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Predictors of pain and disability outcomes in one thousand, one hundred and eight patients who underwent lumbar discectomy surgery

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Abstract

Background

A key component toward improving surgical outcomes is proper patient selection. Improved selection can occur through exploration of prognostic studies that identify variables which are associated with good or poorer outcomes with a specific intervention, such as lumbar discectomy. To date there are no guidelines identifying key prognostic variables that assist surgeons in proper patient selection for lumbar discectomy. The purpose of this study was to identify baseline characteristics that were related to poor or favourable outcomes for patients who undergo lumbar discectomy. In particular, we were interested in prognostic factors that were unique to those commonly reported in the musculoskeletal literature, regardless of intervention type.

Methods

This retrospective study analysed data from 1,108 patients who underwent lumbar discectomy and had one year outcomes for pain and disability. All patient data was part of a multicentre, multi-national spine repository. Ten relatively commonly captured data variables were used as predictors for the study: (1) age, (2) body mass index, (3) gender, (4) previous back surgery history, (5) baseline disability, unique baseline scores for pain for both (6) low back and (7) leg pain, (8) baseline SF-12 Physical Component Summary (PCS) scores, (9) baseline SF-12 Mental Component Summary (MCS) scores, and (10) leg pain greater than back pain. Univariate and multivariate logistic regression analyses were run against one year outcome variables of pain and disability.

Results

For the multivariate analyses associated with the outcome of pain, older patients, those with higher baseline back pain, those with lesser reported disability and higher SF-12 MCS quality of life scores were associated with improved outcomes. For the multivariate analyses associated with the outcome of disability, presence of leg pain greater than back pain and no previous surgery suggested a better outcome.

Conclusions

For this study, several predictive variables were either unique or conflicted with those advocated in general prognostic literature, suggesting they may have value for clinical decision making for lumbar discectomy surgery. In particular, leg pain greater than back pain and older age may yield promising value. Other significant findings such as quality of life scores and prior surgery may yield less value since these findings are similar to those that are considered to be prognostic regardless of intervention type.

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References

  1. Blamoutier A (2013) Surgical discectomy for lumbar disc herniation: surgical techniques. Orthop Traumatol Surg Res 99(1):S187–S196

    Article  CAS  PubMed  Google Scholar 

  2. Mysliwiec LW, Cholewicki J, Winkelpleck MD, Eis GP (2010) MSU classification for herniated lumbar discs on MRI: toward developing objective criteria for surgical selection. Eur Spine J 19(7):1087–93

    Article  PubMed Central  PubMed  Google Scholar 

  3. Chou R, Baisden J, Carragee EJ, Resnick DK, Shaffer WO, Loeser JD (2009) Surgery for low back pain: a review of the evidence for an American Pain Society Clinical Practice Guideline. Spine (Phila Pa 1976) 34(10):1094–1109

    Article  Google Scholar 

  4. Weinstein JN, Lurie JD, Tosteson TD, Tosteson AN, Blood E, Abdu WA et al (2008) Surgical versus non-operative treatment for lumbar disc herniation: four-year results for the spine patient outcomes research trial (SPORT). Spine 33(25):2789–2800

    Article  PubMed Central  PubMed  Google Scholar 

  5. den Boer JJ, Oostendorp RA, Beems T, Munneke M, Evers AW (2006) Reduced work capacity after lumbar disc surgery: the role of cognitive-behavioral and work-related risk factors. Pain 126(1–3):72–78

    Article  Google Scholar 

  6. DeBerard MS, Wheeler AJ, Gundy JM, Stein DM, Colledge AL (2011) Presurgical biopsychosocial variables predict medical, compensation, and aggregate costs of lumbar discectomy in Utah workers’ compensation patients. Spine J 11(5):395–401

    Article  PubMed  Google Scholar 

  7. Horn SD, DeJong G, Deutscher D (2012) Practice-based evidence research in rehabilitation: an alternative to randomized controlled trials and traditional observational studies. Arch Phys Med Rehabil 93(8 Suppl):S127–S137

    Article  PubMed  Google Scholar 

  8. Fairbank JC, Couper J, Davies JB, O’Brien JP (1980) The Oswestry low back pain disability questionnaire. Physiother 66:271–273

    CAS  Google Scholar 

  9. Fairbank JC, Pynsent PB (2000) The Oswestry disability index. Spine (Phila Pa 1976) 25:2940–2952, discussion 2952

    Article  CAS  Google Scholar 

  10. Gallagher EJ, Liebman M, Bijur PE (2001) Prospective validation of clinically important changes in pain severity measured on a visual analog scale. Ann Emerg Med 38:633–638

