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Record W2885295996 · doi:10.1016/j.arthro.2018.06.022

Personalized Blood Flow Restriction Therapy: How, When and Where Can It Accelerate Rehabilitation After Surgery?

2018· review· en· W2885295996 on OpenAlexaff
Brian J. Day

Bibliographic record

VenueArthroscopy The Journal of Arthroscopic and Related Surgery · 2018
Typereview
Languageen
FieldMedicine
TopicCardiovascular and exercise physiology
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsBlood flow restrictionRehabilitationMedicineLimitingBlood flowPhysical medicine and rehabilitationMuscle atrophyBlood pressureSurgeryAtrophyPhysical therapyCardiologyInternal medicine

Abstract

fetched live from OpenAlex

Personalized (based on a percentage of a patient's limb occlusion pressure) blood flow restriction is emerging as a potential advancement in orthopaedic surgery. Safe application of the technology requires the use of medical devices capable of customizing the pressures applied to individual patients. In those circumstances, it is a low risk and noninvasive technique. By limiting muscle atrophy and aiding in the recovery of strength and function, it has the potential to significantly reduce the morbidity from limb trauma and surgery, and aid in achieving a substantially earlier return to full activity.

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)0.002
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 score0.779
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.027
GPT teacher head0.280
Teacher spread0.253 · 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

Citations20
Published2018
Admission routes1
Has abstractyes

Explore more

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