Research Article

Evaluation of hematological parameters related to systemic inflammation in acute and subacute/chronic low back pain

https://orcid.org/0000-0002-9611-1818

Emergency Service, Ankara Yıldırım Beyazıt University, Yenimahalle Training & Research Hospital, Ankara, 38000, Turkey

Search for more papers by this author

Elzem Bolkan Günaydın

*Author for correspondence: Tel.: +90 530 978 7303;

E-mail Address: elzembolkan@yahoo.com

https://orcid.org/0000-0002-4000-6947

Department of Physical Medicine & Rehabilitation, Faculty of Medicine, Ufuk University, Ankara, 38000, Turkey

Search for more papers by this author

Published Online:3 Dec 2021https://doi.org/10.2217/bmm-2021-0431

View article

Abstract

Aim: To compare the hematological parameters associated with systemic inflammation between acute and subacute/chronic nonspecific low back pain and to evaluate their diagnostic roles in relation to chronicity in low back pain. Materials & methods: This retrospective case–control study included 150 participants aged 18–65 years with acute nonspecific low back pain, 150 with subacute/chronic nonspecific low back pain, 150 as the control group. Results: Red cell distribution width was significantly higher in the subacute/chronic pain group compared with the acute pain group (p = 0.003), and had a poor diagnostic value for chronicity (cutoff: 11.95, p = 0.003). There were no significant differences in terms of other parameters (p > 0.05). Conclusion: Red cell distribution width has a poor diagnostic value for chronicity in nonspecific low back pain.

Keywords:

