Evidence map›Paper›PMID 37711038›Full record

ArticlePathologica2023

Diagnostic concordance between traditional and digital workflows. A study on 1427 prostate biopsies.

Evelin Torresani, Maria Adalgisa Gentilini, Stefano Grassi, Luca Cima, Irene Pedrolli, Tommaso Cai, Marco Puglisi, Valentino Vattovani, Bianca Guadin, Matteo Brunelli and 2 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Pathologica, 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

12 authors.

Evelin TorresaniUnit of Surgical Pathology, Santa Chiara Hospital, APSS, Trento, Italy.
Maria Adalgisa GentiliniEpidemiology and Clinical Evaluation Unit, APSS, Trento, Italy.
Stefano GrassiDepartment Pathology, Vita e salute University, San Raffaele Hospital, Milano, Italy.
Luca CimaUnit of Surgical Pathology, Santa Chiara Hospital, APSS, Trento, Italy.
Irene PedrolliUnit of Surgical Pathology, Santa Chiara Hospital, APSS, Trento, Italy.
Tommaso CaiUnit of Urology, Santa Chiara Hospital, APSS, Trento, Italy.
Marco PuglisiUnit of Urology, Santa Chiara Hospital, APSS, Trento, Italy.
Valentino VattovaniUnit of Urology, Santa Chiara Hospital, APSS, Trento, Italy.
Bianca GuadinExperimental and Applied Biology, University of Pavia, Italy.
Matteo BrunelliPathology Unit, Department of Diagnostics and Public Health, University and Hospital Trust of Verona, Verona, Italy.
Claudio DoglioniDepartment Pathology, Vita e salute University, San Raffaele Hospital, Milano, Italy.
Mattia BarbareschiUnit of Surgical Pathology, Santa Chiara Hospital, APSS, Trento, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To evaluate intra-observer diagnostic reproducibility using traditional slides (TS) versus whole slide images (WSI). Methods: TS and WSI of 1427 prostatic biopsies (107 consecutive patients) were evaluated by a single pathologist. Agreement between readings was evaluated with Gwet's Agreement coefficient (AC) and Landis and Koch benchmark scale. Results: The positive/negative agreement between the readings was almost perfect (AC Conclusions: Our data show almost perfect agreement between digital and traditional diagnostic activity in a routine setting, confirming that digital pathology can be safely introduced into routine workflows.

Indexed as

PathologistsProstateBiopsyHumansMaleReproducibility of ResultsWorkflowdigital pathologyhistopathologyhumanprostateprostatic neoplasms

Identifiers

PMID37711038
PMCPMC10688250

What OpenQuestion holds

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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.