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Record W4378628140 · doi:10.1186/s40635-023-00515-5

Temporal relationship between vasopressor and sedative administration and cerebrovascular response in traumatic brain injury: a time-series analysis

2023· article· en· W4378628140 on OpenAlexafffund
Logan Froese, Alwyn Gomez, Amanjyot Singh Sainbhi, Nuray Vakitbilir, Izabella Marquez, Fiorella Amenta, Kevin Y. Stein, Frederick A. Zeiler

Bibliographic record

VenueIntensive Care Medicine Experimental · 2023
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury and Neurovascular Disturbances
Canadian institutionsManitoba HealthUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchUniversity of ManitobaResearch ManitobaHealth Sciences Centre Foundation
KeywordsMedicineSedativeDosingAnesthesiaIntensive care unitTraumatic brain injuryObservational studyIntensive careIntensive care medicineCerebral perfusion pressureCerebral blood flowPharmacologyInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Although vasopressor and sedative agents are commonly used within the intensive care unit to mediate systemic and cerebral physiology, the full impact such agents have on cerebrovascular reactivity remains unclear. Using a prospectively maintained database of high-resolution critical care and physiology, the time-series relationship between vasopressor/sedative administration, and cerebrovascular reactivity was interrogated. Cerebrovascular reactivity was assessed through intracranial pressure and near infrared spectroscopy measures. Using these derived measures, the relationship between hourly dose of medication and hourly index values could be evaluated. The individual medication dose change and their corresponding physiological response was compared. Given the high number of doses of propofol and norepinephrine, a latent profile analysis was used to identify any underlying demographic or variable relationships. Finally, using time-series methodologies of Granger causality and vector impulse response functions, the relationships between the cerebrovascular reactivity derived variables were compared. RESULTS: From this retrospective observational study of 103 TBI patients, the evaluation between the changes in vasopressor or sedative agent dosing and the previously described cerebral physiologies was completed. The assessment of the physiology pre/post infusion agent change resulted in similar overall values (Wilcoxon signed-ranked p value > 0.05). Time series methodologies demonstrated that the basic physiological relationships were identical before and after an infusion agent was changed (Granger causality demonstrated the same directional impact in over 95% of the moments, with response function being graphically identical). CONCLUSIONS: This study suggests that overall, there was a limited association between the changes in vasopressor or sedative agent dosing and the previously described cerebral physiologies including that of cerebrovascular reactivity. Thus, current regimens of administered sedative and vasopressor agents appear to have little to no impact on cerebrovascular reactivity in 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)0.003
metaresearch head score (Gemma)0.009
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 score0.003
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.051
GPT teacher head0.356
Teacher spread0.305 · 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

Citations9
Published2023
Admission routes2
Has abstractyes

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