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Record W1994881072 · doi:10.1002/hed.20900

Evaluation of postoperative drainage with application of platelet‐rich and platelet‐poor plasma following hemithyroidectomy: A randomized controlled clinical trial

2008· article· en· W1994881072 on OpenAlexaff
John Yoo, Kathryn Roth, Brian Hughes, Kevin Fung, Jason Franklin, Howard Lampe, William S. Pietrzak

Bibliographic record

VenueHead & Neck · 2008
Typearticle
Languageen
FieldMedicine
TopicPeriodontal Regeneration and Treatments
Canadian institutionsLondon Health Sciences CentreWestern University
Fundersnot available
KeywordsMedicinePlatelet-rich plasmaHemostasisSalineAnalgesicRandomized controlled trialSurgeryPlateletWound healingAnesthesiaInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Platelet-rich plasma (PRP) and platelet-poor plasma (PPP) have been used to improve hemostasis and wound healing after surgery; however, randomized controlled trials proving their efficacy are lacking. METHODS: Hemithyroidectomy was performed on 52 patients. Autologous PRP and PPP were applied during wound closure in the treatment group, while saline was applied in the controls. Outcome measures were postoperative drainage, pain, analgesic use, and length of hospital stay. RESULTS: The 24-hour cumulative drainage was reduced by 29.3% in the treatment group (44.9 mL vs 63.5 mL, p = .039). The treatment group required less analgesic medication despite similar pain scores; however, the difference was not significant. There was a trend toward decreased length of stay for the PRP/PPP group (p = .059). CONCLUSIONS: Hemithyroidectomy served as a stringent test to evaluate the wound-healing capacity of platelet-rich and platelet-poor plasma. This study provides evidence that PRP and PPP reduced postoperative drainage in soft-tissue surgery.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.487

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
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 head0.049
GPT teacher head0.363
Teacher spread0.314 · 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 designRandomized trial
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

Citations11
Published2008
Admission routes1
Has abstractyes

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