–24of the true GFR.13,26
Furthermore, CG is still widely used in clinics and has not
yet been supplemented by MDRD in terms of GFR assess-
ment for drug dosage adjustment. A new equation to esti-
Recruitment of the population.
514GIANNELLI ET AL.
mate GFR, the Chronic Kidney Disease Epidemiology Col-
laboration (CKD-EPI) equation,27has recently been devel-
oped in a large population but included few elderly people.
None of these equations has been validated in an older
population, and for these reasons CG was used in this study.
However, some analyses were also performed with the
MDRD equation to compare results. Because results obtained
with MDRD are adjusted to body surface area (BSA), we
compared CG subgroup stratification with CG subgroup
stratification adjusted to BSA. Equations 1 and 2 (see Ap-
pendix) show CG28and MDRD29equations, respectively, to
compute GFR. Equation 3 displays the CG equation adjusted
Results were stratified into five categories of KF according
to stages of CKD established by NKF-K/DOQI: Normal KF
(GFR?90mL/min) or Stage 1, mild KF impairment (GFR
60–89mL/min) or Stage 2, moderate KF impairment (GFR
30–59mL/min) or Stage 3, severe KF impairment (GFR 15–
29mL/min) or Stage 4, and terminal kidney failure
(GFR<15mL/min) or Stage 5. CKD is defined by NKF-K/
DOQI guidelines as GFR less than 60mL/min or the pres-
ence of kidney damage defined by structural or functional
abnormalities of the kidney, for 3 months or more.4
Excluded people aged 65 and older were compared to
included participants according to demographics character-
istics, anthropometrics, KF, chronic disease status, treatment
for high blood pressure, and physical and cognitive function
using multiple regression analysis for continuous dependent
variables and logistic regression analysis for dichotomous
dependent variables. The studied population was then
stratified into four subgroups according to their GFR values
at baseline and 3 years of follow-up: High-High (HH),
GFR?60mL/min at baseline and follow-up; High-Low
(HL), GFR?60mL/min at baseline and GFR<60mL/min
at follow-up; Low-High (LH), GFR<60mL/min at baseline
GFR<60mL/min at baseline and at follow-up. Character-
istics of HL, LH, and LL were compared to those of HH
using multiple regression analysis for continuous dependent
variable and logistic regression analysis for dichotomous
dependent variable unadjusted and adjusted for age and
To understand the magnitude of change in KF among
these four subgroups, a new continuous variable ‘‘delta’’ was
created and defined as GFR at follow-up minus GFR at
baseline. To facilitate comparison with the literature, we
computed delta on a yearly basis, dividing delta by 3. Delta
values of participants with GFR<60mL/min were com-
pared to those with GFR?60mL/min at baseline, and delta
values of HL, LH, and LL were then compared to HH, using
multiple regression analysis, unadjusted and adjusted for
age and gender. Delta values were also plotted against GFR
at baseline along with a quadratic regression curve and its
95% confidence interval. The coefficient of determination
was used to assess the amount of variance in delta explained
by the GFR at baseline. A likelihood ratio test was used to
compare the linear and quadratic fit regressions.
Factors associated with a GFR<60mL/min at follow-up
were assessed using logistic regression in a univariate anal-
ysis, using one independent variable at a time, and an ad-
justed full model, including all variables simultaneously. To
build the adjusted full model, baseline characteristics were
used as indicator variable in a forward method using five
models consecutively, each new model adding new variables
to the previous model: Model I, including age in categories
and sex; model II, serum creatinine (mg/dL) and presence of
CKD at baseline (GFR<60mL/min versus GFR?60mL/
min using the CG equation); model III, cognitive perfor-
mance (MMSE score) and education (years of school); model
IV, physical performance (good Short Physical Performance
Battery [SPPB 10–12] versus poor [SPPB<10] performers);
and model V, co-morbidities (number of co-morbidities and
cardiovascular disease, such as stroke, ischemic cardiomy-
opathy, and peripheral arterial disease). All variables with p
values <0.2 or with clinical relevance were kept in the con-
secutive models and included in the final full model. All
statistical analyses were performed using Stata version 11.1
(StataCorp, College Station, TX; 2009).
