Exercise Limitation after Critical versus Mild COVID-19 Infection: A Metabolic Perspective
Abstract
:1. Introduction
2. Materials and Methods
2.1. Patients and Data Sources
2.1.1. COVID-19 ARDS Survivors (ICU Group)
2.1.2. Patients with Long COVID after a Mild Infection (MLC Group)
2.1.3. Obese Patients (OB Group)
2.2. Cardiopulmonary Exercise Testing (CPET)
2.3. Biological Parameters of Critically Ill Survivors at M3
2.4. Statistical Analyses
3. Results
3.1. Patients’ Flow
3.2. Patients’ Characteristics
3.3. CPET and Biological Correlates in the ICU Group
3.4. Comparison of CPET Data between the ICU Group and the MLC Group
3.5. Comparison of CPET Data between ICU Group and OB Group
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Nalbandian, A.; Sehgal, K.; Gupta, A.; Madhavan, M.V.; McGroder, C.; Stevens, J.S.; Cook, J.R.; Nordvig, A.S.; Shalev, D.; Sehrawat, T.S.; et al. Post-acute COVID-19 syndrome. Nat. Med. 2021, 27, 601–615. [Google Scholar] [CrossRef] [PubMed]
- Yong, S.J. Long COVID or post-COVID-19 syndrome: Putative pathophysiology, risk factors, and treatments. Infect. Dis. 2021, 53, 737–754. [Google Scholar] [CrossRef] [PubMed]
- Chen, C.; Haupert, S.R.; Zimmermann, L.; Shi, X.; Fritsche, L.G.; Mukherjee, B. Global Prevalence of Post COVID-19 Condition or Long COVID: A Meta-Analysis and Systematic Review. J. Infect. Dis. 2022, jiac136. [Google Scholar] [CrossRef] [PubMed]
- Rousseau, A.F.; Prescott, H.C.; Brett, S.J.; Weiss, B.; Azoulay, E.; Creteur, J.; Latronico, N.; Hough, C.L.; Weber-Carstens, S.; Vincent, J.L.; et al. Long-term outcomes after critical illness: Recent insights. Crit. Care 2021, 25, 108. [Google Scholar] [CrossRef]
- Silva, C.C.; Bichara, C.N.C.; Carneiro, F.R.O.; Palacios, V.; Berg, A.; Quaresma, J.A.S.; Magno Falcao, L.F. Muscle dysfunction in the long coronavirus disease 2019 syndrome: Pathogenesis and clinical approach. Rev. Med. Virol. 2022, e2355. [Google Scholar] [CrossRef]
- Mezzani, A. Cardiopulmonary Exercise Testing: Basics of Methodology and Measurements. Ann. Am. Thorac. Soc. 2017, 14, S3–S11. [Google Scholar] [CrossRef]
- Baratto, C.; Caravita, S.; Faini, A.; Perego, G.B.; Senni, M.; Badano, L.P.; Parati, G. Impact of COVID-19 on exercise pathophysiology. A combined cardiopulmonary and echocardiographic exercise study. J. Appl. Physiol. 2021, 130, 1470–1478. [Google Scholar] [CrossRef]
- Singh, I.; Joseph, P.; Heerdt, P.M.; Cullinan, M.; Lutchmansingh, D.D.; Gulati, M.; Possick, J.D.; Systrom, D.M.; Waxman, A.B. Persistent Exertional Intolerance After COVID-19: Insights From Invasive Cardiopulmonary Exercise Testing. Chest 2022, 161, 54–63. [Google Scholar] [CrossRef]
- Mancini, D.M.; Brunjes, D.L.; Lala, A.; Trivieri, M.G.; Contreras, J.P.; Natelson, B.H. Use of Cardiopulmonary Stress Testing for Patients With Unexplained Dyspnea Post-Coronavirus Disease. Heart Fail. 2021, 9, 927–937. [Google Scholar] [CrossRef]
- Fresard, I.; Genecand, L.; Altarelli, M.; Gex, G.; Vremaroiu, P.; Vremaroiu-Coman, A.; Lawi, D.; Bridevaux, P.O. Dysfunctional breathing diagnosed by cardiopulmonary exercise testing in ‘long COVID’ patients with persistent dyspnoea. BMJ Open Respir. Res. 2022, 9, e001126. [Google Scholar] [CrossRef]
