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Record W4304205612 · doi:10.1213/ane.0000000000006232

Hospital-, Anesthesiologist-, Surgeon-, and Patient-Level Variations in Neuraxial Anesthesia Use for Lower Limb Revascularization Surgery: A Population-Based Cross-Sectional Study

2022· article· en· W4304205612 on OpenAlexaffabout
Derek J. Roberts, Rahul S Mor, Michael N. Rosen, Robert Talarico, Manoj M. Lalu, Angela Jerath, Duminda N. Wijeysundera, Daniel I. McIsaac

Bibliographic record

VenueAnesthesia & Analgesia · 2022
Typearticle
Languageen
FieldMedicine
TopicPeripheral Artery Disease Management
Canadian institutionsSt. Michael's HospitalHealth Sciences CentreUniversity of TorontoSunnybrook Health Science CentreUniversity of CalgaryInstitute for Clinical Evaluative SciencesOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsMedicineOdds ratioAnesthesiaAnesthesiologyAnestheticRevascularizationCross-sectional studyOddsPopulationEmergency medicineLogistic regressionSurgeryInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Although neuraxial anesthesia may promote improved outcomes for patients undergoing lower limb revascularization surgery, its use is decreasing over time. Our objective was to estimate variation in neuraxial (versus general) anesthesia use for lower limb revascularization at the hospital, anesthesiologist, surgeon, and patient levels, which could inform strategies to increase uptake. METHODS: Following protocol registration, we conducted a historical cross-sectional analysis of population-based linked health administrative data in Ontario, Canada. All adults undergoing lower limb revascularization surgery between 2009 and 2018 were identified. Generalized linear models with binomial response distributions, logit links and random intercepts for hospitals, anesthesiologists, and surgeons were used to estimate the variation in neuraxial anesthesia use at the hospital, anesthesiologist, surgeon, and patient levels using variance partition coefficients and median odds ratios. Patient- and hospital-level predictors of neuraxial anesthesia use were identified. RESULTS: We identified 11,849 patients; 3489 (29.4%) received neuraxial anesthesia. The largest proportion of variation was attributable to the hospital level (50.3%), followed by the patient level (35.7%); anesthesiologists and surgeons had small attributable variation (11.3% and 2.8%, respectively). Mean odds ratio estimates suggested that 2 similar patients would experience a 5.7-fold difference in their odds of receiving a neuraxial anesthetic were they randomly sent to 2 different hospitals. Results were consistent in sensitivity analyses, including limiting analysis to patients with diagnosed peripheral artery disease and separately to those aged >66 years with complete prescription anticoagulant and antiplatelet usage data. CONCLUSIONS: Neuraxial anesthesia use primarily varies at the hospital level. Efforts to promote use of neuraxial anesthesia for lower limb revascularization should likely focus on the hospital context.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
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 head0.032
GPT teacher head0.269
Teacher spread0.237 · 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.

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

Citations5
Published2022
Admission routes2
Has abstractyes

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