Table 1 describes baseline characteristics of the 676 sub-
jects stratified into four subgroups according to their GFR at
baseline and 3 years of follow-up. Compared to HH
(n¼300), all of the other subgroups were significantly older,
had higher proportions of women, and had lower GFR, BMI,
and education. Compared to HH, LL (n¼199) displayed
lower scores of MMSE, lower physical performance, higher
prevalence of congestive heart failure (CHF), and higher le-
vel of serum creatinine, which was, however, still in the
normal range of values; HL (n¼154) and LL had signifi-
cantly higher SBP. The proportion of people with abnormal
values of serum creatinine was significantly higher in LH
(n¼23) and LL compared to HH.
Figure 2A shows the stratification of the study population
by GFR values using CG. From the 454 participants with
baseline GFR?60mL/min, 33.9% worsened at follow-up.
From the 222 participants with baseline GFR<60mL/min,
10.4% improved and 89.6% remained mainly stable. Indeed
16 (7.2%) of the participants with a GFR<60mL/min at
baseline worsened by one stage of CKD at follow-up.
Values of unadjusted mean delta are also shown in Fig.
2A. The total population displayed a mean delta of ?2.7mL/
min per year (?3.3mL/min per year for participants with
GFR?60mL/min, ?1.4mL/min per year for those with
GFR<60mL/min at baseline, difference statistically signifi-
cant unadjusted and adjusted for age and gender, p<0.001).
HL (?6.2mL/min per year) and LH (þ3.8mL/min per year)
were significantly different from HH while adjusting or not
for age and gender. LL (?2.0mL/min per year) was not
different from HH.
Regarding serum creatinine levels, 4 (0.9%) participants
with a GFR?60mL/min at baseline had abnormal high-
level values and 3 (75%) of them displayed a GFR<60mL/
min at follow-up. Among participants with GFR<60mL/
min at baseline, 42 (18.9%) had abnormal high level values,
and of them and at follow-up 5 (11.9 %) improved by one
stage of CKD, 29 (69%) remained stable, and 8 (19.1%)
worsened by one stage of CKD.
Figure 2B shows the stratification by GFR values using
the MDRD equation. From the 607 participants with
NATURAL HISTORY OF IMPAIRED KIDNEY FUNCTION515
Table 1. Population Characteristics at Baseline
HL vs. HH
LH vs. HH
LL vs. HH
Women, n (%)
Women serum creatinine
Men serum creatinine
High level of serum creatinine,
Body mass index
Education, years of school,
Mini-Mental State Exam,
Short Physical Performance Battery
SBP, mmHg, mean?SD
Treatment for high blood pressure,
Diabetes mellitus, n (%)
Stroke, n (%)
Ischemic cardiomyopathy, n (%)
Congestive heart failure, n (%)
Peripheral arterial disease, n (%)
Chronic obstructive pulmonary disease,
Arthritis, n (%)
Cancer, n (%)
Parkinson’s disease, n (%)
HH, High-High; HL, High-Low; LH, Low-High; SD, standard deviation; GFR, glomerular filtration rate; SBP, systolic blood pressure.
(CG). (B) Population stratification by glomerular filtration rate (GFR) estimation using the Modification of Diet in Renal
Disease Study equation (MDRD). CI, Confidence interval.
(A) Population’s stratification by glomerular filtration rate (GFR) estimation using the Cockcroft–Gault equation
NATURAL HISTORY OF IMPAIRED KIDNEY FUNCTION517
GFR?60mL/min per 1.73m2, 22.6% worsened at follow-up.
From the 69 with GFR <60mL/min per 1.73m2, 26.1% im-
proved, and 73.9% remained mainly stable. Only 2 (2.9%)
participants with a GFR<60mL/min per 1.73m2at baseline
worsened by one stage of CKD at follow-up.
The overall absolute loss of GFR of participants with
(?2.1mL/min per year) than the loss of GFR (?0.4mL/min
per year) of participants with GFR<60mL/min per 1.73m2
(n¼69), with the difference statistically significant only with
unadjusted for age and gender values (p¼0.0178). Among
participants with GFR?60mL/min per 1.73m2at baseline,
no one had high abnormal serum creatinine levels at baseline.