References

1. Ng JY, Mohiuddin U, Azizudin AM. Clinical practice guidelines for the treatment and management of low back pain: a systematic review of quantity and quality. Musculoskelet. Sci. Pract. 51, 102295 (2021).
MedlineGoogle Scholar
2. Pergolizzi JV, LeQuang JA. Rehabilitation for low back pain: a narrative review for managing pain and improving function in acute and chronic conditions. Pain Ther. 9, 83–96 (2020).
MedlineGoogle Scholar
3. Hoy D, Brooks P, Blyth F, Buchbinder R. The epidemiology of low back pain. Best Pract. Res. Clin. Rheumatol. 24, 769–781 (2010).
Medline CASGoogle Scholar
4. Mendonça L, Monteiro-Soares M, Azevedo LF. Prediction of clinical outcomes in individuals with chronic low back pain: a protocol for a systematic review with meta-analysis 11 Medical and Health Sciences 1117 Public Health and Health Services. Syst. Rev. 7, 1–6 (2018).
MedlineGoogle Scholar
5. Woolf A. Organization BP-B of the world health, 2003 U. Burden of major musculoskeletal conditions. SciELO Public Heal. 81, 646–656 (2003).
Google Scholar
6. Maher C, Underwood M, Buchbinder R. Non-specific low back pain. Lancet 389, 736–747 (2017).
MedlineGoogle Scholar
7. Linton SJ, Nicholas M, Shaw W. Why wait to address high-risk cases of acute low back pain? A comparison of stepped, stratified, and matched care. Pain 159, 2437–2441 (2018).
MedlineGoogle Scholar
8. George SZ, Lentz TA, Beneciuk JM, Bhavsar NA, Mundt JM, Boissoneault J. Framework for improving outcome prediction for acute to chronic low back pain transitions. PAIN Reports 5, e809 (2020).
MedlineGoogle Scholar
9. Lim YZ, Wang Y, Cicuttini FM et al. Association between inflammatory biomarkers and nonspecific low back pain: a systematic review. Clin. J. Pain 36, 379–389 (2020).
MedlineGoogle Scholar
10. Qaseem A, Wilt TJ, McLean RM, Forciea MA. Noninvasive treatments for acute, subacute, and chronic low back pain: a clinical practice guideline from the American College of Physicians. Ann. Intern. Med. 166, 514–530 (2017).
MedlineGoogle Scholar
11. Khan AN, Jacobsen HE, Khan J et al. Inflammatory biomarkers of low back pain and disc degeneration: a review. Ann. NY Acad. Sci. 1410, 68–84 (2017).
MedlineGoogle Scholar
12. Morris P, Ali K, Merritt M, Pelletier J, Macedo LG. A systematic review of the role of inflammatory biomarkers in acute, subacute and chronic non-specific low back pain. BMC Musculoskelet. Disord. 21, 1–12 (2020).
Google Scholar
13. van den Berg R, Jongbloed EM, de Schepper EIT, Bierma-Zeinstra SMA, Koes BW, Luijsterburg PAJ. The association between pro-inflammatory biomarkers and nonspecific low back pain: a systematic review. Spine J. 18, 2140–2151 (2018).
MedlineGoogle Scholar
14. Teodorczyk-Injeyan JA, Triano JJ, Injeyan HS. Nonspecific low back pain: inflammatory profiles of patients with acute and chronic pain. Clin. J. Pain 35, 818–825 (2019).
MedlineGoogle Scholar
15. May JE, Marques MB, Reddy VVB, Gangaraju R. Three neglected numbers in the CBC: the RDW, MPV, and NRBC count. Cleve. Clin. J. Med. 86, 167–172 (2019).
MedlineGoogle Scholar
16. Gabay C, Kushner I. Acute-phase proteins and other systemic responses to inflammation. N. Engl. J. Med. 340, 448–454 (1999).
Medline CASGoogle Scholar
17. Bozan N, Alpaycı M, Aslan M et al. Mean platelet volume, red cell distribution width, platelet-to-lymphocyte and neutrophil-to-lymphocyte ratios in patients with ankylosing spondylitis and their relationships with high-frequency hearing thresholds. Eur. Arch. Oto-Rhino-Laryngol. 273, 3663–3672 (2016).
MedlineGoogle Scholar
18. Gasparyan AY, Ayvazyan L, Mukanova U, Yessirkepov M, Kitas GD. The platelet-to-lymphocyte ratio as an inflammatory marker in rheumatic diseases. Ann. Lab. Med. 39, 345–357 (2019).
Medline CASGoogle Scholar
19. Georgakopoulou VE, Garmpis N, Damaskos C et al. The impact of peripheral eosinophil counts and eosinophil to lymphocyte ratio (ELR) in the clinical course of covid-19 patients: a retrospective study. In Vivo (Brooklyn) 35, 641–648 (2021).
CASGoogle Scholar
20. Hu B, Yang XR, Xu Y et al. Systemic immune-inflammation index predicts prognosis of patients after curative resection for hepatocellular carcinoma. Clin. Cancer Res. 20, 6212–6222 (2014).
Medline CASGoogle Scholar
21. Walzik D, Joisten N, Zacher J, Zimmer P. Transferring clinically established immune inflammation markers into exercise physiology: focus on neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio and systemic immune-inflammation index. Eur. J. Appl. Physiol. https://doi: 10.1007/s00421-021-04668-7 (2021) (Epub ahead of print).
Google Scholar
22. Yousefi B, Sanaie S, Ghamari AA, Soleimanpour H, Karimian A, Mahmoodpoor A. Red cell distribution width as a novel prognostic marker in multiple clinical studies. Indian J. Crit. Care Med. 24, 49–54 (2020).
Medline CASGoogle Scholar
23. Doğan S, Atakan N. Red blood cell distribution width is a reliable marker of inflammation in plaque psoriasis. Acta Dermatovenerol. Croat. 25, 26–31 (2017).
