Evidence map›Paper›PMID 30236069›Full record

ArticleBMC medical imaging2018

Evaluation of the efficacy of amplitude-integrated electroencephalography in the screening of newborns with metabolic disorder admitted to the NICU.

Maliheh Kadivar, Ziba Mosayebi, Reza Shervin Badoo, Raziyeh Sangesari, Saeed Jedari Attari, Maryam Saeedi, Elahe Movahedi Moghadam

Open access · goldAbstract read
In one paragraph

Article in BMC medical imaging, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.8field-weighted citation impact, top 13% 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

4 citing papers in PubMed, 8 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

7 authors at 1 institution in 1 country.

Maliheh KadivarNeonatal Health Research Center, Research Institute for Children Health, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Ziba MosayebiNeonatal Health Research Center, Research Institute for Children Health, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Reza Shervin BadooNeonatal Health Research Center, Research Institute for Children Health, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Raziyeh SangesariNeonatal Health Research Center, Research Institute for Children Health, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Saeed Jedari AttariNeonatal Health Research Center, Research Institute for Children Health, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Maryam SaeediNeonatal Health Research Center, Research Institute for Children Health, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Elahe Movahedi MoghadamNeonatal Health Research Center, Research Institute for Children Health, Shahid Beheshti University of Medical Sciences, Tehran, Iran. elahehmovahedi@protonmail.com.
Shahid Beheshti University of Medical Sciences · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNeonate patients with metabolic disorder show encephalopathy and seizures that may lead to morbidity and mortality. Thus rapid detection and treatment of these patients is necessary. Although Amplitude-integrated electroencephalography (aEEG) has been used for more than a decade in the evaluation of infants with encephalopathy but has not been used in the assessment of neonates suffering from metabolic disorders. In this study, we tried to determine the efficacy of aEEG as an easily available diagnostic tool in the diagnosis of neonates with metabolic diseases.

methodsAll cases which admitted to the Neonatal Intensive Care Unit (NICU) of the Children's Medical Center during a one-year period were enrolled. aEEG recordings were obtained by installing 4 electrodes on the infant's head by a trained nurse and aEEG was recorded for at least 24 h with a description of the whole tracing. Clinical information, final outcome and questionnaires, including patient information: symptoms of the disease, gender, age, duration of hospitalization and the type of the metabolic disease were recorded in details. The obtained data was analyzed with the Spss24 software.

resultsOnly 3 (two girl and one boy) out of 29 aEEGs recordings were abnormal; other patients showed normal aEEGs. The most common clinical and neurological manifestations were seizure (34.5%), hypotonia (31%), and mortality rate was 10.3%. There was no significant correlation between aEEG findings and gender, age, type of disease, laboratory tests findings and positive family history.

conclusionsAlthough it has been shown that EEG has a diagnostic value in metabolic diseases, there has been no study on the efficacy of aEEG to evaluate neonates with metabolic diseases. But good accessibility and easy of working with aEEG, promote a tendency to use this procedure as screening tool for metabolic diseases. The current study about aEEG monitoring in these patients, while limited, can be used as a pilot study for further research on this topic. Therefore, a correct judgment in this field requires administration of aEEG on a larger population of neonates with metabolic diseases.

Indexed as

Early DiagnosisElectroencephalographyFemaleHumansInfant, NewbornIntensive Care Units, NeonatalMaleMetabolic DiseasesMuscle HypotoniaPilot ProjectsSeizuresSurveys and QuestionnairesaEEGMetabolic diseasesNeonates

Identifiers

PMID30236069
PMCPMC6148992
OpenAlexW2891450565

What OpenQuestion 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 OpenQuestion graph.