Predictive factors associated with change rates of LV hypertrophy
and renal dysfunction in CKD patients
Kozue Okumura, Hiroaki Io, Mayumi Matsumoto, Takuya Seto,
Miyuki Takagi, Atsumi Masuda, Masako Furukawa, Lili
Nagahama, Keisuke Omote, Atsuko Hisada, Chieko Hamada,
Satoshi Horikoshi and Yasuhiko Tomino
Address correspondence and reprint requests to
Yasuhiko Tomino MD. PhD.
Division of Nephrology, Department of Internal Medicine,
Juntendo University Faculty of Medicine,
2-1-1 Hongo, Bunkyo-ku, Tokyo 113-8421, Japan.
Tel&Fax No.81-3-5802-1064 or -1065
E-mail: yasu@juntendo.ac.jp
Word count: 2358 words
（Abstract 199 words, excluding references and figure legends）
1
Running title: Factors associated with change rates of LVMI and
CKD
2
Abstract
Background: This longitudinal study is the first report on the
factors associated with change rates of the estimated glomerular
filtration rate (eGFR) and left ventricular mass index (LVMI)
using echocardiography in chronic kidney disease (CKD) patients.
Methods: Measurements of biochemical and physical values, and
LVMI evaluated by echocardiography were performed twice
(baseline and follow-up period) in pre-dialysis CKD patients.
Blood and urine samples were collected at the time of the
echocardiographic study.
Results: The change rates of hemoglobin (Hb) and transferrin
saturation [TSAT: (serum iron / total iron binding capacity)] were
identified as independent risk factors for changes in eGFR by
multivariate regression analysis. In the LVMI improvement
group, the change rate of systolic blood pressure (sBP) was
identified as an independent factor for change in LVMI. In the
LVMI worsening group, the change rates of sBP, proteinuria, Hb
and serum phosphorus were significantly correlated with those of
LVMI, and change rates of sBP, proteinuria and Hb were
identified as independent risk factors for changes in LVMI.
Conclusions: It appears that treatment of renal and iron
deficiency anemia might prevent progression of renal dysfunction.
To prevent LV hypertrophy in CKD patients, renal anemia,
hypertension and proteinuria should be treated.
3
Key words: Chronic kidney disease, LV hypertrophy, left
ventricular mass index, pre-dialysis
4
Introduction
Incidences of end-stage kidney disease (ESKD) are steadily
increasing around the world. Cardiovascular disease (CVD) is the
main cause of morbidity and mortality in patients with
pre-dialysis CKD (1) (2). Prominent features of cardiovascular
involvement in CKD patients are left ventricular hypertrophy
(LVH) and dysfunction (3) (4). Deaths from CVD in dialysis
patients are 10 to 30 times more frequent than those in the
general population. CVD is also responsible for up to 50% of the
all-cause mortality rate (5). The prevalence of LVH tends to
increase with progression of renal dysfunction. Indeed, 70 to 80%
of patients with stage 4 and stage 5 CKD have some
manifestations of LVH before initiation of dialysis (6). LVH is
recognized as a potent risk factor for cardiovascular death in
dialysis patients (7) and is a strong predictor of myocardial
infarction, cardiac failure, sudden death and stroke (8).
Regression of LVH is associated with a lower incidence of major
cardiovascular events and better survival rate (9). We previously
reported that systolic blood pressure (sBP), residual glomerular
filtration rate (rGFR) and serum albumin levels were predictive
factors for LVMI at initiation of hemodialysis (10). Anemia is a
common complication of CKD patients (11) and usually develops
as a consequence of erythropoietin deficiency. Gouva et al. (12)
reported that early erythropoietin treatment in pre-dialysis
5
patients
with
non-severe
anemia
significantly
slows
the
progression of renal disease and delays the initiation of renal
replacement therapy.
However, few longitudinal analyses have been performed to
investigate the factors associated with change rates (gradients) of
eGFR and left ventricular mass index (LVMI). In the present
study, we designed a retrospective cohort study to identify the
risk factors associated with change rates of eGFR and LVMI in
pre-dialysis CKD patients using multiple regression analysis.
