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Record W2766857343 · doi:10.3171/2017.7.focus17426

Management of raised intracranial pressure in aneurysmal subarachnoid hemorrhage: time for a consensus?

2017· review· en· W2766857343 on OpenAlex
Naif M. Alotaibi, Justin Z. Wang, Christopher R. Pasarikovski, Daipayan Guha, Fawaz Al‐Mufti, Muhammad Mamdani, Gustavo Saposnik, Tom A. Schweizer, R. Loch Macdonald

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueNeurosurgical FOCUS · 2017
Typereview
Languageen
FieldMedicine
TopicTraumatic Brain Injury and Neurovascular Disturbances
Canadian institutionsInstitute for Clinical Evaluative SciencesSt. Michael's HospitalUniversity of Toronto
FundersBrain Aneurysm FoundationHeart and Stroke Foundation of Canada
KeywordsSubarachnoid hemorrhageMedicineTraumatic brain injuryIntracranial pressureIntensive care medicineNeurointensive careRaised intracranial pressurePopulationAnesthesiaPsychiatry

Abstract

fetched live from OpenAlex

Elevated intracranial pressure (ICP) is a well-recognized phenomenon in aneurysmal subarachnoid hemorrhage (aSAH) that has been demonstrated to lead to poor outcomes. Despite significant advances in clinical research into aSAH, there are no consensus guidelines devoted specifically to the management of elevated ICP in the setting of aSAH. To treat high ICP in aSAH, most centers extrapolate their treatment algorithms from studies and published guidelines for traumatic brain injury. Herein, the authors review the current management strategies for treating raised ICP within the aSAH population, emphasize key differences from the traumatic brain injury population, and highlight potential directions for future research in this controversial topic.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.983
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.055
GPT teacher head0.340
Teacher spread0.285 · 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