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Combined prediction of mismatch negativity and P300 for the cognitive function in traumatic brain injury patients

2025· article· zh· W7105598148 on OpenAlexaboutno aff

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2025
Typearticle
Languagezh
FieldMedicine
TopicIntensive Care Unit Cognitive Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsMismatch negativityReceiver operating characteristicCutoffArea under the curveCognitionTraumatic brain injuryLogistic regressionMontreal Cognitive Assessment

Abstract

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Objective To investigate the predictive value of mismatch negativity (MMN) combined with P300 for cognitive dysfunction at 6 months after traumatic brain injury (TBI) in adult patients. Methods A total of 75 adult TBI patients admitted to Xiangya Hospital, Central South University from January 2021 to January 2024 were enrolled. MMN and P300 were monitored within 7d after TBI. Cognitive function was assessed at 6 months after TBI using the Telephone Interview for Cognitive Status (TICS), with a score of<27 indicating cognitive dysfunction. Univariate and multivariate Logistic regression analyses were used to identify influencing factors for cognitive dysfunction at 6 months after TBI. Receiver operating characteristic (ROC) curve was plotted, and the area under the curve (AUC) was calculated to evaluate the predictive performance of the identified factors. Results Lower absolute value of Fz MMN amplitude (OR=0.426, 95%CI: 0.188-0.968; P=0.041) and Cz P300 amplitude (OR=0.399, 95%CI: 0.188-0.847; P=0.017) were identified as risk factors for cognitive dysfunction at 6 months after TBI. ROC curve showed that the AUC for the absolute value of Fz MMN amplitude was 0.713 (95%CI: 0.595-0.830, P=0.002), with an optimal cutoff value of 2.37 μV. The AUC for the absolute value of Cz P300 amplitude was 0.752 (95%CI: 0.641-0.863, P=0.000), with an optimal cutoff value of 3.28μV. When these 2 indicators were combined for ROC curve, the combined indicator yielded an AUC of 0.781 (95%CI: 0.676-0.886, P=0.000). Delong test revealed no statistically significant differences in AUC between the combined indicator and the absolute value of Fz MMN amplitude (Z=1.574, P=0.115) or the absolute value of Cz P300 amplitude (Z=0.939, P=0.348), suggesting comparable predictive performance among the 3 indicators. Conclusions MMN combined with P300 may serve as a favorable indicator for predicting cognitive dysfunction at 6 months after 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)0.003
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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
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 head0.142
GPT teacher head0.497
Teacher spread0.355 · 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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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