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Record W1568685867

The effects of a pneumatic tourniquet on blood loss in total knee arthroplasty.

2001· article· en· W1568685867 on OpenAlexaff
A. Marc Tetro, John F. Rudan

Bibliographic record

VenuePubMed · 2001
Typearticle
Languageen
FieldMedicine
TopicBlood transfusion and management
Canadian institutionsQueen's University
Fundersnot available
KeywordsMedicineTourniquetBlood lossTotal knee arthroplastySurgeryAnesthesiaPerioperativeComplicationArthroplastyProspective cohort studyBlood transfusion
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: In lower-extremity surgery there are significant risks associated with the use of tourniquets. This prospective study was done to assess to what extent these risks may be offset by the potential advantages of tourniquets, namely reductions in blood loss, length of hospital stay and complication rates. DESIGN: A prospective case study. SETTING: A major urban hospital. PATIENTS: Sixty-three consecutive patients scheduled for primary cemented total knee arthroplasty (TKA) were blindly randomized into tourniqet (n = 33) and non-tourniquet (n = 30) groups. INTERVENTION: TKA during which a pneumatic tourniquet was applied or not applied to control blood loss. MAIN OUTCOME MEASURES: Perioperative blood loss, operating time, complication rates, hospital stay and transfusion needs. RESULTS: Differences in the total measured blood loss, intraoperative blood loss and the Hemovac drainage blood loss between the 2 groups were not significantly different (p > 0.25). The calculated total blood loss was actually lower in the non-tourniquet group (p = 0.02). Between the groups there were no statistical differences in surgical time, length of hospital stay, transfusion requirements or rate of complications (although there was a trend to more complications in the tourniquet group (p = 0.06)). CONCLUSION: The effectiveness of a pneumatic tourniquet to control blood loss in TKA is questionable.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.947
Threshold uncertainty score0.234

Codex and Gemma teacher scores by category

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

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 head0.007
GPT teacher head0.207
Teacher spread0.199 · 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.

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

Citations153
Published2001
Admission routes1
Has abstractyes

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