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Record W2101509605 · doi:10.1542/peds.109.2.e31

Neuron-Specific Enolase and S100B in Cerebrospinal Fluid After Severe Traumatic Brain Injury in Infants and Children

2002· article· en· W2101509605 on OpenAlexaboutno aff
Rachel P. Berger, Mary Clyde Pierce, Stephen R. Wisniewski, P. David Adelson, Robert S. B. Clark, Randy A. Ruppel, Patrick M. Kochanek

Bibliographic record

VenuePEDIATRICS · 2002
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicS100 Proteins and Annexins
Canadian institutionsnot available
FundersNational Center for Research ResourcesKorea Electrotechnology Research Institute
KeywordsEnolaseMedicineTraumatic brain injuryCerebrospinal fluidLumbar punctureBrain damageInternal medicineProcalcitoninAnesthesiaPediatricsGastroenterologyPathologyImmunohistochemistrySepsis

Abstract

fetched live from OpenAlex

BACKGROUND: Traumatic brain injury (TBI) is a leading cause of death and disability in children. Considerable insight into the mechanisms involved in secondary injury after TBI has resulted from analysis of ventricular cerebrospinal fluid (CSF) obtained in children with severe noninflicted and inflicted TBI (nTBI and iTBI, respectively). Neuron-specific enolase (NSE) is a glycolytic enzyme that is localized primarily to the neuronal cytoplasm. S100B is a calcium-binding protein localized to astroglial cells. In adults, CSF and serum concentrations of NSE and S100B have served as markers of neuronal damage after TBI. Neither NSE nor S100B has previously been studied in CSF after TBI in infants or children. OBJECTIVE: To compare the time course and magnitude of neuronal and astroglial death after nTBI and iTBI by measuring CSF concentrations of NSE and S100B using a rapid enzyme-linked immunosorbent assay. METHODS: Severe nTBI and iTBI were defined by strict clinical criteria. Serial ventricular CSF samples (n = 35) were obtained from children 1.5 to 9 years with severe nTBI (n = 5) and children 0.2 to 1.5 years (n = 5) with severe iTBI. Lumbar CSF samples from 5 children 0.1 to 2.3 years evaluated for meningitis were used as a comparison group. CSF NSE and S100B concentrations were quantified by an enzyme-linked immunosorbent assay (SynX Pharma Inc, Ontario, Canada). RESULTS: There was no difference in age between patients with iTBI (median [range]: 0.2 years [0.2-1.8]), nTBI (2.0 years [1.5-9]), and the comparison group (0.2 years [0.2-1.8]). The initial Glasgow Coma Scale score was higher in the iTBI group (9 [4-14]) versus the nTBI group (3 [3-7]). NSE was increased in TBI versus the comparison group in 34 of 35 samples. Mean NSE was markedly increased (mean +/- SEM, 117.1 +/- 12.0 ng/mL vs 3.5 +/- 1.4 ng/mL). After nTBI, a transient peak in NSE was seen at a median of 11 hours after injury (range: 5-20 hours). After iTBI, an increase in admission NSE was followed by a sustained and delayed peak at a median of 63 hours after injury (range: 7-94). The magnitude of peak NSE was similar in nTBI and iTBI. S100B was increased versus the comparison group in 35 of 35 samples. Mean S100B was markedly increased in TBI versus the comparison group (1.67 +/- 0.2 ng/mL vs 0.02 +/- 0.0 ng/mL). S100B showed a single peak at 27 hours (range: 5-63 hours) after both nTBI and iTBI. The mean S100B concentration, peak S100B concentration, and the time to peak were not associated with mechanism of injury. CONCLUSIONS: Markers of neuronal and astroglial death are markedly increased in CSF after severe nTBI and iTBI. ITBI produces a unique time course of NSE, characterized by both an early and late peak, presumably representing 2 waves of neuronal death, the second of which may represent apoptosis. Delayed neuronal death may represent an important therapeutic target in iTBI. NSE and S100B may also be useful as markers to identify occult iTBI, help differentiate nTBI and iTBI, and assist in determining the time of injury in cases of iTBI.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.216
Teacher spread0.208 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations219
Published2002
Admission routes1
Has abstractyes

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Same venuePEDIATRICSSame topicS100 Proteins and AnnexinsFrench-language works237,207