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

European spine journal

article

Hanna Iderberg¹  Carl Willers¹  Fredrik Borgström¹  Rune Hedlund⁴  Olle Hägg⁵  Hans Möller⁶  Ewald Ornstein⁷  Bengt Sandén⁸  Holger Stalberg⁹  Hans Torevall-Larsson^1,10  Tycho Tullberg^1,11  Peter Fritzell^1,12 

[1] Ivbar Institute;Department of Learning, Management and Ethics, Medical Management Centre, Karolinska Institutet;Department for Clinical Science and Education, Karolinska Institutet;Department of Orthopaedics, Sahlgrenska University Hospital;Spine Center Göteborg;Department of Clinical Sciences, Karolinska Institutet;Department of Orthopaedics, Örebro University Hosiptal;Section of Orthopedics, Department of Surgical Sciences, Uppsala University;Hälso- o. sjukvårdsförvaltningen, Stockholm County Council;Falu Lasarett;Stockholm Spine Center AB;Futurum Academy;S:t Göran Hospital

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

DOI  :  10.1007/s00586-018-5842-3

来源: Springer

【 摘 要 】

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. 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. 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. 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. These slides can be retrieved under Electronic Supplementary Material.

【 授权许可】

Unknown