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预测成人癫痫患者抗癫痫药物治疗效果的风险评估工具

Risk Assessment Tool in Predicting the Therapeutic Outcomes of Antiseizure Medication in Adults with Epilepsy.

作者信息

Rusli Rose Aniza, Makmor Bakry Mohd, Mohamed Shah Noraida, Loo Xin Ling, Hung Stefanie Kar Yan

机构信息

Faculty of Pharmacy, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia.

Pharmacy Department, Hospital Shah Alam, Shah Alam, Selangor, Malaysia.

出版信息

Ther Clin Risk Manag. 2024 Aug 26;20:529-541. doi: 10.2147/TCRM.S467975. eCollection 2024.

Abstract

AIM

Identifying a patient's risk for poor outcomes after starting antiseizure medication (ASM) therapy is crucial in managing epilepsy pharmacologically. To date, there is a lack of designated tools to assess such risks.

PURPOSE

To develop and validate a risk assessment tool for the therapeutic outcomes of ASM therapy.

PATIENTS AND METHODS

A cross-sectional study was carried out in a hospital-based specialist clinic from September 2022 to August 2023. Data was analyzed from patients' medical records and face-to-face assessments. The seizure control domain was determined from the patients' medical records while seizure severity (SS) and adverse effects (AE) of ASM were assessed using the Seizure Severity Questionnaire and the Liverpool Adverse Event Profile respectively. The developed tool was devised from prediction models using logistic and linear regressions. Concurrent validity and interrater reliability methods were employed for validity assessments.

RESULTS

A total of 397 patients were included in the analysis. For seizure control, the identified predictors include ≥10 years' epilepsy duration (OR:1.87,95% CI:1.10-3.17), generalized onset (OR:7.42,95% CI:2.95-18.66), focal onset seizure (OR:8.24,95% CI:2.98-22.77), non-adherence (OR:3.55,95% CI:1.52-8.27) and having ≥3 ASM (OR:3.29,95% CI:1.32-8.24). Younger age at epilepsy onset (≤40) (OR:3.29,95% CI:1.32-8.24) and neurological deficit (OR:3.55,95% CI:1.52-8.27) were significant predictors for SS. For AE, the positive predictors were age >35 (OR:0.12,95% CI:0.03-0.20), <13 years epilepsy duration (OR:2.89,95% CI:0.50-5.29) and changes in ASM regimen (OR:2.93,95% CI: 0.24-5.62). The seizure control domain showed a good discriminatory ability with a of 0.711. From the Bonferroni (ANOVA) analysis, only SS predicted scores generated a linear plot against the mean of the actual scores. The AE domain was omitted from the final tool because it did not meet the requirements for validity assessment.

CONCLUSION

This newly developed tool (RAS-TO) is a promising tool that could help healthcare providers in determining optimal treatment strategies for adults with epilepsy.

摘要

目的

确定患者在开始抗癫痫药物(ASM)治疗后出现不良预后的风险,对于癫痫的药物治疗管理至关重要。迄今为止,缺乏评估此类风险的指定工具。

目的

开发并验证一种用于ASM治疗疗效的风险评估工具。

患者与方法

2022年9月至2023年8月在一家医院的专科门诊进行了一项横断面研究。对患者的病历数据和面对面评估进行了分析。癫痫发作控制情况通过患者病历确定,而ASM的发作严重程度(SS)和不良反应(AE)分别使用癫痫发作严重程度问卷和利物浦不良事件量表进行评估。所开发的工具是根据使用逻辑回归和线性回归的预测模型设计的。采用同时效度和评分者间信度方法进行效度评估。

结果

共有397例患者纳入分析。对于癫痫发作控制,确定的预测因素包括癫痫病程≥10年(比值比:1.87,95%置信区间:1.10 - 3.17)、全身性发作(比值比:7.42,95%置信区间:2.95 - 18.66)、局灶性发作(比值比:8.24,95%置信区间:2.98 - 22.77)、不依从(比值比:3.55,95%置信区间:1.52 - 8.27)以及服用≥3种ASM(比值比:3.29,95%置信区间:1.32 - 8.24)。癫痫发作起始年龄较小(≤40岁)(比值比:3.29,95%置信区间:1.32 - 8.24)和存在神经功能缺损(比值比:3.55,95%置信区间:1.52 - 8.27)是SS的显著预测因素。对于AE,阳性预测因素为年龄>35岁(比值比:0.12,95%置信区间:0.03 - 0.20)、癫痫病程<13年(比值比:2.89,95%置信区间:0.50 - 5.29)以及ASM治疗方案改变(比值比:2.93,95%置信区间:0.24 - 5.62)。癫痫发作控制领域显示出良好的区分能力,曲线下面积为0.711。根据Bonferroni(方差分析)分析,只有SS预测得分与实际得分均值生成线性图。最终工具中省略了AE领域,因为它不符合效度评估要求。

结论

这种新开发的工具(RAS - TO)是一种很有前景的工具,可帮助医疗保健提供者为成年癫痫患者确定最佳治疗策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8a3f/11363947/bbf9635608b3/TCRM-20-529-g0001.jpg

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