Evidence map›Paper›PMID 39211788›Full record

ArticleAcademic pathology

Asking the PRIME questions for grossing: Teaching a framework for grossing and constructing gross descriptions using the PRIME model.

Christopher C Attaway, Danielle Fortuna

Abstract read
In one paragraph

Article in Academic pathology. 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

2 authors.

Christopher C AttawayDepartment of Pathology and Laboratory Medicine, Hospital of the University of Pennsylvania, Philadelphia, PA, USA.
Danielle FortunaDepartment of Pathology and Laboratory Medicine, Hospital of the University of Pennsylvania, Philadelphia, PA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Grossing is essential to the practice of anatomic pathology. The importance of this skill cannot be understated, but it simultaneously can be enigmatic for novice pathology residents. Successful grossing asks questions to yield the most accurate answers which facilitate a complete report and diagnosis for patient care. To provide a unified framework of approach to grossing specimens, we devised the PRIME (P = process/picture, R = relationships, I = internal, M = margins, E = external) model for grossing. The PRIME model was introduced to anatomic pathology trainees (n = 21) at two academic hospitals through an interactive workshop featuring multiple exercises: (1) scoring provided inadequate gross descriptions of common, familiar objects (fruit) for content quality before and after introduction of the PRIME model, (2) building a gross description as a group with a representative fruit specimen using PRIME, (3) videos of grossing specimens which the participants used to practice constructing their own gross description using PRIME, and (4) analysis of an example surgical specimen's gross description using PRIME. Pre- and post-workshop questionnaires assessed the trainees' experience with grossing before residency, their confidence to write a gross description, and their opinions of the PRIME model. The assessment of fruit gross descriptions before and after the introduction of PRIME was significant (p < 0.05), as well as the participants' confidence level to write an accurate gross description using PRIME. The PRIME model and workshop help to fill a void in pathology education and erode perceived barriers to confident grossing by providing a framework of the key concepts behind grossing specimens, no matter the complexity.

Indexed as

AnatomicEducationGrossingModelPathologyProsectionResidentTrainee

Identifiers

PMID39211788
PMCPMC11357842

What OpenQuestion holds

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Registered trials

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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.