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Record W1766745145 · doi:10.1177/107110070502600305

Survey of Tourniquet Use in Orthopaedic Foot and Ankle Surgery

2005· article· en· W1766745145 on OpenAlexaff
Alastair Younger, Timothy P. Kalla, James A. McEwen, Kevin Inkpen

Bibliographic record

VenueFoot & Ankle International · 2005
Typearticle
Languageen
FieldMedicine
TopicBlood transfusion and management
Canadian institutionsUniversity of British ColumbiaProvidence Health Care
Fundersnot available
KeywordsMedicineAnkleCuffTourniquetFoot (prosody)Foot and ankle surgerySurgeryOrthopedic surgeryGuidelinePhysical therapyAnesthesia

Abstract

fetched live from OpenAlex

BACKGROUND: Tourniquet technique varies among foot and ankle surgeons, and to establish a standard practice guideline the current standard of care should be examined. METHODS: One hundred and forty responses were received after 253 surveys were mailed to American Orthopaedic Foot and Ankle Society (AOFAS) members, concerning type of tourniquets, location, and pressures used. RESULTS: Cuff pressures most commonly used were 301 to 350 mmHg for thigh cuffs (49% of thigh cuff users) and 201 to 250 mmHG for calf and ankle cuffs (52% of calf cuff users, 66% of ankle cuff users). A substantial number of foot and ankle surgeons who use calf and ankle cuffs frequently use pressures above 250 mmHg (41% of calf cuff users, 19% of ankle cuff users). Only 9% use limb occlusion pressure when determining cuff pressure. CONCLUSION: Based on the existing evidence-based literature these pressures may be higher than necessary for many patients, and increased adoption of optimal pressure setting techniques as reported in the literature may help reduce tourniquet pressures used and risk of tourniquet injury. Respondents reported experiencing or hearing reports of breakthrough bleeding, nerve injury, and skin injuries under the cuff.

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)0.002
metaresearch head score (Gemma)0.010
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.045
GPT teacher head0.289
Teacher spread0.244 · 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

Citations52
Published2005
Admission routes1
Has abstractyes

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