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Record W2091847504 · doi:10.1097/prs.0000000000001046

Ketorolac Does Not Increase Perioperative Bleeding

2015· letter· en· W2091847504 on OpenAlexaffabout
John S. Davidson, Kim Turner

Bibliographic record

VenuePlastic & Reconstructive Surgery · 2015
Typeletter
Languageen
FieldMedicine
TopicCancer, Stress, Anesthesia, and Immune Response
Canadian institutionsQueen's University
Fundersnot available
KeywordsKetorolacMedicinePerioperativeAbdominoplastySurgeryMammaplastyRandomized controlled trialPlastic surgeryAnesthesiaAnalgesic

Abstract

fetched live from OpenAlex

Sir: Despite the assurance of a well-designed and rigorous meta-analysis showing no increased overall risk of perioperative surgical bleeding with ketorolac, we would echo and emphasize the authors’ caveat that one be selective in its use as determined by the type of procedure and patient risk. We recently published the experience at our center with the use of ketorolac in reduction mammaplasty, demonstrating a significant increase in surgical bleeding complications in patients treated with this agent.1 Admittedly, our study design lacked the precision of a randomized and blinded trial, but the data are compelling enough to arguably preclude one even being attempted. We feel that ketorolac should not be used in outpatient and short-stay surgical procedures where there is extensive surgical undermining in subcutaneous and prefascial tissue planes where large bleeding surfaces obscured by subcutaneous fat are created. Notwithstanding the obvious opioid-sparing benefit of ketorolac in these settings, we have stopped the routine use of this agent for reduction mammaplasty and abdominoplasty procedures. However, the authors have convincingly demonstrated a wide array of surgical settings in plastic surgery where ketorolac remains a useful therapeutic adjunct for postoperative analgesia. DISCLOSURE The authors have no financial interest in any of the products, devices, or drugs mentioned in this communication. John S. D. Davidson, M.D. Department of Surgery Division of Plastic Surgery Kim Turner, M.D. Departments of Anesthesiology and Perioperative Medicine Queen’s University Kingston, Ontario, Canada

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)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.574
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.003
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 head0.024
GPT teacher head0.249
Teacher spread0.225 · 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
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

Citations7
Published2015
Admission routes2
Has abstractyes

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