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Record W2793032789 · doi:10.1093/jcag/gwy009.232

A232 AUTOMATED TELEPHONE REMINDER TO IMPROVE BOWEL PREPARATION QUALITY FOR COLONOSCOPY

2018· article· en· W2793032789 on OpenAlexaffabout
Mitchell Church, Lawrence Hookey, Natalie Rubinger

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2018
Typearticle
Languageen
FieldMedicine
TopicColorectal Cancer Screening and Detection
Canadian institutionsQueen's University
Fundersnot available
KeywordsColonoscopyMedicineRandomized controlled trialInformed consentBowel preparationTelephone callPhoneRandomizationColorectal cancerMedical emergencySurgeryAlternative medicineInternal medicineComputer scienceCancer

Abstract

fetched live from OpenAlex

Colonoscopy preparation is challenging, involving the consumption of a large volume of prep solution in the day leading up to procedure. Adequate preparation is vital for the endoscopist to visualize the full colon. Upwards of 20% of outpatient colonoscopies have inadequate bowel prep, often requiring a repeat procedure and accompanying costs and risks. Prior research has examined the impact of educational tools such as booklets and visual aids to improve bowel prep quality. The best success thus far has been with time-intensive physician or nurse delivered educational sessions (in person or by phone). No studies to date have quantified the impact of an automated telephone reminder system on bowel prep quality. This study aims to determine the impact of an automated telephone reminder system on measured quality of bowel preparation in patients undergoing outpatient colonoscopy. This study is a prospective trial, using a randomized consent structure. Adult patients were consented to a receive telephone reminder at their initial booking visit. Those who consented were randomized into either the intervention group that received a reminder in addition to written instructions, or a control group that received written instructions alone. The automated reminder was a 30 second recorded message that reminded patients of the upcoming colonoscopy and emphasized the importance of fluid intake and following the bowel prep instructions. Upon arrival for colonoscopy, subjects were informed of the study, asked for consent to participate in the full study, and completed a questionnaire regarding their fluid consumption and recollection of receiving a telephone reminder. Each colonoscopy was scored by the endoscopist performing the procedure. They were blinded to the group allocation. The primary outcome was the numeric score of bowel preparation quality using the Ottawa bowel preparation scale. 298 patients agreed to receive a telephone reminder, with 260 randomized to intervention and control groups. The randomized consent protocol meant that participants had to consent again prior to colonoscopy. Ultimately, 108 patients were included in the intervention group and 115 in the control group. Analysis of the endoscopist-scored bowel preparation quality showed no significant difference in the primary outcome of mean Ottawa Bowel Preparation Score between the two groups. The reminder group had a score of 5.41 versus a score of 5.81 in the no reminder group (the score is from 0 to 14, where a lower score indicates better prep). This study did not show any significant difference in measured bowel preparation quality between those who had received an automated telephone reminder and those who did not. Despite this, patients subjectively reported satisfaction with the reminder phone call. Figure 1: Study results Ferring Pharmaceuticals

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.001

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 head0.014
GPT teacher head0.312
Teacher spread0.298 · 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 designNon-randomized trial
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
Published2018
Admission routes2
Has abstractyes

Explore more

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