This study aims to analyze the risk factors associated with delayed postoperative bleeding (DPPB) following colorectal polyp surgery, develop a dynamic nomogram and evaluate the model efficacy, provide a reference for clinicians to identify the patients at high risk of DPPB. Retrospective study was done on patients who underwent endoscopic colorectal polypectomy at the First Hospital of Lanzhou University from January 2020 to March 2023. Differences between the group with and without DPPB were compared, and independent risk factors for DPPB occurrence were identified through univariate analysis and combination LASSO and logistic regression. A dynamic nomogram was constructed based on multiple logistic regression to predict DPPB following colorectal polyp surgery. Model evaluation included receiver operating characteristic (ROC), Calibration curve, Decision curve analysis (DCA). DPPB occurred in 38 of the 1544 patients included. multivariate analysis showed that direct oral anticoagulants (DOACs), polyp location in the right hemi colon, polyp diameter, drink, and prophylactic hemoclips were the independent risk factors for DPPB and dynamic nomogram were established. Model validation indicated area under the ROC curve values of 0.936, 0.796, and 0.865 for the training set, validation set, and full set, respectively. The calibration curve demonstrated a strong alignment between the predictions of the column-line diagram model and actual observations. The decision curve analysis (DCA) displayed a significant net clinical benefit across the threshold probability range of 0-100%. The dynamic nomogram aids clinicians in identifying high-risk patients, enabling personalized diagnosis and treatment.
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http://dx.doi.org/10.1038/s41598-024-70635-9 | DOI Listing |
J Magn Reson Imaging
February 2025
Department of Radiology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, China.
Backgrounds: Anti-vascular endothelial growth factor (VEGF) therapy has been developed and recognized as an effective treatment for hepatocellular carcinoma (HCC). However, there remains a lack of noninvasive methods in precisely evaluating VEGF expression in HCC.
Purpose: To establish a visual noninvasive model based on clinical indicators and MRI features to evaluate VEGF expression in HCC.
Chin Med
January 2025
School of Pharmacy, Hangzhou Normal University, Hangzhou, China.
Background: The individualized prediction and discrimination of precancerous lesions of gastric cancer (PLGC) is critical for the early prevention of gastric cancer (GC). However, accurate non-invasive methods for distinguishing between PLGC and GC are currently lacking. This study therefore aimed to develop a risk prediction model by machine learning and deep learning techniques to aid the early diagnosis of GC.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Gastrointestinal Surgical Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, China.
The aim of this study was to explore the high-risk factors for recurrence in patients with locally advanced esophageal squamous cell carcinoma (ESCC) undergoing definitive chemoradiotherapy or radiotherapy (dCRT or dRT). Conditional survival (CS) was used to evaluate the dynamic survival and recurrence risk of patients after treatment, and individualized monitoring strategies were developed for patients. Logistic regression analysis was performed to determine independent recurrence risk factors.
View Article and Find Full Text PDFFront Oncol
December 2024
Department of Radiology, Shenzhen People's Hospital, The Second Clinical Medical College of Jinan University, Shenzhen, China.
Objective: This study aimed to develop a nomogram that combines intratumoral and peritumoral radiomics based on multi-parametric MRI for predicting the postoperative pathological upgrade of high-risk breast lesions and sparing unnecessary surgeries.
Methods: In this retrospective study, 138 patients with high-risk breast lesions (January 1, 2019, to January 1, 2023) were randomly divided into a training set (n=96) and a validation set (n=42) at a 7:3 ratio. The best-performing MRI sequence for intratumoral radiomics was selected to develop individual and combined radiomics scores (Rad-Scores).
Front Oncol
December 2024
Department of Neurosurgery, West China Hospital/West China School of Medicine, Sichuan University, Chengdu, Sichuan, China.
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