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Record W2057479332 · doi:10.1155/2015/628049

The Effectiveness of Short Message Service to Assure the Preparation-to-Colonoscopy Interval before Bowel Preparation for Colonoscopy

2015· article· en· W2057479332 on OpenAlexaboutno aff
Jongha Park, Nae-Young Lee, Hyoung-Jun Kim, Eun Hee Seo, Nae‐Yun Heo, Young-Soo Moon

Bibliographic record

VenueGastroenterology Research and Practice · 2015
Typearticle
Languageen
FieldMedicine
TopicColorectal Cancer Screening and Detection
Canadian institutionsnot available
FundersInje University
KeywordsMedicineBowel preparationColonoscopyInterval (graph theory)CatharticGeneral surgeryGastroenterologyInternal medicineColorectal cancer

Abstract

fetched live from OpenAlex

Background/Aims. The preparation-to-colonoscopy (PC) interval is one of several important factors for the bowel preparation. Short message service (SMS) reminder from a cellular phone has been suggested to improve compliance in various medical situations. We evaluated the effectiveness of SMS reminders to assure the PC interval for colonoscopy. Methodology. This prospective randomized study was investigator blinded. In the No-SMS group, patients took the first 2 L polyethylene glycol (PEG) between 6 and 8 PM on the day before colonoscopy and the second 2 L PEG approximately 6 hours before the colonoscopy without SMS. In the SMS group, patients took first 2 L PEG in the same manner as the No-SMS group and the second 2 L PEG after receiving an SMS 6 hours before the colonoscopy. Results. The SMS group had a lower score than the No-SMS group, according to the Ottawa Bowel Preparation Scale (P < 0.001). Multivariate logistic regression analysis showed that compliance with diet instructions (odds ratio (OR) 2.109; 95% confidence interval (CI), 1.11-3.99, P = 0.022) and intervention using SMS ((OR) 2.329; 95% (CI), 1.34-4.02, P = 0.002) were the independent significant factors for satisfactory bowel preparation. Conclusions. An SMS reminder to assure PC interval improved the bowel preparation quality for colonoscopy with bowel preparation.

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)0.009
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.959
Threshold uncertainty score0.624

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.005
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 head0.065
GPT teacher head0.438
Teacher spread0.372 · 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 designRandomized 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

Citations43
Published2015
Admission routes1
Has abstractyes

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