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Record W2026056461 · doi:10.1159/000323260

Impact of Hypotension and Low Cerebral Perfusion Pressure on Outcomes in Children Treated with Hypothermia Therapy following Severe Traumatic Brain Injury: A post hoc Analysis of the Hypothermia Pediatric Head Injury Trial

2010· article· en· W2026056461 on OpenAlexafffund
James S. Hutchison, Helena Frndova, Tsz-Yan Milly Lo, Anne‐Marie Guerguerian

Bibliographic record

VenueDevelopmental Neuroscience · 2010
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury and Neurovascular Disturbances
Canadian institutionsHospital for Sick ChildrenSickKids Foundation
FundersCanadian Institutes of Health Research
KeywordsMedicineHypothermiaCerebral perfusion pressureTraumatic brain injuryAnesthesiaIntracranial pressurePerfusionRandomized controlled trialHead injuryClosed head injuryCerebral blood flowSurgeryInternal medicine

Abstract

fetched live from OpenAlex

Hypotension and low cerebral perfusion pressure are known to be associated with unfavorable outcome in children and adults with traumatic brain injury. Using the database from a previously published, randomized controlled trial of 24 h of hypothermia therapy in children with severe traumatic brain injury, we compared the number of patients with hypotension or low cerebral perfusion pressure between the hypothermia therapy and normothermia groups. We also determined the association between these physiologic insults and unfavorable outcome using regression analysis. There were more patients with episodes of hypotension or low cerebral perfusion pressure in the hypothermia therapy group than in the normothermia group. These physiologic insults were associated with unfavorable outcome in both intervention groups. Hypotension and low cerebral perfusion pressure should be anticipated and prevented in future trials of hypothermia therapy in patients with traumatic brain injury.

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)0.006
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.004
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.002
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 head0.016
GPT teacher head0.276
Teacher spread0.261 · 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

Citations51
Published2010
Admission routes2
Has abstractyes

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