Materials and Methods
Study design and population
A retrospective longitudinal study was performed on 109 CKD
patients before starting dialysis (73 males and 36 females) in
Juntendo University Hospital, Tokyo, Japan. Characteristics of
the 109 patients are summarized in Table 1. The protocol of this
study was in conformity with the ethical guidelines of our
institution. Measurements of biochemical and physical values,
and LVMI evaluated by echocardiography were performed twice
(baseline and follow-up period) from July 2000 to June 2009.
Blood and urine samples were collected at the time of the
echocardiographic study. The clinical, laboratory and urine
parameters were recorded at baseline and in the follow-up period
(21.2± 17.9 months). These parameters were compared by
6
calculating the change rates [ (baseline－follow-up)/ baseline],
and analyzed by univariate analysis and stepwise multivariate
regression analysis. Renal function was determined by estimated
GFR. The estimated (e) GFR was calculated from the serum
creatinine value (s-Cr) and age, using the new Japanese
coefficient 0.808 for modified IDMS-MDRD and the new Japanese
equation: GFR (mL/min/1.73m2)=194×S-Cr-1.094×Age-0.287 (×0.739
if female) (13). We used a modified National Kidney Foundation
classification of CKD (14), which classified eGFR in the following
ranges: 60 to 89 ml/ minute/ 1.73m2 (stage 2 CKD), 30 to 59 ml/
minute/ 1.73m2 (stage 3 CKD), 15 to 29 ml/ minute/ 1.73m2 (stage
4 CKD), and less than 15 ml/ minute/ 1.73m2 (stage 5 CKD). For
the factors associated with progression of renal dysfunction, the
correlation of the change rates of each factor was examined. For
the factors associated with progression of LVMI, the correlation of
the change rates of each factor was examined.
Physical and laboratory examinations
Blood
pressure
(BP)
was
measured
with
a
manual
sphygmomanometer in the sitting position after 5 minutes of rest
before echocardiographic studies or at routine visits to the
outpatient clinic. The laboratory parameters were as follows:
serum creatinine (s-Cre), eGFR, serum albmin (Alb), hemoglobin
(Hb), serum calcium, serum phosphorus (Pi), intact parathyroid
7
hormone (PTH), and the lipid profile [total cholesterol (T-cho), low
density lipoprotein cholesterol (LDL-C), high density lipoprotein
cholesterol (HDL-C)], ferritin and transferrin saturation (TSAT).
TSAT was calculated as [serum iron (Fe) / total iron binding
capacity (TIBC)] ×100(%).
Echocardiography
Echocardiographic
examinations,
i.e.
cardiac
hypertrophy
examination, and two-dimensional and M-mode echocardiography,
were performed using a Toshiba Ultrasound System (model 260
SS-A equipped with a 2.5 MHz phased array transducer, Tokyo,
Japan) in all patients. All examinations on the patients were
performed in the left lateral recumbent position, and all
echocardiographic
data
were
evaluated
according
to
the
guidelines of American Society of Echocardiography（15）. The left
atrial (LA) and ventricular size, intraventricular septal thickness
(IVST), posterior left ventricular wall thickness (PWT) and left
ventricular mass were recorded (16). Left ventricular mass was
corrected by the body surface area and expressed as LVMI (17).
The severity of LVH was assessed by LVMI.
Statistical analyses
All data were expressed as means ± standard deviations (SD).
In this study, statistical analysis was performed by Stat View
8
version 5.0. The differences in the average values between the
groups were analyzed by Student’s t-test for unpaired groups.
Univariate analysis was performed using Student’s t-test or
Fisher’s exact test. Variables with P-values of less than 0.05 were
analyzed using a stepwise linear regression analysis on the basis
of a forward-backward procedure. The F-value for entry or
removal of candidate variables from the discriminant function
was set at 4.0. Repeated ANOVA was performed for comparisons
of serial changes in the clinical data and echocardiographic
parameters. All calculations were performed using Stat View
version 5.0. P< 0.05 was considered as statistically significant.
