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Klassifikation des kardiorenalen SyndromsDefinition kardiorenales Syndrom (CRS) :Eine pathophysiologische Erkrankung von Herz und Niere, wobei eine akute oder chronische Erkrankung eines Organes die Dysfunktion im anderen Organ verursacht.
CRS Typ I (das akute kardiorenale Syndrom)Akute Verschlechterung der kardialen Funktion (durch kardiogenen Schock oder dekompensierter Herzinsuffizienz) führt zum akuten Nierenversagen (prärenale Azotämie).
CRS Typ II (das chronische kardiorenale Syndrom)Chronische kardiale Dysfunktion (z.B. chronische Herzinsuffizienz) führt zu einer zunehmenden und potentiell chronischen Nierenerkrankung.
CRS Type III (das akute renokardiale Syndrom)Akute Verschlechterung der renalen Funktion (z.B. akute Tubulusnekrose oder Glomerulonephritis) verursacht eine akute kardiale Funktionsstörung (z.B. Herzinsuffizienz, Arrhythmie, kardiale Ischämie)
CRS Typ IV (das chronische renokardiale Syndrom)Chronische Nierenerkrankung (z.B. interstitielle Nephropathie, Glomerulopathie) trägt zu einer eingeschränkten kardialen Pumpfunktion, kardialer Hypertrophie und einem erhöhten Risiko für kardiovaskuläre Ereignisse bei.
CRS Typ V (das sekundäre kardiorenale Syndrom)Systemmanifestation oder –krankheit (z.B. Diabetes, Sepsis, Wegner) verursacht sowohl kardiale als auch renale Manifestationen.
NATURE CLINICAL PRACTICE NEPHROLOGY JUNE 2008 VOL 4 NO 6: 310
Klassifikation des kardiorenalen SyndromsDefinition kardiorenales Syndrom (CRS) :Eine pathophysiologische Erkrankung von Herz und Niere, wobei eine akute oder chronische Erkrankung eines Organes die Dysfunktion im anderen Organ verursacht.
CRS Typ I (das akute kardiorenale Syndrom)Akute Verschlechterung der kardialen Funktion (durch kardiogenen Schock oder dekompensierter Herzinsuffizienz) führt zum akuten Nierenversagen (prärenale Azotämie).
CRS Typ II (das chronische kardiorenale Syndrom)Chronische kardiale Dysfunktion (z.B. chronische Herzinsuffizienz) führt zu einer zunehmenden und potentiell chronischen Nierenerkrankung.
CRS Type III (das akute renokardiale Syndrom)Akute Verschlechterung der renalen Funktion (z.B. akute Tubulusnekrose oder Glomerulonephritis) verursacht eine akute kardiale Funktionsstörung (z.B. Herzinsuffizienz, Arrhythmie, kardiale Ischämie)
CRS Typ IV (das chronische renokardiale Syndrom)Chronische Nierenerkrankung (z.B. interstitielle Nephropathie, Glomerulopathie) trägt zu einer eingeschränkten kardialen Pumpfunktion, kardialer Hypertrophie und einem erhöhten Risiko für kardiovaskuläre Ereignisse bei.
CRS Typ V (das sekundäre kardiorenale Syndrom)Systemmanifestation oder –krankheit (z.B. Diabetes, Sepsis, Wegner) verursacht sowohl kardiale als auch renale Manifestationen.
NATURE CLINICAL PRACTICE NEPHROLOGY JUNE 2008 VOL 4 NO 6: 310
J Am Soc Nephrol 2006;17:2034-2047
All-cause mortality in chronic kidney disease (CKD)
Heart Failure
CVD
Hypertension
General
OtherCKD
Berl, T. et al. Clin J Am Soc Nephrol 2006;1:8-18
Kaplan-Meier estimates of the rates of death at 3 yr from cardiovascular (CV) causes, reinfarction, congestive heart failure (CHF), stroke, resuscitation after cardiac arrest, and the composite end point, according to the estimated GFR
at baseline
Begleiterkrankungen bei Nierenerkrankungen
Stadium 1: > 90%Stadium 2: 60-89%Stadium 3: 30-59%Stadium 4: 15-29%Stadium 5: < 15% oder Dialyse
DM = DiabetesHTN = BluthochdruckCVD = Herz-/ GefäßkrankheitenObesity = FettsuchtSmoking = Rauchen
and other cardiac events) were 59.2% in the inci-dent cohort and 60.2% in the prevalent cohort.
