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Record W2895332081 · doi:10.2147/ca.s167728

Surgical audit of a single-surgeon experience with laparoscopic cholecystectomy in northern Saskatchewan, Canada

2018· article· en· W2895332081 on OpenAlexaffabout
Bernado Verdolin, Yagan Pillay

Bibliographic record

VenueClinical Audit · 2018
Typearticle
Languageen
FieldMedicine
TopicGallbladder and Bile Duct Disorders
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsMedicineReferralAuditGeneral surgeryLaparoscopic cholecystectomyCholecystectomyMedical recordLaparoscopic surgerySurgeryLaparoscopyFamily medicine

Abstract

fetched live from OpenAlex

Aims: This study reviewed laparoscopic cholecystectomy in the clinical practice of a single general surgeon in northern Saskatchewan, Canada. Methods: Data were accumulated from the electronic medical records (EMRs) software and health records (HRs) department of the Victoria Hospital. This audit searched for all laparoscopic cholecystectomies between the years 2009 and 2016 inclusive. Results: Two hundred and ninety laparoscopic cholecystectomies were performed over 7 years. They were analyzed for various aspects such as age, with the majority of patients between 41and 65years, and gender, with the female gender in 71.8% of cases. Our complication rates in both elective and emergency procedures, along with conversion (1.37%) and reoperation (1.03%) rates, were examined. The lengths of stay in elective (1.02 days) and emergency (2.13 days) surgeries were comparable to the reported literature. We examined associated procedures performed with the laparoscopic cholecystectomy, procedure duration, converted surgeries, and reoperated patients, as well as the referral rate of patients to a quaternary care hospital for super specialist evaluation and management not available locally. Biliary leakage was diagnosed in four cases postoperatively (1.37%), showing similar trends to published literature rates varying from 0.56% to 3.5%. Conclusion: In Prince Albert Parkland health region, even with limited resources in a small city such as Prince Albert in northern Saskatchewan and great distances between the two health care centers, it is possible to provide a high standard of surgical care for the population with results comparable to published international standards in minimally invasive ­gallbladder surgery. Keywords: surgical audit, laparoscopic cholecystectomy, rural surgery, audit database

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 score0.852
Threshold uncertainty score0.925

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.025
GPT teacher head0.303
Teacher spread0.278 · 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

Citations1
Published2018
Admission routes2
Has abstractyes

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