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Record W3164879965 · doi:10.1503/cjs.002421

The effect of the COVID-19 pandemic on bariatric surgery delivery in Edmonton, Alberta: a single-centre experience

2021· article· en· W3164879965 on OpenAlexaffvenueabout
Nawaf Abu-Omar, Gabriel Marcil, Valentin Mocanu, Jerry T. Dang, Noah J. Switzer, Aliyah Kanji, Daniel W. Birch, Shahzeer Karmali

Bibliographic record

VenueCanadian Journal of Surgery · 2021
Typearticle
Languageen
FieldMedicine
TopicBariatric Surgery and Outcomes
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicinePandemicCoronavirus disease 2019 (COVID-19)Context (archaeology)AccreditationSurgeryHealth careSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)General surgeryMedical emergencyIntensive care medicineInternal medicineDisease

Abstract

fetched live from OpenAlex

<h3>Summary</h3> Delays in the delivery of bariatric surgery in Canada in the context of the COVID-19 pandemic have not been previously explored. Understanding the potential barriers associated with these delays may help in the implementation and delivery of enhanced bariatric protocols, thereby minimizing health care system burden and improving bariatric delivery. We present the experience of a single high-volume, accredited bariatric program in Edmonton, Alberta, in 2020. Although reductions in bariatric cases occurred during lockdown months, the overall number of cases was comparable to 2019 owing to the adoption of strategies aimed at offsetting the burden of hospital resources. These strategies included optimizing patient selection, implementing bariatric Enhanced Recovery After Surgery protocols, and minimizing unnecessary postoperative investigations to allow most patients to be discharged on postoperative day 1. We advocate to continue optimizing bariatric delivery in the face of the COVID-19 pandemic that so disproportionally affects those with severe obesity and its metabolic complications.

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)0.002
metaresearch head score (Gemma)0.017
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.077
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
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 head0.042
GPT teacher head0.256
Teacher spread0.214 · 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

Citations12
Published2021
Admission routes3
Has abstractyes

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