Figure 3A shows, for each participant, GFR at 3 years of
follow-up (y axis) according to GFR at baseline (x axis) using
the CG. Overall, GFR worsened for the majority of the
population after 3 years (majority of circles under the iden-
tity line), but the magnitude of GFR loss was more important
at higher GFR (higher dispersion of circles) than at lower
GFR values. Fifty-five percent of participants (n¼47) classi-
fied as stage 1 at baseline worsened to stage 2 and 10%
(n¼9) worsened to stage 3 at follow-up. However 57% of
people with stage 2 and 83% with stage 3 at baseline stayed
in the same class of CKD at follow-up and 39% of people
with stage 2 and 6% of participants with stage 3 at baseline
worsened by one stage. Five percent of the study population
displayed an improvement of their KF at follow-up. The
magnitude of improvement was larger at higher KF
Figure 3B shows the delta value versus GFR estimation at
baseline. People with a higher level of KF at baseline expe-
rienced a larger magnitude of GFR loss (line’s steep slope)
compared to those with lower level of KF. Persons with
GFR<60mL/min at baseline experienced less variation of
their KF as shown by the quadratic regression curve (curve
with 95% confidence interval) which was associated with a
statistically significant better fit (adjusted R2¼10.4 %) than a
linear regression (adjusted R2¼9.6 %) (likelihood ratio test,
Table 2 shows the crude and final adjusted odds ratio of
having a GFR<60mL/min at 3 years of follow-up among
the whole population. In the univariate analyses, an age of 75
years and older, higher serum creatinine, a GFR<60mL/
min at baseline, poor physical performance, two or more co-
morbidities, and SBP of 160 mmHg or higher were associated
with a GFR<60mL/min at follow-up. Male gender, higher
scores of MMSE, education, and BMI were associated with a
significant protective effect.
In the final multivariate model, an age of 75 years and
older, higher serum creatinine, a GFR<60mL/min at
baseline and a SBP of 160 mmHg and higher were associ-
ated with a GFR<60mL/min at follow-up whereas male
gender, former and current treatment for high blood pres-
sure, and higher BMI were associated with a significant
Overall, these results highlight different points. Older
patients do not represent a homogeneous population with a
constant and irreversible loss of GFR throughout time. Dif-
ferent trajectories can be expected, including improvement of
KF. They also stress the pitfall of relying only on serum
creatinine as evidence of KF: only 19% of participants with
GFR<60mL/min at baseline had an abnormal high level of
In this cohort, participants with a criterion of CKD at
baseline represented the most stable subset of the popula-
baseline (BL) (x axis) using the Cockcroft–Gault equation. (B) Yearly difference of renal function between baseline and follow-
up, named Delta GFR versus glomerular filtration rate (GFR) estimation at baseline using the Cockcroft–Gault equation.
A quadratic fit curve (delta GFR¼?1.8325þ0.0463*GFR ? 0.0008*GFR2) with its 95% confidence interval is also shown.
(A) Glomerular filtration rate (GFR) estimation at 3 years of follow-up (FU) (y axis) according to GFR estimation at
518GIANNELLI ET AL.
tion, whereas participants with a GFR?60mL/min dis-
played larger variations of their GFR.
The overall mean change of GFR in our community-
dwelling participants was ?2.7?0.2mL/min per year. A
smaller prospective study of 269 individuals over 65 years
and living in the community of San Paulo found a similar
overall change in GFR of ?2.37?0.23mL/min per year us-
ing CG. A higher rate of GFR loss was also found in par-
ticipants with higher levels of creatinine clearance at
baseline, but interestingly at an older age.31We would expect
that older patients would have the lowest GFR. Indeed, in
our study, older participants were more likely to be in sub-
group LL, which displayed the lowest rate of GFR loss.
