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Record W61165066

Preoperative bowel preparation for patients undergoing elective colorectal surgery: a clinical practice guideline endorsed by the Canadian Society of Colon and Rectal Surgeons.

2010· article· en· W61165066 on OpenAlexaffabout
Cagla Eskicioglu, Shawn Forbes, Darlene Fenech, Robin S. McLeod

Bibliographic record

VenuePubMed · 2010
Typearticle
Languageen
FieldMedicine
TopicSurgical site infection prevention
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineGuidelineAnastomosisColorectal surgeryGeneral surgeryEvidence-based medicinePreoperative fastingSurgeryIntensive care medicineAlternative medicineAbdominal surgery
DOInot available

Abstract

fetched live from OpenAlex

BACKGROUND: Despite evidence that mechanical bowel preparation (MBP) does not reduce the rate of postoperative complications, many surgeons still use MBP before surgery. We sought to appraise and synthesize the available evidence regarding preoperative bowel preparation in patients undergoing elective colorectal surgery. METHODS: We searched MEDLINE, EMBASE and Cochrane Databases to identify randomized controlled trials (RCTs) comparing patients who received a bowel preparation with those who did not. Two authors reviewed the abstracts to identify articles for critical appraisal. We used the methods of the United States Preventive Services Task Force to grade study quality and level of evidence, as well as formulate the final recommendations. Outcomes assessed included postoperative infectious complications, such as anastomotic dehiscence and superficial surgical site infections. RESULTS: Our review identified 14 RCTs and 8 meta-analyses. Based on the quality and content of these original manuscripts, we formulated 6 recommendations for various aspects of bowel preparation in patients undergoing elective colorectal surgery. CONCLUSION: Taking into account the lack of difference in postoperative infectious complication rates when MBP is omitted and the adverse effects of MBP, we believe that, based on the literature, MBP before surgery should be omitted.

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)0.003
metaresearch head score (Gemma)0.009
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 score0.119
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.009
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 head0.021
GPT teacher head0.317
Teacher spread0.296 · 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

Citations69
Published2010
Admission routes2
Has abstractyes

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