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Record W4390910987 · doi:10.3389/fneur.2023.1223960

Serum GFAP, NfL, and tau concentrations are associated with worse neurobehavioral functioning following mild, moderate, and severe TBI: a cross-sectional multiple-cohort study

2024· article· en· W4390910987 on OpenAlexaff
Katie A. Edwards, Rael T. Lange, Sara M. Lippa, Tracey A. Brickell, Jessica Gill, Louis M. French

Bibliographic record

VenueFrontiers in Neurology · 2024
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsUniversity of British Columbia
FundersDefense and Veterans Brain Injury CenterTraumatic Brain Injury Center of Excellence
KeywordsTraumatic brain injuryMedicineAngerCohortNeuropsychologyGlial fibrillary acidic proteinDepression (economics)Internal medicineAnxietyPsychologyPsychiatryPhysical therapyClinical psychologyCognition

Abstract

fetched live from OpenAlex

Introduction The purpose of this study was to examine whether blood-based biomarkers associate with neurobehavioral functioning at three time points following traumatic brain injury (TBI). Materials and methods Participants were 328 United States service members and veterans (SMVs) prospectively enrolled in the Defense and Veterans Brain Injury Center-Traumatic Brain Injury Center of Excellence (DVBIC-TBICoE) 15-Year Longitudinal TBI Study, recruited into three groups: uncomplicated mild TBI (MTBI, n = 155); complicated mild, moderate, severe TBI combined (STBI, n = 97); non-injured controls (NIC, n = 76). Participants were further divided into three cohorts based on time since injury (≤12 months, 3–5 years, and 8–10 years). Participants completed the Minnesota Multiphasic Personality Inventory-2-Restructured Format (MMPI-2-RF) and underwent blood draw to measure serum concentrations of glial fibrillary acidic protein (GFAP), neurofilament light (NfL), and tau. A total of 11 MMPI-2-RF scales were examined (e.g., depression, anxiety, anger, somatic, cognitive symptoms). Stepwise hierarchical regression models were conducted within each group. Results Significant associations were found between biomarkers and MMPI-2-RF scales (all p < 0.05; R2Δ > 0.10). GFAP was inversely related to (a) neurological complaints in the MTBI group at ≤12 months, (b) demoralization, anger proneness in the STBI group at ≤12 months, and (c) head pain complaints in the STBI group at 8–10 years. NfL was (a) related to low positive emotions in the NIC group; and inversely related to (b) demoralization, somatic complaints, neurological complaints, cognitive complaints in the MTBI group at ≤12 months, (c) demoralization in the STBI group at ≤12 months, and (d) demoralization, head pain complaints, stress/worry in the STBI group at 3–5 years. In the STBI group, there were meaningful findings (R2Δ > 0.10) for tau, NFL, and GFAP that did not reach statistical significance. Discussion Results indicate worse scores on some MMPI-2-RF scales (e.g., depression, stress/worry, neurological and head pain complaints) were associated with lower concentrations of serum GFAP, NfL, and tau in the sub-acute and chronic phase of the recovery trajectory up to 5 years post-injury, with a reverse trend observed at 8–10 years. Longitudinal studies are needed to help elucidate any patterns of association between blood-based biomarkers and neurobehavioral outcome over the recovery trajectory following TBI.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.042
GPT teacher head0.317
Teacher spread0.275 · 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

Citations18
Published2024
Admission routes1
Has abstractyes

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