- Joris, M.; Minguet, P.; Colson, C.; Joris, J.; Fadeur, M.; Minguet, G.; Guiot, J.; Misset, B.; Rousseau, A.F. Cardiopulmonary Exercise Testing in Critically Ill Coronavirus Disease 2019 Survivors: Evidence of a Sustained Exercise Intolerance and Hypermetabolism. Crit. Care Explor. 2021, 3, e0491. [Google Scholar] [CrossRef] [PubMed]
- Karampela, I.; Vallianou, N.; Magkos, F.; Apovian, C.M.; Dalamaga, M. Obesity, Hypovitaminosis D, and COVID-19: The Bermuda Triangle in Public Health. Curr. Obes. Rep. 2022, 1–10. [Google Scholar] [CrossRef] [PubMed]
- Lambermont, B.; Rousseau, A.F.; Seidel, L.; Thys, M.; Cavalleri, J.; Delanaye, P.; Chase, J.G.; Gillet, P.; Misset, B. Outcome Improvement Between the First Two Waves of the Coronavirus Disease 2019 Pandemic in a Single Tertiary-Care Hospital in Belgium. Crit. Care Explor. 2021, 3, e0438. [Google Scholar] [CrossRef] [PubMed]
- Darcis, G.; Bouquegneau, A.; Maes, N.; Thys, M.; Henket, M.; Labye, F.; Rousseau, A.F.; Canivet, P.; Desir, C.; Calmes, D.; et al. Long-term clinical follow-up of patients suffering from moderate-to-severe COVID-19 infection: A monocentric prospective observational cohort study. Int. J. Infect. Dis. 2021, 109, 209–216. [Google Scholar] [CrossRef]
- Schetz, M.; De Jong, A.; Deane, A.M.; Druml, W.; Hemelaar, P.; Pelosi, P.; Pickkers, P.; Reintam-Blaser, A.; Roberts, J.; Sakr, Y.; et al. Obesity in the critically ill: A narrative review. Intensive Care Med. 2019, 45, 757–769. [Google Scholar] [CrossRef]
- Della Guardia, L.; Codella, R. Exercise tolls the bell for key mediators of low-grade inflammation in dysmetabolic conditions. Cytokine Growth Factor Rev. 2021, 62, 83–93. [Google Scholar] [CrossRef]
- Preiser, J.C.; Ichai, C.; Orban, J.C.; Groeneveld, A.B. Metabolic response to the stress of critical illness. Br. J. Anaesth. 2014, 113, 945–954. [Google Scholar] [CrossRef] [Green Version]
- Stanojcic, M.; Finnerty, C.C.; Jeschke, M.G. Anabolic and anticatabolic agents in critical care. Curr. Opin. Crit. Care 2016, 22, 325–331. [Google Scholar] [CrossRef]
- Graham, B.L.; Steenbruggen, I.; Miller, M.R.; Barjaktarevic, I.Z.; Cooper, B.G.; Hall, G.L.; Hallstrand, T.S.; Kaminsky, D.A.; McCarthy, K.; McCormack, M.C.; et al. Standardization of Spirometry 2019 Update. An Official American Thoracic Society and European Respiratory Society Technical Statement. Am. J. Respir. Crit. Care Med. 2019, 200, e70–e88. [Google Scholar] [CrossRef]
- American Thoracic, S.; American College of Chest, P. ATS/ACCP Statement on cardiopulmonary exercise testing. Am. J. Respir. Crit. Care Med. 2003, 167, 211–277. [Google Scholar] [CrossRef]
- Pincemail, J.; Vanbelle, S.; Gaspard, U.; Collette, G.; Haleng, J.; Cheramy-Bien, J.P.; Charlier, C.; Chapelle, J.P.; Giet, D.; Albert, A.; et al. Effect of different contraceptive methods on the oxidative stress status in women aged 40–48 years from the ELAN study in the province of Liege, Belgium. Hum. Reprod. 2007, 22, 2335–2343. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Pincemail, J.; Defraigne, J.O.; Cheramy-Bien, J.P.; Dardenne, N.; Donneau, A.F.; Albert, A.; Labropoulos, N.; Sakalihasan, N. On the potential increase of the oxidative stress status in patients with abdominal aortic aneurysm. Redox Rep. 2012, 17, 139–144. [Google Scholar] [CrossRef]
