Department of Anesthesiology, University of Kentucky, Lexington, Kentucky, USA.
Department of Biostatistics, University of Kentucky, Lexington, Kentucky, USA.
World Neurosurg. 2020 Aug;140:e153-e160. doi: 10.1016/j.wneu.2020.04.203. Epub 2020 May 5.
Patients with aneurysmal subarachnoid hemorrhage (aSAH) may have significant potentially harmful ionizing radiation exposure (PHIRE) from diagnostic tests and medical procedures (DTMP) during their initial hospitalization.
In this single-center, retrospective, observational study, we evaluated the incidence of PHIRE using all patients with radiographically proven aSAH who survived hospitalization over a 6-year period. Patient data were then used to fit a full logistic regression model, a reduced-variable logistic regression model with least absolute shrinkage and selection operator penalty, and a nonparametric tree-based model. Testing data were then used to calculate each predictive model's accuracy.
Of 192 patients included in this study, 69 (35.9%) met criteria for PHIRE. Patients with PHIRE were more likely to have a poor Hunt-Hess Score (40.6% vs. 12.2%, P < 0.0001), a poor modified Fischer Grading Scale score (30.4% vs. 16.3%, P = 0.03), ventriculostomy (91.3% vs. 47.2%, P < 0.0001), vasospasm (81.2% vs. 34.1%, P < 0.0001), and ventriculoperitoneal shunt (31.9% vs. 10.6%, P < 0.001). Parametric PHIRE prediction modeling with a full logistic regression model and reduced-logistic regression modeling with least absolute shrinkage and selection operator penalty demonstrated PHIRE prediction accuracy of 67% and 78% accuracy, respectively. Nonparametric tree-based PHIRE modeling demonstrated a prediction accuracy of 58%.
On the basis of our data, PHIRE occurs in approximately 35% of aSAH patients. The reduced-variable logistic regression model had the greatest predictive accuracy for PHIRE. Future studies should validate our findings and predictive models and, if our conclusions hold, further clarification of the risks of PHIRE and methods to reduce PHIRE should be investigated.
患有颅内动脉瘤性蛛网膜下腔出血（aSAH）的患者在其初始住院期间可能会因诊断性检查和医疗程序（DTMP）而受到大量潜在有害的电离辐射暴露（PHIRE）。
在这项单中心、回顾性、观察性研究中，我们评估了在 6 年期间幸存住院的所有经影像学证实患有 aSAH 的患者中 PHIRE 的发生率。然后，使用患者数据拟合全逻辑回归模型、具有最小绝对值收缩和选择算子惩罚的简化变量逻辑回归模型以及非参数树基模型。然后，使用测试数据计算每个预测模型的准确性。
在本研究纳入的 192 名患者中，有 69 名（35.9%）符合 PHIRE 标准。有 PHIRE 的患者更有可能具有较差的 Hunt-Hess 评分（40.6% 比 12.2%，P < 0.0001）、较差的改良 Fischer 分级量表评分（30.4% 比 16.3%，P = 0.03）、脑室造口术（91.3% 比 47.2%，P < 0.0001）、血管痉挛（81.2% 比 34.1%，P < 0.0001）和脑室-腹腔分流术（31.9% 比 10.6%，P < 0.001）。全逻辑回归模型和最小绝对值收缩和选择算子惩罚简化逻辑回归模型的参数 PHIRE 预测建模分别显示 PHIRE 预测准确性为 67%和 78%。非参数树基 PHIRE 建模显示预测准确性为 58%。
根据我们的数据，大约 35%的 aSAH 患者发生 PHIRE。简化变量逻辑回归模型对 PHIRE 具有最大的预测准确性。未来的研究应验证我们的发现和预测模型，如果我们的结论成立，应进一步阐明 PHIRE 的风险并研究减少 PHIRE 的方法。