SBP Risk Profiles in the Incident SampleResults of the 1-year Cox models for incident
patients are listed in Table 2. Conventional 1-yearmodels showed a clear association between SBPand death risk. The initial SBP categories ofnormal (SBP ! 120 mm Hg), prehypertension(SBP, 120 to 140 mm Hg), and stage 1 hyperten-sion (SBP, 140 to 160 mm Hg) were associatedwith significant hazard ratios (HRs) of 3.68,1.68, and 1.08 compared with the stage 2 refer-ence group (SBP, 160 to 180 mm Hg). Of pa-tients with higher SBPs, only stage 2"" (SBP !200 mm Hg) was associated with a higher HRthat was not significant statistically. Statisticaladjustment for case-mix with or without BSA didnot alter the findings.
Time-varying models used “time-linked” SBP.HRs increased to 7.42, 2.21, and 1.22 for the 3lower SBP categories of patients and to 1.25 forstage 2"" hypertension, now significantly asso-ciated with risk, respectively. Statistical adjust-ments did not noticeably influence risk patterns.Comparison of the 2 types of Cox models sug-gests that the recent SBP was more important(sensitive) than remote SBP when evaluatingsurvival regardless of whether SBP is normal orvery high. Figure 3 shows risk profiles graphi-cally.
SBP Risk Profiles in the Prevalent SampleResults of the 2 Cox models for prevalent pa-
tients are listed in Table 3, with graphic illustrationsshown in Fig 4. Risk patterns and change in pat-terns from conventional to time-varying Cox mod-els were similar to those observed for incident
Predialysis systolic blood pressure (mmHg)
Fre
qu
ency
(x
1,00
0)
60 80 100 120 140 160 180 200 220 2400
1
2
3
4
5
6
Incident Patients
Predialysis systolic blood pressure (mmHg)
Fre
qu
ency
(x1,
000)
60 80 100 120 140 160 180 200 220 2400
1
2
3
4
5
6
Prevalent Patients
SBPGroup %Patients<120 9.0
120-140 26.0140-160 36.7160-180 21.3180-200 6.1
?200 1.0
SBPGroup %Patients<120 5.7
120-140 20.1140-160 35.6160-180 28.1180-200 9.3
?200 1.2
Fig 1. Distributions of predialysis SBPs in incident and prevalent patient samples.
Incident Patients
Days since day 30 after first hemodialysis
Surv
ival
prob
ablit
y
SBP, mmHg
<120
<140
<160
<180
<200
>=200
0 30 60 90 120 150 180 210 240 270 300 330 3600.5
0.6
0.7
0.8
0.9
1
Prevalent Patients
Days since January 1, 2002
Surv
ival
prob
ablit
y
SBP, mmHg
<120
<140
<160
<180
<200
>=200
0 30 60 90 1201501802102402703003303600.5
0.6
0.7
0.8
0.9
1
Fig 2. One-year survival curves for the initial predialysis SBP categories in incident and prevalent patientsamples.
SBP AND MORTALITY IN HEMODIALYSIS 609
Am J Kidney Dis 48:606-615 BP goal?
lowering with a statin in patients who had diabetes and wereon dialysis (19) did not show a significant reduction in thecomposite outcome of death from cardiac causes, nonfatal myo-cardial infarction, and stroke. An alternative explanation for theinverse association between cholesterol and mortality is a trueprotective effect of higher lipid levels. The hypothesis champi-oned by Rauchhaus et al. (20,21) suggests that binding of lipopro-teins to bacterial endotoxins may result in reduced inflammation;therefore, higher lipoprotein levels may be of benefit. Indeed,contrasting the studies by Liu et al. and Iseki et al., other studies inpatients who were on RRT could not account for the inverseassociation between total cholesterol and mortality by adjustingfor surrogates of MICS (7,8).
