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The SHORE Score: A Novel Predictive Tool for Improvement After Decompression Surgery in Adult Chiari Malformation
James Feghali1, Yangyiran Xie2, Yuxi Chen2
1Department of Neurosurgery, Johns Hopkins University, Baltimore, Maryland, USA.
Background:
A practical scoring system predicting significant improvement after surgical decompression in adult Chiari malformation type I (CM-1) based on validated outcome measures is lacking. We aimed to develop a simple score and improvement calculator to facilitate the decision making process in symptomatic CM-1 patients.
Methods:
We evaluated adult CM-1 patients who presented to our institution between September 2006 and September 2018 and underwent surgical decompression. Previously treated patients were excluded. Univariable analysis and multivariable logistic regression were conducted to derive an optimal model predictive of improvement on last follow-up as measured by the Chicago Chiari Outcome Scale. A score was derived using the beta coefficients of the model, and predictive performance was assessed using receiver operating curves with bootstrap validation. Finally, a web-based improvement calculator was deployed.
Results:
The surgical cohort consisted of 149 adult CM-1 patients, of which 100 (67%) experienced significant clinical improvement (Chicago Chiari Outcome Scale ≥14) after a mean follow-up of 1.9 years. The final model predictive of significant clinical improvement consisted of headache with Valsalva (odds ratio [OR] = 2.39; P = 0.030), nonwhite race (OR = 2.57; P = 0.041), absence of visual symptoms (OR = 2.59; P = 0.015), syrinx absence (OR = 1.59; P = 0.315), and increased odontoid retroflexion (OR = 2.82; P = 0.009). The score was termed SHORE, which summarizes the model's predictive factors, each assigned 1 point. The model had an area under the curve of 0.754 with an optimism-correct value of 0.721. A calculator was deployed under: https://jhuspine2.shinyapps.io/SHORE_score/.
Conclusions:
The score and calculator can serve as supplements to clinical decision making by providing realistic and personalized expectations of postoperative outcome.
