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Chronic traumatic encephalopathy: predictors of the development of cognitive disorders and functional disability

2024· article· en· W4390637281 on OpenAlexaboutno aff
Khrystyna Duve, Svitlana Shkrobot, Z.V. Salii

Bibliographic record

VenueINTERNATIONAL NEUROLOGICAL JOURNAL · 2024
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsnot available
Fundersnot available
KeywordsMontreal Cognitive AssessmentMedicineChronic traumatic encephalopathyComorbidityCognitionDementiaPsychiatryLogistic regressionClinical psychologyCognitive impairmentInternal medicineDiseasePoison controlInjury preventionMedical emergency

Abstract

fetched live from OpenAlex

Background. Predicting the individual risk of developing cognitive impairment and functional disability in everyday life among patients with chronic traumatic encephalopathy (CTE) will allow timely and adequate treatment to prevent dementia. Therefore, the study aimed to develop a mathematical model for predicting the risk of cognitive disorders and functional disability in patients with CTE based on the analysis of polymorphic variants of the ACE, AT2R1, eNOS, ePON1, IL-1β, IL-10, TNF-α genes, as well as cofactors (gender, age group, follow-up, presence/absence of somatic comorbidity). Materials and methods. We examined 145 individuals with CTE who were undergoing inpatient treatment in the Communal Non-Profit Enterprise “Ternopil Regional Clinical Psychoneurological Hospital” in 2021–2022 and were included in the retrospective analysis. The molecular and genetic testing was performed for 26 patients. The molecular and genetic differentiation of the studied polymorphic variants of genes was carried out in the molecular and genetic laboratory of the State Institution “Reference Centre for Molecular Diagnostics of the Ministry of Health of Ukraine” in Kyiv. Cognitive functions were studied using the Montreal Cognitive Assessment (MoCA), activities of daily living — with the Barthel index. Statistical analysis was done using Microsoft Excel and Statistica 13.0 computer software. A logistic regression analysis was performed to determine the likelihood of cognitive impairment and functional disability in patients with CTE. Results. When analyzing polymorphic variants of the ACE, AT2R1, eNOS, ePON1, IL-1β, IL-10, TNF-α genes, as well as such cofactors as gender, age group, follow-up, presence/absence of somatic comorbidity in the context of the development of cognitive disorders in patients with CTE, it has been found that the I/D polymorphism of the ACE gene has the most significant prognostic value (in the presence of the D/D genotype, the probability of cognitive impairment is 83.33 %). At the same time, patients with CTE who were carriers of the D allele of the ACE gene had a significant decrease in the MoCA score compared to the group of those who didn’t carry this allele. Regarding the development of functional disability in patients with CTE, the C108T polymorphism of the PON1 gene has the most significant prognostic value (in the presence of the T/T genotype, the risk of functional disability is 41.49 %, with significantly lower Barthel index compared to the C/C homozygotes). Conclusions. It was found that the I/D polymorphism of the ACE gene and the C108T polymorphism of the PON1 gene are likely associated with the development of cognitive impairment and functional disability in patients with CTE that indicates the feasibility of further studies involving a larger sample of patients.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.174
Threshold uncertainty score0.649

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
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 head0.053
GPT teacher head0.330
Teacher spread0.277 · 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 teacher head, 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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Citations1
Published2024
Admission routes1
Has abstractyes

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