Evidence map›Paper›PMID 40597577›Full record

ReviewInternational journal of emergency medicine2025

Neuron-specific enolase: a potential biomarker in the prediction of pediatric head trauma outcomes: a systematic review and meta-analysis.

Amir Behforouz, Masoud Arabfard, Mohammad Javad Behzadnia

Abstract readReview
In one paragraph

Review in International journal of emergency medicine, 2025. 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
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

1 citing paper in PubMed.

  1. Article
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

3 authors.

Amir BehforouzTrauma Research Center, Baqiyatallah University of Medical Sciences, Tehran, Iran.
Masoud ArabfardChemical Injuries Research Center, Systems Biology and Poisonings Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran.
Mohammad Javad BehzadniaTrauma Research Center, Baqiyatallah University of Medical Sciences, Tehran, Iran. mjbehzad1359@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTraumatic brain injury (TBI) is the most common type of brain injury and significantly contributes to morbidity and mortality in both adults and children. Diagnosing pediatric head trauma with precision is difficult, particularly for youngsters displaying mild symptoms. Contemporary research has investigated the capacity of biomarkers, including neuron-specific enolase (NSE), to enhance the precision of diagnosis.

objectiveThe objective of this systematic review and meta-analysis was to assess the levels of NSE in pediatrics with head trauma.

methodsA comprehensive literature search was performed among PubMed, Scopus, and Embase databases, from the inception to August 17

resultsFollowing the screening and eligibility validation process, 12 studies were selected, which evaluated 806 participants. Meta-analyses revealed markedly elevated NSE levels in patients as compared to controls (p-value < 0.001), indicating its potential as a biomarker for head injury. Further subgroup analyses demonstrated more pronounced correlations between increased NSE levels and severe trauma (p-value < 0.001). In addition, cerebrospinal fluid samples had significantly higher NSE levels than other sample origins (p-value < 0.001). Elevated levels of NSE were also associated with unfavorable results, as assessed by the Glasgow Outcome Scale (p-value < 0.001).

conclusionThe findings emphasize the capacity of NSE as a diagnostic and predictive instrument for pediatric head injury, justifying additional research into its clinical uses.

Indexed as

Head injuriesNeuron-specific enolasePediatrics

Identifiers

PMID40597577
PMCPMC12211948

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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.