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Predicting clinical outcome and length of sick leave after surgery for lumbar spinal stenosis in Sweden: a multi-register evaluation

  • Hanna IderbergEmail author
  • Carl Willers
  • Fredrik Borgström
  • Rune Hedlund
  • Olle Hägg
  • Hans Möller
  • Ewald Ornstein
  • Bengt Sandén
  • Holger Stalberg
  • Hans Torevall-Larsson
  • Tycho Tullberg
  • Peter Fritzell
Original Article

Abstract

Purpose

Lumbar spinal stenosis (LSS) can be surgically treated, with variable outcome. Studies have linked socioeconomic factors to outcome, but no nation-wide studies have been performed. This register-based study, including all patients surgically treated for LSS during 2008–2012 in Sweden, aimed to determine predictive factors for the outcome of surgery.

Methods

Clinical and socioeconomic factors with impact on outcome in LSS surgery were identified in several high-coverage registers, e.g., the national quality registry for spine surgery (Swespine, FU-rate 70–90%). Multivariate regression analyses were conducted to assess their effect on outcome. Two patient-reported outcome measures, Global Assessment of leg pain (GA) and the Oswestry Disability Index (ODI), as well as length of sick leave after surgery were analyzed.

Results

Clinical and socioeconomic factors significantly affected health outcome (both GA and ODI). Some predictors of a good outcome (ODI) were: being born in the EU, reporting no back pain at baseline, a high disposable income and a high educational level. Some factors predicting a worse outcome were previous surgery, having had back pain more than 2 years, having comorbidities, being a smoker, being on social welfare and being unemployed.

Conclusions

The study highlights the relevance of adding socioeconomic factors to clinical factors for analysis of patient-reported outcomes, although the causal pathway of most predictors’ impact is unknown. These findings should be further investigated in the perspective of treatment selection for individual LSS patients. The study also presents a foundation of case mix algorithms for predicting outcome of surgery for LSS.

Graphical abstract

These slides can be retrieved under Electronic Supplementary Material.

Keywords

Lumbar spinal stenosis Regression analysis Patient-reported outcome Sick leave Prediction algorithms Spine surgery Global assessment Functional disability Socioeconomic factors Multi-register study 

Notes

Acknowledgements

The authors thank Swespine, Swedish Society of Spinal Surgery (4 s) and all participating county councils. Partial funding from Forte programme Grant 2012/1688 (“Value and choice”) is gratefully acknowledged.

Funding

Funding for this research was provided by Sveus, through the Ministry of Health and Social Affairs (Dnr S2012/8356/FS) and seven Swedish regions. Sveus is a research collaboration in which seven Swedish regions develop systems for value-based monitoring of health care. The overarching aim of Sveus is to stimulate a value-driven, efficient and patient-centered health care, and the work has been carried out for a number of different patient groups, of which spine surgery is one.

Compliance with ethical standards

Conflict of interest

HI, CW and FB are employees at Ivbar Institute (a healthcare research consultancy), which has received research grants from Sveus (county council consortium) for the submitted work. FB holds shares in Ivbar Institute. The other authors declare that they have no conflict of interest.

Supplementary material

586_2018_5842_MOESM1_ESM.pptx (208 kb)
Supplementary material 1 (PPTX 207 kb)
586_2018_5842_MOESM2_ESM.docx (92 kb)
Supplementary material 2 (DOCX 92 kb)

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Hanna Iderberg
    • 1
    • 2
    Email author
  • Carl Willers
    • 1
    • 3
  • Fredrik Borgström
    • 1
    • 2
  • Rune Hedlund
    • 4
  • Olle Hägg
    • 5
  • Hans Möller
    • 6
  • Ewald Ornstein
    • 7
  • Bengt Sandén
    • 8
  • Holger Stalberg
    • 9
  • Hans Torevall-Larsson
    • 10
  • Tycho Tullberg
    • 11
  • Peter Fritzell
    • 12
    • 13
  1. 1.Ivbar InstituteStockholmSweden
  2. 2.Department of Learning, Informatics, Management and Ethics, Medical Management CentreKarolinska InstitutetStockholmSweden
  3. 3.Department for Clinical Science and EducationKarolinska InstitutetStockholmSweden
  4. 4.Department of OrthopaedicsSahlgrenska University HospitalGothenburgSweden
  5. 5.Spine Center GöteborgGothenburgSweden
  6. 6.Department of Clinical Sciences, Intervention and Technology (CLINTEC)Karolinska InstitutetStockholmSweden
  7. 7.Department of OrthopaedicsÖrebro University HosiptalÖrebroSweden
  8. 8.Section of Orthopedics, Department of Surgical SciencesUppsala UniversityUppsalaSweden
  9. 9.Hälso- o. sjukvårdsförvaltningen, Stockholm County CouncilStockholmSweden
  10. 10.Falu LasarettFalunSweden
  11. 11.Stockholm Spine Center ABLöwenströmska SjukhusetUpplands VäsbySweden
  12. 12.Futurum AcademyJönköpingSweden
  13. 13.S:t Göran HospitalStockholmSweden

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