Results
1). Patient characteristics
The mean values of clinical and laboratory findings of the
patients at baseline and follow-up are shown in Table 2. The
levels of eGFR and Hb at follow-up (eGFR; 16.0±25.0ml/min, Hb;
9.5±2.0mg/dl) were significantly decreased when compared with
those at baseline (24.8±24.5ml/min, p<0.01, 10.0±2.2mg/dl,
p<0.01). The level of Pi at follow-up (4.9±1.2mg/dl) was
significantly higher than that at baseline (4.3±0.9mg/dl) (p<0.01).
The level of total cholesterol at follow-up (183.2±47.5mg/dl) was
significantly lower than that at baseline (199.4±61.4mg/dl)
(p<0.05). The number of antihypertensive drugs increased at
9
follow-up (2.6±1.4) compared with that at baseline (2.2±1.3)
(p<0.05).
2). Factors associated with the change rate of eGFR
Table 3 shows stepwise linear regression analysis of factors
associated with the change rate of eGFR. Age was inversely
correlated with the change rate of eGFR (R=-0.3, p<0.01). The
change rates of sBP, LVMI, the urinary protein/ creatinine ratio,
s-Cr and s-Pi were inversely correlated with those of eGFR. The
change rates of Hb, TSAT and LDL-C were significantly
correlated with that of eGFR (Figure 1). Since it was natural that
s-Cr was correlated with eGFR, multivariate regression analysis
was performed excluding s-Cr. The change rates of Hb and TSAT
were identified as independent risk factors for the change rate of
eGFR in a multivariate regression analysis.
3). Factors associated with the change rate of LVMI
Table 4 shows stepwise linear regression analysis of factors
associated with the change rate of LVMI. The change rates of sBP
and the urinary protein/ creatinine ratio were significantly
correlated with that of LVMI (Figure 2). The change rates of Hb
and eGFR were inversely correlated with those of LVMI (Figure 3).
The change rates of sBP and Hb were identified as independent
risk factors for the change rate of LVMI in a multivariate
10
regression analysis.
Table 4-1 shows univariate analysis of factors associated with
LVMI in improvement group. The change rate of sBP was
significantly correlated with that of LVMI. Table 4-2 shows the
results of stepwise linear regression analysis of factors associated
with LVMI in worsening group. The change rates of sBP, the
urinary protein/ creatinine ratio and Pi were significantly
correlated with that of LVMI while the change rate of Hb was
inversely correlated with that of LVMI. The change rates of sBP,
the urinary protein/ creatinine ratio and Hb were identified as
independent risk factors for the change rate of LVMI in a
multivariate regression analysis.
Discussion
A
previous
study
reported
that
recombinant
human
erythropoietin (rhEPO) therapy improved anemia in pre-dialysis
patients and did not accelerate the rate of progression to end
stage kidney disease (18). Only a few studies on large numbers of
pre-dialysis patients have been performed to investigate factors
associated with the change rate (gradient) of eGFR. The present
results showed that the change rate of Hb is an independent risk
factor for changes in eGFR. In this study, the change rate of TSAT
was significantly correlated with that of eGFR and was identified
as an independent risk factor. These results were supported by
11
the findings of previous studies. Iron deficiency causes anemia in
patients at all stages of CKD. The current Clinical Practice
Guidelines of the National Kidney Foundation Dialysis Outcome
Quality Initiative (NKFK/DOQI) recommend that TSAT should be
maintained at >20% and serum ferritin at >100 ng/ml in order to
achieve adequate hemoglobin and hematocrit levels in CKD
patients receiving rhEPO therapy (19). Another study concluded
that lower serum TSAT (<15%) was associated with higher
mortality and higher serum TSAT (>23%) was associated with
progression of CKD (20).
Previously, some studies reported that treatment of hypertention
inhibited progression of renal dysfunction (21). Previous data
showed that elevated sBP was associated with the development of
LVH in ESKD patients (22). In this study, the change rate of sBP
was inversely correlated with that of eGFR, but it was not
identified as an independent risk factor for eGFR. This may be
due to the fact that there was no significant difference in the sBP
between baseline (141.0±17.6 mmHg) and the follow-up period
(144.0±20.6 mmHg) for treatment with antihypertensive drugs.