    Article  CAS  PubMed  Google Scholar 

  11. Hagg O, Fritzell P, Nordwall A (2003) Swedish Lumbar Spine Study Group. The clinical importance of changes in outcome scores after treatment for chronic low back pain. Eur Spine J 12:12–20

    CAS  PubMed  Google Scholar 

  12. Goode A, Cook C, Brown C, Isaacs R, Roman M, Richardson W (2011) Differences in comorbidities on low back pain and low back related leg pain. Pain Pract 11(1):42–47

    Article  PubMed Central  PubMed  Google Scholar 

  13. Abdolell M, LeBlanc M, Stephens D, Harrison RV (2002) Binary partitioning for continuous longitudinal data: categorizing a prognostic variable. Statist Med 21:3395–3409

    Article  CAS  Google Scholar 

  14. Lausen B, Schumacher M (1996) Evaluating the effect of optimized cutoff values in the assessment of prognostic factors. Computational Stat Data Anal 21:307–326

    Article  Google Scholar 

  15. Hollander N, Sauerbrei W, Schumacher M (2004) Confidence intervals for the effect of a prognostic factor after selection of an 'optimal' cutpoint. Stat Med 23:17

    Article  Google Scholar 

  16. Shen J, Gao SA (2008) Solution to separation and multicollinearity in multiple logistic regression. J Data Sci 6(4):515–531

    PubMed Central  PubMed  Google Scholar 

  17. Dworkin RH, Turk DC, Wyrwich KW, Beaton D, Cleeland CS, Farrar JT et al (2008) Interpreting the clinical importance of treatment outcomes in chronic pain clinical trials: IMMPACT recommendations. J Pain 9(2):1

    Article  Google Scholar 

  18. Homer DW, Lemeshow S (2000) Applied logistic regression. 2nd Edition ed. Wiley, New York

    Book  Google Scholar 

  19. Nagelkerke NJD (1991) A note on a general definition of the coefficient of determination. Biometrika 78:691–692

    Article  Google Scholar 

  20. Laisné F, Lecomte C, Corbière M (2012) Biopsychosocial predictors of prognosis in musculoskeletal disorders: a systematic review of the literature. Disabil Rehabil 34(5):355–382

    Article  PubMed  Google Scholar 

  21. Shin BJ (2014) Risk factors for recurrent lumbar disc herniations. Asian Spine J 8(2):211–215

    Article  PubMed Central  PubMed  Google Scholar 

  22. Kongsted A, Kent P, Albert H, Jensen TS, Manniche C (2012) Patients with low back pain differ from those who also have leg pain or signs of nerve root involvement—a cross-sectional study. BMC Musculoskelet Disord 13:236

    Article  PubMed Central  PubMed  Google Scholar 

  23. Kovac I (2011) (abstract). Low back pain vs. leg dominant pain. Reumatizam 58(2):108–111

    PubMed  Google Scholar 

  24. Patrick DL, Deyo RA, Atlas SJ, Singer DE, Chapin A, Keller RB (1995) Assessing health-related quality of life in patients with sciatica. Spine (Phila Pa 1976) 20(17):1899–1908, discussion 1909

    Article  CAS  Google Scholar 

  25. Weinstein JN, Lurie JD, Tosteson TD, Hanscom B, Tosteson AN, Blood EA et al (2007) Surgical versus nonsurgical treatment for lumbar degenerative spondylolisthesis. N Engl J Med 356(22):2257–2270

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  26. Sargious A, Lee SJ (2014) Remote collection of questionnaires. Clin Exp Rheumatol 32(5 Suppl 85):S-168–S-172

    Google Scholar 

  27. Grevitt M, Pande K, O’Dowd J, Webb J (1998) Do first impressions count? A comparison of subjective and psychologic assessment of spinal patients. Eur Spine J 7:218–223

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  28. Rodeghero J, Cook C (2014) The use of big data in manual physiotherapy. Man Ther 9(6):509–510

    Article  Google Scholar 

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Correspondence to Chad E. Cook.

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Cook, C.E., Arnold, P.M., Passias, P.G. et al. Predictors of pain and disability outcomes in one thousand, one hundred and eight patients who underwent lumbar discectomy surgery. International Orthopaedics (SICOT) 39, 2143–2151 (2015). https://doi.org/10.1007/s00264-015-2748-0

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  • DOI: https://doi.org/10.1007/s00264-015-2748-0

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