In a prospective study of a nonrepresentative Canadian
population referred to a laboratory service comparing dia-
betic with nondiabetic participants over 66 years and fol-
lowed during 2 years, the greatest decline in GFR as assessed
with MDRD was found in diabetic subjects (?5.1mL/min
per 1.73m2for diabetic men and ?4.2mL/min per 1.73m2
for diabetic women; ?2.7mL/min per 1.73m2for men and
?1.5mL/min per 1.73m2for women without diabetes). In
this study, the proportion of people with a loss of KF over
15mL/min per 1.73m2was greater for participants with
higher mean GFR over 2 years (13.6 % of subjects with mean
GFR 60–89mL/min per 1.73m2) compared to those with
lower mean GFR (8.6% of subjects with mean GFR<30mL/
min per 1.73m2).The authors decided to stratify the CKD
stages by the mean of GFR along the entire period to reduce
effect of regression to the mean phenomenon. This method is
theoretically interesting but not relevant in clinical practice.32
In our study, up to 10.4% of participants with GFR<
60mL/min improved their KF at 3 years, results supporting
that the natural history of KF is not always a progressive and
irreversible decline with age. In the Baltimore longitudinal
study of aging, 35% of all subjects had no absolute decrease in
KF and around 1.6% showed a statistically significant increase
in creatinine clearance with age.14In the Cardiovascular
Health Study using two measurements of kidney function,
39% of the cohort displayed an increase of their KF.33
The strengths of the current study are that it uses data
from a sample of community-dwelling older adults well
characterized in terms of disease status and body composi-
tion. However, it represents a healthier subset of the popu-
lation because it consists of older adults who survived for 3
years, consented to blood draws at both time points, and
displayed mostly moderate KF impairment. Given that, the
Table 2. Odds Ratios for Glomerular Filtration Rate (GFR) Less Than 60mL/min at 3 Years
of Follow–Up in a Population of People Aged 65 and Older Using Univariate (One Independent Variable
at a Time) and Multivariate (All Variables Included Simultaneously) Logistic Regression Models
CrudeAdjusted full model
Marker at baselineOR 95% CIp OR95% CIp
Serum creatinine, mg/dL
Mini Mental State
Education, years of school
Short Physical Performance
Battery: poor performers
Treatment for high
Body mass indexa
Peripheral arterial disease
0.89 [0.84–0.94]0.0011.00 [0.91–1.09]0.946
aBody mass index (BMI) was treated as a continuous variable after having tested its log linearity relationship with the outcome.
Abbreviations: OR, Odds ratio; CI, confidence interval; GFR, glomerular filtration rate; SBP, systolic blood pressure.
NATURAL HISTORY OF IMPAIRED KIDNEY FUNCTION 519
rate of decline in KF may be underestimated, especially in
the subset of the population with severe CKD. However, this
survival bias probably may have a low impact on the results
because no participants died due to advanced chronic kidney
disease. Another limitation is that this study uses a single
serum creatinine measurement at baseline and follow-up,
therefore variability due to acute renal insufficiency can not
be excluded. The urinary albumin-to-creatinine ratio was not
assessed in this population and may have improved the
predictive model of having a CKD at follow-up (Table 2), as
it has been recently shown.34,35There is no gold standard
marker of KF leading to use an estimation equation of GFR
not validated in an older population. Finally, results re-
garding kidney function evolution may be partly explained
by a regression-to-the mean phenomenon, especially re-
garding the larger drop of GFR among participants with a
GFR?60mL/min at baseline in the first group. However,
the fact that the mean delta in the whole population is neg-
ative underlines that there is a clear, but not homogeneous,
decline of kidney function with age.
In our study, using the MDRD equation, only 10% of the
included subjects had a GFR<60mL/min per 1.73m2at
baseline compared to 33% using CG. Overestimation of the
true GFR by the MDRD equation may explain an important
classification difference at baseline, leading to missing an
important subset of the population displaying a GFR around
the cut-off values for CKD (60mL/min). However, using
either MDRD or CG, patients displaying criteria of CKD at
baseline represented the more stable population.
After adjusting CG to BSA, 67 subjects out of 676 (9.9%)
were classified differently at baseline from results obtained
with CG: 26 were found to have a worse KF and conversely
41 were found to have a better KF at baseline.33Without a
gold standard marker of KF, we can not tell which classifi-
cation is closer to reality. None of these equations is vali-
dated in this extreme age group, therefore we decided to
keep CG for all our analyses because it is the most used
estimation equation in the geriatric clinical setting. These
data also stress the need to develop an equation specific to
the very old population.
