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Record W4408667455 · doi:10.2106/jbjs.24.00266

Association Between Tourniquet Use and Patient-Reported Outcomes Following Total Knee Arthroplasty

2025· article· en· W4408667455 on OpenAlexaff
Brian Gibbs, Jhase Sniderman, Shariq Mohammed, Michael S. Kain, David M. Freccero, Ayesha Abdeen

Bibliographic record

VenueJournal of Bone and Joint Surgery · 2025
Typearticle
Languageen
FieldMedicine
TopicBlood transfusion and management
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsMedicineTourniquetMinimal clinically important differenceOsteoarthritisArthroplastySurgeryPatient-reported outcomeTotal knee arthroplastyAnalgesicPatient satisfactionPhysical therapyQuality of life (healthcare)Randomized controlled trialAnesthesia

Abstract

fetched live from OpenAlex

BACKGROUND: Total knee arthroplasty (TKA) is one of the most commonly performed elective procedures in North America. While advancements have been made in patient optimization, surgical technique, and implant design, tourniquet use remains a contentious issue as it relates to patient outcomes and postoperative experience. METHODS: As part of the PEPPER trial, we identified 5,684 patients who underwent primary TKA, of whom 4,866 (85.6%) underwent surgery with a tourniquet (the YT group) and 818 (14.4%) underwent surgery without a tourniquet (the NT group). The cohort was predominantly female (60.8%), White (77%), and of an ethnicity other than Hispanic or Latino (96.8%). The mean age of the patients was 64.6 ± 9.2 years. The primary outcomes were the Knee injury and Osteoarthritis Outcome Score, Joint Replacement (KOOS JR); Patient-Reported Outcomes Measurement Information System Physical Health Summary (PROMIS-PH10); and numeric pain rating scale (NPRS), which were captured preoperatively and at 1, 3, and 6 months postoperatively. The secondary outcomes were length of stay, discharge disposition, analgesic consumption, and postoperative complications. Multivariable analysis was performed to assess the associations between tourniquet use and patient-reported outcome measures (PROMs) following TKA. RESULTS: The percentages of patients achieving the minimal clinically important difference (MCID) for the KOOS JR were significantly different at 1 month only (YT, 55.4%; NT, 47.9%). This difference disappeared at 3 and 6 months. There was no difference between the YT and NT groups in terms of the percentage of patients achieving the MCID for the PROMIS-PH10 or NPRS at any time point. There were no differences between the YT and NT groups at any time point with respect to the KOOS JR, PROMIS-PH10, and NPRS. There were no differences in opioid consumption, operative time, length of stay, wound-related complications, or readmissions postoperatively. CONCLUSIONS: Tourniquet use was associated with more patients achieving the MCID for the KOOS JR at 1 month compared with no tourniquet use. This difference disappeared at 3 and 6 months. At 1, 3, and 6 months, there were no differences in opioid consumption, health-care utilization, or complications between patients undergoing TKA with a tourniquet versus without a tourniquet. Tourniquet use did not have a clinically meaningful impact on PROMs in the multivariable analysis. Arthroplasty surgeons may use these data during preoperative discussions with patients regarding tourniquet use as it relates to the surgeon's preference and how it could influence postoperative function. LEVEL OF EVIDENCE: Therapeutic Level III . See Instructions for Authors for a complete description of levels of evidence.

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)0.009
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 score0.002
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.022
GPT teacher head0.250
Teacher spread0.228 · 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

Citations5
Published2025
Admission routes1
Has abstractyes

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