Evidence map›Paper›PMID 36385248›Full record

ArticleActa neurologica Belgica2023

Clinical characteristics of MRI-negative temporal lobe epilepsy.

Ali A Asadi-Pooya, Mohsen Farazdaghi

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Article in Acta neurologica Belgica, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.7field-weighted citation impact, top 30% 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

3 citing papers in PubMed, 5 citations in OpenAlex.

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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

2 authors at 2 institutions in 2 countries.

Ali A Asadi-PooyaEpilepsy Research Center, Shiraz University of Medical Sciences, Shiraz, Iran. aliasadipooya@yahoo.com.ORCID http://orcid.org/0000-0002-2598-7601
Mohsen FarazdaghiEpilepsy Research Center, Shiraz University of Medical Sciences, Shiraz, Iran.
Shiraz University of Medical Sciences · IRThomas Jefferson University · US

Funding

Shiraz University of Medical Sciences 12345
6 · The paper itself

Abstract

purposeTo investigate the characteristics of patients with MRI-negative temporal lobe epilepsy (TLE) (1.5 T brain MRI) in comparison with: (i) patients with hippocampal sclerosis (HS)-TLE; (ii) persons with non-HS structural TLE; and (iii) patients with dual pathology.

methodsThis was a retrospective study. All patients with an electro-clinical diagnosis of TLE were studied at the outpatient epilepsy clinic at Shiraz University of Medical Sciences, Shiraz, Iran, from 2008 until 2020.

resultsSix hundred and forty-one patients were studied [273 (42.6%) HS, 154 (24.0%) non-HS structural TLE, 174 (27.1%) MRI-negative TLE, and 40 (6.2%) dual pathology]. The groups differed significantly. Important dissimilarities included: (i) compared with HS-TLE group, patients with MRI-negative TLE more often had a family history of epilepsy and less often had a history of febrile convulsion; (ii) compared with non-HS structural TLE group, patients with MRI-negative TLE more often had focal to bilateral tonic-clonic seizures, less often had focal seizures with impaired awareness, and more often had a family history of epilepsy; (iii) compared with the dual pathology group, patients with MRI-negative TLE less often were male and less often had a history of febrile convulsion.

conclusionPatients with MRI-negative TLE are not a homogenous group of people and it is not necessarily a distinct entity from other forms of TLE either. With the emergence of advanced imaging technologies, the underlying pathologies of MRI-negative TLE may be revealed.

Indexed as

Epilepsy, Temporal LobeSeizures, FebrileFemaleHippocampusHumansMagnetic Resonance ImagingMaleRetrospective StudiesSclerosisSeizuresElectroencephalographyEpilepsySeizuresTemporal lobe

Identifiers

PMID36385248
OpenAlexW4309245659

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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 OpenQuestion graph.