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Record W2415119925

Contemporary perspectives on the management of posterior epistaxis: survey of canadian otolaryngologists.

2011· article· en· W2415119925 on OpenAlexaffabout
Samantha Tam, Brian Rotenberg

Bibliographic record

VenuePubMed · 2011
Typearticle
Languageen
FieldMedicine
TopicVascular Anomalies and Treatments
Canadian institutionsWestern University
Fundersnot available
KeywordsMedicineOtorhinolaryngologyNasal packingHead and neckHead and neck surgerySurgery
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: To describe current management of posterior epistaxis among Canadian otolaryngology-head and neck surgeons. METHODS: A cross-sectional Internet-based survey was distributed to all 550 members of the Canadian Society of Otolaryngology-Head and Neck Surgery with an electronic mail contact. The survey consisted of three sections: (1) demographic data, (2) opinions regarding management options for posterior epistaxis, and (3) opinions regarding management of complications after placement of a posterior nasal pack. The survey was available for completion from July 2009 until October 2009. Main outcome measures were ranking of preference, comfort level, and perceived best management option for posterior epistaxis. RESULTS: A total of 152 completed surveys were collected (28% response rate). Respondents were most comfortable with and most preferred inflatable balloon packing for treatment of posterior epistaxis. However, it was felt that endoscopic sphenopalatine arterial ligation was the best available intervention. After placement of a posterior nasal pack, respondents felt that monitoring of vital signs was required for all patients, but a lower-intensity monitoring setting may be sufficient. CONCLUSIONS: There is a discrepancy between actual practice and perceived best available management for posterior epistaxis. Respondents also favoured a lower-intensity monitoring setting for patients with posterior nasal packing. Practice guidelines may be helpful in ensuring that patients receive the best possible care while making the best use of limited hospital resources.

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)0.000
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 score0.221
Threshold uncertainty score0.772

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.112
GPT teacher head0.238
Teacher spread0.126 · 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

Citations8
Published2011
Admission routes2
Has abstractyes

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