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Record W7116966608 · doi:10.1002/alz70861_108461

Association of Centrally Acting Medications, Chronic Pain, and Orthopedic Surgical History with Cognitive Impairment and Neurobehavioral Dysregulation in Former American Football Players

2025· article· en· W7116966608 on OpenAlexaboutno aff
Alexa Puleio, Ina Hoti, William Barr, Sarah J Banks, Jennifer V. Wethe, Yorghos Tripodis, Charles Adler, Laura J. Balcer, Charles Bernick, David W. Dodick, Robert C. Cantu, Douglas I. Katz, Jesse Mez, Joseph Palmisano, Brett Martin, J Cummings, EM Reiman, Martha E. Shenton, Robert A. Stern, Michael L. Alosco, Steven Lenio

Bibliographic record

VenueAlzheimer s & Dementia · 2025
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsnot available
Fundersnot available
KeywordsAssociation (psychology)Cognitive impairmentFootballOrthopedic surgeryFootball playersCognitionCollege footballAthletes

Abstract

fetched live from OpenAlex

BACKGROUND: Exposure to repetitive head impacts (RHI) is associated with developing chronic traumatic encephalopathy (CTE) neuropathology. Cognitive and behavioral symptoms have been associated with CTE neuropathology, but efforts to define the specific clinical syndrome are ongoing. This study characterizes the current use of centrally acting medications (CAMs), chronic pain, and number of orthopedic surgeries in former American football players and evaluates for associations with cognitive and behavioral symptoms. METHODS: This study analyzed data from the DIAGNOSE CTE Research Project, which includes 120 former professional football players, 60 collegiate football players, and 56 asymptomatic men without history of RHI. Medical history was obtained by self-report, and participants completed the Montreal Cognitive Assessment (MoCA), Brief Pain Inventory, Barratt Impulsiveness Scale-11 (BIS-11), BRIEF-A Behavioral Regulation Index (BRI), Beck Depression Inventory-II (BDI-II), Beck Anxiety Index (BAI), and Brown-Goodwin Lifetime History of Aggression adulthood score (BGLHA). Logistic regression assessed the association of CAMs, average pain score, and orthopedic surgeries on the cognitive impairment and neurobehavioral dysregulation components of the NINDS traumatic encephalopathy syndrome (TES) research criteria, in former American football players. Linear regression assessed the associations with MoCA and behavioral scales. Models were adjusted for age, education, race, and years of football played. RESULTS: Tables 1 and 2 describe the sample and CAM burden. More orthopedic surgeries, CAMs, and higher average pain were observed in former American football players. Number of CAMs was associated with neurobehavioral dysregulation (OR = 2.18), lower MoCA (β = -0.47), and higher BIS-11 (β = 2.23), BDI-II (β = 2.01), BRI (β = 3.71), BAI (β = 2.04), and BGLHA (β = 0.68) scores. Higher average pain was associated with neurobehavioral dysregulation (OR = 1.57) and higher BIS-11 (β = 2.20), BDI-II (β = 1.98), BRI (β = 2.20), BAI (β = 1.84), and BGLHA (β = 0.52) scores. No associations were observed with orthopedic surgeries. CONCLUSIONS: In former American football players, the number of CAMs and higher average pain were associated with neurobehavioral dysregulation. No associations were observed with diagnosis of cognitive impairment by TES criteria, though the number of CAMs was associated with decreased MoCA.

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 score0.015
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
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 head0.025
GPT teacher head0.307
Teacher spread0.283 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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