Clinical Rheumatology

, Volume 37, Issue 4, pp 979–985 | Cite as

Red blood cell distribution width as a related factor of pulmonary arterial hypertension in patients with systemic sclerosis

  • Jiuliang Zhao
  • Hongnan Mo
  • Xiaoxiao Guo
  • Qian Wang
  • Dong Xu
  • Yong Hou
  • Zhuang Tian
  • Yongtai Liu
  • Hui Wang
  • Jinzhi Lai
  • Mengtao Li
  • Xiaofeng Zeng
Original Article
  • 164 Downloads

Abstract

The aim of this study was to investigate the utility of red blood cell distribution width (RDW) as a simple and readily available marker of occurrence of pulmonary arterial hypertension (PAH) in patients with systemic sclerosis (SSc). One hundred and forty-five consecutive patients with SSc were recruited to the single-center cross-sectional study. Demographic characteristics, hematological parameters, Modified Rodnan Skin Score, and World Health Organization functional classification were determined. Diagnosis of PAH was based on screening by echocardiography and was confirmed by right heart catheterization. Interstitial lung disease (ILD) was diagnosed based on chest high-resolution computed tomography findings. There were no significant differences in gender, age, or disease duration between limited and diffused SSc groups. PAH was detected in 28 of lcSSc (33.3%) and 14 of dcSSc (23.0%) subjects. Patients with higher RDW values were more likely to be men with high anti-u1RNP titers and PAH. A significant correlation was found between RDW and high-sensitivity C-reactive protein (p = 0.375, p < 0.01) and the diffusing capacity of the lungs for carbon monoxide (ρ = − 0.396, p < 0.01). The SSc-PAH group had significantly higher RDW values compared to the SSc group without pulmonary disease (15.7 ± 2.2 and 13.7 ± 1.0, p < 0.001). The mean RDW in the SSc-PAH-ILD group was significantly higher than that in the SSc-ILD group (16.3 ± 2.2% and 14.0 ± 1.5%, p < 0.001). Besides the recognized risk factors, high RDW was an independent predictor of PAH in patients with SSc (OR = 3.314 [95%CI 1.038–10.580], p < 0.05). RDW may be a related factor for identifying the pulmonary arterial hypertension in SSc patients.

Keywords

Inflammation Pulmonary arterial hypertension Red blood cell distribution width Systemic sclerosis 

Notes

Acknowledgements

This study was supported by EULAR Scleroderma Trial and Research (EUSTAR) Group, National Major Scientific and Technological Special Project (2012ZX09303006-002), Chinese National Key Technology R&D Program, Ministry of Science and Technology (2011BAI11B15), National Natural Science Foundation of China (81072485, 81071300, 81500306), Research Special Fund for Public Welfare Industry of Health (201202004), Fund of Capital Medical Development and Research (2009-2003), Clinical Research Project of Chinese Medical Association (12040740374) and Peking Union Medical College (PUMC) Youth Fund, and the Fundamental Research Funds for the Central Universities.

Compliance with ethical standards

The study was approved by the medical ethics committee of Peking Union Medical College Hospital and was conducted in accordance with the Declaration of Helsinki principles and followed the International Conference on Harmonisation Guideline for Good Clinical Practice. Written informed consent was obtained from all the patients.

Disclosures

None.

