[1]
Ng JK, Li PK. Chronic kidney disease epidemic: How do we deal with it? Nephrology
(Carlton) 2018; 4: 116–120.
[2]
Tanaka K, Jujo K, Yamaguchi Y, Ogawa H. Hagiwara N. Optimal blood pressure in
patients with coronary artery disease and chronic kidney disease: HIJ-CREATE
substudy. Am J Med Sci 2019; 358: 219-226.
[3]
Jhund PS, Solomon SD, Docherty KF, Heerspink HJL, Anand IS, Böhm M, et al.
Efficacy of dapagliflozin on renal function and outcomes in patients with heart failure
with reduced ejection fraction: results of DAPA-HF. Circulation; 2021;143: 298–309.
[4]
Patel RB, Mehta R, Redfield MM, Borlaug BA, Hernandez AF, Shah SJ, et al. Renal
dysfunction in heart failure with preserved ejection fraction: insights from the RELAX
Trial. J Card Fail 2020; 26: 233–242.
[5]
Takaya Y, Kumasaka R, Arakawa T, Ohara T, Nakanishi M, Noguchi T, et al. Impact
of cardiac rehabilitation on renal function in patients with and without chronic kidney
disease after acute myocardial infarction. Circ J 2014; 78: 377-384.
[6]
Scrutinio D, Agostoni P, Gesualdo L, Corrà U, Mezzani A, Piepoli M, et al. Metabolic
Exercise test data combined with Cardiac and Kidney Indexes (MECKI) Score
Research Group. Renal function and peak exercise oxygen consumption in chronic
heart failure with reduced left ventricular ejection fraction, Circ. J. 79 (2015) 583–591.
[7]
Ezzatvar Y, Izquierdo M, Núñez J, Calatayud J, Ramírez-Vélez R, García-Hermoso A.
Cardiorespiratory fitness measured with cardiopulmonary exercise testing and
mortality in patients with cardiovascular disease: a systematic review and metaanalysis. J Sport Health Sci 2021; 10: 609–619.
[8]
Cahalin LP, Chase P, Arena R, Myers J, Bensimhon D, Peberdy MA, et al. A metaanalysis of the prognostic significance of cardiopulmonary exercise testing in patients
with heart failure. Heart Fail Rev 2013; 18: 79–94.
[9]
Del Buono MG, Arena R, Borlaug BA, Carbone S, Canada JM, Kirkman DL, et al.
Exercise intolerance in patients with heart failure: JACC State-of-the-Art Review. J
Am Coll Cardiol 2019; 73: 2209–2225.
[10]
Van Craenenbroeck AH, Van Craenenbroeck EM, Van Ackeren K, Hoymans VY,
Verpooten GA, Vrints CJ, et al. Impaired vascular function contributes to exercise
intolerance in chronic kidney disease. Nephrol Dial Transplant 2016; 31: 2064–2072.
[11]
Ronco C, Bellasi A, Lullo LD. Cardiorenal syndrome: an overview. Adv Chronic
Kidney Dis 2018; 25: 382–390.
[12]
Chinnappa S, Lewis N, Baldo O, Shih MC, Tu YK, Mooneyet A. Cardiac and
noncardiac determinants of exercise capacity in CKD. J Am Soc Nephrol 2021; 32:
1813–1822..
[13]
Binder RK, Wonisch M, Corra U, Cohen-Solal A, Vanhees L, Saner H, et al.
Methodological approach to the first and second lactate threshold in incremental
cardiopulmonary exercise testing. Eur J Cardiovasc Prev Rehabil 2008; 15: 726–734.
[14]
Salvadori A, Fanari P, Mazza P, Agosti R, Longhini E. Work capacity and
cardiopulmonary adaptation of the obese subject during exercise testing. Chest 1992;
101:674–679.
[15]
Baumbach P, Schmidt-Winter C, Hoefer J, Derlien S, Best N, Herbsleb M, et al. A
pilot study on the association of mitochondrial oxygen metabolism and gas exchange
during cardiopulmonary exercise testing: Is there a mitochondrial threshold? Front
Med (Lausanne) 2020; 7: 585462.
[16]
Ogura A, Izawa KP, Sato S, Tawa H, Kureha F, Wada M, Kanai M, Kubo I, Brubaker
PH, Yoshikawa R, Matsuda Y. Relationship of end-tidal oxygen partial pressure to the
determinants of anaerobic threshold in post-myocardial infarction patients. Heart
Vessels 2021; 36: 1811–1817.
