Dataset Information

The Scoliosis Research Society adult spinal deformity standard outcome set.

ABSTRACT:

Purpose

Symptomatic adult spinal deformity (ASD) with an extremely variable presentation with pain, with and without neurogenic leg pain, and/or disturbed sagittal and coronal balance, causes a significant societal burden of disease. It is an important consequence of the aging adult population, generating a plethora of spine-related interventions with variable treatment efficacy and consistently high costs. Recent years have witnessed more than a threefold increase in the prevalence and treatment of ASD, and further increases over the coming decades are expected with the growing elderly population worldwide. The ability to monitor and assess clinical outcomes has not kept pace with these developments. This paper addresses the pressing need to provide a set of common outcome metrics for this growing group of patients with back pain and other disabilities due to an adult spinal deformity.

Methods

The standard outcome set was created by a panel with global representation, using a thorough modified Delphi procedure. The three-tiered outcome hierarchy (Porter) was used as a framework to capture full cycle of care. The standardized language of the International Classification of Functioning, Disability and Health (WHO-ICF) was used.

Results

Consensus was reached on a core set of 25 WHO-ICF outcome domains ('What to measure'); on the accompanying globally available clinician and patient reported measurement instruments and definitions ('How to measure'), and on the timing of the measurements ('When to measure'). The current work has brought to light domains not routinely reported in the spinal literature (such as pulmonary function, return to work, social participation), and domains for which no adequate instruments have yet been identified (such as how to clinically quantify in routine practice lumbar spinal stenosis, neurogenic claudication, radicular pain, and loss of lower extremity motor function).

Conclusion

A standard outcome set was developed for patients undergoing treatment for adult spinal deformity using globally available outcome metrics. The current framework can be considered a reference for further work, and may provide a starting point for routine methodical and systematic monitoring of outcomes. Post-COVID e-health may accelerate the routine capture of these types of data.

SUBMITTER: de Kleuver M

PROVIDER: S-EPMC8363534 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Study designA post hoc analysis.ObjectiveAdvances in machine learning (ML) have led to tools offering individualized outcome predictions for adult spinal deformity (ASD). Our objective is to examine the properties of these ASD models in a cohort of adult symptomatic lumbar scoliosis (ASLS) patients.Summary of background dataML algorithms produce patient-specific probabilities of outcomes, including major complication (MC), reoperation (RO), and readmission (RA) in ASD. External validation of these models is needed.MethodsThirty-nine predictive factors (12 demographic, 9 radiographic, 4 health-related quality of life, 14 surgical) were retrieved and entered into web-based prediction models for MC, unplanned RO, and hospital RA. Calculated probabilities were compared with actual event rates. Discrimination and calibration were analyzed using receiver operative characteristic area under the curve (where 0.5=chance, 1=perfect) and calibration curves (Brier scores, where 0.25=chance, 0=perfect). Ninety-five percent confidence intervals are reported.ResultsA total of 169 of 187 (90%) surgical patients completed 2-year follow up. The observed rate of MCs was 41.4% with model predictions ranging from 13% to 68% (mean: 38.7%). RO was 20.7% with model predictions ranging from 9% to 54% (mean: 30.1%). Hospital RA was 17.2% with model predictions ranging from 13% to 50% (mean: 28.5%). Model classification for all three outcome measures was better than chance for all [area under the curve=MC 0.6 (0.5-0.7), RA 0.6 (0.5-0.7), RO 0.6 (0.5-0.7)]. Calibration was better than chance for all, though best for RA and RO (Brier Score=MC 0.22, RA 0.16, RO 0.17).ConclusionsASD prediction models for MC, RA, and RO performed better than chance in a cohort of adult lumbar scoliosis patients, though the homogeneity of ASLS affected calibration and accuracy. Optimization of models require samples with the breadth of outcomes (0%-100%), supporting the need for continued data collection as personalized prediction models may improve decision-making for the patient and surgeon alike.

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