External Validation of an Extreme Gradient Boosting Model for Prediction of Delayed Cerebral Ischemia After Aneurysmal Subarachnoid Hemorrhage

被引:2
|
作者
Palmisciano, Paolo [1 ]
Hoz, Samer S. [1 ]
Johnson, Mark D. [1 ]
Forbes, Jonathan A. [1 ]
Prestigiacomo, Charles J. [1 ]
Zuccarello, Mario [1 ]
Andaluz, Norberto [1 ]
机构
[1] Univ Cincinnati Coll Med, Dept Neurosurg, Cincinnati, OH 45267 USA
关键词
Aneurysmal subarachnoid hemorrhage; Delayed cerebral ischemia; Machine learning; Predictive analysis; Vasospasm; SYMPTOMATIC VASOSPASM; NEURAL-NETWORK; EPIDEMIOLOGY; RISK;
D O I
10.1016/j.wneu.2023.03.036
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
BACKGROUND: Delayed cerebral ischemia (DCI) may significantly worsen the functional status of patients with aneurysmal subarachnoid hemorrhage (aSAH). Several authors have designed predictive models for early identi-fication of patients at risk of post-aSAH DCI. In this study, we externally validate an extreme gradient boosting (EGB) forecasting model for post-aSAH DCI prediction. METHODS: A 9-year institutional retrospective review of patients with aSAH was performed. Patients were included if they underwent surgical or endovascular treatment and had available follow-up data. DCI was diagnosed as new -onset neurologic deficits at 4-12 days after aneurysm rupture, defined as worsening Glasgow Coma Scale score for & DDAG;2 points, and new ischemic infarcts at imaging.RESULTS: We collected 267 patients with aSAH. At admission, median Hunt-Hess score was 2 (range, 1-5), median Fisher score 3 (range, 1-4), and median modified Fisher score 3 (range, 1-4). One-hundred and forty-five patients underwent external ventricular drainage place-ment for hydrocephalus (54.3%). The ruptured aneurysms were treated with clipping (64%), coiling (34.8%), and stent-assisted coiling (1.1%). Fifty-eight patients (21.7%) were diagnosed with clinical DCI and 82 (30.7%) with asymptomatic imaging vasospasm. The EGB classifier correctly predicted 19 cases of DCI (7.1%) and 154 cases of no-DCI (57.7%), achieving sensitivity of 32.76% and speci-ficity of 73.68%. The calculated F1 score and accuracy were 0.288% and 64.8%, respectively.CONCLUSIONS: We validated that the EGB model is a potential assistant tool to predict post-aSAH DCI in clinical practice, finding moderate-high specificity but low sensi-tivity. Future research should investigate the underlying pathophysiology of DCI to allow the development of high -performing forecasting models.
引用
收藏
页码:E108 / E114
页数:7
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