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预测颞叶切除术治疗癫痫后言语记忆下降。

Predicting verbal memory decline following temporal lobe resection for epilepsy.

机构信息

Department of Clinical Neuroscience, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden.

Statistiska Konsultgruppen, Gothenburg, Sweden.

出版信息

Acta Neurol Scand. 2019 Nov;140(5):312-319. doi: 10.1111/ane.13146. Epub 2019 Jul 30.

Abstract

OBJECTIVES

The aim of the study was to develop a prediction model for verbal memory decline after temporal lobe resection (TLR) for epilepsy. The model will be used in the preoperative counselling of patients to give individualized information about risk for verbal memory decline.

MATERIALS AND METHODS

A sample of 110 consecutive patients who underwent TLR for epilepsy at Sahlgrenska University Hospital between 1987 and 2011 constituted the basis for the prediction model. They had all gone through a formal neuropsychological assessment before surgery and 2 years after. Penalized regression and 20 × 10-fold cross-validation were used in order to build a reliable model for predicting individual risks.

RESULTS

The final model included four predictors: side of surgery; inclusion or not of the hippocampus in the resection; preoperative verbal memory function; and presence/absence of focal to bilateral tonic-clonic seizures (TCS) the last year prior to the presurgical investigation. The impact of a history of TCS is a new finding which we interpret as a sign of a more widespread network disease which influences neuropsychological function and the cognitive reserve. The model correctly identified 82% of patients with post-operative decline in verbal memory, and the overall accuracy was 70%-85% depending on choice of risk thresholds.

CONCLUSIONS

The model makes it possible to provide patients with individualized prediction regarding the risk of verbal memory decline following TLR. This will help them make more informed decisions regarding treatment, and it will also enable the epilepsy surgery team to prepare them better for the rehabilitation process.

摘要

目的

本研究旨在为颞叶切除术(TLR)治疗癫痫后言语记忆下降建立预测模型。该模型将用于患者术前咨询,为言语记忆下降风险提供个体化信息。

材料和方法

1987 年至 2011 年,在萨尔格伦斯卡大学医院接受 TLR 治疗的 110 例连续癫痫患者构成了预测模型的基础。所有患者在手术前和手术后 2 年均接受了正式的神经心理学评估。使用惩罚回归和 20×10 倍交叉验证来构建用于预测个体风险的可靠模型。

结果

最终模型包括四个预测因素:手术侧;是否包括海马在内的切除术;术前言语记忆功能;以及术前调查前一年是否存在局灶性双侧强直阵挛发作(TCS)。TCS 病史的影响是一个新的发现,我们将其解释为更广泛的网络疾病影响神经心理学功能和认知储备的迹象。该模型正确识别了 82%术后言语记忆下降的患者,总体准确性为 70%-85%,具体取决于风险阈值的选择。

结论

该模型能够为 TLR 后言语记忆下降的风险提供个体化预测。这将帮助他们做出更明智的治疗决策,也使癫痫手术团队能够更好地为康复过程做好准备。

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