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Record W1997246891 · doi:10.1002/lary.23437

Multi‐institutional evaluation of a sinus surgery checklist

2012· article· en· W1997246891 on OpenAlexaff
Zachary M. Soler, David A. Poetker, Luke Rudmik, Alkis J. Psaltis, John D. Clinger, Jess C. Mace, Timothy L. Smith

Bibliographic record

VenueThe Laryngoscope · 2012
Typearticle
Languageen
FieldMedicine
TopicSinusitis and nasal conditions
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMcNemar's testChecklistTest (biology)Observational studyMedicineTask (project management)PsychologyStatisticsMathematicsCognitive psychologyInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVES/HYPOTHESIS: To examine the frequency of safe surgical practices specific to endoscopic sinus surgery (ESS) before and after implementation of a checklist at four institutions across North America. STUDY DESIGN: Prospective, multi-institutional, observational study. METHODS: Consecutive surgeries were observed at four institutions before (n = 100) and after (n = 100) implementation of the ESS Checklist. A passive observer documented whether 10 specific tasks were performed by the surgical team during the course of each case. The frequency with which each item was performed was tabulated, and differences across institutions were evaluated using the Pearson χ(2) test. Improvement in the frequency of each single item between pre- and postintervention time periods was assessed by the McNemar χ(2) test. RESULTS: Successful performance of all 10 tasks in the prechecklist period was not observed for any ESS case at any of the four study sites. As might be expected, performance of any individual task was highly variable, ranging from 14% to 95%. After implementation of the ESS Checklist, successful performance of all 10 tasks during an individual surgery increased from 0% to 87% across all institutions, a change that was highly significant (P < .001). Significant increases in the performance of individual tasks was observed for nine of 10 items across all institutions (P ≤ .031 for all). CONCLUSIONS: Significant heterogeneity exists with regard to performance of specific tasks aimed at minimizing error during ESS. Utilization of the ESS Checklist standardized practice across four institutions and significantly increased the likelihood that individual safety tasks were performed during the course of sinus 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 score0.302
Threshold uncertainty score0.977

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)0.0010.000

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 head0.089
GPT teacher head0.343
Teacher spread0.255 · 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

Citations21
Published2012
Admission routes1
Has abstractyes

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