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Record W2419440510 · doi:10.1097/dss.0000000000000557

Retraction of the Plunger on a Syringe of Hyaluronic Acid Before Injection

2015· article· en· W2419440510 on OpenAlexaff
Wayne Carey, Susan Weinkle

Bibliographic record

VenueDermatologic Surgery · 2015
Typearticle
Languageen
FieldMedicine
TopicFacial Rejuvenation and Surgery Techniques
Canadian institutionsMcGill University
FundersGalderma
KeywordsSyringePlungerMedicineHyaluronic acidSurgerySyringe driverAnesthesiaBiomedical engineeringMaterials scienceAnatomy

Abstract

fetched live from OpenAlex

BACKGROUND: Controversy exists concerning the need for aspiration before injection with hyaluronic acid (HA) fillers. OBJECTIVE: The authors undertook a study of HA products to determine if blood could be aspirated back into a syringe of HA when the needle has been primed or filled with HA. METHODS AND MATERIALS: Two studies were set up to determine if or when blood could be withdrawn from a heparinized fresh tube of blood into the HA syringe. Two different techniques were tested; one using a slow-pull retraction of the plunger and up to a 5-second waiting time before release versus a rapid pullback and quick release. RESULTS: Review of these data demonstrates that the usual clinical method, which involves quick withdrawal and instant release of the syringe plunger does not allow for sufficient removal of the filler found intraluminal in the needle and may give rise to false negative results in vitro and likely in vivo with the exception being the Galderma/Medicis products. CONCLUSION: In summary, withdrawal of the syringe plunger with no visible blood in the syringe does not eliminate the possibility of intravascular placement of the syringe needle.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
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 head0.059
GPT teacher head0.289
Teacher spread0.230 · 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 designCase report
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

Citations47
Published2015
Admission routes1
Has abstractyes

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