ArticleThe Turkish journal of gastroenterology : the official journal of Turkish Society of Gastroenterology2021
Nomogram for the Prediction of Delayed Colorectal Post-Polypectomy Bleeding.
Article in The Turkish journal of gastroenterology : the official journal of Turkish Society of Gastroenterology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06220149 (FIT for Post poLypectomy bLeeding Prediction), which is not on this map. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
FIT for Post poLypectomy bLeeding Prediction
Who cites it
4 citing papers in PubMed.
- Impact of Dialysis Method on Colon Postpolypectomy Bleeding in Patients with End-stage Renal Disease.The Turkish journal of gastroenterology : the official journal of Turkish Society of Gastroenterology · 2024Article
- Development and validation of a nomogram to predict the risk factors of major complications after radical rectal cancer surgery.Frontiers in oncology · 2024Article
- Phase angle is a predictor for postoperative complications in colorectal cancer.Frontiers in nutrition · 2024Article
- Development and Validation of a Nomogram for Predicting the Severity of Coronary Artery Disease Based on Cardiopulmonary Exercise Testing.Clinical and applied thrombosis/hemostasis : official journal of the International Academy of Clinical and Applied Thrombosis/HemostasisArticle
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Authors and funding
3 authors.
Funding
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Abstract
backgroundDelayed colorectal post-polypectomy bleeding (PPB) is a fairly common complication after polypectomy. The present study aimed to build a novel nomogram-based model of delayed PPB.
methodsA cohort of 2494 patients who had undergone colonoscopic polypectomy between January 2016 and April 2020 were consecutively enrolled. The patient demographics, polyp characteristics, laboratory factors, and pathological parameters were collected. The least absolute shrinkage and selection operator (LASSO) regression was applied for selecting potential variables. Multivariate logistic regression was used to develop the nomogram. A bootstrapping method was employed for internal validation. The performance of the nomogram was evaluated on the basis of its calibration, discrimination, and clinical usefulness.
resultsOf 2494 patients undergoing colonoscopic polypectomy, 40 (1.6%) developed delayed PPB. The LASSO regression identified 6 variables (age, gender, polyp location, polyp morphology, antithrombotic medication use, and modality of polypectomy), and a predictive model was subsequently established. The area under the curve (AUC) of the predictive model and the internal validation were 0.838 (95% CI: 0.775-0.900) and 0.824 (95% CI: 0.759-0.889), respectively. The predictive model provided acceptable calibration, and a decision curve analysis (DCA) showed its clinical utility.
conclusionThis predictive model may enable clinicians to predict the risk of delayed PPB and optimize preoperative decision-making, for effective treatment.
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