References

  1. 1.
    Steen VD, Medsger TA (2007) Changes in causes of death in systemic sclerosis, 1972–2002. Ann Rheum Dis 66(7):940–944.  https://doi.org/10.1136/ard.2006.066068 CrossRefPubMedPubMedCentralGoogle Scholar
  2. 2.
    Mukerjee D, St George D, Coleiro B, Knight C, Denton CP, Davar J, Black CM, Coghlan JG (2003) Prevalence and outcome in systemic sclerosis associated pulmonary arterial hypertension: application of a registry approach. Ann Rheum Dis 62(11):1088–1093.  https://doi.org/10.1136/ard.62.11.1088 CrossRefPubMedPubMedCentralGoogle Scholar
  3. 3.
    Subhashree AR, Shanthi B, Parameaswari PJ (2013) The red cell distribution width as a sensitive biomarker for assessing the pulmonary function in automobile welders—a cross sectional study. J Clin Diagn Res 7(1):89–92.  https://doi.org/10.7860/JCDR/2012/5051.2678 PubMedGoogle Scholar
  4. 4.
    Ujszaszi A, Molnar MZ, Czira ME, Novak M, Mucsi I (2013) Renal function is independently associated with red cell distribution width in kidney transplant recipients: a potential new auxiliary parameter for the clinical evaluation of patients with chronic kidney disease. Br J Haematol 161(5):715–725.  https://doi.org/10.1111/bjh.12315 CrossRefPubMedGoogle Scholar
  5. 5.
    Felker GM, Allen LA, Pocock SJ, Shaw LK, McMurray JJ, Pfeffer MA, Swedberg K, Wang D, Yusuf S, Michelson EL, Granger CB, CHARM Investigators (2007) Red cell distribution width as a novel prognostic marker in heart failure: data from the CHARM Program and the Duke Databank. J Am Coll Cardiol 50(1):40–47.  https://doi.org/10.1016/j.jacc.2007.02.067 CrossRefPubMedGoogle Scholar
  6. 6.
    Tonelli M, Sacks F, Arnold M, Moye L, Davis B, Pfeffer M, for the Cholesterol and Recurrent Events (CARE) Trial Investigators (2008) Relation between red blood cell distribution width and cardiovascular event rate in people with coronary disease. Circulation 117(2):163–168.  https://doi.org/10.1161/CIRCULATIONAHA.107.727545 CrossRefPubMedGoogle Scholar
  7. 7.
    Hampole CV, Mehrotra AK, Thenappan T, Gomberg-Maitland M, Shah SJ (2009) Usefulness of red cell distribution width as a prognostic marker in pulmonary hypertension. Am J Cardiol 104(6):868–872.  https://doi.org/10.1016/j.amjcard.2009.05.016 CrossRefPubMedGoogle Scholar
  8. 8.
    Rhodes CJ, Wharton J, Howard LS, Gibbs JS, Wilkins Red MR (2011) Cell distribution width outperforms other potential circulating biomarkers in predicting survival in idiopathic pulmonary arterial hypertension. Heart 97(13):1054–1060.  https://doi.org/10.1136/hrt.2011.224857 CrossRefPubMedGoogle Scholar
  9. 9.
    Farkas N, Szabo A, Lorand V, Sarlos DP, Minier T, Prohaszka Z, Czirjak L, Varju C (2014) Clinical usefulness of measuring red blood cell distribution width in patients with systemic sclerosis. Rheumatology (Oxford) 53(8):1439–1445.  https://doi.org/10.1093/rheumatology/keu022 CrossRefGoogle Scholar
  10. 10.
    Subcommittee for scleroderma criteria of the American Rheumatism Association Diagnostic and Therapeutic Criteria Committee (1980) Preliminary criteria for the classification of systemic sclerosis (scleroderma). Arthritis Rheum 23:581–590Google Scholar
  11. 11.
    LeRoy EC, Black C, Fleischmajer R, Jablonska S, Krieg T, Jr Medsger TA et al (1988) Scleroderma (systemic sclerosis): classification, subsets and pathogenesis. J Rheumatol 15(2):202–205PubMedGoogle Scholar
  12. 12.
    Khanna D, Nagaraja V, Tseng CH et al (2015) Predictors of lung function decline in scleroderma-related interstitial lung disease based on high-resolution computed tomography: implications for cohort enrichment in systemic sclerosis-associated interstitial lung disease trials. Arthritis Res Ther 17(1):372.  https://doi.org/10.1186/s13075-015-0872-2 CrossRefPubMedPubMedCentralGoogle Scholar