It is unclear whether findings from studies of patients who areon dialysis or other patient populations can be extrapolated topatients who have CKD and are not yet on dialysis. In 807 par-ticipants with eGFR of 15 to 60 ml/min per 1.73 m2 from theAtherosclerosis Risk in Communities (ARIC) study, Muntner et al.(22) showed a higher relative risk for incident coronary heartdisease with higher total cholesterol and triglyceride levels, com-
pared with patients with no CKD. Conversely, in 1249 elderlypatients who had moderate CKD (eGFR 50 ! 10 ml/min per 1.73m2) and participated in the Cardiovascular Health Study, none ofthe lipid parameters examined (LDL cholesterol, triglycerides, andHDL cholesterol) was associated with cardiovascular mortality(23). Our study is, to our knowledge, the first to examine associ-ations of all components of the lipid panel with all-cause andcardiovascular mortality in a patient population with moderateand advanced CKD. We examined the associations between singlebaseline values of the components of the lipid panels (fixed-covariate models) but also conducted time-dependent analyses toaccount for the effects of temporal changes in lipid levels, thera-peutic agents, and various clinical and biochemical characteristics,the last yielding similar results to the fixed-covariate models. Wefound that both case-mix characteristics and MICS play a signifi-cant role in the observed inverse association between lipid levelsand mortality. The inverse association between total cholesterol,LDL cholesterol, and triglycerides and mortality was weakenedafter adjustment for case mix and was attenuated further (andmostly rendered nonsignificant) after adjustment for MICS. Wedid not detect interactions with markers of MICS; therefore, we
Figure 1. Hazard ratio (HR; 95% confidence interval [CI]) ofall-cause and cardiovascular mortality associated with variouslevels of total cholesterol in a fixed-covariate Cox model. Adjust-ments were made for age, race, and body mass index (BMI; model1); age, race, BMI, comorbidities, smoking, BP, kidney function,proteinuria, calcium, phosphorus, and medication use (model 2);and age, race, BMI, comorbidities, smoking, BP, kidney function,proteinuria, calcium, phosphorus, medication use, albumin, whiteblood cell (WBC) count, hemoglobin, percentage of lymphocytesin WBC, and bicarbonate (model 3). The group with total choles-terol level of "215 mg/dl served as reference.
Figure 2. HR (95% CI) of all-cause and cardiovascular mortalityassociated with various levels of LDL cholesterol in a fixed-covariate Cox model. Adjustments were made for age, race, andBMI (model 1); age, race, BMI, comorbidities, smoking, BP,kidney function, proteinuria, calcium, phosphorus, and medi-cation use (model 2); and age, race, BMI, comorbidities, smok-ing, BP, kidney function, proteinuria, calcium, phosphorus,medication use, albumin, WBC count, hemoglobin, percentageof lymphocytes in WBC, and bicarbonate (model 3). The groupwith LDL cholesterol level of "135 mg/dl served as reference.
308 Journal of the American Society of Nephrology J Am Soc Nephrol 18: 304–311, 2007
J Am Soc Nephrol 18: 304–311, 2007
inverse epidemiology
•Klassische Risikofaktoren
•Inflammation
•Calcium-Phosphat
•Anämie
Chronische Nierenerkrankungen und Herz- Pathophysiologie
Atherosclerosis — An Inflammatory DiseaseNEJM 1998; 340:115
the modified inflammation composites remained similar tothose presented (data not shown).