In a community-based longitudinal study of adults over
65 belonging to The Cardiovascular Health Study, mean
annual GFR decline was assessed using MDRD. In this
study, older age and female gender were predictors of an-
nual KF decline.33We found similar results. In addition, in
our study, higher SBP was also found to be a predictor of loss
of KF, a finding corroborated by others36,37and thus stres-
sing the role of screening and management of cardiovascular
risk factor in slowing rate loss of KF. Gender effect regarding
progression of KF remains controversial; while some studies
have found a protective effect,33others have found that male
gender was predictor of KF decline.37, 38
In our study, diabetes did not affect subgroup allocation
(Table 1) or CKD at follow-up risk (Table 2) and may reflect
that diabetic nephropathy is not the major determinant of
CKD impairment in an older population and that CKD
evolution may be explained by other causes such as ne-
phrosclerosis due to higher SBP. This hypothesis was also
suggested in another study assessing older hospitalized di-
abetic patients in which renal insufficiency was found to
often occur without albuminuria, an early-stage marker of
To assess the long-term prognosis and change in GFR of
patient with criteria of CKD, a longitudinal observation
study of people living in northern Norway, referred for
laboratory testing and displaying GFR between 30 and
59mL/min per 1.73m2using MDRD found a 10-year cu-
mulative incidence of renal failure as low as 0.04 (95% CI
0.03–0.06). However, 10-year cumulative incident mortality
reached up to 0.51 (95% CI 0.48–0.55). Causes of death were
not identified, but renal failure was excluded as a cause
based on expected GFR at the time of death. In this popu-
lation, a similar mean change in GFR was found (?1.04mL/
min per 1.73m2per year; ?1.60mL/min per 1.73m2per year
for subjects aged 70–79 years, respectively, >79 years).The
authors conclude that high mortality pre-empted the devel-
opment of renal failure in many patients.38
The same pattern was found in a large national cohort of
U.S. veterans who met criteria for stage 3 or higher CKD.
Older participants, especially those aged 75 years and older,
were far more likely to die than to develop end-stage renal
disease (ESRD). In this cohort, the threshold of GFR esti-
mated using MDRD, and below which the risk of ESRD
exceeds the risk of death, varied by age and was below
15mL/min per 1.73m2for those aged 65–84 years old. For
participants aged 85 years and older, the risk of death always
exceeds the risk of ESRD.40The association of all-cause and
cardiovascular mortality with CKD was assessed in a large
cohort study of people over 75 years, with a mean GFR of
62.4mL/min per 1.73m2for men and 55.8mL/min per
1.73m2for women, registered in 53 general practices in Great
Britain, with a median follow-up of 7.3 years. In this com-
munity-dwelling older population, results showed a graded
and independent increase in all-cause and cardiovascular
mortality risk as GFR decreased, especially in men and those
with a GFR ?45mL/min per 1.73m2.41The same pattern
was found in a longitudinal study of adult members of a
Health Maintenance Organization in Oregon in which death
was far more common than dialysis in all stages. Further
analysis found that CHF, coronary artery disease, diabetes,
and anemia were more prevalent in the patients who died,
stressing the need to screen and manage CKD complications
in this population.42
In conclusion, this study demonstrates that older people
with impaired renal function represent a subset of the pop-
ulation with a very low progression of renal disease and
therefore are at higher risk to suffer from co-morbidities re-
lated to CKD than to progress to end-stage renal disease.
We thank Professor Pierre-Yves Martin (Division of
Switzerland) and Dr. Lesley A. Stevens (Division of Ne-
phrology, Tufts-New England Medical Center, Boston, MA)
for their advice and suggestions. Everyone who contributed
significantly to the work is listed. Author contributions were
as follows: Sandra V. Giannelli, study concept and design,
analysis and interpretation of data, preparation of the man-
uscript; Christophe E. Graf, analysis and interpretation of
data, preparation of manuscript; Franc ¸ois R. Herrmann,
analysis and interpretation of data, preparation of manu-
script; Jean-Pierre Michel, analysis and interpretation of data,
preparation of manuscript; Kushang V. Patel, analysis and
520GIANNELLI ET AL.
interpretation of data, preparation of manuscript; Francesco
Pizzarelli, analysis and interpretation of data, preparation of
manuscript; Luigi Ferrucci, acquisition of subjects and data,
analysis and interpretation of data, preparation of the manu-
script; Jack M. Guralnik, acquisition of subjects and data, anal-
ysis and interpretation of data, preparation of the manuscript.
