Frontiers in Neurology (Jan 2024)

Development and validation of a prognostic computed tomography scoring model for functional outcomes in patients with large hemispheric infarction following decompressive craniectomy

  • Yutong Zhao,
  • Yuguang Tang,
  • Zongyi Xie

DOI
https://doi.org/10.3389/fneur.2024.1336121
Journal volume & issue
Vol. 15

Abstract

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BackgroundThere is no established prognostic scoring system developed for patients with large hemispheric infarction (LHI) following decompressive craniectomy (DC) based on imaging characteristics. The present study aimed to develop and validate a new computed tomography scoring model to assess the 6-month risk of poor functional outcomes (modified-Rankin scale [mRS] score of 4–6) in patients with LHI receiving DC.MethodsThis retrospective cohort study included patients at two tertiary stroke centers. A prediction model was developed based on a multivariable logistic regression. The final risk factors included the ASPECTS (Alberta Stroke Program Early Computed Tomography Score), longitudinal fissure cistern, Sylvian fissure cistern, and additional vascular territory involvement. 1,000 bootstrap resamples and temporal validation were implemented as validations for the scoring system.ResultsOf the 100 individuals included in the development cohort, 71 had poor functional outcomes. The scoring model presented excellent discrimination and calibration with C-index = 0.87 for the development cohort, and C-index = 0.83 for the temporal validation cohort with non-significant Hosmer-Lemeshow goodness-of-fit test. The scoring model also showed an improved AUC compared to the ASPECTS. For each point in the score model, the adjusted risk of poor functional outcomes increase by 47.8% (OR = 1.48, p < 0.001). The scores were inversely correlated with MAP (mean arterial pressure, paired t-test, p = 0.0015) and CPP (cerebral perfusion pressure, rho = −0.17, p = 0.04).ConclusionIn patients with LHI following DC, the score system is an excellent predictor of poor functional outcomes and is associated with CPP and MAP, which might be worth considering in clinical settings after further external validation.

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