Medline CASGoogle Scholar
24. Korniluk A, Koper-Lenkiewicz OM, Kamińska J, Kemona H, Dymicka-Piekarska V. Mean platelet volume (MPV): new perspectives for an old marker in the course and prognosis of inflammatory conditions. Mediators Inflamm. 2019, 1–14 (2019).
Google Scholar
25. Zahorec R. Ratio of neutrophil to lymphocyte counts–rapid and simple parameter of systemic inflammation and stress in critically ill. Bratisl. Lek. Listy. 102, 5–14 (2001).
Medline CASGoogle Scholar
26. Zarbock A, Polanowska-Grabowska RK, Ley K. Platelet-neutrophil-interactions: linking hemostasis and inflammation. Blood Rev. 21, 99–111 (2007).
Medline CASGoogle Scholar
27. Çekici Y, Yılmaz M, Seçen Ö. New inflammatory indicators: association of high eosinophil-to-lymphocyte ratio and low lymphocyte-to-monocyte ratio with smoking. J. Int. Med. Res. 47, 4292–4303 (2019).
Medline CASGoogle Scholar
28. Klyne DM, Barbe MF, Hodges PW. Systemic inflammatory profiles and their relationships with demographic, behavioural and clinical features in acute low back pain. Brain Behav. Immun. 60, 84–92 (2017).
MedlineGoogle Scholar
29. Saravanan A, Bajaj P, Mathews HL, Tell D, Starkweather A, Janusek L. Behavioral symptom clusters, inflammation, and quality of life in chronic low back pain. Pain Manag. Nurs. https://doi.org/10.1016/j.pmn.2020.11.012 (2021) ( Epub ahead of print).
Google Scholar
30. Klyne DM, Barbe MF, van den Hoorn W, Hodges PW. ISSLS prize in clinical science 2018: longitudinal analysis of inflammatory, psychological, and sleep-related factors following an acute low back pain episode—the good, the bad, and the ugly. Eur. Spine J. 27, 763–777 (2018).
MedlineGoogle Scholar
31. Karabaş Ç, Tomruk Sütbeyaz S, Aykaç Cebiçci M. Fibromyalji hastalarında nötrofil/lenfosit oranı, platelet/lenfosit oranı ve ortalama trombosit hacminin değerlendirilmesi. J. Anatol. Med. Res. 3, 1–10 (2018).
Google Scholar
32. Seng JJB, Kwan YH, Low LL, Thumboo J, Fong WSW. Role of neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR) and mean platelet volume (MPV) in assessing disease control in Asian patients with axial spondyloarthritis. Biomarkers 23, 335–338 (2018).
Medline CASGoogle Scholar
33. Zhou Y-Q, Mei W, Tian X-B, Tian Y-K, Liu D-Q, Ye D-W. The therapeutic potential of Nrf2 inducers in chronic pain: evidence from preclinical studies. Pharmacol. Ther. 225, 107846 (2021).
Medline CASGoogle Scholar
34. Hu L, Li M, Ding Y et al. Prognostic value of RDW in cancers: a systematic review and meta-analysis. Oncotarget 8, 16027–16035 (2017).
MedlineGoogle Scholar
35. Lippi G, Henry BM, Sanchis-Gomar F. Red blood cell distribution is a significant predictor of severe illness in coronavirus disease 2019. Acta Haematol. https://doi.org/10.1159/000510914 (2020) (Epub ahead of print).
Google Scholar
36. Goyal H, Lippi G, Gjymishka A, John B, Chhabra R, May E. Prognostic significance of red blood cell distribution width in gastrointestinal disorders. World J. Gastroenterol. 23, 4879–4891 (2017).
MedlineGoogle Scholar
37. Xing X, Deng Y, Zhu Y et al. Red cell distribution width for prognosis in patients with pulmonary embolism: a systematic review and meta-analysis. Clin. Respir. J. 14, 901–907 (2020).
MedlineGoogle Scholar
38. Song GG, Lee YH. Red cell distribution width, platelet-to-lymphocyte ratio, and mean platelet volume in ankylosing spondylitis and their correlations with inflammation: a meta-analysis. Mod. Rheumatol. 30, 894–899 (2020).
Medline CASGoogle Scholar
39. Zhang L, Yu C, Guo K, Huang C, Mo L. Prognostic role of red blood cell distribution width in patients with sepsis: a systematic review and meta-analysis. BMC Immunol. 21, 40 (2020).
MedlineGoogle Scholar
40. Tecer D, Sezgin M, Kanik A et al. Can mean platelet volume and red blood cell distribution width show disease activity in rheumatoid arthritis? Biomark. Med. 10, 967–974 (2016).
CASGoogle Scholar
41. Masoumi M, Shadmanfar S, Davatchi F et al. Correlation of clinical signs and symptoms of Behçet’s disease with mean platelet volume (MPV) and red cell distribution width (RDW). Orphanet. J. Rare Dis. 15, 1–8 (2020).
MedlineGoogle Scholar

Vol. 16, No. 1

Metrics

Downloaded 73 times

History

Received 30 May 2021

Accepted 14 October 2021

Published online 3 December 2021

Published in print January 2022

Information

Keywords

Financial & competing interests disclosure

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

No writing assistance was utilized in the production of this manuscript.

Ethical conduct of research

Ethics committee approval was obtained (decision number/date: 2021-06-10/05.05.2021/ethics committee of Ankara Yıldırım Beyazıt University, Yenimahalle Training and Research Hospital, Ankara, Turkey). Registration number and date: Clinical trials.org identifier: NCT04897620/18.05.2021. Consent to participate: for this type of study, formal consent is not required.

PDF download