C-reactive protein misdiagnoses delayed postoperative spinal implant infections in patients with low-virulent microorganisms

  • Doruk Akgün
  • Justus Bürger
  • Matthias PumbergerEmail author
  • Michael Putzier
Original Article



C-reactive protein (CRP) has been shown to be a powerful parameter for detecting acute postoperative spinal implant infections (PSII) with a high sensitivity and specificity. However, little data are available on the performance of CRP in the diagnosis of delayed PSII. The aim of the current study was therefore to establish cutoff values for diagnosing delayed infection based on serum CRP.


All patients who underwent a revision surgery after instrumented spinal fusion from January 2013 through January 2016 were included. Demographic data, laboratory values, type of infection (including microbiological and pathological results), comorbidities and clinical manifestation were collected. The European Bone and Joint Infection Society criteria, proposed to diagnose periprosthetic joint infection, were used to diagnose PSII.


A total of 257 patients were included. PSII was diagnosed in 61 patients, representing 24% of the study cohort. There was a significant difference in serum CRP levels between septic and aseptic cohorts (19.3 vs. 4.8 mg/l, p < 0.001). However, 26 patients (43%) from the PSII group had a normal (< 5 mg/l) serum CRP level prior to revision surgery. According to the ROC curve, a serum CRP threshold of 4.05 mg/l had a sensitivity of 64% and specificity of 68%. The most common isolated microorganism was Propionibacterium spp. followed by coagulase-negative staphylococci.


Serum CRP showed low sensitivity and specificity for diagnosis of delayed PSII, even after applying cutoffs optimized by using receiver operating curve analysis, because of the high incidence of low-virulent pathogens.

Graphical abstract

These slides can be retrieved under Electronic Supplementary Material.


Infection Spine surgery CRP Diagnostic Posterior fusion Revision surgery 


Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary material

586_2019_5889_MOESM1_ESM.pptx (158 kb)
Supplementary material 1 (PPTX 157 kb)


  1. 1.
    Kowalski TJ, Berbari EF, Huddleston PM, Steckelberg JM, Mandrekar JN, Osmon DR (2007) The management and outcome of spinal implant infections: contemporary retrospective cohort study. Clin Infect Dis 44(7):913–920CrossRefGoogle Scholar
  2. 2.
    Piper KE, Fernandez-Sampedro M, Steckelberg KE et al (2010) C-reactive protein, erythrocyte sedimentation rate and orthopedic implant infection. PLoS ONE 5(2):e9358CrossRefGoogle Scholar
  3. 3.
    Kang BU, Lee SH, Ahn Y, Choi WC, Choi YG (2010) Surgical site infection in spinal surgery: detection and management based on serial C-reactive protein measurements. J Neurosurg Spine 13(2):158–164CrossRefGoogle Scholar
  4. 4.
    Mok JM, Pekmezci M, Piper SL et al (2008) Use of C-reactive protein after spinal surgery: comparison with erythrocyte sedimentation rate as predictor of early postoperative infectious complications. Spine 33(4):415–421CrossRefGoogle Scholar
  5. 5.
    Akgun D, Muller M, Perka C, Winkler T (2018) The serum level of C-reactive protein alone cannot be used for the diagnosis of prosthetic joint infections, especially in those caused by organisms of low virulence. Bone Joint J 100-B(11):1482–1486CrossRefGoogle Scholar
  6. 6.
    Hahn F, Zbinden R, Min K (2005) Late implant infections caused by Propionibacterium acnes in scoliosis surgery. Eur Spine J 14(8):783–788CrossRefGoogle Scholar
  7. 7.
    Charlson ME, Pompei P, Ales KL, MacKenzie CR (1987) A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis 40(5):373–383CrossRefGoogle Scholar
  8. 8.
    Bossuyt PM, Reitsma JB, Bruns DE et al (2003) Towards complete and accurate reporting of studies of diagnostic accuracy: the STARD initiative. Clin Chem Lab Med 41(1):68–73CrossRefGoogle Scholar
  9. 9.
    von Elm E, Altman DG, Egger M et al (2007) The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Epidemiology 18(6):800–804CrossRefGoogle Scholar
  10. 10.
    Ochsner PEBO, Bodler PM, Broger I, Eich G, Hefti F, Maurer T, Nötzli H, Seiler S, Suva D, Trampuz A, Uckay I, Vogt M, Zimmerli W (2016) Infections of the musculoskeletal system: basic principles, prevention, diagnosis and treatment. Swiss Orthopaedics In-House Publisher, GrandvauxGoogle Scholar
  11. 11.
    Krenn V, Morawietz L, Perino G et al (2014) Revised histopathological consensus classification of joint implant related pathology. Pathol Res Pract 210(12):779–786CrossRefGoogle Scholar
  12. 12.
    Kim JI, Suh KT, Kim SJ, Lee JS (2010) Implant removal for the management of infection after instrumented spinal fusion. J Spinal Disord Tech 23(4):258–265CrossRefGoogle Scholar
  13. 13.
    Chen SH, Lee CH, Huang KC, Hsieh PH, Tsai SY (2015) Postoperative wound infection after posterior spinal instrumentation: analysis of long-term treatment outcomes. Eur Spine J 24(3):561–570CrossRefGoogle Scholar
  14. 14.
    Meredith DS, Kepler CK, Huang RC, Brause BD, Boachie-Adjei O (2012) Postoperative infections of the lumbar spine: presentation and management. Int Orthop 36(2):439–444CrossRefGoogle Scholar
  15. 15.
    Hu X, Lieberman IH (2018) Revision adult spinal deformity surgery: does the number of previous operations have a negative impact on outcome? Eur Spine J. Google Scholar
  16. 16.
    Tzeng A, Tzeng TH, Vasdev S et al (2015) Treating periprosthetic joint infections as biofilms: key diagnosis and management strategies. Diagn Microbiol Infect Dis 81(3):192–200CrossRefGoogle Scholar
  17. 17.
    Zimmerli W, Moser C (2012) Pathogenesis and treatment concepts of orthopaedic biofilm infections. FEMS Immunol Med Microbiol 65(2):158–168CrossRefGoogle Scholar
  18. 18.
    Bemer P, Corvec S, Tariel S et al (2008) Significance of Propionibacterium acnes-positive samples in spinal instrumentation. Spine 33(26):E971–E976CrossRefGoogle Scholar
  19. 19.
    Collins I, Wilson-MacDonald J, Chami G et al (2008) The diagnosis and management of infection following instrumented spinal fusion. Eur Spine J 17(3):445–450CrossRefGoogle Scholar
  20. 20.
    Lewkonia P, DiPaola C, Street J (2016) Incidence and risk of delayed surgical site infection following instrumented lumbar spine fusion. J Clin Neurosci 23:76–80CrossRefGoogle Scholar
  21. 21.
    Portillo ME, Salvado M, Alier A et al (2013) Prosthesis failure within 2 years of implantation is highly predictive of infection. Clin Orthop Relat Res 471(11):3672–3678CrossRefGoogle Scholar
  22. 22.
    Ben-Galim P, Rand N, Giladi M et al (2006) Association between sciatica and microbial infection: true infection or culture contamination? Spine 31(21):2507–2509CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Doruk Akgün
    • 1
  • Justus Bürger
    • 2
  • Matthias Pumberger
    • 1
    Email author
  • Michael Putzier
    • 1
  1. 1.Spine DepartmentCenter for Musculoskeletal Surgery, Charité University Medicine BerlinBerlinGermany
  2. 2.Charité University Medicine BerlinBerlinGermany

Personalised recommendations