This study was supported as a ‘‘targeted project’’ (ICS
100.1\RS97.71) by the Italian Ministry of Health, and in part
by the Intramural Research Program of the National Institute
on Aging, National Institutes of Health (NIH). Sandra V.
Giannelli was supported by funds from the Department of
Rehabilitation and Geriatrics, Geneva University Hospitals,
Geneva, Switzerland. The granting institutions named did
not interfere in any way with the design, methods, subjects
recruitment, data collections, analysis, and preparation of
The results of this work were presented in a poster session
at the Congre `s International Francophone de Ge ´riatrie et
Ge ´rontologie in Nice, France (CIFGG) in October, 2010, and
VII European Congress Healthy And Active Ageing For All
Europeans II, Bologna, Italy, April, 2011.
Author Disclosure Statement
No competing financial interests exist.
1. Coresh J, Selvin E, Stevens LA, Manzi J, Kusek JW, Eggers P,
Van Lente F, Levey AS. Prevalence of chronic kidney disease
in the United States. JAMA 2007;298:2038–2047.
2. Cirillo M, Laurenzi M, Mancini M, Zanchetti A, Lombardi C,
De Santo NG. Low glomerular filtration in the population:
Prevalence, associated disorders, and awareness. Kidney Int
3. Roderick PJ, Atkins RJ, Smeeth L, Nitsch DM, Hubbard RB,
Fletcher AE, Bulpitt CJ. Detecting chronic kidney disease in
older people; what are the implications? Age Ageing 2008;
4. K/DOQI clinical practice guidelines for chronic kidney dis-
ease: Evaluation, classification, and stratification. Am J
Kidney Dis 2002;39:S1–S266.
5. Khan SS, Kazmi WH, Abichandani R, Tighiouart H, Pereira
BJ, Kausz AT. Health care utilization among patients with
chronic kidney disease. Kidney Int 2002;62:229–236.
6. Nissenson AR, Collins AJ, Hurley J, Petersen H, Pereira BJ,
Steinberg EP. Opportunities for improving the care of pa-
tients with chronic renal insufficiency: Current practice
patterns. J Am Soc Nephrol 2001;12:1713–1720.
7. Obrador GT, Pereira BJ, Kausz AT. Chronic kidney disease
in the United States: An underrecognized problem. Semin
8. Nitsch D, Nonyane BA, Smeeth L, Bulpitt CJ, Roderick PJ,
Fletcher A. CKD and hospitalization in the elderly: A com-
munity-based cohort study in the United Kingdom. Am J
Kidney Dis 2011;57:664–672.
9. Pizzarelli F, Lauretani F, Bandinelli S, Windham GB, Corsi
AM, Giannelli SV, Ferrucci L, Guralnik JM. Predictivity of
survival according to different equations for estimating renal
function in community-dwelling elderly subjects. Nephrol
Dial Transplant 2009;24:1197–1205.
10. Maaravi Y, Bursztyn M, Hammerman-Rozenberg R, Cohen
A, Stessman J. Moderate renal insufficiency at 70 years
predicts mortality. QJM 2006;99:97–102.
11. Manjunath G, Tighiouart H, Coresh J, Macleod B, Salem DN,
Griffith JL, Levey AS, Sarnak MJ. Level of kidney function as
a risk factor for cardiovascular outcomes in the elderly.
Kidney Int 2003;63:1121–1129.
12. Rifkin DE, Shlipak MG, Katz R, Fried LF, Siscovick D,
Chonchol M, Newman AB, Sarnak MJ. Rapid kidney func-
tion decline and mortality risk in older adults. Arch Intern
13. Giannelli SV, Patel KV, Windham BG, Pizzarelli F, Ferrucci
L, Guralnik JM. Magnitude of underascertainment of im-
paired kidney function in older adults with normal serum
creatinine. J Am Geriatr Soc 2007;55:816–823.
