Limited Predictive Performance of the Global Alignment and Proportion (GAP) Score for Mechanical Complications in Older Asian Patients With Adult Spinal Deformity: A Multicenter Validation Study.
retrospective_cohort · Level III
Where this comes from
- Record sourced from PubMed, PMID 42531466.
- Also identified by DOI 10.1177/21925682261474872 and PMC identifier 13423955.
- Licence recorded as CC BY-NC-ND.
- Because redistribution is not established, this page shows the abstract only. Follow the links below for the full text.
Abstract
Study DesignRetrospective cohort study.ObjectivesSurgery for adult spinal deformity (ASD) is associated with postoperative mechanical complications (MCs), such as proximal junctional kyphosis (PJK). The applicability of the Global Alignment and Proportion (GAP) score for predicting MCs in older Asians remains unclear. This study aimed to evaluate the validity of the GAP score in Asians patients by stratifying them into younger and older groups.MethodsWe studied 274 patients who had undergone multi-level spinal fusion and were followed up for at least 2 years. Patients were divided into a younger group (Under-69, n = 122) and an older group (Over-70, n = 152). MCs were assessed at 2 years postoperatively. Propensity score matching was performed to compare the incidence of MCs across groups. Logistic regression models were used to examine the interaction between GAP score and age.ResultsMC occurred in 93 patients (34%), with no significant differences between groups. In the Under-69 group, GAP scores did not correlate with MC occurrence. In contrast, the in the Over-70 group patients with MCs had significantly lower GAP scores (6.6 ± 3.4 vs. 8.0 ± 3.2, <i>P</i> = 0.022). The interaction between GAP score and age was not significant in the logistic regression models.ConclusionsThe GAP score demonstrated limited predictive ability for MCs in this Asian ASD cohort, particularly in older patients. These findings suggest that alignment-based prediction models alone may be insufficient for MC risk stratification in aging populations.