  13. 13.
    Wells AU, Hansell DM, Corrin B, Harrison NK, Goldstraw P, Black CM, du Bois RM (1992) High resolution computed tomography as a predictor of lung histology in systemic sclerosis. Thorax 47(9):738–742.  https://doi.org/10.1136/thx.47.9.738 CrossRefPubMedPubMedCentralGoogle Scholar
  14. 14.
    Authors/Task Force, M, Galie N, Humbert M, Vachiery JL, Gibbs S, Lang I et al (2015) 2015 ESC/ERS Guidelines for the diagnosis and treatment of pulmonary hypertension: The Joint Task Force for the Diagnosis and Treatment of Pulmonary Hypertension of the European Society of Cardiology (ESC) and the European Respiratory Society (ERS) Endorsed by: Association for European Paediatric and Congenital Cardiology (AEPC), International Society for Heart and Lung Transplantation (ISHLT). Eur Heart J 37(1):67–119.  https://doi.org/10.1093/eurheartj/ehv317 Google Scholar
  15. 15.
    Plastiras SC, Karadimitrakis SP, Kampolis C, Moutsopoulos HM, Tzelepis GE (2007) Determinants of pulmonary arterial hypertension in scleroderma. Semin Arthritis Rheum 36(6):392–396.  https://doi.org/10.1016/j.semarthrit.2006.10.004 CrossRefPubMedGoogle Scholar
  16. 16.
    Coghlan JG, Denton CP, Grunig E, Bonderman D, Distler O, Khanna D et al (2014) Evidence-based detection of pulmonary arterial hypertension in systemic sclerosis: the DETECT study. Ann Rheum Dis 73(7):1340–1349.  https://doi.org/10.1136/annrheumdis-2013-203301 CrossRefPubMedGoogle Scholar
  17. 17.
    Solak Y, Yilmaz MI, Saglam M, Caglar K, Verim S, Unal HU et al (2014) Red cell distribution width is independently related to endothelial dysfunction in patients with chronic kidney disease. Am J Med Sci 347(2):118–124.  https://doi.org/10.1097/MAJ.0b013e3182996a96 CrossRefPubMedGoogle Scholar
  18. 18.
    Fatini C, Mannini L, Sticchi E, Rogai V, Guiducci S, Conforti ML, Cinelli M, Pignone AM, Bolli P, Abbate R, Cerinic MM (2006) Hemorheologic profile in systemic sclerosis: role of NOS3 -786T > C and 894G >T polymorphisms in modulating both the hemorheologic parameters and the susceptibility to the disease. Arthritis Rheum 54(7):2263–2270.  https://doi.org/10.1002/art.21933 CrossRefPubMedGoogle Scholar
  19. 19.
    Lippi G, Targher G, Montagnana M, Salvagno GL, Zoppini G, Guidi GC (2009) Relation between red blood cell distribution width and inflammatory biomarkers in a large cohort of unselected outpatients. Arch Pathol Lab Med 133(4):628–632.  https://doi.org/10.1043/1543-2165-133.4.628 PubMedGoogle Scholar
  20. 20.
    Rezende SM, Lijfering WM, Rosendaal FR, Cannegieter SC (2014) Hematologic variables and venous thrombosis: red cell distribution width and blood monocyte count are associated with an increased risk. Haematologica 99(1):194–200.  https://doi.org/10.3324/haematol.2013.083840 CrossRefPubMedPubMedCentralGoogle Scholar
  21. 21.
    Lambova S, Muller-Ladner U (2010) Pulmonary arterial hypertension in systemic sclerosis. Autoimmun Rev 9(11):761–770.  https://doi.org/10.1016/j.autrev.2010.06.006 CrossRefPubMedGoogle Scholar

Copyright information

© International League of Associations for Rheumatology (ILAR) 2017

Authors and Affiliations

  • Jiuliang Zhao
    • 1
  • Hongnan Mo
    • 1
  • Xiaoxiao Guo
    • 2
  • Qian Wang
    • 1
  • Dong Xu
    • 1
  • Yong Hou
    • 1
  • Zhuang Tian
    • 2
  • Yongtai Liu
    • 2
  • Hui Wang
    • 2
  • Jinzhi Lai
    • 2
  • Mengtao Li
    • 1
  • Xiaofeng Zeng
    • 1
  1. 1.Department of Rheumatology, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical SciencesKey Laboratory of Rheumatology and Clinical Immunology, Ministry of EducationBeijingChina
  2. 2.Department of CardiologyPeking Union Medical College HospitalBeijingChina

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