A Nomogram to Predict Seizure Outcomes after Resective Epilepsy Surgery

预测癫痫切除手术后癫痫发作结果的列线图

• 批准号: 10181321
• 负责人: Lara Jehi
• 金额: $ 30.82万
• 依托单位: CLEVELAND CLINIC LERNER COM-CWRU
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-01 至 2023-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10181321
• 关键词: 2019-nCoV; Acute; Age; Area; Autopsy; Blood; Brain; COVID-19; Cardiovascular Diseases; Case Series; Chronic lung disease; Clinic; Clinical; Clinical Research; Code; Cognitive; Coin; Collection; Critical Care; Data; Delirium; Diabetes Mellitus; Diagnosis; Discipline; Disease; Disease Progression; Drug resistance; Electronic Health Record; Electronic Mail; Epidemiology; Epilepsy; Excision; Feces; Freedom; Functional disorder; Funding; Gene Proteins; Genes; Genetic; Genomics; Health system; Healthcare Systems; Heart; Hospitalization; Human; Human Cell Line; Hypertension; Image; Impaired cognition; Incidence; Individual; Infection; Infrastructure; Institutional Review Boards; Intensive Care Units; Interdisciplinary Study; Kidney; Kidney Diseases; Knowledge; Lesion; Liver; Malignant Neoplasms; Manuals; Medicine; Methodology; Modeling; Molecular; Network-based; Neurologic; Neurologic Effect; Neurologic Symptoms; Nomograms; Operative Surgical Procedures; Outcome; Parents; Patient Care; Patients; Performance; Phenotype; Physiology; Population; Protein Analysis; Proteins; Proteomics; Pulmonology; Registries; Research; Research Project Grants; Residual state; Resources; Respiratory System; Rest; Risk; Risk Factors; Sampling; Seeds; Seizures; Series; Severities; Severity of illness; Smoking; Statistical Models; Stream; Stroke; Surveys; Symptoms; System; Testing; Tissue Sample; Tissues; Urine; Validation; Viral Load result; Work; arm; base; biobank; brain surgery; clinical care; cohort; coronavirus disease; differential expression; experimental study; follow-up; high risk; human interactome; innovation; interest; neurological pathology; novel; novel diagnostics; pandemic disease; personalized predictions; personalized risk prediction; predictive modeling; prospective; protein protein interaction; screening; statistics; stroke patient; tool; transcriptome sequencing; transcriptomics; virus host interaction

Project Summary The full spectrum of neurological manifestations of severe acute respiratory syndrome coronavirus 2 (SARS- CoV-2) infection has not been clarified. Previous studies have been limited to case series and have described only neurological complications observed in patients hospitalized with COVID-19 or admitted to intensive care units. While these studies provide important information, they do not clarify the range of neurological manifestations in individuals showing different severities of symptoms during infection, the long-term neurological effects of the disease, and they do not provide any understanding of the pathophysiology of the disease. In our current project (1R01NS097719-04-A1), we have constructed a large data and biospecimen infrastructure to develop statistical models for individualized prediction of epileptic seizure-freedom and cognitive outcomes after resective brain surgery for drug resistant seizures. In this competitive revision application, we propose to pair our infrastructure (predictive modeling and genomic expertise) with institutional resources (Cleveland Clinic COVID-19 Registry and Biobank) to advance the epidemiological and mechanistic understanding of neurological complications of COVID-19, particularly epilepsy, stroke, and delirium, and to generate nomograms and online risk calculators for the relevant neurological COVID-19 complications. The objectives of this revised proposal are to characterize the incidence and manifestation phenotype of new onset seizures, stroke, and delirium in all patients diagnosed as COVID+ (3,177 as of May 7) in our healthcare system, to build and validate prediction models to identify individuals at risk of neurological complications, and to identify systematically disease modules (molecular determinants of disease pathobiology/physiology) for COVID-19 that can reveal novel underlying mechanisms for SARS-CoV-2 associated neurological manifestations. Older age, smoking, diabetes, hypertension, cardiovascular disease, kidney disease, chronic lung disease, and cancer correlate with progression to severe disease in patients hospitalized with COVID-19. We hypothesize that these factors are similarly associated with a higher risk of neurological complications. However, these “risk factors” are not specific, occur in various combinations, and have limited value as isolated indicators of specific neurological complications. Our team's expertise will be used to generate nomograms and online risk calculators for the relevant neurological complications observed in the CCHS COVID-19 registry cohort, to explore underlying mechanisms of these neurological complications using innovative human protein-protein analyses, and to generate tools that can guide decisions in clinical care.

