(Circulation. 2000;102:3060.)
© 2000 American Heart Association, Inc.
Clinical Investigation and Reports |
Plasma Cytokine Parameters and Mortality in Patients With Chronic Heart Failure
From Clinical Cardiology, National Heart and Lung Institute (M.R., W.D., D.P.F., C.D., J.N., A.J.S.C., S.D.A.), and Biochemistry, Royal Brompton Hospital (M.K., J.H.), London, UK; the Universitätsklinik und Poliklinik für Innere Medizin III, Martin-Luther-Universität (M.R.), Halle, Germany; and the Institut für Medizinische Immunologie, Charité (Campus Mitte) (C.L., H.-D.V.), and Franz-Volhard-Klinik (Charité, Campus Berlin-Buch) am Max-Delbrück Centrum für Molekulare Medizin (S.D.A.), Berlin, Germany.
Correspondence to Mathias Rauchhaus, MD, Universitätsklinik und Poliklinik für Innere Medizin III, Martin-Luther-Universität, Ernst-Grube-Str. 40, 06097 Halle, Germany. E-mail mathias.rauchhaus{at}medizin.uni-halle.de
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Abstract |
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 Top Abstract IntroductionMethodsResultsDiscussionReferences |
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Background—Inflammatory immune activation is an important feature in chronic heart failure (CHF). Little is known about the prognostic importance of tumor necrosis factor-
(TNF-), soluble TNF-receptor 1 and 2
(sTNF-R1/sTNF-R2), interleukin-6 (IL-6), and soluble CD14 receptors
(sCD14) in CHF patients.
Methods and Results—In
152 CHF patients (age 61±1 years, New York Heart Association [NYHA]
class 2.6±0.1, peak
O2
17.3±0.6
mL · kg-1 · min-1,
mean±SEM) plasma concentrations of immune variables were prospectively
assessed. During a mean follow-up of 34 months (>12 months in all
patients), 62 patients (41%) died. Cumulative mortality was 28% at 24
months. In univariate analyses, increased total and trimeric TNF-,
sTNF-R1, and sTNF-R2 (all
P
0.0001), sCD14
(P=0.0007), and IL-6
(P=0.005) predicted 24-month
mortality. With multivariate analysis and receiver operating
characteristics, sTNF-R1 emerged among all cytokine parameters as the
strongest and most accurate prognosticator in this CHF population,
regardless of follow-up duration and independently of NYHA class, peak
O2,
E/CO2
slope, left ventricular ejection fraction, and wasting
(P<0.001). The receiver
operating characteristic area under the curve for sTNF-R1 was greater
than for sTNF-R2 at 6, 12, and 18 months (all
P<0.05).
Conclusions—sTNF-R1 was
the strongest and most accurate prognosticator, independent of
established markers of CHF severity. Assessment of sTNF-R1 may be
useful in identifying patients who are at high risk of death and in
monitoring patients undergoing anti–TNF-
treatment.
