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Decision analysis to identify the ideal treatment for adult spinal deformity: What is the impact of complications on treatment outcomes? | LitMetric

AI Article Synopsis

Article Abstract

Objective: The aim of this study was to analyze the impact of treatment complications on outcomes in adult spinal deformity (ASD) using a decision analysis (DA) model.

Methods: The study included 535 ASD patients (371 with non-surgical (NS) and 164 with surgical (S) treatment) from an international multicentre database of ASD patients. DA was structured in two main steps; 1) Baseline analysis (Assessing the probabilities of outcomes, Assessing the values of preference -utilities-, Combining information on probability and utility and assigning the quality adjusted life expectancy (QALE) for each treatment) and 2) Sensitivity analysis. Complications were analyzed as life threatening (LT) and nonlife threatening (NLT) and their probabilities were calculated from the database as well as a thorough literature review. Outcomes were analyzed as improvement, no change and deterioration. Death/complete paralysis was considered as a separate category.

Results: All 535 patients were analyzed in regard to complications. Overall, there were 78 NLT and 12 LT complications and 3 death/paralysis. Surgical treatment offered significantly higher chances of clinical improvement but also was significantly more prone to complications (31.7% vs. 11.1%, p < 0.001).

Conclusion: Surgical treatment of ASD is more likely to cause complications compared to NS treatment. On the other hand, surgery has been shown to provide a higher likelihood of improvement in HRQoL scores. So, the decision on the type of treatment in ASD needs to take both chances of improvement and burden associated with S or NS treatments and better be arrived by the active participation of patients and physicians equipped with the present information.

Level Of Evidence: Level II, Decision analysis.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6197456PMC
http://dx.doi.org/10.1016/j.aott.2017.03.003DOI Listing

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