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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. These slides can be retrieved under Electronic Supplementary Material. [ABSTRACT FROM AUTHOR]

Self-report questionnaires are commonly used in family research, but very little attention is paid to the specific measurement properties of the ordered categorical data recorded. The item responses of self-report questionnaires consist of ordered categories. The main property of this type of data is that the labels do not represent a mathematical value but only an order, i.e., one set of labels can be replaced by another set of increasing numbers of symbols. The non-additivity of categorical data means that sum scores cannot be used as a global assessment of the variable. The aims of this study were to further develop the third version of the self-report questionnaire Family Adaptability and Cohesion, Evaluation Scales (FACES), for use in Sweden and to construct a global scale of family function for the variables cohesion and adaptability. The statistical methods used take account of the rank-invariant properties of ordered categorical data. [ABSTRACT FROM AUTHOR]