Key Words: heart failure • immune system • proteins • prognosis • mortality
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Introduction |
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TopAbstractIntroductionMethodsResultsDiscussionReferences |
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Tumor necrosis factor-
(TNF-) and other proinflammatory cytokine
parameters can be elevated in patients with advanced chronic heart
failure
(CHF).1 2 3
Little is known, however, about the prognostic importance of these
immune markers in CHF. Previous reports on inflammatory cytokines and
cytokine receptors are controversial or refer to short-term follow-up
only.4 5 6
Soluble TNF receptor 1 and 2 (sTNF-R1 and sTNF-R2) have been found to
be particularly high in unstable patients with New York Heart
Association (NYHA) class III and IV who died during 1 month of
follow-up
(P<0.001).7
Plasma concentrations of soluble TNF receptors vary less than those of
TNF- and interleukin-6
(IL-6)8 and appear to reflect
the history of inflammatory immune activation. They may therefore more
closely relate to the patient’s clinical
condition. |
Methods |
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TopAbstractIntroductionMethodsResultsDiscussionReferences |
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Patient Population
Between 1992 and 1998, we consecutively enrolled 152 patients (142 men, 10 women) aged 23 to 85 years into our metabolic study program. The clinical details are given in Table 1
. The diagnosis of CHF was based on standard
criteria.2 In 135 patients,
near-maximal exercise capacity was achieved, as indicated by a
respiratory exchange ratio >1.00 during treadmill exercise testing
with gas exchange analysis (Amis 2000). All patients were receiving
standard medical treatment consisting of diuretics (96%), ACE
inhibitors (91%), digoxin, aspirin, oral nitrates, statins, warfarin,
calcium antagonists, angiotensin II receptor blockers (7%), and
ß-adrenoreceptor antagonists (12%) in various combinations. Patients
were excluded from the study if they had clinical signs of acute
infection, rheumatoid disease, severe renal failure (creatinine >250
µmol/L), or myocardial infarction within the previous 12 months or if
they were suspected of having a malignant or a primary wasting
disorder. The presence of cardiac cachexia (n=44) was diagnosed as
defined previously.9 Sixty
(29%) of the 152 patients were studied before June 1995 and were
included in a previous mortality study that focused on
cachexia.9
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Follow-Up
We planned a minimum follow-up of 12 months in all
patients. This was achieved by outpatient assessments, telephone
contact with the patient or his or her local physician, or through the
Hospital Information System by October 1999. Of the survivors, 26
patients were censored with a follow-up between 1 and 2 years.
Twenty-one patients died between 25 and 75 months and have been
censored for the follow-up of interest. The primary end point of the
study was all-cause mortality.
Laboratory Measurements
Fasting blood samples were collected after supine
rest for 20 minutes. The procedures for collecting blood samples and
assaying EDTA plasma concentrations of sTNF-R1, sTNF-R2, soluble CD14
(sCD14), and total TNF- (ie, trimers and
fragments10 ) have been
described elsewhere.11
Concentrations of trimeric, bioactive
TNF-10 were determined by
the high-sensitivity human TNF- test (R&D Systems, sensitivity 0.18
pg/mL). Plasma concentrations of interleukin-6 (IL-6) were measured by
Immulite (sensitivity 1.0 pg/mL, Random Access Immunoassay Analyzer,
DPC Biermann).
Statistical Analyses
Data are given as mean±SEM. IL-6 and TNF- plasma
concentrations were log-transformed before analysis. The unpaired
Student t test,
2 test, and Cox proportional hazards
analyses were used as appropriate. Hazard ratios (RRs) with 95% CIs
and probability values by the likelihood ratio test are given (StatView
5.0, Abacus Concepts).
To compare different predictive values at a particular time point, areas under the curve (AUCs) for sensitivity and specificity were constructed. The best prognostic cutoff for survival status at a given time point was defined as that which gave the highest product of sensitivity and specificity. To contrast prognostic accuracy, statistical comparison of receiver operating characteristics (ROC)12 was performed (MedCalc, version 5.0, MedCalc Software).
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Results |
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TopAbstractIntroductionMethodsResultsDiscussionReferences |
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Survival
Of the 152 CHF patients, 62 (41%) died after 4 to 2286 days (median 404 days). Mean follow-up period of the 90 survivors was 1355±88 days (range 366 to 2747, median 1114 days). Cumulative mortality rate for all patients was 11% (95% CI 6% to 16%) at 6 months (17 deaths), 20% (95% CI 13% to 26%) at 12 months (30 deaths), 26% (95% CI 19% to 33%) at 18 months (39 deaths), and 27% (95% CI 21% to 35%) at 24 months (41 deaths).
Cytokine Concentrations
Plasma concentrations of the immune markers are
depicted in
Table 1
. Most of the cytokine parameters correlated with
each other significantly, except for the relationship of IL-6 with
trimeric TNF- and sCD14
(r<0.10,
P>0.40). The strongest
relationships were found between sTNF-R1 and sTNF-R2
(r=0.73) and between total
TNF- and trimeric TNF-
(r=0.63, both
P<0.0001). The relationship
between plasma concentrations of sTNF-R1 and NYHA functional class is
illustrated in
Figure 1A.
