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Record W2768607419 · doi:10.1136/ebmed-2016-110633

Don’t put off until tomorrow what you can do today: Early cholecystectomy is cost-effective in symptomatic cholelithiasis requiring hospitalization

2017· letter· en· W2768607419 on OpenAlexaff
Charles de Mestral

Bibliographic record

VenueEvidence-Based Medicine · 2017
Typeletter
Languageen
FieldMedicine
TopicGallbladder and Bile Duct Disorders
Canadian institutionsSt. Michael's Hospital
Fundersnot available
KeywordsMedicineAcute cholecystitisBiliary colicCholecystectomyCholecystitisGeneral surgeryLaparoscopic cholecystectomyGallbladderBile ductPopulationRandomized controlled trialEmergency surgeryClinical trialSurgeryInternal medicine

Abstract

fetched live from OpenAlex

Commentary on : Sutton AJ, Vohra RS, Hollyman M, et al . Cost-effectiveness of emergency versus delayed laparoscopic cholecystectomy for acute gallbladder pathology. Br J Surg 2016;104:98–107. Randomised trial and population-based data support the clinical benefit of early over delayed laparoscopic cholecystectomy for acute cholecystitis.1 Concern of increased risk of major bile duct injury or death with early surgery in the setting of acute inflammation has been refuted and there is 20%–30% risk of recurrent gallstone symptoms if surgery is delayed.2 Early and delayed surgery have also been previously compared with economic models informed by randomised controlled trial and population-based data. While most studies have focused on acute cholecystitis, Sutton and colleagues have considered patients across the spectrum of symptomatic cholelithiasis—biliary colic and cholecystitis—requiring hospitalisation. This study …

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Other designlow
models splitAgreement compares identical category sets and study designs across arms.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.389
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.003
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 head0.032
GPT teacher head0.305
Teacher spread0.273 · 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

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designObservational · Other design
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

Citations1
Published2017
Admission routes1
Has abstractyes

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