- Pincemail, J.; Cavalier, E.; Charlier, C.; Cheramy-Bien, J.P.; Brevers, E.; Courtois, A.; Fadeur, M.; Meziane, S.; Goff, C.L.; Misset, B.; et al. Oxidative Stress Status in COVID-19 Patients Hospitalized in Intensive Care Unit for Severe Pneumonia. A Pilot Study. Antioxidants 2021, 10, 257. [Google Scholar] [CrossRef]
- Vanhorebeek, I.; Van den Berghe, G. The neuroendocrine response to critical illness is a dynamic process. Crit. Care Clin. 2006, 22, 1–15. [Google Scholar] [CrossRef] [PubMed]
- Cox, C.E. Persistent systemic inflammation in chronic critical illness. Respir. Care 2012, 57, 859–864, discussion 864–856. [Google Scholar] [CrossRef] [PubMed]
- Jeschke, M.G.; Chinkes, D.L.; Finnerty, C.C.; Kulp, G.; Suman, O.E.; Norbury, W.B.; Branski, L.K.; Gauglitz, G.G.; Mlcak, R.P.; Herndon, D.N. Pathophysiologic response to severe burn injury. Ann. Surg. 2008, 248, 387–401. [Google Scholar] [CrossRef] [Green Version]
- Griffith, D.M.; Lewis, S.; Rossi, A.G.; Rennie, J.; Salisbury, L.; Merriweather, J.L.; Templeton, K.; Walsh, T.S.; Investigators, R. Systemic inflammation after critical illness: Relationship with physical recovery and exploration of potential mechanisms. Thorax 2016, 71, 820–829. [Google Scholar] [CrossRef] [Green Version]
- Zuo, L.; Prather, E.R.; Stetskiv, M.; Garrison, D.E.; Meade, J.R.; Peace, T.I.; Zhou, T. Inflammaging and Oxidative Stress in Human Diseases: From Molecular Mechanisms to Novel Treatments. Int. J. Mol. Sci. 2019, 20, 4472. [Google Scholar] [CrossRef] [Green Version]
- TPCC Group. Clinical characteristics with inflammation profiling of long COVID and association with 1-year recovery following hospitalisation in the UK: A prospective observational study. Lancet Respir. Med. 2022. [Google Scholar] [CrossRef]
- van de Vyver, M.; Myburgh, K.H. Variable inflammation and intramuscular STAT3 phosphorylation and myeloperoxidase levels after downhill running. Scand. J. Med. Sci. Sports 2014, 24, e360–e371. [Google Scholar] [CrossRef]
- Morozov, V.I.; Tsyplenkov, P.V.; Golberg, N.D.; Kalinski, M.I. The effects of high-intensity exercise on skeletal muscle neutrophil myeloperoxidase in untrained and trained rats. Eur. J. Appl. Physiol. 2006, 97, 716–722. [Google Scholar] [CrossRef]
- Bonen, A.; Ness, G.W.; Belcastro, A.N.; Kirby, R.L. Mild exercise impedes glycogen repletion in muscle. J. Appl. Physiol. 1985, 58, 1622–1629. [Google Scholar] [CrossRef] [PubMed]
- Rinaldo, R.F.; Mondoni, M.; Parazzini, E.M.; Pitari, F.; Brambilla, E.; Luraschi, S.; Balbi, M.; Sferrazza Papa, G.F.; Sotgiu, G.; Guazzi, M.; et al. Deconditioning as main mechanism of impaired exercise response in COVID-19 survivors. Eur. Respir. J. 2021, 58, 2100870. [Google Scholar] [CrossRef]
Data | ICU Group n = 31 | MLC Group n = 23 | OB Group n = 15 | |
---|---|---|---|---|
Age, y | 61 [54–67] | 44 [37–50] | 53 [45–69] | |
Male, n (%) | 21 (67.7) | 7 (30.4) | 8 (53.3) | |