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Univariate Survival Analyses
Cox proportional hazards analysis showed that
increased concentrations of sTNF-R1
(2=26.1), sTNF-R2
(2=15.1), both total and trimeric TNF-
(2=14.5 and 24.1, respectively, all
P0.0001), sCD14
(2=11.4,
P=0.003), and IL-6
(2=7.9,
P=0.005) predicted 24-month
mortality
(Table 2). Peak
O2
(2=25.5,
P<0.0001, n=135), NYHA class
(2=18.3,
P<0.0001), serum creatinine
(2=14.8,
P<0.0001),
E/CO2
slope (2=12.1,
P=0.0001, n=135), left
ventricular ejection fraction (LVEF)
(2=10.3,
P=0.004, n=130, 26 patients
with LVEF >40%), age (2=7.3,
P=0.009), and the presence of
cardiac cachexia (2=6.5,
P=0.008) were also significant
prognosticators, whereas serum sodium concentration was not
(2=3.1,
P=0.08). Plasma concentrations
of all immune markers within the highest quartile were significantly
predictive for impaired 24-month survival
(Table 2). Highest quartiles of creatinine (>142 µmol/L,
RR=3.64, P<0.0001) and
E/CO2
slope (>43.9, RR=2.49,
P=0.006) and lowest quartiles
of peak
O2
(12.2
mL·kg-1·min-1,
RR 3.43, P=0.0002), LVEF
(17%, RR=2.94, P=0.001), and
serum sodium (135 mmol/L, RR=2.40,
P=0.006) also predicted
increased 24-month mortality. No significance was seen for the highest
quartile of age (>69.6 years, RR=1.39,
P=0.34).
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Multivariate Survival Analyses
sTNF-R1
(P<0.0001), trimeric TNF-
(P<0.0001), IL-6
(P=0.006), and total TNF-
(P=0.02, n=85) predicted
24-month mortality independently of age and peak
O2.
A trend was seen for sCD14
(P=0.06, n=120). In bivariate
Cox proportional hazards analyses with all cytokines, sTNF-R1 emerged
as the strongest mortality-predicting immune parameter
(P<0.001 versus sTNF-R2, total
TNF-, IL-6, and sCD14). Among the cytokine parameters measured, only
trimeric TNF- (P=0.014)
predicted mortality independently of sTNF-R1
(P=0.0015). Trimeric TNF-
also predicted 24-month mortality independently of other cytokine
parameters studied (P<0.001 in
all paired analyses) with the exception of IL-6, which was the only
other significant parameter. Quartiles of sTNF-R1 in relation to
24-month mortality are illustrated in
Figure 1B. CHF patients in the top quartile had a 12-fold
higher risk of death than patients in the lowest quartile (RR=12.34,
95% CI 4.9 to 31.3,
P<0.0001). Clinical variables
that predicted 24-month mortality independently of sTNF-R1 (LVEF, peak
O2,
NYHA functional class, and
E/CO2
slope) are presented in
Table 3.
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In multivariate analysis with sTNF-R1 and clinical
parameters (peak
O2,
E/CO2,
LVEF, and NYHA class), only sTNF-R1
(P<0.0001), LVEF
(P<0.01), and peak
O2
(P<0.01) related to 24-month
mortality independently
(Table 3, analysis 1). The presence of cachexia predicted
24-month mortality independently of peak
O2
and LVEF
(Table 3, analysis 2). However, when sTNF-R1 was added to
these 3 variables, cachexia no longer had independent prognostic value
(analysis 3). The best 3-parameter model for mortality prediction
included sTNF-R1, LVEF, and peak
O2
(joint 2=54.4,
P<0.0001, analysis 4). Age,
serum sodium, and measures of liver and kidney function were not
predictive of mortality in multivariate analyses. After adjustment for
body wasting, differences in drug therapy, or the dose of diuretics,
the principal results did not change. When the group of noncachectic
patients was analyzed alone, sTNF-R1 also revealed the strongest
prognostic power (P<0.0001) in
univariate and multivariate analyses
(Table 4).
