A65 ENDOSCOPIST-TARGETED INTERVENTIONS TO OPTIMIZE ADENOMA DETECTION RATE - A SYSTEMATIC REVIEW AND META-ANALYSIS
Notice bibliographique
Résumé
Abstract Background Adenoma detection rate (ADR) has emerged as the strongest quality assurance metric that has consistently been shown to be inversely associated with the development of colorectal cancer after colonoscopy. Unfortunately, marked variability in ADR exists among endoscopists. A multitude of interventions targeted at endoscopists to optimize their ADR have been reported, including but not limited to withdrawal time, in room observers, physician report cards, and quality improvement and training programs. However, it is unclear which of them are truly effective. Aims We performed a systematic review and meta-analysis of the literature to evaluate the effectiveness of endoscopist-targeted interventions to improve adenoma detection rate (ADR) or polyp detection rate (PDR). Methods Systematic searches of major databases were conducted through to March 2018 to identify potentially relevant studies. Both randomized controlled trials and observational studies were included. Data for ADR and PDR were analyzed on the log-odds scale using a random-effects meta-analysis model using restricted maximum likelihood (with Mantel-Haenszel fixed-effect meta-analysis used for fewer than 4 studies). Statistical effect-size heterogeneity was assessed using a Chi2 test and quantifying the relative proportion of variation using the I2 statistic. Publication bias was assessed by the Harbord regression test. Results From 4299 initial studies, 24 were included in the systematic review and 13 were included in the meta-analysis representing a total of 55,090 colonoscopies. Physician report card interventions (7 studies) and withdrawal time focused interventions (6 studies) were meta-analyzed. The pooled odds ratio for ADR for report card interventions was 1.31 (95% CI: 1.15, 1.50; p<0.0001), favoring report cards to detect more adenomas. Statistical heterogeneity was detected with substantial relative effect-size variability (Chi2, p<0.0001; I2=80.1%). No statistical evidence of publication bias was found. 6 studies reported data for PDR using withdrawal time focused interventions, with 3 of these reporting data on ADR. The pooled odds ratio for ADR was 1.02 (95% CI: 0.86, 1.22; p=0.81) and for PDR was 1.07 (95% CI: 0.88, 1.31; p=0.51) which were not statistically significant. Statistical heterogeneity was detected in both groups (Chi2, p<0.001; I2=82.2% for ADR and I2=89.4% for PDR) and there was statistical evidence of publication bias. Figures 1 and 2 represent Forest plots for the effect of pre-and post-report card and withdrawal time focused interventions on ADR. Conclusions Our study provides evidence that the distribution of colonoscopy quality report cards to physicians significantly improves overall ADR and should strongly be considered as part of quality improvement programs aimed at optimizing colonoscopy performance. Funding Agencies None
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,015 | 0,038 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,002 |
| Méta-épidémiologie (sens large) | 0,019 | 0,043 |
| Bibliométrie | 0,009 | 0,007 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,004 | 0,003 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,003 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».