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Record W4389704371 · doi:10.1055/s-0043-1777439

Diverticulitis: A Review of Current and Emerging Practice-Changing Evidence

2023· review· en· W4389704371 on OpenAlexaff
Sonia Wu, Maher Al Khaldi, Carole Richard, François Dagbert

Bibliographic record

VenueClinics in Colon and Rectal Surgery · 2023
Typereview
Languageen
FieldMedicine
TopicDiverticular Disease and Complications
Canadian institutionsCentre Hospitalier de l’Université de Montréal
Fundersnot available
KeywordsDiverticulitisMedicineIntensive care medicineGeneral surgeryColonoscopyDiverticular diseaseDiseaseColorectal cancerSurgeryInternal medicineCancer

Abstract

fetched live from OpenAlex

Acute diverticulitis represents a common colorectal emergency seen in the Western world. Over time, management of this condition has evolved. This review aims to highlight recent evidence and update current recommendations. Notable evidence has emerged in certain aspects of diverticulitis. This includes disease pathogenesis, as emerging data suggest a potentially greater role for the microbiome and genetic predisposition than previously thought. Acute management has also seen major shifts, where traditional antibiotic treatment may no longer be necessary for acute uncomplicated diverticulitis. Following successful medical management of acute diverticulitis, indications for elective sigmoidectomy have decreased. The benefit of emergency surgery remains for peritonitis, sepsis, obstruction, and acute diverticulitis in certain immunocompromised patients. Routine colonoscopy, once recommended after all acute diverticulitis episodes, has been shown to be beneficial for cancer exclusion in a distinct patient population. Despite advances in research, certain entities remain poorly understood, such as smoldering diverticulitis and symptomatic uncomplicated diverticular disease. As research in the field expands, paradigm shifts will shape our understanding of diverticulitis, influencing how clinicians approach management and educate patients.

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)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.815
Threshold uncertainty score0.784

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.256
GPT teacher head0.492
Teacher spread0.236 · 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 designOther design
Domainnot available
GenreReview

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

Citations5
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueClinics in Colon and Rectal SurgerySame topicDiverticular Disease and ComplicationsFrench-language works237,207