Background: Post-ERCP pancreatitis (PEP) with trans-papillary approach remains a major issue, and the multi-factorial etiology can lead to the development of unpredictable PEP. Therefore, the early identification of PEP is highly desirable to assist with the health cost containment, the reduction in unnecessary admissions, earlier appropriate primary care, and intensive care for preventing progression of severe pancreatitis. This study aimed to establish a simplified predictive scoring system for PEP.
Methods: Between January 1, 2012, and December 31, 2019, 3362 consecutive trans-papillary ERCP procedures were retrospectively analyzed. Significant risk factors were extracted by univariate, multivariate, and propensity score analyses, and the probability of PEP in the combinations of each factor were quantified using propensity score analysis. The results were internally validated using bootstrapping resampling.
Results: In the scoring system with four stratifications using combinations of only five extracted risk factors, the very high-risk group showed 28.79% (95% confidence interval [CI], 18.30%-41.25%; P < 0.001) in the predicted incidence rate of PEP, and 9.09% (95% CI, 3.41%-18.74%; P < 0.001) in that of severe PEP; although the adjusted prevalence revealed 3.74% in PEP and 0.90% in severe PEP, respectively. The prediction model had an area under the curve of 0.86 (95% CI, 0.82-0.89) and the optimism-corrected model as an internal validation had an area under the curve of 0.81 (95% CI, 0.77-0.86).
Conclusions: We established and validated a simplified predictive scoring system for PEP using five risk factors immediately after ERCP to assist with the early identification of PEP.
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http://dx.doi.org/10.1007/s00464-020-08173-4 | DOI Listing |
Orphanet J Rare Dis
January 2025
Department of Human Genetics, Emory University, Atlanta, GA, USA.
Background: Late-onset Pompe disease (LOPD) is an autosomal recessive lysosomal storage disorder that results in severe progressive proximal muscle weakness. Over time, reductions in muscle strength result in respiratory failure and a loss of ambulation. Delayed diagnosis of LOPD deprives patients of treatments that can enhance quality of life and potentially slow disease progression.
View Article and Find Full Text PDFBMC Med Educ
January 2025
Department of Surgery, Saint-Louis Regional Hospital, Gaston Berger University, Road of Ngallelle, 234, Saint-Louis, Senegal.
Introduction: Video feedback, particularly with a head-mounted camera, has previously been described as a useful debriefing tool in well-funded health systems but has never been performed in a low-resource environment. The purpose of this randomized, intervention-controlled study is to evaluate the feasibility of using video feedback with a head-mounted camera during intestinal anastomosis simulation training in a low-resource setting.
Methodology: This study recruited 14 first-year surgery residents in Senegal, who were randomized into control and camera groups.
BMC Oral Health
January 2025
Pediatric Dentistry Department, Faculty of Dentistry, Başkent University, 06490, Ankara, Turkey.
Background: Hypodontia is the absence of one or more teeth in the primary or permanent dentition during development, and radiographic imaging is the most common method of diagnosis. However, in recent years, artificial intelligence-based decision support systems have been employed to make highly accurate diagnoses. The aim of this study was to classify single premolar agenesis, multiple premolar agenesis, and without tooth agenesis using various artificial intelligence approaches.
View Article and Find Full Text PDFBMC Genom Data
January 2025
Department of Management Information Systems, National Chung Hsing University, Taichung, 402, Taiwan.
Background: miRNAs (microRNAs) are endogenous RNAs with lengths of 18 to 24 nucleotides and play critical roles in gene regulation and disease progression. Although traditional wet-lab experiments provide direct evidence for miRNA-disease associations, they are often time-consuming and complicated to analyze by current bioinformatics tools. In recent years, machine learning (ML) and deep learning (DL) techniques are powerful tools to analyze large-scale biological data.
View Article and Find Full Text PDFEur Spine J
January 2025
Department of Orthopaedic Surgery, Medical College of Wisconsin, Milwaukee, USA.
Purpose: No studies have explored the reliability of the Rigo classification system using surface topography (ST), which would allow optimization without radiation exposure. This study aims to measure and compare the intra- and inter-observer reliability (Kappa values) and accuracy of the Rigo system between ST and X-ray for overall types and subtypes.
Methods: X-ray and ST images of 31 adolescent idiopathic scoliosis patients were selected.
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