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A Segmental Bowel Prep Scale for a Screening Colonoscopy and a New Reporting System

2015· article· en· W2978424335 on OpenAlexaboutno aff
Vijaypal Arya, Shashank Agarwal, Ashok Valluri, Shikha Singh, Kalpana A. Gupta

Bibliographic record

VenueThe American Journal of Gastroenterology · 2015
Typearticle
Languageen
FieldMedicine
TopicColorectal Cancer Screening and Detection
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineColonoscopyAscending colonDescending colonRectumSigmoid colonCecumTransverse colonScale (ratio)Intraclass correlationInternal medicineRadiologyGeneral surgerySurgeryColorectal cancerPsychometrics

Abstract

fetched live from OpenAlex

Introduction: The diagnostic accuracy of quality colonoscopy requires thorough visualization of the entire colonic mucosa, making bowel preparation a vital element of the procedure. Failure to sufficiently cleanse the colon prior to colonoscopy may lead to incomplete and more frequent procedures, increase the chances of complications and missed lesions which leads to both patient and physician dissatisfaction. Suboptimal preparation is a major barrier to fulfill the criterias for a quality colonoscopy. In research studies, the most widely used bowel preparation scales are -, Boston Bowel Prep Scale (BBPS), Ottawa Scale and the Aronchick Scale. These scales, score based on three large segments, and give a cumulated score. To be more precise, We propose to divide the colon in six segments- Rectum-R, Sigmoid-S, Descending- D, Transverse-T, Ascending-A, Cecum-C). Methods: The evaluation involves the rating of six anatomical segments of the colon (rectum, sigmoid, descending colon, transverse colon, ascending colon and cecum) on the 5 point Arya Bowel Prep Score (ABPS) (Table 1). A score of 4 and 3 were “Adequate.” A combination of geographical clues and segmental length were considered to identify the individual segments (Table 2). To assess the reliability of ABPS, we trained 4 gastroenterologists and 3 fellows with the description as well as the endoscopic images corresponding to the 5-point scale (0-4). Ten colonoscopy videos were randomly selected and these DVDs were then evaluated and scored by them separately.Table 1: Arya bowel prep scaleTable 2: Identification landmarks of different segments and their intraclass correlationResults: The results of the colon prep were reported as Rx, Sx, Dx, Tx, Ax, Cx where “x” represents the prep score in that individual segment. The validation results for the 4 attending and 3 fellows are shown in Table 2. The same scale was used successfully in a pilot study and a randomized clinical trial to test the efficacy of Shudh Colon Cleanse (SCC) with a conventional PEG based prep. Conclusion: Two-thirds of colorectal malignancies are localized in the left colon and rectum. This scale considers the incidence of colon cancer based on the location so that more emphasis will be laid on a particular smaller segment while scoring the bowel prep. Segmental scores might also help to explain any interval cancer in retrospect. A cumulative score for the entire colon can be misleading as the quality of bowel prep varies through different segments.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.024
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.040
GPT teacher head0.309
Teacher spread0.269 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreMethods

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
Published2015
Admission routes1
Has abstractyes

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