Progression to refractory status epilepticus: A machine learning analysis by means of classification and regression tree analysis
Decision-tree analysis provided a meaningful risk stratification based on few variables that are easily obtained at SE first evaluation: consciousness before treatment, etiology, and severe EEG patterns. CART models must be viewed as potential new method for the stratification RSE at single subject level deserving further exploration and validation.
Authors
- Gianni Turcato (ORCID: https://orcid.org/0000-0002-8890-4113)
- Stefano Meletti (ORCID: https://orcid.org/0000-0003-0334-539X)
- Simona Lattanzi (ORCID: https://orcid.org/0000-0001-8748-0083)
- Francesco Brigo (ORCID: https://orcid.org/0000-0003-0928-1577)
- Giada Giovannini (ORCID: https://orcid.org/0000-0002-3585-5872)
- Niccolò Orlandi (ORCID: https://orcid.org/0000-0002-5717-7363)
- Arian Zaboli (ORCID: https://orcid.org/0000-0002-4204-8884)
Institutions
- Marche Polytechnic University (IT)
- Ospedale Sant Antonio (IT)
- Krankenhaus Meran (IT)
Publication Details
- Journal
- Epilepsy & Behavior
- Published
- 2024-09-21
- DOI
- https://doi.org/10.1016/j.yebeh.2024.110005
- Citations
- 4
- Primary Topic
- Epilepsy research and treatment
- Type
- article
- Field-Weighted Citation Impact
- 1.54
Funders
- Ministry of Health
- Ministero della Salute
- Eisai
- Kementerian Kesihatan Malaysia