Weight, kg | 96.1 [88.9–100] | 76.3 [64.3–90.6] | 94 [90–110] | |
BMI, kg/m2 | 32.9 [30.1–34.8] | 25.8 [22.3–30] | 33 [30.7–35.4] | |
Comorbidities | Diabetes | 18 (58.1) | 2 (8.7) | 2 (13.3) |
Hypertension | 18 (58.1) | 3 (13) | 7 (46.7) | |
Cardiac disease † | 9 (29) | 0 | 2 (13.3) | |
Respiratory disease †† | 5 (16.1) | 7 (30.4) | 15 (100) | |
Chronic kidney disease | 1 (3.2) | 0 | 0 | |
Active smoking | 1 (3.2) | 0 | 1 (6.7) | |
SOFA at ICU admission | 5.5 [3.7–7] | |||
Mechanical ventilation, n (%) | 22 (71) | |||
Duration of mechanical ventilation, d | 15.5 [11.8–24] | |||
Corticosteroids, n (%) | 22 (71) | |||
Renal replacement therapy, n (%) | 3 (9.7) | |||
Extracorporeal membrane oxygenation, n (%) | 0 | |||
ICU LOS, d | 15.4 [9.7–25.6] | |||
Hospital LOS, d | 29 [21–42.7] | |||
Beta-blockers medication at CPET time | 20 (64.5) | 1 (4.3) | 4 (26.7) |
Data | ICU Group n = 31 | MLC Group n = 23 | OB Group n = 15 |
---|---|---|---|
FVC, % predicted | 90 [72–104.5] | 100 [95–110.8] | 98 [90–106.5] |
FEV1, % predicted | 92 [80–105.5] | 97.5 [89.5–104.3] | 102 [89–106] |
DLCO, % predicted | 98 [84.5–110] | 95 [82.2–101.8] | 89 [84–104.5] |
Data | ICU Group n = 31 | MLC Group n = 23 | Adjusted p Value (Comparison between ICU Group and LC Group) | OB Group n = 15 | Adjusted p Value (Comparison between ICU Group and OB Group) | Kruskal–Wallis Test p Value | |
---|---|---|---|---|---|---|---|
Maximum predicted | VO2 (mL/min/kg) | 24.8 [19.7–28] | 26.2 [23.7–33.4] | NS | 22.3 [15.5–25.5] | NS | 0.048 |
HR (bpm) | 159 [152–167] | 176 [170–183] | <0.001 | 168 [151–190] | NS | 0.001 | |
Workload (W) | 155.5 [131–172] | 136 [128–182] | NS | 135 [103–185] | NS | NS | |
πO2 (mL/beat) | 15.8 [10.8–17.1] | 10.3 [9.1–15.2] | NS | 14.5 [11.7–18.8] | NS | 0.036 | |
Resting state | HR (bpm) | 77 [66–87] | 76 [66–86] | NS | 91 [74–99] | NS | 0.051 |
Systolic blood pressure (mmHg) | 140 [130–145] | 120 [110–120] | <0.001 | 125 [117–130] | NS | <0.001 | |
Diastolic blood pressure (mmHg) | 70 [70–70] | 60 [60–70] | 0.03 | 80 [70–85] | NS | 0.004 | |
VO2 (mL/min/kg) | 8 [5.6–9.7] | 6.1 [4.4–7.6] | NS | 4.4 [3.3–5.2] | <0.001 | 0.001 | |
MET | 2.4 [1.8–3.1] | 1.7 [1.3–2.3] | NS | 1.3 [0.9–1.5] | <0.001 | <0.001 | |
RER | 0.85 [0.8–0.91] | 0.77 [0.73–0.82] | 0.001 | 0.8 [0.76–0.84] | NS | 0.002 | |
πO2 (mL/beat) | 7.7 [6.2–13.2] | 5.5 [4.8–6.1] | 0.028 | 4.1 [3.3–5.2] | <0.001 | <0.001 | |
Veq CO2 | 29.6 [26.2–34.4] | 35.9 [31.3–40.1] | 0.004 | 32.3 [30.4–34.5] | NS | 0.005 | |
ADT | VO2 (% peak) | 66 [57–74] | 52 [48–59] | <0.001 | |||
AT | VO2 (% peak) | 81 [72.5–87.2] | 85 [75–91] | NS | 44.5 [34.5–58.3] | <0.001 | <0.001 |
Peak | Workload (% max predicted) | 66 [40.9–79.2] | 104.4 [95.6–122.3] | <0.001 | 94.7 [77.7–123.9] | 0.003 | <0.001 |
VO2 (% max predicted) | 74.5 [62.6–102.8] | 105.3 [86.8–132.8] | 0.005 | 74 [62–84.3] | NS | <0.001 | |
HR (% max predicted) | 76.7 [65.1–90.3] | 97.9 [88.7–101.1] | <0.001 | 80.6 [74–89.3] | NS | <0.001 | |
πO2 (% max predicted) | 109 [75.5–135.4] | 116 [105–134] | NS | 72.9 [56.4–85.4] | 0.002 | <0.001 | |
Veq CO2 | 29.5 [26.6–34.4] | 33 [30.4–40.9] | NS | 31.5 [29.6–34.3] | NS | 0.117 | |