[17]
Balady GJ, Arena R, Sietsema K, Myers J, Coke L, Fletcher GF, et al. American Heart
Association Exercise, Cardiac Rehabilitation, and Prevention Committee of the
Council on Clinical Cardiology; Council on Epidemiology and Prevention; Council on
Peripheral Vascular Disease; Interdisciplinary Council on Quality of Care and
Outcomes Research. Clinician’s guide to cardiopulmonary exercise testing in adults: a
scientific statement from the American Heart Association. Circulation 2010; 122: 191–
255.
[18]
L.S. Pescatello. ACSM’s Guidelines for Exercise Testing and Prescription.
Philadelphia: Wolters Kluwer/Lippincott Williams & Wilkins Health, 2014:151.
[19]
Matsuo S, Imai E, Horio M, Yasuda Y, Tomita K, Nitta K, et al. Collaborators
developing the Japanese equation for estimated GFR. Revised equation for estimated
GFR from serum creatinine in Japan. Am J Kidney Dis 2009; 53: 982–992.
[20]
Kidney Disease: Improving Global Outcomes (KDIGO) Acute Kidney Injury Work
Group, KDIGO clinical practice guideline for acute kidney injury. Kidney Int 2012; 2:
1–138.
[21]
McCullough PA, Franklin BA, Leifer E, Fonarow GC. Impact of reduced kidney
function on cardiopulmonary fitness in patients with systolic heart failure. Am J
Nephrol 2010; 32: 226–233.
[22]
Kinugawa S, Takada S, Matsushima S, Okita K, Tsutsui H. Skeletal muscle
abnormalities in heart failure. Int Heart J 2015; 56: 475–484
[23]
Keshavarz-Bahaghighat H, Darwesh AM, Sosnowski DK, Seubert JM. Mitochondrial
dysfunction and inflammaging in heart failure: novel roles of CYP-derived
epoxylipids. Cells 2020; 9: 1565.
[24]
Poznyak AV, Ivanova EA, Sobenin IA, Yet SF, Orekhov AN. The role of mitochondria
in cardiovascular diseases. Biology (Basel) 2020; 9: 137.
[25]
Yokoi H, Yanagita M, Decrease of muscle volume in chronic kidney disease: the role
of mitochondria in skeletal muscle. Kidney Int 2014; 85: 1258–1260.
[26]
Alcalde-Estévez E, Sosa P, Asenjo-Bueno A, Plaza P, Olmos G, Naves-Díaz M, ey al.
Uraemic toxins impair skeletal muscle regeneration by inhibiting myoblast
proliferation, reducing myogenic differentiation, and promoting muscular fibrosis. Sci
Rep 2021; 11: 512.
[27]
Yazdi PG, Moradi H, Yang JY, Wang PH, Vaziri ND. Skeletal muscle mitochondrial
depletion and dysfunction in chronic kidney disease. Int J Clin Exp Med 2013; 6: 532–
539.
[28]
Adey D, Kumar R, McCarthy JT, Nair KS. Reduced synthesis of muscle proteins in
chronic renal failure. Am J Physiol Endocrinol Metab 2000; 278: E219–E225.
[29]
Roibal Pravio J, Barge Caballero E, Barbeito Caamaño C, Paniagua Martin MJ, Barge
Caballero G, Couto Mallon D, et al. Determinants of maximal oxygen uptake in
patients with heart failure. ESC Heart Fail 2021; 8: 2002–2008.
[30]
Guimarães GV, Ribeiro F, Castro RE, Roque JM, Machado ADT, Antunes-Correa LM,
et al. Effects of the exercise training on skeletal muscle oxygen consumption in heart
failure patients with reduced ejection fraction. Int J Cardiol 2021; 343: 73–79.
[31]
Tedeschi A, Agostoni P, Pezzuto B, Corra' U, Scrutinio D, La Gioia R, et al. Role of
comorbidities in heart failure prognosis Part 2: Chronic kidney disease, elevated serum
uric acid. Eur J Prev Cardiol 2020; 27: 35–45.
[32]
Zhang S, Zhang F, Du M, Huang K, Wang C. Efficacy and safety of iron
supplementation in patients with heart failure and iron deficiency: a meta-analysis. Br
J Nutr 2019; 121: 841-848.
[33]
Mafra D, Gidlund EK, Borges NA, Magliano DC, Lindholm B, Stenvinkel P, et al.
Bioactive food and exercise in chronic kidney disease: Targeting the mitochondria.
Eur J Clin Invest 2018; 48: e13020.
[34]
Gu C, Yan J, Zhao L, Wu G, Wang YL. Regulation of mitochondrial dynamics by
aerobic exercise in cardiovascular diseases. Front Cardiovasc Med 2022; 13:788505.