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Receiver Operating Characteristics
Sensitivity and specificity for the cytokine
parameters, LVEF, and peak
O2
to predict mortality at 6, 12, 18, and 24 months were assessed across a
range of cutoff values. At all time points, the ROC AUC for mortality
prediction was highest for sTNF-R1 (best cutoff values 1067, 958, 1460,
and 1124 pg/mL, respectively, for 6, 12, 18, and 24 months of
follow-up). (A table giving detailed results on sensitivity,
specificity, and best cutoff values for all parameters can be obtained
from the authors on request.) To illustrate the relationships between
cytokines, soluble receptors, and mortality, Kaplan-Meier survival
curves using the optimal cutoff at 24 months are presented in
Figure 2. The best cutoff value for sTNF-R1 at 24-month
follow-up had 83% sensitivity (95% CI 68% to 93%) and 73%
specificity (95% CI 62% to 82%) to predict mortality (ROC AUC
0.84±0.04, 95% CI 0.78 to 0.91). This was the highest observed ROC
AUC. The ROC AUCs for sTNF-R1 were somewhat larger at all respective
time points than that of peak
O2,
but the differences did not reach significance at any specific time
point (all P>0.19). Compared
with LVEF, prognostic importance of sTNF-R1 increased with time
of follow-up (6, 12, 18, 24 months:
P=0.44,
P=0.19,
P=0.03, and
P=0.01, respectively). sTNF-R1
predicted mortality significantly better than sTNF-R2 at 6 months (AUC
0.78±0.07 versus 0.62±0.08,
P=0.017), 12 months (0.77±0.05
versus 0.63±0.06, P=0.003,
Figure 3), and 18 months of follow-up (0.83±0.04 versus
0.73±0.05, P=0.034). There was
also a trend at 24 months
(P=0.07). At 24 months, the ROC
AUC for sTNF-R1 was significantly larger than that for IL-6
(P=0.0001) and sCD14
(P=0.004), but it was not
significantly different from that of total TNF-
(P=0.09) and was nearly
identical to that of trimeric TNF- (0.80±0.06,
P=0.62). The accuracy of both
TNF- test kits, as assessed by ROC AUCs, was not significantly
different at 6, 12, 18, and 24 months (all
P>0.20).
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Discussion |
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TopAbstractIntroductionMethodsResultsDiscussionReferences |
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Our study reveals that increased plasma concentrations of cytokines and soluble cytokine receptors significantly predict impaired median to longer-term survival in patients with CHF. The best mortality predictive value and accuracy was found for sTNF-R1, which provided the highest sensitivity and specificity among all immune parameters, independently of clinical variables and length of follow-up.
Interleukin-6
Most studied in CHF is the relationship between
mortality and IL-6 plasma concentrations. IL-6 has been linked to CHF
severity,4 13 and
it has been associated with a poor
short-term14 and long-term
clinical
outcome.6 15 In
CHF patients enrolled in PRAISE (Prospective Randomized Amlodipine
Survival Evaluation),5
adverse events occurred somewhat more commonly in patients with higher
IL-6 levels (P=0.07), whereas a
report from the SOLVD treatment trial (Studies Of Left Ventricular
Dysfunction) did not find such a relationship in patients with NYHA
class I to III functional classification
(P=0.72).4
We found, consistent with other
studies,16 17
that IL-6 concentrations were increased mainly in patients with NYHA
class IV (data not shown) and that IL-6 is a significant prognosticator
in univariate analysis
(P=0.005). IL-6, however, lost
its prognostic power (P=0.33)
in multivariate analysis with sTNF-R1
(P<0.0001). Because Cox
proportional hazards analysis assumes normally distributed variables,
IL-6 required transformation. This was not commented on in the
long-term study by Tsutamoto et
al.6 Additionally, in that
study,6 TNF receptors were
not measured, and therefore a comparison between the 2 cytokine
parameters is not possible. Because of a relatively high short-term
variability of IL-6
concentrations,8
interpretation of results may vary between studies. Different methods
of assessing IL-6 plasma concentrations may further complicate
comparisons between studies. Finally, a slightly different genetic
predisposition of an Asian CHF population may contribute to the
impressive prognostic power of IL-6 in the study by Tsutamoto et
al.6
Tumor Necrosis Factor-
For approximately 10 years, it has been known that
TNF- concentrations are raised in patients with severe CHF,
particularly in those with
cachexia.1 2 3
In the SOLVD study,4 TNF-
(R&D ELISA) has been linked to weakly impaired long-term survival in
CHF patients (P=0.07), but NYHA
class IV patients were not included in the assessment. Differences
between studies may be explained by marked daily and weekly variability
of TNF-,8 its short
half-life, and differences between test
kits.18 We found a
relatively good sensitivity and specificity of both total and trimeric
TNF- for predicting clinical outcome. Both TNF- indices predicted
prognosis independently of peak
O2,
and the prognostic value of the 2 TNF- indices did not differ
significantly.
