Evidence map›Paper›PMID 34741222›Full record

ArticleNeurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology2022

Perioperative routine EEG can reliably predict de novo seizures after supratentorial craniotomy.

Mousareza Anbarlouei, Maziar Emamikhah, Kamal Basiri, Gholamreza Farzanegan

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Article in Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact, top 82% 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

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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

1 citing paper in PubMed, 2 citations in OpenAlex.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors at 2 institutions in 1 country.

Mousareza AnbarloueiTrauma Research Center, Baqiyatallah University of Medical Sciences, Tehran, Iran.
Maziar EmamikhahTrauma Research Center, Baqiyatallah University of Medical Sciences, Tehran, Iran.
Kamal BasiriDepartment of Emergency Medicine, Prehospital and Hospital Emergency Research Center, Tehran University of Medical Sciences, Tehran, Iran.
Gholamreza FarzaneganTrauma Research Center, Baqiyatallah University of Medical Sciences, Tehran, Iran. drrezafarzanegan44@gmail.com.ORCID http://orcid.org/0000-0002-9346-7747
Baqiyatallah University of Medical Sciences · IRTehran University of Medical Sciences · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe contributing risk factors in development of seizure after supratentorial craniotomy, the optimal duration of prophylactic antiepileptic therapy, the high-risk patient to treat, and the drug of choice are subjects of debate as is the gold standard diagnostic tool for patient screening. Combining routine electroencephalography (EEG) with clinical data to identify high-risk patients and determine the ideal time of recording after surgery was the goal of this study.

methodsIn this prospective cohort, 59 patients were evaluated with three EEG recordings after different intervals of supratentorial craniotomy due to different etiologies and were followed for 9 months for development of seizures. Demographic and disease-related variables as well as EEG results were analyzed to determine the contributing risk factors for development of seizures.

resultsNeoplastic etiology and abnormal perioperative EEG (performed before surgery or in the first postoperative week) were the only independent variables associated with development of de novo seizure.

conclusionRoutine EEG in the perioperative period and neoplastic etiology are two independent powerful predictors of developing seizure after supratentorial craniotomy and may help deciding whether to continue prophylactic antiepileptic medications for an extended period or not.

Indexed as

CraniotomySeizuresAnticonvulsantsElectroencephalographyHumansProspective StudiesAnticonvulsantsAntiepilepticsCraniotomyEEGSeizure

Identifiers

PMID34741222
OpenAlexW3210691253

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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.