[35]
Cardoso AL, Fernandes A, Aguilar-Pimentel JA, de Angelis MH, Guedes JR, Brito
MA, et al. Towards frailty biomarkers: Candidates from genes and pathways regulated
in aging and age-related diseases. Ageing Res Rev 2018; 47: 214–277.
[36]
Kameda M, Teruya T, Yanagida M, Kondoh H. Reduced uremic metabolites are
prominent feature of sarcopenia, distinct from antioxidative markers for frailty. Aging
(Albany NY) 2021; 13: 20915–20934.
[37]
Potok OA, Ix JH, Shlipak MG, Katz R, Hawfield AT, Rocco MV, et al. The difference
between cystatin C- and creatinine-based estimated GFR and associations with frailty
and adverse outcomes: a cohort analysis of the systolic blood pressure intervention
trial (SPRINT). Am J Kidney Dis 2020; 76: 765–774.
[38]
Damman K, Testani JM. The kidney in heart failure: an update. Eur Heart J 2015; 36:
1437–1444.
Gu C, Yan J, Zhao L, Wu G, Wang YL. Regulation of mitochondrial dynamics by
aerobic exercise in cardiovascular diseases. Front Cardiovasc Med 2022; 13:788505.
Table 1
Patient characteristics and CPET parameters.
eGFR <45
eGFR 45–59
eGFR ≥60
(n=30)
(n=59)
(n=112)
Age, years
71.4 ± 7.7
67.8 ± 7.8
Male, n (%)
29 (96.7)
Body mass index, kg/m2
P- value
eGFR <45 vs.
eGFR 45–59 vs.
eGFR <45 vs.
eGFR 45–59
eGFR ≥60
eGFR ≥60
61.2 ± 10.8
0.300
<0.001
<0.0001
50 (84.7)
104 (92.9)
0.46
0.33
23.2 ± 2.8
23.1 ± 3.2
23.8 ± 2.9
0.45
0.88
MI, n (%)
19 (63.3)
43 (72.9)
86 (76.8)
0.63
AP, n (%)
0 (0)
4 (6.8)
16 (14.3)
0.887
0.632
0.071
CHF, n (%)
24 (80.0)
19 (32.2)
25 (22.3)
<0.001
0.666
<0.001
LVEF, (%)
51.2 (38.9–54.4)
58.7 (49.0–65.4)
59.3 (51.5–68.2)
0.090
0.384
<0.001
Hypertension, n (%)
24 (80.0)
36 (61.0)
74 (66.1)
0.35
0.64
Diabetes, n (%)
17 (56.7)
20 (33.9)
36 (32.1)
0.201
0.073
36.8 (32.2–40.5)
54.6 (51.7–57.0)
71.2 (65.2–80.0)
<0.001
<0.001
<0.001
12.7 ± 1.8
13.3 ± 1.5
14.2 ± 1.3
0.221
<0.001
<0.001
Beta blockers, n (%)
23 (76.7)
45 (77.6)
72 (64.9)
0.38
0.95
ACE-I, n (%)
8 (26.7)
9 (15.3)
33 (29.5)
0.94
0.19
ARB, n (%)
15 (50.0)
24 (40.7)
39 (34.8)
0.57
CCB, n (%)
9 (30.0)
6 (10.2)
21 (18.8)
0.12
0.64
0.83
Diuretics, n (%)
19 (63.3)
16 (27.1)
14 (12.5)
0.006
0.088
<0.001
Statin, n (%)
19 (63.3)
49 (83.1)
95 (84.8)
0.212
0.054
16.2 ± 3.9
19.7 ± 4.7
23.0 ± 4.5
0.002
<0.001
<0.001
70.6 ± 16.4
82.8 ± 18.7
92.8 ± 19.0
0.011
0.003
<0.001
10.9 ± 2.1
12.4 ± 2.5
14.0 ± 2.6
0.029
<0.001
<0.001
Peak RER
1.20 ± 0.05
1.20 ± 0.06
1.18 ± 0.06
0.086
0.382
AT RER
0.96 ± 0.02
0.96 ± 0.03
0.95 ± 0.04
0.14
0.11
Peak WR, watts
VE vs. VCO2 slope
． ．
Minimum VE/VCO2
86.2 ± 17.2
102.3 ± 28.6
122.9 ± 28.3
0.028
<0.001
<0.001
33.9 (30.8–38.5)
30.6 (27.9–33.5)
29.2 (26.3–31.7)
0.007
0.137
<0.001
36.1 (33.5–39.9)
33.9 (30.9–37.4)
30.8 (28.8–34.5)
0.173
0.002
<0.001
8.6 ± 2.0
9.6 ± 2.5
11.1 ± 2.2
0.181
<0.001
<0.001
8.1 ± 1.6
8.8 ± 1.4
9.4 ± 1.3
0.051
0.030
<0.001
Laboratory values
eGFR, mL/min/1.73m2
Hemoglobin, g/dL
Medications
CPET parameters
Peak VO2, mL/min/kg
%Peak VO2, %
AT VO2, mL/min/kg