Soluble TNF Receptors
The best overall predictive value for increased
mortality among all the cytokine parameters, across different time
points as well as after restriction of mortality to noncachectic CHF
patients, was found for sTNF-R1. For each 1000-pg/mL increase in
sTNF-R1 concentrations, the mortality hazard increased by 50% (95% CI
50% to 100%).
Like TNF- and IL-6, sTNF receptors are highest in
patients with severe CHF: in NYHA class
IV,7 19 during
phases of edematous
decompensation,20 and in
cachectic CHF patients.21
Moreover, compared with healthy subjects, increased concentrations of
sTNF-R1 are already present in stable, noncachectic patients with mild
CHF.21 sTNF-R1 appears to be
the most powerful and independent immune marker and may well reflect
its longer half-life and lower short-term
variability.8 sTNF-R1 is also
likely to best reflect the history of inflammatory immune activation in
patients with CHF. Previous findings on short-term risk stratification
in CHF patients suggested elevated sTNF-R2 concentrations to be
somewhat better related to poor clinical outcome than those of
sTNF-R1.7 However, the number
of patients in that study7
was relatively small (n=37, 10 deaths), and the difference has not been
tested statistically. In the present study, predictive accuracy of
sTNF-R1 was consistently better than that of sTNF-R2 during follow-up
between 6 and 24 months.
Clinical Implications
The primary goals for the treatment of end-stage
CHF are improvements in survival and in quality of life. To achieve
these goals, treatment needs to be tailored individually. To this end,
prognostic markers that accurately define risk groups are needed. In
the present study, the best mortality-predicting 3-parameter model
included sTNF-R1, LVEF, and peak
O2.
Our study confirms that cachexia predicts prognosis independently of
LVEF and peak
O2
as previously shown.9
However, the "bedside marker" cardiac cachexia lost its independent
prognostic power in multivariate comparison when the humoral marker
sTNF-R1 was included. This was not entirely unexpected, because wasting
is closely associated with immune
activation.2 21
Moreover, a dichotomous marker is very likely to lose significance when
comparison is made with a continuously distributed variable with >4000
degrees of freedom. Additionally, we found a somewhat higher proportion
of cachectic patients in the present study (28.9%) than in a previous
study (16.4%).9 We believe
this does not reflect a selection bias toward patients with wasting,
although we have a strong interest in studying cardiac cachexia. It
may, however, result from our very strict assessment of cachexia in all
CHF patients referred to our center using a semistandardized
questionnaire. Because we perform very detailed metabolic assessments,
we cannot entirely exclude the possibility that more cachectic patients
are being referred to us than to other centers. Most importantly, in
this context, the results of the analyses in noncachectic patients
alone need to be considered
(Table 4). All our findings, particularly with regard to the
importance of sTNF-R1, are still valid when cachectic CHF patients are
excluded.
