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Record W4401908129 · doi:10.1097/io9.0000000000000031

Practice variations in the surgical treatment of small bowel obstruction in Quebec

2024· article· en· W4401908129 on OpenAlexaffabout
Maude Rancourt, Sonia Gabriela Cheng Oviedo, Nathalie McFadden

Bibliographic record

VenueInternational Journal of Surgery Open · 2024
Typearticle
Languageen
FieldMedicine
TopicIntestinal and Peritoneal Adhesions
Canadian institutionsCentre Hospitalier Universitaire de Sherbrooke
Fundersnot available
KeywordsMedicineBowel obstructionGeneral surgerySurgery

Abstract

fetched live from OpenAlex

Background: Small bowel obstruction (SBO) is a common emergency and selectively requires surgical management. There is growing evidence supporting the use of laparoscopic surgery (LS) compared to open surgery for SBO. Methods: An online survey-based cohort study examining surgeon characteristics, patient factors, and clinical situations that impact decision making regarding the use of LS for SBO was sent to the 538 members of the Association Québécoise de Chirurgie and their answers were collected over a 4-month period in 2019. Results: The response rate was 27.1% ( n =146). The gender, sex or the practice setting did not have an impact on the surgical approach. It was noted that surgeons who were more comfortable with laparoscopy used it more often ( P =0.002). The three factors favoring the initial approach by laparotomy were most frequently cited: hostile abdomen, severe abdominal distension, and hemodynamic instability. Young surgeons had more homogenous answers ( P =0.03). The surgeons having a practice oriented into LS had different decision criteria compared to those doing more open surgery. Conclusion: This article emphasizes key clinical scenarios and determinants that shape the surgical strategy for SBO treatment. The authors aim for this research to stimulate more discussions and contemplation about using laparoscopic methods for treating SBO in certain patients, thereby potentially elevating the frequency of surgeons adopting this approach. Moreover, considering the existing literature supports LS as a viable and safe method for SBO treatment, and noting the enhanced outcomes for patients, it becomes increasingly vital to advocate for this conversation.

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 score0.395
Threshold uncertainty score0.992

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)0.0000.000

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 head0.088
GPT teacher head0.381
Teacher spread0.293 · 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

Citations0
Published2024
Admission routes2
Has abstractyes

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