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Record W2957129721 · doi:10.3171/2019.4.jns19252

Antithrombotic agents and traumatic brain injury in the elderly population: hemorrhage patterns and outcomes

2019· article· en· W2957129721 on OpenAlexaff
Pasquale Scotti, Chantal Séguin, Benjamin Lo, Élaine de Guise, J Troquet, Judith Marcoux

Bibliographic record

VenueJournal of neurosurgery · 2019
Typearticle
Languageen
FieldMedicine
TopicIntracerebral and Subarachnoid Hemorrhage Research
Canadian institutionsMcGill University Health CentreUniversité de Montréal
Fundersnot available
KeywordsMedicineGlasgow Coma ScaleTraumatic brain injuryRivaroxabanWarfarinTrauma centerDabigatranGlasgow Outcome ScaleStroke (engine)AspirinAnesthesiaHead traumaGeriatric traumaPopulationClopidogrelInternal medicineInjury Severity ScoreEmergency medicineAtrial fibrillationSurgeryRetrospective cohort studyPoison controlInjury prevention

Abstract

fetched live from OpenAlex

OBJECTIVE: Among the elderly, use of antithrombotics (ATs), antiplatelets (APs; aspirin, clopidogrel), and/or anticoagulants (ACs; warfarin, direct oral ACs [DOACs; dabigatran, rivaroxaban, apixaban]) to prevent thromboembolic events must be carefully weighed against the risk of intracranial hemorrhage (ICH) with trauma. The goal of this study was to assess the risk of sustaining a traumatic brain injury (TBI), ICH, and poorer outcomes in relation to AT use among all patients 65 years or older presenting to a single institution with head trauma. METHODS: Data were collected from all head trauma patients 65 years or older presenting to the authors' supraregional tertiary trauma center over a 24-month period and included age, sex, injury mechanism, medical history, international normalized ratio, Glasgow Coma Scale (GCS) score, ICH presence and type, hospital admission, reversal therapy, surgery, discharge destination, Extended Glasgow Outcome Scale (GOSE) score at discharge, and mortality. RESULTS: A total of 1365 head trauma patients 65 years or older were included; 724 were on AT therapy (413 on APs, 151 on ACs, 59 on DOACs, 48 on 2 APs, 38 on AP+AC, and 15 on AP+DOAC) and 641 were not. Among all head trauma patients, the risk of sustaining a TBI was associated with AP use after adjusting for covariates. Of the 731 TBI patients, those using ATs had higher rates of ICH (p <0.0001), functional dependency at discharge (GOSE score ≤ 4; p < 0.0001), and mortality (p < 0.0001). Elevated rates of ICH progression on follow-up CT scanning were observed in patients in the warfarin monotherapy (OR 5.30, p < 0.0001) and warfarin + AP (OR 6.15, p = 0.0011). Risk of mortality was not associated with single antiplatelet use but was notably high with 2 APs (OR 4.66, p = 0.0056), warfarin (OR 5.18, p = 0.0003), and DOAC use (OR 5.09, p = 0.0149). CONCLUSIONS: Elderly trauma patients on ATs, especially combination therapy, are at elevated risk of ICH and poor outcomes compared with those not on AT therapy. While both AP and warfarin use alone and in combination were associated with significantly elevated odds of sustaining an ICH among TBI patients, only warfarin use was a predictor of hemorrhage progression on follow-up scans. The use of a single AP was not associated with mortality; however, the combination of both aspirin and clopidogrel was. Warfarin and DOAC users had comparable mortality rates; however, DOAC users had lower rates of ICH progression, and fewer survivors were functionally dependent at discharge than were warfarin users. DOACs are an overall safer alternative to warfarin for patients at high risk of falls.

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 score0.005
Threshold uncertainty score0.010

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 studies0.0000.000
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 head0.034
GPT teacher head0.320
Teacher spread0.287 · 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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Citations102
Published2019
Admission routes1
Has abstractyes

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