Department of Neurology and Neurosurgery, University Medical Center Utrecht, Utrecht, The Netherlands.
Department of Neurology and Neurosurgery, University Medical Center Utrecht, Utrecht, The Netherlands.
World Neurosurg. 2023 Jul;175:e693-e703. doi: 10.1016/j.wneu.2023.04.008. Epub 2023 Apr 8.
Cranioplasty after craniectomy can result in high rates of postoperative complications. Although determinants of postoperative outcomes have been identified, a prediction model for predicting cranioplasty implant survival does not exist. Thus, we sought to develop a prediction model for cranioplasty implant survival after craniectomy.
We performed a retrospective cohort study of patients who underwent cranioplasty following craniectomy between 2014 and 2020. Missing data were imputed using multiple imputation. For model development, multivariable Cox proportional hazards regression analysis was performed. To test whether candidate determinants contributed to the model, we performed backward selection using the Akaike information criterion. We corrected for overfitting using bootstrapping techniques. The performance of the model was assessed using discrimination and calibration.
A total of 182 patients were included (mean age, 43.0 ± 19.7 years). Independent determinants of cranioplasty implant survival included the indication for craniectomy (compared with trauma-vascular disease: hazard ratio [HR], 0.65 [95% confidence interval (CI), 0.36-1.17]; infection: HR, 0.76 [95% CI, 0.32-1.80]; tumor: HR, 1.40 [95% CI, 0.29-6.79]), cranial defect size (HR, 1.01 per cm [95% CI, 0.73-1.38]), use of an autologous bone flap (HR, 1.63 [95% CI, 0.82-3.24]), and skin closure using staples (HR, 1.42 [95% CI, 0.79-2.56]). The concordance index of the model was 0.60 (95% CI, 0.47-0.73).
We have developed the first prediction model for cranioplasty implant survival after craniectomy. The findings from our study require external validation and deserve further exploration in future studies.
颅骨切除术 后行颅骨修补术可导致术后并发症发生率较高。尽管已经确定了术后结局的决定因素，但尚无预测颅骨修补术植入物存活率的预测模型。因此，我们试图开发一种预测颅骨切除术 后颅骨修补术植入物存活率的模型。
我们对 2014 年至 2020 年间行颅骨修补术的患者进行了回顾性队列研究。使用多重插补法对缺失数据进行插补。为了开发模型，我们进行了多变量 Cox 比例风险回归分析。为了测试候选决定因素是否对模型有贡献，我们使用赤池信息量准则进行了向后选择。我们使用自举技术纠正过拟合。使用区分度和校准度评估模型的性能。
共纳入 182 例患者（平均年龄 43.0 ± 19.7 岁）。颅骨修补术植入物存活率的独立决定因素包括颅骨切除术的指征（与创伤血管疾病相比：风险比 [HR]，0.65 [95%置信区间 （CI），0.36-1.17]；感染：HR，0.76 [95%CI，0.32-1.80]；肿瘤：HR，1.40 [95%CI，0.29-6.79]）、颅骨缺损大小（HR，每厘米增加 1.01 [95%CI，0.73-1.38]）、使用自体骨瓣（HR，1.63 [95%CI，0.82-3.24]）和使用订书钉进行皮肤闭合（HR，1.42 [95%CI，0.79-2.56]）。模型的一致性指数为 0.60（95%CI，0.47-0.73）。
我们已经开发出第一个颅骨切除术 后颅骨修补术植入物存活率的预测模型。我们的研究结果需要外部验证，值得在未来的研究中进一步探讨。