The change rate of sBP was identified as an independent risk
factor for changes in LVMI.
Previous studies showed that
treatment of hypertension patially improves LV dilatation and
LVH (30)(31).
Recently, it was reported that systolic arterial
hypertension and elevated pulse pressure are closely associated
12
with LVH in pre-dialysis patients, suggesting that fluid overload
and increased arterial stiffness play important roles in LVH well
before starting dialysis therapy (32).
Levin et al. (4) reported
that increases in age of 5 years and sBP of 5 mmHg were
associated with a 3% increase in risk of LVH. For each 10 g/dl in
Hb, the risk of LVH increased by 6%, and for each 5ml/min decline
in creatinine clearance, the risk increased by 3%. Thus,
hypertension
has
been
consistently
associated
with
cardiovascular morbidity and LVH in CKD patients, and the
results of our study are consistent with those in the literature.
Maintaining low levels of sBP should have beneficial effects on
the course of LVH in CKD patients.
The change rate of Hb was identified as an independent risk
factor for changes in LVMI. Previously, numerous studies
demonstrated a close relationship among anemia, cardiovascular
morbidity and mortality, as well as a relationship between LVH
and anemia. Anemia is considered as one of the uremia-related
factors associated with cardiovascular risk in patients with CKD
(23), but few studies are available on the relationship between
anemia and cardiovascular morbidity and mortality before
starting dialysis treatment. Treatment of anemia improves
survival, decreases morbidity and mortality and increases quality
of life in CKD patients. Partial elimination of anemia in patients
with heart failure and CKD improves cardiac function (24).
13
Previously, it was reported that LVMI was reduced by increases in
Hb (23, 25). Our results were supported by findings of previous
studies evaluating patients with CKD. However, recently the
CHOIR study revealed that a targeted hemoglobin level of 13.5
g/dl was more harmful than 11.3 g/dl in pre-dialysis patients with
CKD and resulted in no incremental improvement in the quality
of life (26). Also, the CREATE study showed that in patients with
stage 3 or stage 4 CKD and mild-to-moderate anemia,
normalization of hemoglobin levels in the range from 13.0 to 15.0
g/dl did not reduce cardiovascular events when compared with the
use of a lower target range (10.5 to 11.5g/dl) (27). Guidelines for
treatment of anemia in CKD patients have existed since 1997 (28),
but the optimal target hemoglobin levels for patients with various
stages of CKD are unclear. Following studies that did not provide
support for these guidelines, the guidelines were revised in 2007
to reset the upper limit target value to 12 g/dl (29). Evidence
concerning the target value of anemia treatment of CKD patients
is not sufficient, especially for the upper limit target value, and
more studies are required. Moreover, it is thought that aggressive
treatment is needed since the level of Hb did not reach the target
value in our study (baseline 10.0±2.2mg/dl, follow-up period
9.5±2.0mg/dl). Our study showed that treatment of anemia should
prevent LVH and progression of renal dysfunction.
In conclusion, it is important to treat renal and iron deficiency
14
anemia to prevent the progression of renal dysfunction in CKD
patients. To prevent LV hypertrophy in CKD patients, renal
anemia, hypertension and proteinuria should be treated. It was
suggested that theses findings may have some therapeutic
implications for treatment strategies in pre-dialysis CKD
patients.
Acknowledgements
We are indebted to the nephrologists and the patients at the
Juntendo university Hospital for their collaboration in this study.
15
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Figure legends
Figure 1: Correlation between change rates of hemoglobin (Hb)
and eGFR
The change rate of Hb was significantly correlated
with that of eGFR.
Figure 2: Correlation between change rates of sBP and LVMI
The change rate of sBP was significantly correlated
with that of LVMI.
Figure 3: Correlation between change rates of Hb and LVMI
The change rate of Hb was inversely correlated with
that of LVMI.
27