Finally, as albumin and WBC count are routinely obtainedin medical practice, we re-defined inflammation composite asbeing in both the upper quartile of race-specific WBC countand the lower quartile of albumin in the CHS cohort,resulting in 472 (8.4%) of individuals defined with inflam-mation. We then defined elevated CRP as 49.0mg l!1
(n" 484, 8.6%) by taking a similar percentage of individuals.There again was significant agreement between inflammationindicators (j-coefficient" 0.16; Po0.001) despite only 23%of individuals with ‘inflammation’ having high CRP. Inmultivariable models, the magnitude of risk associated withthe inflammation composite and elevated CRP was verysimilar (Table 6). Notably in the CKD subgroup, theinflammation composite, but not elevated CRP, was associatedwith cardiac events in multivariable models (HRinflammation"1.41 (1.02, 1.96) versus HRCRP" 1.00 (0.71, 1.39)), althoughhazards for the composite outcome were similar(HRinflammation" 1.26 (1.00, 1.59) versus HRCRP" 1.30(1.04, 1.63)).
DISCUSSIONIn this study, we confirm the association between markersof inflammation and mortality and cardiovascular outcomesin a community-based population, regardless of the presenceor absence of reduced kidney function. In exploring thisrelationship, we found that, although both CKD andinflammation are associated with increased risk of adverseevents, they factors do not exhibit synergy. Additionally, wedemonstrate that, regardless of kidney function, a compositeof reduced serum albumin, elevated fibrinogen, and elevatedWBC count, and a composite of only the more commonmeasures (albumin and WBC count), both predict adverseevents in an elderly population to a degree similar as CRP.
Markers of inflammation have previously been evaluatedin several studies of the general population. CRP, evaluated ina nested case–control study within a subset of AtherosclerosisRisk in Communities Study (ARIC), was a risk factor forcoronary outcomes; however, this effect was attenuated byaccounting for other markers of inflammation, includingWBC count and fibrinogen.13 Other inflammatory markers,including fibrinogen, were evaluated in other studies of the
Table 5 | Inflammation composite and elevated CRP in the subgroup of individuals from CHS
Event n (%) Cardiac 1222 (21.8%) Stroke 688 (12.3%) Death 1878 (33.6%) Composite 2623 (46.9%)
UnivariateInflammation 1.48 (1.31, 1.68) 1.40 (1.18, 1.66) 1.51 (1.37, 1.67) 1.40 (1.28, 1.53)Elevated CRP 1.44 (1.27, 1.63) 1.33 (1.12, 1.58) 1.46 (1.32, 1.62) 1.36 (1.25, 1.49)
MultivariableInflammation 1.28 (1.13, 1.46) 1.22 (1.03, 1.45) 1.25 (1.13, 1.38) 1.20 (1.09, 1.31)Elevated CRP 1.29 (1.13, 1.47) 1.20 (1.01, 1.43) 1.31 (1.18, 1.45) 1.26 (1.15, 1.38)
CHS, Cardiovascular Health Study; CRP, C-reactive protein.The variable, inflammation, refers to having two of the following three characteristics: upper quartile of fibrinogen, upper quartile of race-specific WBC count, and lowerquartile of albumin. For this comparison, elevated CRP X3.6mg l!1.Multivariable models were adjusted for age, sex, race, CKD, cardiovascular disease, diabetes, hypertension, smoking, systolic blood pressure, and non-HDL cholesterol.Education, race, body mass index, and alcohol use were not statistically significant in composite models, and therefore were not included in these multivariable models.
