ArticleJournal of radiological science
Pancreatic Cyst Management: A Multimodal and Interdisciplinary Approach.
Article in Journal of radiological science. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
With improvements in advanced cross-sectional imaging, there has been an increase in the detection of incidental pancreatic cystic lesions (PCLs). Mucinous PCLs are known precursors of pancreatic cancer, underscoring the need for early detection and appropriate management. When a PCL is initially diagnosed, the next step is to decide among three key management strategies: surgery, surveillance, or reassurance and discharge without follow-up. However, current management guidelines exhibit inconsistencies and limitations, contributing to overtreatment and increased surveillance of PCLs. This review explores the current landscape of PCL management, highlighting the roles of advanced imaging, cyst fluid biomarkers, and developments in artificial intelligence (AI) and radiomics in refining cyst classification, malignancy prediction, and clinical decision-making. Given the heterogeneity of PCLs, we advocate for a multidisciplinary approach that includes diverse clinical expertise and explainable AI model outputs to facilitate accurate risk stratification and individualized patient management.
Indexed as
Identifiers
42787534PMC13602157What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.