PDF(Pubmed)
Abstract：
OBJECTIVE: We aimed to develop a new data-driven method to predict the therapeutic indication of redeemed prescriptions in secondary data sources using antiepileptic drugs among individuals aged ≥65 identified in Danish registries.
METHODS: This was an incident new-user register-based cohort study using Danish registers.
METHODS: The study setting was Denmark and the study period was 2005-2017.
METHODS: Participants included antiepileptic drug users in Denmark aged ≥65 with a confirmed diagnosis of epilepsy.
METHODS: Sensitivity served as the performance measure of the algorithm.
RESULTS: The study population comprised 8609 incident new users of antiepileptic drugs. The sensitivity of the algorithm in correctly predicting the therapeutic indication of antiepileptic drugs in the study population was 65.3% (95% CI 64.4 to 66.2).
CONCLUSIONS: The algorithm demonstrated promising properties in terms of overall sensitivity for predicting the therapeutic indication of redeemed antiepileptic drugs by older individuals with epilepsy, correctly identifying the therapeutic indication for 6 out of 10 individuals using antiepileptic drugs for epilepsy.
METHODS: This was an incident new-user register-based cohort study using Danish registers.
METHODS: The study setting was Denmark and the study period was 2005-2017.
METHODS: Participants included antiepileptic drug users in Denmark aged ≥65 with a confirmed diagnosis of epilepsy.
METHODS: Sensitivity served as the performance measure of the algorithm.
RESULTS: The study population comprised 8609 incident new users of antiepileptic drugs. The sensitivity of the algorithm in correctly predicting the therapeutic indication of antiepileptic drugs in the study population was 65.3% (95% CI 64.4 to 66.2).
CONCLUSIONS: The algorithm demonstrated promising properties in terms of overall sensitivity for predicting the therapeutic indication of redeemed antiepileptic drugs by older individuals with epilepsy, correctly identifying the therapeutic indication for 6 out of 10 individuals using antiepileptic drugs for epilepsy.
摘要：
目的：我们旨在开发一种新的数据驱动方法，在丹麦登记处确定的年龄≥65岁的个体中，利用抗癫痫药，在二级数据源中预测兑换处方的治疗指征。
方法：这是一项基于新用户注册的队列研究，使用丹麦注册。
方法：研究设置为丹麦，研究期为2005-2017年。
方法：参与者包括丹麦65岁以上确诊为癫痫的抗癫痫药物使用者。
方法：灵敏度是算法的性能度量。
结果：研究人群包括8609名抗癫痫药物新用户。该算法在正确预测研究人群中抗癫痫药物治疗适应症的敏感性为65.3％（95％CI64.4至66.2）。
结论：该算法在预测老年癫痫患者使用赎回抗癫痫药物的治疗适应症的总体敏感性方面表现出了有希望的特性，正确确定10名患者中有6名使用抗癫痫药物治疗癫痫的治疗适应症。
方法：这是一项基于新用户注册的队列研究，使用丹麦注册。
方法：研究设置为丹麦，研究期为2005-2017年。
方法：参与者包括丹麦65岁以上确诊为癫痫的抗癫痫药物使用者。
方法：灵敏度是算法的性能度量。
结果：研究人群包括8609名抗癫痫药物新用户。该算法在正确预测研究人群中抗癫痫药物治疗适应症的敏感性为65.3％（95％CI64.4至66.2）。
结论：该算法在预测老年癫痫患者使用赎回抗癫痫药物的治疗适应症的总体敏感性方面表现出了有希望的特性，正确确定10名患者中有6名使用抗癫痫药物治疗癫痫的治疗适应症。