Table 6 | Abbreviated inflammation composite (based only on reduced albumin and elevated WBC count) and elevated CRP inthe subgroup of individuals from CHS
Cardiac Stroke Death Composite
Entire populationUnivariateEvents (%) 1222 (21.8%) 688 (12.3%) 1878 (33.6%) 2623 (46.9%)Inflammation 1.50 (1.25, 1.80) 1.39 (1.09, 1.78) 1.62 (1.41, 1.87) 1.45 (1.28, 1.65)Elevated CRP 1.45 (1.21, 1.73) 1.64 (1.30, 2.06) 1.56 (1.35, 1.80) 1.45 (1.28, 1.64)
MultivariableInflammation 1.36 (1.13, 1.63) 1.23 (0.96, 1.59) 1.34 (1.16, 1.55) 1.28 (1.12, 1.45)Elevated CRP 1.23 (1.02, 1.48) 1.46 (1.16, 1.85) 1.34 (1.16, 1.55) 1.30 (1.15, 1.48)
CKD onlyMultivariableEvents (%) 338 (27.9%) 191 (15.7%) 608 (50.1%) 749 (61.7%)Inflammation 1.41 (1.02, 1.96) 1.41 (0.91, 2.18) 1.10 (0.84, 1.43) 1.26 (1.00, 1.59)Elevated CRP 1.00 (0.71, 1.39) 1.57 (1.05, 2.36) 1.14 (0.89, 1.45) 1.30 (1.04, 1.63)
CHS, Cardiovascular Health Study; CKD, chronic kidney disease; CRP, C-reactive protein; WBC, white blood cell.The variable, inflammation, refers to having both of the following: upper quartile of race-specific WBC count and lowest quartile of albumin among all individuals with CRPlevels.Multivariable models were adjusted for age, sex, race, CKD (or eGFR in CKD only), cardiovascular disease, diabetes, hypertension, smoking, systolic blood pressure, and non-HDL cholesterol. Education, race, body mass index, and alcohol use were not statistically significant in composite models, and therefore were not included in thesemultivariable models.
Kidney International (2008) 73, 1406–1412 1409
DE Weiner et al.: Inflammation, kidney disease, and adverse outcomes o r ig ina l a r t i c l e
CHS, Cardiovascular Health Study; CRP, C-reactive protein. The variable, inflammation, refers to having two of the following three characteristics: upper quartile of fibrinogen, upper quartile of race-specific WBC count, and lower quartile of albumin. For this comparison, elevated CRP X3.6 mg. Multivariable models were adjusted for age, sex, race, CKD, cardiovascular disease, diabetes, hypertension, smoking, systolic blood pressure, and non-HDL cholesterol. Education, race, body mass index, and alcohol use were not statistically significant in composite models, and therefore were not included in these multivariable models.
Kidney International (2008) 73, 1406–1412;
Inflammation and cardiovascular events in individuals with and without chronic kidney disease
No inflammation n=16 819 (82.4%)
Inflammation n=3594 (17.6%)
Braunwald E. N Engl J Med 2008;358:2148-2159
Reported Associations between Heart-Failure Biomarkers and Heart Failure or Death. Panel A shows data pooled for 105 controls and 102 patients with heart failure. Levels of myeloperoxidase were correlated with plasma brain natriuretic peptide (BNP) levels (r=0.39, P<0.001) and with frequency of heart failure (adjusted for age and BNP). Panel B shows the results of the Valsartan Heart Failure Trial (VAL-HeFT) involving 4300 patients with heart failure who were followed for up to 35 months. Mortality increased with increasing BNP and norepinephrine levels measured at baseline; the association was stronger with BNP than with norepinephrine. To convert values for norepinephrine to nanomoles per liter, multiply by 0.005911. Panel A is adapted from Tang et al.; Panel B is adapted from Anand et al.
Reported Associations between Heart-Failure Biomarkers and
Heart Failure or Death
Braunwald E. N Engl J Med 2008;358:2148-2159
Macrophage lipid homeostasis in chronic renal disease
CKD upregulation of scavenger receptors CD36 and SR-A enhances cholesterol uptake whereas downregulation of ABCA1 transporter represses cholesterol efflux that promotes foam cell formation. CKD induces oxidative stress, inflammatory cytokines, and dyslipidemia that may regulate cellular processes involved in macrophage lipid metabolism. Rx, possible therapeutic interventions; oxLDL, oxidized light density lipoprotein; SRA, scavenger receptor A; CD36, scavenger receptor 36; ABCA1, ATP binding cassette transporter A1; ABCG1, ATP binding cassette transporter G1; SRB1, scavenger receptor B1; ApoAI, apolipoprotein AI; HDL, high density lipoprotein; LXR, liver X receptor; RXR, retinoid X receptor; PPAR, peroxisome proliferator-activated receptor; NFκB, nuclear factor kappa B.
