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Record W4234471265 · doi:10.1016/j.jalz.2016.06.2308

P4‐216: Reduction in Hippocampal Volume is Associated With Age and Memory Deficits in Retired Professional Football Players

2016· article· en· W4234471265 on OpenAlexaffabout
Karen Misquitta, Mahsa Dadar, Apameh Tarazi, Ahmed Ebraheem, Namita Multani, Mozhgan Khodadadi, Ruma Goswami, Richard Wennberg, Charles H. Tator, Robin Green, Brenda Colella, Karen D. Davis, David J. Mikulis, D. Louis Collins, Maria Carmela Tartaglia

Bibliographic record

VenueAlzheimer s & Dementia · 2016
Typearticle
Languageen
FieldNeuroscience
TopicFunctional Brain Connectivity Studies
Canadian institutionsUniversity Health NetworkMcGill UniversityMontreal Neurological Institute and HospitalOccupational Cancer Research CentreUniversity of Toronto
Fundersnot available
KeywordsFootballPsychologyFootball playersHippocampal formationCollege footballReduction (mathematics)MedicineGerontologyNeuroscienceHistoryMathematics

Abstract

fetched live from OpenAlex

Repeated concussions are associated with post-concussive symptoms including memory impairment. Professional athletes in contact sports seem to be at greater risk of persistent symptoms due to repeated concussions. We used volumetric analysis to test whether repeated concussions have delayed effects in terms of decreased hippocampal volume and poor memory performance in former professional football players. Participants were 38 retired Canadian Football League (ex-CFL) players (age=56.0+12.9 years) and 21 healthy male controls (age=48.3+10.7 years) without history of concussion. Controls from the Alzheimer’s Disease Neuroimaging Initiative database (ADNI) (N=179) were used for validation because of our small control sample size. The number of self-reported concussions in the ex-CFL group ranged from 0-48. Participants underwent a 3T T1-weighted structural MRI scan and a Rey Auditory Verbal Learning Test (RAVLT) to assess verbal memory. Scans were pre-processed using a standard pipeline: image intensity non-uniformity correction, intensity range normalization (0-100), stereotaxic registration and non-linear warping to an average template brain (Montreal Neurological Institute ICBM-152). Volumetric analysis was performed and hippocampal volumes were correlated with age, adjusting for intracranial volume, and with RAVLT word recall scores, adjusting for age. The ex-CFL players showed a significant association between age and left hippocampal (LH) (r=-.60,p<.001) and right hippocampal (RH) volume (r=-.57,p<.001), whereas in controls this trend was non-significant (LH r=-.32,p=.16; RH r=-.33,p=.14, respectively). A similar but significant association was found between age and both the LH and RH volumes (r=-.40,p<.001; r=-.36,p<.001, respectively) in controls from the ADNI database. In the ex-CFL group, we found a correlation between volume of the LH and RH and word recall performance on the RAVLT short delay (r=.45,p=.01; r=.42,p=.02 respectively) and long delay (r=.41,p=.02; r=.38,p=.04 respectively). No association was observed between LH and RH volumes and RAVLT short or long delay scores in our control group. Our data suggest a stronger effect of age on hippocampal volume in ex-CFL than in individuals without a history of concussion. The hippocampal volumes in the ex-CFL were related to performance on a verbal memory task. Multiple concussions may contribute to accelerated aging of the hippocampus that could explain some of the cognitive complaints reported by athletes.

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)0.001
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 score0.023
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.039
GPT teacher head0.259
Teacher spread0.220 · 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

Citations1
Published2016
Admission routes2
Has abstractyes

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