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Record W2531050326 · doi:10.1177/0885066616672643

The Impact of Mean Arterial Pressure on Functional Outcome Post Trauma-Related Acute Spinal Cord Injury: A Scoping Systematic Review of the Human Literature

2016· article· en· W2531050326 on OpenAlexaff
Behzad Sabit, Frederick A. Zeiler, Neil Berrington

Bibliographic record

VenueJournal of Intensive Care Medicine · 2016
Typearticle
Languageen
FieldMedicine
TopicSpinal Cord Injury Research
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsMedicineSystematic reviewCochrane LibraryMEDLINESpinal cord injuryMeta-analysisScopusMean arterial pressurePhysical therapyIntensive care medicineBlood pressureSpinal cordInternal medicinePsychiatryHeart rate

Abstract

fetched live from OpenAlex

PURPOSE: To perform a scoping systematic review on the literature surrounding mean arterial pressure (MAP) and functional outcomes post traumatic acute spinal cord injury (ASCI). METHODS: We performed a systematic review of the literature via searching MEDLINE, BIOSIS, EMBASE, Global Health, SCOPUS, and Cochrane Library from inception to January 2015. We also performed a handsearch of various published meeting proceedings. Through a 2-step review process, employing 2 independent reviewers, we selected articles for the final review based on predefined inclusion/exclusion criteria. RESULTS: Nine studies were included in the final review. Only 2 were prospective studies. All studies documented some degree of objective functional outcome in relation to MAP posttraumatic ASCI. Four studies documented a relation between higher MAP and improved functional outcome. Five studies failed to show any relationship between MAP and functional outcome. CONCLUSIONS: Although no definitive conclusions could be reached based on the data collected, this study does give valuable insight into future avenues of research on the topic of hemodynamic management in traumatic ASCI as well as provides guidelines for refinement of future study design.

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)0.001
metaresearch head score (Gemma)0.014
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.571
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.049
GPT teacher head0.427
Teacher spread0.378 · 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 designSystematic review
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

Citations22
Published2016
Admission routes1
Has abstractyes

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