14. Lindeman RD, Tobin J, Shock NW. Longitudinal studies on
the rate of decline in renal function with age. J Am Geriatr
15. Rowe JW, Andres R, Tobin JD, Norris AH, Shock NW. The
effect of age on creatinine clearance in men: a cross-sectional
and longitudinal study. J Gerontol 1976;31:155–163.
16. Folstein MF, Folstein SE, McHugh PR. "Mini-mental state."
A practical method for grading the cognitive state of patients
for the clinician. J Psychiatr Res 1975;12:189–198.
17. Guralnik JM, Fried LP, Simonsik EM, Kasper JD, Lafferty
ME (eds). The Women’s Health and Aging Study: Health
and Social Characteristics of Older Women with Disability.
National Institute on Aging, Bethesda, MD, 1995.
18. Guralnik JM, Simonsik EM, Ferrucci L, Glynn RJ, Berkman
LF, Blazer DG, Scherr PA, Wallace RB. A short physical
performance battery assessing lower extremity function:
association with self-reported disability and prediction of
mortality and nursing home admission. J Gerontol 1994;
19. Doolan PD, Alpen EL, Theil GB. A clinical appraisal of the
plasma concentration and endogenous clearance of creati-
nine. Am J Med 1962;32:65–79.
20. Froissart M, Rossert J, Jacquot C, Paillard M, Houillier P.
Predictive performance of the modification of diet in renal
disease and Cockcroft–Gault equations for estimating renal
function. J Am Soc Nephrol 2005;16:763–773.
21. Kang YS, Han KH, Han SY, Kim HK, Cha DR. Character-
istics of population with normal serum creatinine impaired
renal function and: the validation of a MDRD formula in a
healthy general population. Clin Nephrol 2005;63:258–266.
22. Lamb EJ, Webb MC, Simpson DE, Coakley AJ, Newman DJ,
O’Riordan SE. Estimation of glomerular filtration rate in
older patients with chronic renal insufficiency: Is the modi-
fication of diet in renal disease formula an improvement? J
Am Geriatr Soc 2003;51:1012–1017.
23. Lamb EJ, Wood J, Stowe HJ, O’Riordan SE, Webb MC,
Dalton RN. Susceptibility of glomerular filtration rate esti-
mations to variations in creatinine methodology: A study in
older patients. Ann Clin Biochem 2005;42:11–18.
24. Van Den Noortgate NJ, Janssens WH, Delanghe JR, Afschrift
MB, Lameire NH. Serum cystatin C concentration compared
with other markers of glomerular filtration rate in the old
old. J Am Geriatr Soc 2002;50:1278–1282.
25. Verhave JC, Fesler P, Ribstein J, du Cailar G, Mimran A.
Estimation of renal function in subjects with normal serum
creatinine levels: influence of age and body mass index. Am
J Kidney Dis 2005;46:233–241.
26. Van Pottelbergh G, Van Heden L, Mathei C, Degryse J.
Methods to evaluate renal function in elderly patients: a
systematic literature review. Age Ageing 2010;39:542–548.
27. Levey AS, Stevens LA, Schmid CH, Zhang YL, Castro AF
3rd, Feldman HI, Kusek JW, Eggers P, Van Lente F, Greene
NATURAL HISTORY OF IMPAIRED KIDNEY FUNCTION 521
T, Coresh J. A new equation to estimate glomerular filtration
rate. Ann Intern Med 2009;150:604–612.
28. Cockcroft DW, Gault MH. Prediction of creatinine clearance
from serum creatinine. Nephron 1976;16:31–41.
29. Levey AS, Bosch JP, Lewis JB, Greene T, Rogers N, Roth D.
A more accurate method to estimate glomerular filtration
rate from serum creatinine: A new prediction equation.
Modification of Diet in Renal Disease Study Group. Ann
Intern Med 1999;130:461–470.
30. Du Bois D, Du Bois EF. Clinical calorimetry tenth paper a
formula to estimate the approximate surface area if height
and weight be known. Arch Intern Med 1916;XVII:863–871.