Curr Opin Nephrol Hypertens 2009, 18:181
Kidney International 1999;55:648-658
280 HD Patienten
- Pathophysiologie des sekundären Hyperparathyreoidismus -
GFR
Ca x HP04
Weichteil-verkalkungen
1α-Hydroxylase
1,25(OH)2D3 = Calcitriol
Ca++
PTH
P04
Parenchym
25(OH)2D3
Calcium-Phosphat-Haushalt bei Niereninsuffizienz
Kalzifizierende urämische Arteriolopathie
AJKD 1998;32:391
Association between mineral metabolism disturbances and risk of mortality and CV events in CKD 1519
Table 7. Summary of results of studies analysing the risk of CV morbidity with changes in mineral metabolism parameters
Study Type of Type of cardiac Mineral metabolism Method of Levels CV morbidity P-valuedialysis morbidity variable assessment
RR HR OR
Stack, 2001 [56] HD/PD Cardiac failure Calcium (mg/dL) Dichotomous <8 1!8 1.41 <0.01
Phosphorus (mg/dL) <6.8 1!6.8 1.34 <0.01
Foley, 1996 [22] HD/PD Cardiac failure(de novo)
Calcium (mg/dL) Dichotomous >8.8 1
"8.8 2.43 0.068Cardiac failure
(recurrent)>8.8 1
"8.8 2.66 0.008Slinin, 2005 [36] HD Overall CV events Phosphorus (mg/dL) "4.4 1
4.5–5.3 1.06 <0.055.4–6.3 1.13 <0.00016.4–7.5 1.14 <0.0001>7.5 1.25 <0.0001
PTH (pg/mL) "37 138–99 1.03 NS
Categorical 100–210 1.04 NS211–480 1.04 NS>480 1.12 <0.05
Calcium (mg/dL) "8.7 18.8–9.2 1.03 NS9.3–9.6 1.04 NS9.7–10.2 1.03 NS>10.2 1.08 <0.05
Kestenbaum, CKD Myocardial Phosphorus (mg/dL) Continuous Risk per increase 1.35 <0.052005 [26] infarction of 1 mg/dL
CKD, chronic kidney disease; CV, cardiovascular; HD, haemodialysis; HR, hazard ratio; OR, odds ratio; PD, peritoneal dialysis; PTH, parathyroidhormone; RR, risk ratio.
Table 8. Variations in the method of mineral parameter assessment and risk measurements across the identified studies
Outcome of interest Method of mineral parameter assessment (number of studies) Method of riskestimation
Categorical Dichotomous Continuous Categorical and Dichotomous and Categorical, RR HR ORcontinuous continuous continuous,
dichotomous
All-cause mortality (n = 22) 7 6 7 1 0 1 14 8 0CV mortality (n = 8) 0 2 5 0 1 0 6 2 0CV events (n = 4) 1 2 1 0 0 0 1 2 1
the threshold level at which the risk begins to increase andtends to force a linear relationship between mineral param-eters and outcome risk. Dichotomous analysis prevents thecomparability of results across studies. However, fewer thanhalf of the observational studies evaluated mineral parame-ters categorically (n = 9). A large sample used continuousonly (n = 10), dichotomous only (n = 7) or both (n = 1).The mineral levels used as a reference in calculating risklacked consistency, thus further limiting the ability to com-pare results across studies. Table 8 describes the variationsin method of mineral parameter assessment and risk calcu-lation across studies.
