Date of Submission

Spring 2022

Academic Program

Biology

Project Advisor 1

Gabriel Perron

Abstract/Artist's Statement

Previous strategies, such as the Global Alignment and Proportionality (GAP) score and age-adjusted alignment, have sought to incorporate age into realignment goals to mitigate the occurrence of radiographic or mechanical complications. While age is often a component studied in previous investigations, there is a lack of literature characterizing mechanical failure across the age spectrum in patients undergoing adult spinal deformity correction. To investigate the role of age in mechanical complications for patients undergoing correction for adult spinal deformity (ASD), we performed a retrospective study of a prospectively enrolled, single-center ASD database. We incorporated ASD patients aged 18 or older, with three or more levels fused, as well as complete baseline and up to three-year follow-up data. The 480 ASD patients that met our inclusion criteria were grouped by age such that individuals at or below 60 years of age (Younger) were separated from those over 60 (Older) at the time of surgery. We further stratified our groups by global deformity based on T1 Pelvic Angle (T1PA) into high global deformity (HighD) and low deformity (LowD). Mechanical complications were classified as major, if involving invasive intervention or having prolonged or permanent morbidity or mortality. Radiographic angles evaluated included PI-LL, PT, SVA, T1PA, L1PA, and L4-S1. Descriptive analyses identified mean demographic and surgical details of the cohort. Means comparison tests were used to compare baseline demographics, surgical details, radiographic and clinical outcomes between age deformity groups. Binary logistic regression analysis assessed variables as predictors for mechanical complication rates, overall and major, in each age deformity group. Multivariable logistic regression analyses were used to develop a model consisting of significant predictors for mechanical complications in each age deformity group. Although there were no significant predictors for overall mechanical complications in any of the age deformity groups, different individual predictors were identified for major mechanical complications in each group. Despite this, all patients that experienced major mechanical complications also underwent pelvic fixation in every group. Each model also incorporated different factors, though baseline PI-LL was incorporated in every model.

Previous strategies, such as the Global Alignment and Proportionality (GAP) score and age-adjusted alignment, have sought to incorporate age into realignment goals to mitigate the occurrence of radiographic or mechanical complications. While age is often a component studied in previous investigations, there is a lack of literature characterizing mechanical failure across the age spectrum in patients undergoing adult spinal deformity correction. To investigate the role of age in mechanical complications for patients undergoing correction for adult spinal deformity (ASD), we performed a retrospective study of a prospectively enrolled, single-center ASD database. We incorporated ASD patients aged 18 or older, with three or more levels fused, as well as complete baseline and up to three-year follow-up data. The 480 ASD patients that met our inclusion criteria were grouped by age such that individuals at or below 60 years of age (Younger) were separated from those over 60 (Older) at time of surgery. We further stratified our groups by global deformity based on T1 Pelvic Angle (T1PA) into high global deformity (HighD) and low deformity (LowD). Mechanical complications were classified as major, if involving invasive intervention or having prolonged or permanent morbidity or mortality. Radiographic angles evaluated included PI-LL, PT, SVA, T1PA, L1PA, and L4-S1. Descriptive analyses identified mean demographic and surgical details of cohort. Means comparison tests were used to compare baseline demographics, surgical details, radiographic and clinical outcomes between age deformity groups. Binary logistic regression analysis assessed variables as predictors for mechanical complication rates, overall and major, in each age deformity group. Multivariable logistic regression analyses were used to develop a model consisting of significant predictors for mechanical complications in each age deformity group. Although there were no significant predictors for overall mechanical complications in any of the age deformity groups, different individual predictors were identified for major mechanical complications in each group. Despite this, all patients that experienced major mechanical complications also underwent pelvic fixation in every group. Each model also incorporated different factors, though baseline PI-LL was incorporated in every model.

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