项目摘要 严重急性呼吸系统综合征冠状病毒2（SARS- CoV-2感染尚未得到澄清。以前的研究仅限于病例系列， 仅在因COVID-19住院或接受重症监护的患者中观察到神经系统并发症 单位虽然这些研究提供了重要的信息，但它们并没有阐明神经系统疾病的范围。 在感染过程中表现出不同严重程度症状的个体表现，长期神经系统 他们没有提供对疾病的病理生理学的任何理解。 在我们目前的项目（1 R 01 NS 097719 -04-A1）中，我们构建了一个大型数据和生物标本基础设施 开发统计模型，用于个性化预测癫痫无症状和认知结果 因为抗药性癫痫而接受了脑部切除手术在此竞争性修订申请中，我们建议 将我们的基础设施（预测建模和基因组专业知识）与机构资源（克利夫兰诊所 COVID-19登记处和生物库），以促进对神经系统疾病的流行病学和机制的了解。 COVID-19的并发症，特别是癫痫，中风和谵妄，并生成列线图和在线 相关神经系统COVID-19并发症的风险计算器。 本修订提案的目的是描述新的乳腺癌的发病率和表现表型， 在我们的医疗保健中，所有被诊断为COVID+的患者（截至5月7日为3，177人）都出现癫痫发作，中风和谵妄 系统，以建立和验证预测模型，以识别有神经系统并发症风险的个体，以及 系统地确定疾病模块（疾病病理生物学/生理学的分子决定因素）， COVID-19可以揭示SARS-CoV-2相关神经系统的新潜在机制 表现。 老年、吸烟、糖尿病、高血压、心血管疾病、肾脏疾病、慢性肺病，以及 癌症与因COVID-19住院的患者进展为严重疾病相关。我们假设 这些因素同样与神经系统并发症的高风险相关。然而，这些“风险 这些因素不是特定的，以各种组合出现，作为特定的孤立指标价值有限。 神经系统并发症我们团队的专业知识将用于生成列线图和在线风险计算器 对于在CCHS COVID-19登记队列中观察到的相关神经系统并发症， 这些神经系统并发症的潜在机制使用创新的人类蛋白质-蛋白质分析， 并生成可以指导临床护理决策的工具。

项目成果

Longitudinal trajectory of quality of life and psychological outcomes following epilepsy surgery.

• DOI: 10.1016/j.yebeh.2020.107283
• 发表时间: 2020-10
• 期刊: Epilepsy & behavior : E&B
• 作者: Winslow J;Hu B;Tesar G;Jehi L
• 通讯作者: Jehi L

Molecular subtypes of epilepsy associated with post-surgical seizure recurrence.

• DOI: 10.1093/braincomms/fcad251
• 发表时间: 2023
• 期刊: Brain communications
• 影响因子: 4.8

Automated analysis of cortical volume loss predicts seizure outcomes after frontal lobectomy.

• DOI: 10.1111/epi.16877
• 发表时间: 2021-05
• 期刊: Epilepsia
• 影响因子: 5.6
• 作者: Whiting AC;Morita-Sherman M;Li M;Vegh D;Machado de Campos B;Cendes F;Wang X;Bingaman W;Jehi LE
• 通讯作者: Jehi LE

Beyond seizure freedom: Dissecting long-term seizure control after surgical resection for drug-resistant epilepsy.

• DOI: 10.1111/epi.17445
• 发表时间: 2023-01
• 期刊: EPILEPSIA
• 影响因子: 5.6
• 作者: Hsieh, Jason K.;Pucci, Francesco G.;Sundar, Swetha J.;Kondylis, Efstathios;Sharma, Akshay;Sheikh, Shehryar R.;Vegh, Deborah;Moosa, Ahsan N.;Gupta, Ajay;Najm, Imad;Rammo, Richard;Bingaman, William;Jehi, Lara
• 通讯作者: Jehi, Lara

Does etiology really matter for epilepsy surgery outcome?

• DOI: 10.1111/bpa.12965
• 发表时间: 2021-07
• 期刊: Brain pathology (Zurich, Switzerland)
• 作者: Jehi L;Braun K
• 通讯作者: Braun K