In spite of this heterogeneity, the review identified a sig-nificant relationship between mineral parameters and all-cause mortality, CV mortality and CV events in dialysispatients. However, data on risk of outcomes in pre-dialysispatients was less conclusive due to limited evidence. Data
supports a greater mortality risk with phosphorus followedby calcium and PTH. All but one study assessing phospho-rus showed a significant all-cause mortality risk. However,the strong association may be due to ‘negative publicationbias’. In contrast, the risk of mortality with calcium andPTH was significant in only six of nine studies and sevenof eleven studies, respectively. No significant relationshipwas observed between low PTH levels and risk of all-causemortality. However, a recent cross-sectional study by Nakaiet al. [57] observed a significantly lower risk of all-causemortality with low PTH levels at a threshold level of 60–119 pg/mL as compared to the reference level of 180–359 pg/mL (HR = 0.891; P = 0.0173). This finding maybe attributed to utilization of baseline PTH levels insteadof time-dependent PTH levels in the measurement of mor-tality risk and misclassification of mineral parameter lev-els due to the cross-sectional nature of the database. The
CKD, chronic kidney disease; CV, cardiovascular; HD, haemodialysis; HR, hazard ratio; OR, odds ratio; PD, peritoneal dialysis; PTH, parathyroid hormone; RR, risk ratio.
Nephrol Dial Transplant (2009) 24: 1506–1523
Possible Mechanisms
Involved in the Genesis of
Anemia in Heart Failure
Anand, I. S. J Am Coll Cardiol 2008;52:501-511
Possible Sequence of Events Involved
in the Pathogenesis of Heart Failure in Chronic Severe
Anemia
Anand, I. S. J Am Coll Cardiol 2008;52:501-511
Summary of All Published Studies That Have Tested the Effects of Erythropoietin-Stimulating Agents in Anemic Patients With HF
Table 1 Summary of All Published Studies That Have Tested the Effects of Erythropoietin-Stimulating Agents in Anemic Patients With HF
Author,Year (Ref. #) Study Design Inclusion Criteria
Patients(n)
Follow-UpDuration(months)
BaselineHgb
(g/dl)
TargetHgb
(g/dl)Achieved Hgb
(g/dl)Agents andDose Used Outcomes
Silverberg et al.,2000 (65)
Single-center,uncontrolled,open-label
EF !35, Hgb !12 g/dl 26 7.2 " 5.5 10.2 12.0 12.1 S/C epoetin alfa (mean5,277 IU/week) # IViron sucrose (mean185 mg/month)
2NYHA functional class (3.7 " 0.5 to 2.7 " 0.7,p ! 0.05),1LVEF (28 " 5% to35 " 8%, p ! 0.001)
Decrease in diuretic doseDecrease in hospitalizations
Silverberg et al.,2001 (66)
Single-center,randomized,no placebo,open-label
NYHA functional classIII/IV, EF !40%,Hgb 10–11.5 g/dl
16 usual care,16 EPO
8.2 " 2.6 10.3 12.5 12.9 S/C epoetin alfa (4,000IU 1–3$ week) IV ironsucrose (200 mg/2$weeks)
2NYHA functional class,1LVEF #5.5%Decrease in diuretic doseDecrease in hospitalizations
Mancini et al.,2003 (67)
Single-center,single-blind,randomized,placebo-controlled
NYHA functional classII/IV, Hct !35%,
9 control, 17 EPO 3.0 11.0 " 0.6 Hct %45% 14.3 " 1.2 S/C epoetin alfa 15,000to 30,000 IU/ week #oral iron 325 mg andfolate 1 mg OD
1Peak VO2 11 " 0.8 to 12.7 " 2.8 ml/kg/min(p ! 0.05),16MWD
Improvement in MLHFQ
Palazzuoli et al.,2007 (68)
Single-center,randomized,double-blind,placebo-controlled
