Department of Neurology, Massachusetts General Hospital/Harvard Medical School, Boston, MA, United States; Center for Value-based Health Care and Sciences, Massachusetts General Hospital, Boston, MA, United States.
Epilepsy Center, Cleveland Clinic Foundation, Cleveland, OH, United States.
Clin Neurol Neurosurg. 2024 Jun;241:108275. doi: 10.1016/j.clineuro.2024.108275. Epub 2024 Apr 6.
Post-hospitalization follow-up visits are crucial for preventing long-term complications. Patients with electrographic epileptiform abnormalities (EA) including seizures and periodic and rhythmic patterns are especially in need of follow-up for long-term seizure risk stratification and medication management. We sought to identify predictors of follow-up.
This is a retrospective cohort study of all patients (age ≥ 18 years) admitted to intensive care units that underwent continuous EEG (cEEG) monitoring at a single center between 01/2016-12/2019. Patients with EAs were included. Clinical and demographic variables were recorded. Follow-up status was determined using visit records 6-month post discharge, and visits were stratified as outpatient follow-up, neurology follow-up, and inpatient readmission. Lasso feature selection analysis was performed.
723 patients (53 % female, mean (std) age of 62.3 (16.4) years) were identified from cEEG records with 575 (79 %) surviving to discharge. Of those discharged, 450 (78 %) had outpatient follow-up, 316 (55 %) had a neurology follow-up, and 288 (50 %) were readmitted during the 6-month period. Discharge on antiseizure medications (ASM), younger age, admission to neurosurgery, and proximity to the hospital were predictors of neurology follow-up visits. Discharge on ASMs, along with longer length of stay, younger age, emergency admissions, and higher illness severity were predictors of readmission.
ASMs at discharge, demographics (age, address), hospital care teams, and illness severity determine probability of follow-up. Parameters identified in this study may help healthcare systems develop interventions to improve care transitions for critically-ill patients with seizures and other EA.
住院后的随访对于预防长期并发症至关重要。存在电描记癫痫样异常（EA）包括发作以及周期性和节律性模式的患者尤其需要进行长期癫痫风险分层和药物管理的随访。我们旨在确定随访的预测因素。
这是一项对在单个中心接受连续脑电图（cEEG）监测的所有患者（年龄≥18 岁）进行的回顾性队列研究，研究时间为 2016 年 1 月至 2019 年 12 月。纳入存在 EA 的患者。记录临床和人口统计学变量。使用出院后 6 个月的就诊记录确定随访情况，并将就诊分为门诊随访、神经科随访和住院再入院。进行了套索特征选择分析。
从 cEEG 记录中确定了 723 名患者（53%为女性，平均（标准差）年龄为 62.3（16.4）岁），其中 575 名（79%）存活至出院。出院患者中，450 名（78%）进行了门诊随访，316 名（55%）进行了神经科随访，288 名（50%）在 6 个月内再次入院。出院时使用抗癫痫药物（ASM）、年龄较小、收入神经外科以及靠近医院是神经科随访的预测因素。出院时使用 ASM，以及住院时间延长、年龄较小、急诊入院和疾病严重程度较高是再次入院的预测因素。
出院时使用 ASM、人口统计学因素（年龄、住址）、医院护理团队和疾病严重程度决定了随访的可能性。本研究确定的参数可能有助于医疗保健系统制定干预措施，以改善患有癫痫和其他 EA 的危重病患者的护理过渡。
