Evidence map›Paper›PMID 37762812›Full record

ReviewJournal of clinical medicine2023

A Comparison of Single Dimension and Volume Measurements in the Risk Stratification of Pancreatic Cystic Lesions.

Da Yeon Ryoo, Bryn Koehler, Jennifer Rath, Zarine K Shah, Wei Chen, Ashwini K Esnakula, Phil A Hart, Somashekar G Krishna

Abstract readReview
In one paragraph

Review in Journal of clinical medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Da Yeon RyooDepartment of Internal Medicine, Ohio State University Wexner Medical Center, Columbus, OH 43210, USA.
Bryn KoehlerDepartment of Internal Medicine, Ohio State University Wexner Medical Center, Columbus, OH 43210, USA.
Jennifer RathDepartment of Radiology, Ohio State University Wexner Medical Center, Columbus, OH 43210, USA.
Zarine K ShahDepartment of Radiology, Ohio State University Wexner Medical Center, Columbus, OH 43210, USA.
Wei ChenDepartment of Pathology, Ohio State University Wexner Medical Center, Columbus, OH 43210, USA.
Ashwini K EsnakulaDepartment of Pathology, Ohio State University Wexner Medical Center, Columbus, OH 43210, USA.ORCID 0000-0001-6029-0124
Phil A HartDivision of Gastroenterology, Department of Internal Medicine, Ohio State University Wexner Medical Center, Columbus, OH 43210, USA.
Somashekar G KrishnaDivision of Gastroenterology, Department of Internal Medicine, Ohio State University Wexner Medical Center, Columbus, OH 43210, USA.ORCID 0000-0001-5748-7890

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The incidence of pancreatic cystic lesions (PCLs) has been rising due to improvements in imaging. Of these, intraductal papillary mucinous neoplasms (IPMNs) are the most common and are thought to contribute to almost 20% of pancreatic adenocarcinomas. All major society guidelines for the management of IPMNs use size defined by maximum diameter as the primary determinant of whether surveillance or surgical resection is recommended. However, there is no consensus on how these measurements should be obtained or whether a single imaging modality is superior. Furthermore, the largest diameter may fail to capture the complexity of PCLs, as most are not perfectly spherical. This article reviews current PCL measurement techniques in CT, MRI, and EUS and posits volume as a possible alternative to the largest diameter.

Indexed as

CTEUSIPMNmaximum diameterMRCPMRIpancreatic cancerpancreatic cystic lesionvolume

Identifiers

PMID37762812
PMCPMC10531933

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.