NYHA functional classIII/IV, EF !40%,Hgb 9.0–12.0 g/dl,serum creatinine1.5–3.0 mg/dl
25 control,26 beta EPO
12 10.4 " 0.6 NA 12.4 " 0.8 S/C epoetin beta 6,000IU/2$ week # oral iron300 mg for 1 year
1LVEF,2LV volumes, mass2PAP and BNPNo change in serum creatinine
Ponikowski et al.,2007 (69)
Multicenter,randomized,double-blind,placebo-controlled
Hgb 9.0–12.0 g/dl,peak VO2 !16ml/kg/min
22 placebo,19 darbepoetin
27 weeks 11.8 " 0.2 13.0–15.0 13.9 " 0.4 Darbepoetin alfa, 0.75!g/kg Q2W #200–300 oral iron ifserum ferritin!800 ng/ml
Mean change in peak Vo2 (45 ml/min,p & 0.27) or (0.5 ml/kg/min, p & 0.40)Ex duration 108 s (p & 0.08),1PGA(79% vs. 41%, p & 0.01)
No change in KCCQ/MLHFQNo change in BNP or Cr
van Veldhuisen et al.,2007 (70)
Multicenter,randomized,double-blind,placebo-controlled
Hgb %9.0 and!12.5 g/dl, NYHAfunctional class II/IIICHF, LVEF !40%
55 placebo,56 darbepoetin(weight based),and 54darbepoetin(fixed dose)
27 weeks 11.5 14 " 1.0 13.3 Darbepoetin weightadjusted 0.75 !g/kgvs. fixed dose 50 !gvs. placebo Q2W #oral iron (200 mg ODif serum ferritin!800 ng/ml)
Rate of rise Hgb 1.87 vs. 1.64 g/dl in weight-based vs. fixed dose (p & 0.07), improvementin KCCQ (p ! 0.03), no significantimprovement in 6MWD (p & 0.074), patientsglobal assessment (p & 0.057), NYHAfunctional class, LVEF, or MLHFQ score
Ghali et al., 2008(STAMINA-HeFT)(71)
Multicenter,randomized,double-blind,placebo-controlled
Hgb %9.0 and!12.5 g/dl, NYHAfunctional class II/IVCHF, LVEF !40%,
157 placebo,162 darbepoetin
27 weeks forefficacy 55weeks forsafety
11.4 14 " 1.0 13.4 at27 weeks,13.4 at53 weeks
Darbepoetin dose 0.75!g/kg Q2W vs. placebo# oral iron (200 mg ODif serum ferritin!800 ng/ml)
No significant difference in exercise duration,NYHA functional class or quality of life scoresat 27 weeks but trend to a decrease in thecombined end point of death andhospitalization for HF
van Veldhuisen andMcMurray 2007(72)
Combined safetyanalysis
Hgb %9.0 and!12.5 g/dl, NYHAfunctional class II/IIICHF, LVEF !40%
209 placebo,266 darbepoetin
55 weeks 11.4 " 0.8 14 " 1.0 13.4 Darbepoetin dose 0.75!g/kg or 50 !g vs.placebo Q2W # oraliron (200 mg ODif serum ferritin!800 ng/ml)
Trend to a decrease in the combined endpoint ofdeath and hospitalization for HF (hazard ratio)and 95% confidence interval) for darbepoetinvs. placebo 0.67 (0.44 to 1.03), p & 0.06
CHF & congestive heart failulre; EF & ejection fraction; EPO & epoetin; Hct & hematocrit; HF & heart failure; Hgb & hemoglobulin; IV & intravenous; KCCQ & Kansas City Cardiomyopathy Questionnaire; LV & left ventricular; MLHFQ & Minnesota Living with Heart FailureQuestionnaire; NYHA & New York Heart Association; OD & once daily; PAP & systolic pulmonary artery pressure; PGA & Patient’s Global Assessment; Q2W & every 2 weeks; S/C & subcutaneous; 6MWD & 6-min walk distance.
506Anand
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andChronic
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Studie N Abnahme der Follow-up
LV-Masse (%) in Monat.
Silberberg 22 16 10
Goldberg 15 30 6
Löw-Friedrich 25 11 4
Pascual 15 34 12
Martinez-Vea 9 25 24
London 11 18 6
Macdougall 10 28 12
Abnahme der linksventrikulären Masse unter EPO-Therapie
Am J Kid Dis 1995; 25; Suppl 1: S3-S7