Peak O2 pulse
ΔVO2/ΔWR
Rest PETO2, mmHg
107.2 ± 5.5
107.8 ± 4.9
108.1 ± 4.2
0.88
AT PETO2, mmHg
107.1 ± 5.4
105.0 ± 5.5
102.4 ± 4.7
0.216
0.004
<0.001
0.1 (-1.1–1.4)
2.4 (0.8–4.0)
5.2 (3.7–7.4)
<0.001
<0.001
<0.001
ΔPETO2, mmHg
CPET, cardiopulmonary exercise testing; eGFR, estimated glomerular filtration rate; MI, myocardial infarction; AP, angina pectoris; CHF,
chronic heart failure; LVEF, left ventricular ejection fraction; ACE-I, angiotensin converting enzyme inhibitor; ARB, angiotensin II
receptor blocker; CCB, calcium channel blocker; VO2, oxygen uptake; AT, anaerobic threshold; RER, respiratory exchange ratio; WR,
． ．
work rate; VE, expiratory minute volume; VCO2, carbon dioxide output; VE/VCO2, ventilatory equivalent for carbon dioxide; O2, oxygen;
PETO2, end-tidal oxygen partial pressure.
Values shown are % (n), mean ± standard deviation, or median (interquartile range).
Table 2
Univariate and multivariate linear regression analyses for peak VO2 in all subjects.
Univariate
Multivariate
P-value
95% CI
P-value
Age
-0.451
<0.001
-0.142
-0.128, -0.009
0.023
LVEF
0.113
<0.001
0.150
0.018, 0.110
0.006
eGFR strata
0.508
<0.001
0.154
0.128, 2.000
0.026
Hb
0.148
<0.001
0.167
0.164, 0.914
0.005
ΔPETO2
0.552
<0.001
0.356
0.308, 0.690
<0.001
Rest PETO2
0.121
0.020
-0.194
-0.335, -0.092
<0.001
R2
0.462
VO2, oxygen uptake; CI, confidence interval; LVEF, left ventricular ejection fraction; eGFR, estimated
glomerular filtration rate; Hb, hemoglobin; PETO2, end-tidal oxygen partial pressure.
Table 3
Univariate and multivariate linear regression analyses for peak VO2 by eGFR strata.
Univariate
P-value
Age
-0.358
0.052
LVEF
0.572
Hb
Multivariate
95% CI
P-value
<0.001
0.518
0.086, 0.229
<0.001
0.616
<0.001
0.567
0.728, 1.766
<0.001
ΔPETO2
0.175
0.356
Rest PETO2
0.121
0.059
eGFR <45 group
R2
0.620
eGFR 45–59 group
-0.354
-0.297, -0.052
0.006
0.004
0.258
0.241, 1.449
0.007
0.523
<0.001
0.501
0.402, 1.013
<0.001
0.062
0.058
-0.181
-0.384, -0.016
0.035
Age
-0.521
<0.001
LVEF
0.183
0.166
Hb
0.365
ΔPETO2
Rest PETO2
R2
0.538
eGFR ≥60 group
Age
-0.236
0.012
-0.215
-0.140, 0.017
0.125
LVEF
0.198
0.036
0.146
-0.014, 0.137
0.113
Hb
0.078
0.416
ΔPETO2
0.314
<0.001
0.308
0.154, 0.716
0.003
Rest PETO2
0.036
0.045
-0.193
-0.154, -0.013
0.037
R2
0.194
VO2, oxygen uptake; CI, confidence interval; eGFR, estimated glomerular filtration rate; LVEF, left ventricular
ejection fraction; Hb, hemoglobin; PETO2, end-tidal oxygen partial pressure.
Figure 1. Comparison of the change in end-tidal oxygen partial pressure (ΔPETO2) at
different values of estimated glomerular filtration rate (eGFR).
Figure 2. Coefficients of determination for peak V̇O2 for each group. Coefficients of
determination of the (a) age, (b) left ventricular ejection fraction (LVEF), (c) hemoglobin
(Hb), and (d) change in end-tidal oxygen partial pressure (∆PETO2) to peak V̇O2 for each
group.
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