31. Sesso R, Prado F, Vicioso B, Ramos LR. Prospective study of
progression of kidney dysfunction in community-dwelling
older adults. Nephrology (Carlton) 2008;13:99–103.
32. Hemmelgarn BR, Zhang J, Manns BJ, Tonelli M, Larsen E,
Ghali WA, Southern DA, McLaughlin K, Mortis G, Culleton
BF. Progression of kidney dysfunction in the community-
dwelling elderly. Kidney Int 2006;69:2155–2161.
33. Shlipak MG, Katz R, Kestenbaum B, Fried LF, Newman AB,
Siscovick DS, Stevens L, Sarnak MJ. Rate of kidney function
decline in older adults: a comparison using creatinine and
cystatin C. Am J Nephrol 2009;30:171–178.
34. Peralta CA, Shlipak MG, Judd S, Cushman M, McClellan W,
Zakai NA, Safford MM, Zhang X, Muntner P, Warnock D.
Detection of chronic kidney disease with creatinine, cystatin
C, and urine albumin-to-creatinine ratio and association
with Progression to end-stage renal disease and mortality.
35. Tangri N, Stevens LA, Griffith J, Tighiouart H, Djurdjev O,
Naimark D, Levin A, Levey AS. A predictive model for
progression of chronic kidney disease to kidney failure.
36. Hunsicker LG, Adler S, Caggiula A, England BK, Greene T,
Kusek JW, Rogers NL, Teschan PE. Predictors of the pro-
gression of renal disease in the Modification of Diet in Renal
Disease Study. Kidney Int 1997;51:1908–1919.
37. Levin A, Djurdjev O, Beaulieu M, Er L. Variability and risk
factors for kidney disease progression and death following
attainment of stage 4 CKD in a referred cohort. Am J Kidney
38. Eriksen BO, Ingebretsen OC. The progression of chronic
kidney disease: A 10-year population-based study of the
effects of gender and age. Kidney Int 2006;69:375–382.
39. Vischer UM, Giannelli SV, Weiss L, Perrenoud L, Frangos
E, Herrmann FR. The prevalence, characteristics and met-
abolic consequences of renal insufficiency in very old
hospitalized diabetic patients. Diabetes Metab 2011;37:
40. O’Hare AM, Choi AI, Bertenthal D, Bacchetti P, Garg AX,
Kaufman JS, Walter LC, Mehta KM, Steinman MA, Allon M,
McClellan WM, Landefeld CS. Age affects outcomes in
chronic kidney disease. J Am Soc Nephrol 2007;18:2758–
41. Roderick PJ, Atkins RJ, Smeeth L, Mylne A, Nitsch DD,
Hubbard RB, Bulpitt CJ, Fletcher AE. CKD and mortality
risk in older people: A community-based population
study in the United Kingdom. Am J Kidney Dis 2009;
42. Keith DS, Nichols GA, Gullion CM, Brown JB, Smith DH.
Longitudinal follow-up and outcomes among a population
with chronic kidney disease in a large managed care orga-
nization. Arch Intern Med 2004;164:659–663.
Address correspondence to:
Sandra V. Giannelli
Department of Internal Medicine, Rehabilitation and Geriatrics
Geneva University Hospitals
Rue du Pont-Bochet 3
1226 Tho ˆnex
Received: March 2, 2011
Accepted: April 26, 2011
522 GIANNELLI ET AL.
Equation 1: CG formula28:
ð Þ¼[140?age (years) ]·weight (kg)· 0:85 if $
72·creatinine (mg /dL)
Equation 2: MDRD formula29:
GFR (mL /min per 1.73m2Þ¼186·(creatinine (mg /dL))?1:154·[age (years)]?0:203· 0:742 if $
Because the studied population was Italian, we did not have to adjust this equation for race.
Equation 3: CG adjusted to body surface area (BSA) according to the Dubois and Dubois formula30:
GFR (mL /min per 1.73m2Þ¼CG·[1:73=BSA]
ð Þ 0:725·Weight kg
NATURAL HISTORY OF IMPAIRED KIDNEY FUNCTION523
Page 12Download full-text