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Record W3023509685 · doi:10.2196/17372

Enhanced Patient Education for Colonic Polyp and Adenoma Detection: Meta-Analysis of Randomized Controlled Trials

2020· review· en· W3023509685 on OpenAlexvenueno aff
Xu Tian, Ling-Li Xu, Xiaoling Liu, Weiqing Chen

Bibliographic record

VenueJMIR mhealth and uhealth · 2020
Typereview
Languageen
FieldMedicine
TopicColorectal Cancer Screening and Detection
Canadian institutionsnot available
Fundersnot available
KeywordsColonoscopyMedicineAdenomaRandomized controlled trialInternal medicineColorectal cancerHyperplastic PolypWithdrawal timeGastroenterologyCancer

Abstract

fetched live from OpenAlex

Background To improve patients’ comprehension of bowel preparation instructions before colonoscopy, enhanced patient education (EPE) such as cartoon pictures or other visual aids, phone calls, mobile apps, multimedia education and social media apps have been proposed. However, it is uncertain whether EPE can increase the detection rate of colonic polyps and adenomas. Objective This meta-analysis aimed to evaluate the efficacy of EPE in detecting colonic polyps and adenomas. Methods We searched PubMed, EMBASE, and Cochrane Central Register of Controlled Trials from their inception to June 2019 for the identification of trials comparing the EPE with standard patient education for outpatients undergoing colonoscopy. We used a random effects model to calculate summary estimates of the polyp detection rate (defined as the number of patients with at least one polyp divided by the total number of patients undergoing selective colonoscopy), adenoma detection rate (defined as the number of patients with at least one adenoma divided by the total number of patients undergoing selective colonoscopy), advanced adenoma detection rate (defined as the number of patients with at least one advanced adenoma divided by the total number of patients undergoing selective colonoscopy), sessile serrated adenoma detection rate (defined as the number of patients with at least one sessile serrated adenoma divided by the total number of patients undergoing selective colonoscopy), cancer detection rate (defined as the number of patients with at least one cancer divided by the total number of patients undergoing selective colonoscopy), or adenoma detection rate - plus (defined as the number of additional adenomas found after the first adenoma per colonoscopy). Moreover, we conducted trial sequential analysis (TSA) to determine the robustness of summary estimates of all primary outcomes. Results We included 10 randomized controlled trials enrolling 4560 participants for analysis. The meta-analysis suggested that EPE was associated with an increased polyp detection rate (9 trials; 3781 participants; risk ratio [RR] 1.19, 95% CI 1.05-1.35; P<.05; I2=42%) and adenoma detection rate (5 trials; 2133 participants; RR 1.37, 95% CI 1.15-1.64; P<.001; I2=0%), which were established by TSA. Pooled result from the inverse-variance model illustrated an increase in the sessile serrated adenoma detection rate (3 trials; 1248 participants; odds ratio 1.76, 95% CI 1.22-2.53; P<.05; I2=0%). One trial suggested an increase in the adenoma detection rate - plus (RR 4.39, 95% CI 2.91-6.61; P<.001). Pooled estimates from 3 (1649 participants) and 2 trials (1375 participants) generated no evidence of statistical difference for the advanced adenoma detection rate and cancer detection rate, respectively. Conclusions The current evidence indicates that EPE should be recommended to instruct bowel preparation in patients undergoing colonoscopy because it can increase the polyp detection rate, adenoma detection rate, and sessile serrated adenoma detection rate. However, further trials are warranted to determine the efficacy of EPE for advanced adenoma detection rate, adenoma detection rate - plus, and cancer detection rate because of limited data.

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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Meta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.805
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0260.005
Bibliometrics0.0010.001
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 head0.153
GPT teacher head0.459
Teacher spread0.306 · 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.

Study designMeta-analysis
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

Citations17
Published2020
Admission routes1
Has abstractyes

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