Our study adds evidence to recent findings that show
neurohormonal and immunologic factors may be of greater prognostic
importance than the more conventional assessments of the hemodynamic
and clinical
status.22 23 This
suggests that immunologic abnormalities are not simply an epiphenomenon
in patients with CHF but that they carry independent pathophysiological
importance that ultimately leads to a prognostic impact on mortality,
which is supported by findings of Meldrum and
coworkers.24 By specifically
targeting TNF- using a TNF receptor/human IgG-fusion protein, one
study has already shown some clinical benefit in a small group of CHF
patients.25 Larger clinical
trials are currently ongoing to examine the effects of antagonizing
TNF- bioactivity.26 It is
hoped that this will demonstrate whether counteracting the TNF-
pathway in patients with moderate to severe CHF in general confers
morbidity and mortality benefits. If this is not the case, then a
well-reproducible measure of inflammatory immune activation with strong
prognostic value (like sTNF-R1) may define patient subgroups likely to
benefit from anti-TNF- therapy.
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Acknowledgments |
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Dr Rauchhaus was supported by grants of the Commission of the European Communities, Brussels, and of the Deutsche Herzstiftung, Frankfurt. Dr Doehner is supported by a grant of the Verein der Freunde und Förderer der Berliner Charité and a PhD studentship of the National Heart & Lung Institute, London. Dr Francis was supported by the British Heart Foundation. Dr Coats is supported by the Viscount Royston Trust and the British Heart Foundation. Dr Anker was supported by the Ernst- und Bertha-Grimmke-Stiftung in Düsseldorf, Germany, and by a postgraduate fellowship of the Max Delbrück Centrum, Berlin. Support was also received from the Royal Brompton & Harefield NHS Trust Joint Committee for Research, London, UK. The authors thank Dr Aidan Bolger for critically reading the manuscript.
Received May 12, 2000; revision received July 26, 2000; accepted August 1, 2000.
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H. Krum and J. J. McMurray Statins and chronic heart failure: do we need a large-scale outcome trial? J. Am. Coll. Cardiol., May 15, 2002; 39(10): 1567 - 1573. [Abstract] [Full Text] [PDF]
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R Sharma and S.D Anker From tissue wasting to cachexia: changes in peripheral blood flow and skeletal musculature Eur. Heart J. Suppl., April 1, 2002; 4(suppl_D): D12 - D17. [Abstract] [PDF]
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W. S. Bradham, B. Bozkurt, H. Gunasinghe, D. Mann, and F. G. Spinale Tumor necrosis factor-alpha and myocardial remodeling in progression of heart failure: a current perspective Cardiovasc Res, March 1, 2002; 53(4): 822 - 830. [Abstract] [Full Text] [PDF]
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R. Kell, A. Haunstetter, T.J. Dengler, C. Zugck, W. Kubler, and M. Haass Do cytokines enable risk stratification to be improved in NYHA functional class III patients?. Comparison with other potential predictors of prognosis Eur. Heart J., January 1, 2002; 23(1): 70 - 78. [Abstract] [Full Text] [PDF]
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A. P. Bolger, R. Sharma, P. Aukrust, L. Gullestad, H. Aass, J. G. Fjeld, L. Wikeby, A. K. Andreassen, H. Ihlen, S. Simonsen, et al. Increase in Anti-Inflammatory Cytokine Levels in Chronic Heart Failure: A Measure of Treatment Success or Failure? Response Circulation, October 30, 2001; 104 (18): e97 - e97. [Full Text] [PDF]
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 G. Zoppini, G. Faccini, M. Muggeo, L. Zenari, G. Falezza, and G. Targher Elevated Plasma Levels of Soluble Receptors of TNF-{alpha} and Their Association with Smoking and Microvascular Complications in Young Adults with Type 1 Diabetes J. Clin. Endocrinol. Metab., August 1, 2001; 86(8): 3805 - 3808. [Abstract] [Full Text] [PDF]
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A. Deswal, N. J. Petersen, A. M. Feldman, J. B. Young, B. G. White, and D. L. Mann Cytokines and Cytokine Receptors in Advanced Heart Failure : An Analysis of the Cytokine Database from the Vesnarinone Trial (VEST) Circulation, April 24, 2001; 103(16): 2055 - 2059. [Abstract] [Full Text] [PDF]
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W. W. Parmley How Many Medicines Do Patients With Heart Failure Need? Circulation, March 27, 2001; 103(12): 1611 - 1612. [Full Text] [PDF]
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