Evidence map›Paper›PMID 37373723›Full record

ArticleJournal of clinical medicine2023

Classification Model for Epileptic Seizure Using Simple Postictal Laboratory Indices.

Sun Jin Jin, Taesic Lee, Hyun Eui Moon, Eun Seok Park, Sue Hyun Lee, Young Il Roh, Dong Min Seo, Won-Joo Kim, Heewon Hwang

Open access · goldAbstract read
In one paragraph

Article in Journal of clinical medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.9field-weighted citation impact, top 27% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 4 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 1 institution in 1 country.

Sun Jin JinDepartment of Neurology, Wonju Severance Christian Hospital, Yonsei University Wonju College of Medicine, Wonju 26426, Republic of Korea.
Taesic LeeDivision of Data Mining and Computational Biology, Institute of Global Health Care and Development, Wonju 26426, Republic of Korea.ORCID 0000-0002-0706-167X
Hyun Eui MoonDepartment of Family Medicine, Yonsei University Wonju College of Medicine, Wonju 26426, Republic of Korea.
Eun Seok ParkDepartment of Neurology, Wonju Severance Christian Hospital, Yonsei University Wonju College of Medicine, Wonju 26426, Republic of Korea.
Sue Hyun LeeDepartment of Neurology, Wonju Severance Christian Hospital, Yonsei University Wonju College of Medicine, Wonju 26426, Republic of Korea.ORCID 0000-0002-0279-9616
Young Il RohDepartment of Emergency Medicine, Yonsei University Wonju College of Medicine, Wonju 26426, Republic of Korea.ORCID 0000-0001-8317-4943
Dong Min SeoDepartment of Medical Information, Yonsei University Wonju College of Medicine, Wonju 26426, Republic of Korea.
Won-Joo KimDepartment of Neurology, Gangnam Severance Christian Hospital, Yonsei University College of Medicine, Seoul 06273, Republic of Korea.
Heewon HwangDepartment of Neurology, Wonju Severance Christian Hospital, Yonsei University Wonju College of Medicine, Wonju 26426, Republic of Korea.ORCID 0000-0002-0782-6724
Yonsei University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Distinguishing syncope from epileptic seizures in patients with sudden loss of consciousness is important. Various blood tests have been used to indicate epileptic seizures in patients with impaired consciousness. This retrospective study aimed to predict the diagnosis of epilepsy in patients with transient loss of consciousness using the initial blood test results. A seizure classification model was constructed using logistic regression, and predictors were selected from a cohort of 260 patients using domain knowledge and statistical methods. The study defined the diagnosis of seizures and syncope based on the consistency of the diagnosis made by an emergency medicine specialist at the first visit to the emergency room and the diagnosis made by an epileptologist or cardiologist at the first outpatient visit using the International Classification of Diseases 10th revision (ICD-10) code. Univariate analysis showed higher levels of white blood cells, red blood cells, hemoglobin, hematocrit, delta neutrophil index, creatinine kinase, and ammonia levels in the seizure group. The ammonia level had the highest correlation with the diagnosis of epileptic seizures in the prediction model. Therefore, it is recommended to be included in the first examination at the emergency room.

Indexed as

ammoniabayes approachseizureserumsyncope

Identifiers

PMID37373723
PMCPMC10298879
OpenAlexW4380682540

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.