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Record W2922109966 · doi:10.1093/jcag/gwz006.114

A115 SYSTEMATIZATION AND MODERNIZATION OF AN ANTI-SMOKING PROGRAM IN CROHN’S DISEASE

2019· article· en· W2922109966 on OpenAlexaff
Benjamin Cox, Dustin Loomes

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsUniversity of AlbertaUniversity of British Columbia Hospital
Fundersnot available
KeywordsMedicineCrohn's diseaseSmoking cessationDiseaseInternal medicineIntervention (counseling)Physical therapyPathology

Abstract

fetched live from OpenAlex

There is a well-established relationship between smoking and disease activity in Crohn’s. The impact of smoking on Crohn’s disease includes increased risk of relapse, disease complications, need for surgery, hospitalization, and flare severity. Despite clear evidence that smoking has a negative impact on Crohn’s disease, research has shown that patients with Crohn’s disease are often unaware of this fact. Furthermore, studies have demonstrated that gastroenterologists do not frequently discuss the importance of smoking cessation or offer cessation strategies to patients. Studies exploring the effect of smoking cessation in Crohn’s patients have found that cessation results in reduced rates of disease flares and the need for steroids and immunosuppression therapy when compared to active smokers. This highlights the importance of smoking cessation in Crohn’s disease, and that it should be an integral part of the management plan for Crohn’s patients. The aim of this study was to evaluate if a comprehensive standardized process for identifying and targeting patients with Crohn’s disease would change management, starting with improved documentation of smoking status in Crohn’s patients, and further progressing to targeted patient education. A standardized anti-smoking program was implemented into the offices of two gastroenterologists. This process change began at patient intake utilizing a patient questionnaire, non-MD EMR input of smoking status, targeted patient intervention using “Smoking and Crohn’s Disease” information pamphlets, and EMR smart-phrases to rapidly document smoking intervention. After 20 months, a chart review was performed on 50 patients from these two offices as well as 200 charts from the offices of an additional ten local gastroenterologists. The rates of smoking status documentation as well as discussion about smoking cessation were compared. Of the charts reviewed from the offices that implemented the standardized anti-smoking program intervention, 96% had a documented smoking status, compared to 57% of the charts in the non-intervention group (p = < 0.001). In the intervention group, smoking cessation strategies were discussed with 75% of smokers while there was no documented smoking cessation discussion in the non-intervention group (p = 0.077). Having a standardized and comprehensive anti-smoking program and process leads to an increase in documentation rates and discussion about smoking cessation strategies in Crohn’s disease. Table 1. Smoking status documentation Group A: Offices without a standardized process for smoking documentation (N=10). Group B: Offices with a standardized process for smoking documentation (N=2). Table 1. Smoking status documentation Group A: Offices without a standardized process for smoking documentation (N=10). Group B: Offices with a standardized process for smoking documentation (N=2). Image 1. Smoking information for Crohn’s patients. None

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)0.007
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.004
GPT teacher head0.210
Teacher spread0.207 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2019
Admission routes1
Has abstractyes

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