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Record W2095583559 · doi:10.1017/s0022215114001790

Does pterygopalatine canal injection with local anaesthetic and adrenaline decrease bleeding during functional endoscopic sinus surgery?

2014· article· en· W2095583559 on OpenAlexaff
Constanza J. Valdés, Yahya Al Badaai, Mariana Bogado, M Samaha

Bibliographic record

VenueThe Journal of Laryngology & Otology · 2014
Typearticle
Languageen
FieldMedicine
TopicSinusitis and nasal conditions
Canadian institutionsRoyal Victoria Hospital
Fundersnot available
KeywordsMedicinePterygopalatine fossaFunctional endoscopic sinus surgeryAnesthesiaSurgeryBlood lossParanasal sinusesSinusitis

Abstract

fetched live from OpenAlex

OBJECTIVE: To determine the effect of pterygopalatine fossa injection with xylocaine and adrenaline on: surgical field bleeding and blood loss during functional endoscopic sinus surgery for chronic rhinosinusitis, and the duration of the procedure. METHODS: A prospective, single-blinded, controlled trial was performed in a tertiary care academic centre. A total of 45 patients undergoing functional endoscopic sinus surgery for chronic rhinosinusitis, whose disease was symmetrical based on computed tomography grading, were included. A unilateral pterygopalatine fossa injection with 1 per cent xylocaine and 1:100 000 adrenaline was performed after the induction of anaesthesia. The contralateral side served as the control. The operating surgeon, who was blinded to the injected side, assessed the surgical field using a validated six-item grading system. Blood loss, blood pressure, heart rate and end-tidal carbon dioxide were recorded every 15 minutes for each side separately, and duration of surgery was noted. RESULTS: There was no statistically significant difference in the surgical field grade between the injected and non-injected sides (p = 0.161). There were no differences in blood loss or duration of surgery. CONCLUSION: Pterygopalatine fossa injection prior to functional endoscopic sinus surgery did not decrease intra-operative surgical field bleeding, blood loss or duration of 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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.067
Threshold uncertainty score0.327

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.009
GPT teacher head0.222
Teacher spread0.213 · 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

Citations26
Published2014
Admission routes1
Has abstractyes

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