VE (l/min) | 61.1 [44.7–72.8] | 79.4 [64.4–89.5] | 0.007 | 60 [40–71] | NS | 0.004 | |
VE/VCO2 slope | 33.6 [29.1–44.9] | 26 [22.9–34.9] | NS | 32.1 [29.5–33.5] | NS | 0.066 | |
CR (%) | 57.8 [35.5–79.3] | 96.5 [73.2–101.7] | <0.001 | 59.5 [43.1–71.7] | NS | <0.001 | |
BR (%) | 33 [19.8–41.5] | 19.1 [6.6–31.2] | NS | 48 [30–58] | NS | 0.001 | |
T1/2 | VO2 (% peak) | 51 [49.2–53] | 50 [49–51] | NS | 49.4 [45.2–52.4] | NS | 0.212 |
HR (% peak) | 79.2 [75–85] | 69.2 [64.6–74.2] | <0.001 | 78.7 [76.4–90.4] | NS | <0.001 | |
RER | 1.13 [1–1.2] | 0.97 [0.91–1.03] | 0.021 | 1.38 [1.29–1.45] | <0.001 | <0.001 | |
πO2 (% peak) | 62.4 [56.2–69.9] | 47.6 [42.2–53.8] | <0.001 | 59.7 [54.8–68.2] | NS | <0.001 | |
Veq CO2 (% peak) | 107.4 [100.2–117.4] | 133.1 [121.7–144.7] | <0.001 | 107.8 [102.9–114.5] | NS | <0.001 |
Data | n | Blood Concentrations | Reference Ranges |
---|---|---|---|
C-reactive protein (CRP), mg/L | 31 | 1.95 [0.95–2.69] | 0–5 |
Thyroid-stimulating hormone (TSH), mUI/L | 31 | 1.05 [0.49–1.75] | 0.35–4.94 |
Thyroxine (T4), pmol/L | 31 | 10.95 [9.82–13.23] | 8.7–16.8 |
Cortisol, nmol/L | 31 | 210.9 [152.4–267.8] | 80–477.3 |
Albumin, g/L | 10 | 44 [41–46.25] | 35–52 |
Hemoglobin, g/dL | 10 | 13 [10.93–14.7] | Male: 13.2–17.2 Female: 11.7–15 |
White blood cells, 103/mm3 | 10 | 7.27 [6.2–8.32] | 4.6–10.1 |
Neutrophils, % | 10 | 54.6 [39.8–62.3] | 42.2–71 |
Vitamin C, mg/L | 10 | 7.32 [5.19–9.88] | 6–18 |
Thiol proteins (PSH), µM | 10 | 296 [260–360] | 310–523 |
Glutathione peroxidase (GPx), UI/g | 10 | 64.5 [61.7–90] | 20–58 |
Cupper (Cu), mg/L | 10 | 0.91 [0.82–1.19] | 0.7–1.1 |
Zinc (Zn), mg/L | 10 | 0.8 [ 0.73–0.99] | 0.7–1.2 |
Cu/Zn ratio | 10 | 1.18 [0.95–1.24] | 1–1.17 |
Lipid peroxides (ROOH), µM | 10 | 427 [366–949.3] | 0–432 |
Myeloperoxidase (MPO), ng/mL | 10 | 92 [75.5–106.5] | 0–55 |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Joris, M.; Pincemail, J.; Colson, C.; Joris, J.; Calmes, D.; Cavalier, E.; Misset, B.; Guiot, J.; Minguet, G.; Rousseau, A.-F. Exercise Limitation after Critical versus Mild COVID-19 Infection: A Metabolic Perspective. J. Clin. Med. 2022, 11, 4322. https://doi.org/10.3390/jcm11154322
Joris M, Pincemail J, Colson C, Joris J, Calmes D, Cavalier E, Misset B, Guiot J, Minguet G, Rousseau A-F. Exercise Limitation after Critical versus Mild COVID-19 Infection: A Metabolic Perspective. Journal of Clinical Medicine. 2022; 11(15):4322. https://doi.org/10.3390/jcm11154322
Chicago/Turabian StyleJoris, Maurice, Joël Pincemail, Camille Colson, Jean Joris, Doriane Calmes, Etienne Cavalier, Benoit Misset, Julien Guiot, Grégory Minguet, and Anne-Françoise Rousseau. 2022. "Exercise Limitation after Critical versus Mild COVID-19 Infection: A Metabolic Perspective" Journal of Clinical Medicine 11, no. 15: 4322. https://doi.org/10.3390/jcm11154322
APA StyleJoris, M., Pincemail, J., Colson, C., Joris, J., Calmes, D., Cavalier, E., Misset, B., Guiot, J., Minguet, G., & Rousseau, A. -F. (2022). Exercise Limitation after Critical versus Mild COVID-19 Infection: A Metabolic Perspective. Journal of Clinical Medicine, 11(15), 4322. https://doi.org/10.3390/jcm11154322