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Record W3099907029 · doi:10.14245/ns.2040144.072

Hemodynamic Management of Acute Spinal Cord Injury: A Literature Review

2020· review· en· W3099907029 on OpenAlexaff
Young‐Seok Lee, Kyoung‐Tae Kim, Brian K. Kwon

Bibliographic record

VenueNeurospine · 2020
Typereview
Languageen
FieldMedicine
TopicSpinal Cord Injury Research
Canadian institutionsInternational Collaboration On Repair DiscoveriesVancouver Spine Surgery InstituteUniversity of British Columbia
FundersMinistry of Science and ICT, South KoreaNational Research Foundation of KoreaNational Research Foundation
KeywordsHemodynamicsMedicineSpinal cord injurySpinal cordAnesthesiaPsychiatry

Abstract

fetched live from OpenAlex

The goal of acute spinal cord injury (SCI) management is to reduce secondary injuries and improve neurological recovery after its occurrence. This review aimed to explore the literature regarding hemodynamic management to reduce ischemic secondary injury and improve neurologic outcome following acute SCI. The PubMed database was searched for studies investigating blood flow, mean arterial pressure (MAP), and spinal cord perfusion pressure after SCI. The 2013 guidelines of the American Association of Neurological Surgeons/Congress of Neurological Surgeons recommended maintaining MAP at 85-90 mmHg for 7 days after SCI to potentially improve outcome. However, this recommendation was based on weak evidence for neurologic benefit. The maintenance of MAP will typically require vasopressors, which may have their own set of complications. More recently, studies have suggested the potential importance of considering spinal cord perfusion pressure in addition to the MAP. Further research on the hemodynamic management of acute SCI is required to determine how to optimize neurologic recovery. Evidence-based guidelines for hemodynamic management should acknowledge the gaps in knowledge and the limitations of the current literature.

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 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)0.000
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 score0.664
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.002
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 head0.063
GPT teacher head0.455
Teacher spread0.392 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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

Citations62
Published2020
Admission routes1
Has abstractyes

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