Evidence map›Paper›PMID 29607083›Full record

ArticleBDJ open2017

Emerging paradigm of virtual-microscopy for histopathology diagnosis: survey of US and Canadian oral pathology trainees.

Ngozi N Nwizu, Adepitan Owosho, Kalu U E Ogbureke

Open access · goldAbstract read
In one paragraph

Article in BDJ open, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.4field-weighted citation impact, top 28% of its field
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

2 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. 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

3 authors at 1 institution in 1 country.

Ngozi N NwizuDepartment of Diagnostic and Biomedical Sciences, The University of Texas School of Dentistry at Houston, Houston, TX, USA.
Adepitan OwoshoDepartment of Surgery, Dental Services, Memorial Sloan-Kettering Cancer Center, New York, USA.
Kalu U E OgburekeDepartment of Diagnostic and Biomedical Sciences, The University of Texas School of Dentistry at Houston, Houston, TX, USA.
Memorial Sloan Kettering Cancer Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

OBJECTIVES/

aimsThe application of virtual microscopy (VM) to research, pre-doctoral medical and dental educational training, and diagnostic surgical and anatomic pathology is well-documented but its application to the field of oral and maxillofacial pathology has not been explored. This is the first study to evaluate the enthusiasm and readiness of US-/Canada-based oral and maxillofacial pathology (OMFP) residents toward employing VM use over conventional microscopy (CM) for diagnostic purposes. MATERIALS AND

methodsAll 46 current US-/Canada-based OMFP residents were invited to participate in an anonymous electronic survey via 'Survey Monkey' in 2015. The survey comprised sixteen multiple choice questions and two 'free text' questions.

results14% of respondents of the 22 (48%) respondents who completed the survey indicated a willingness to substitute CM with VM in <5 years, and 33% within 10 years. 52% reported they would never substitute CM with VM. Approximately 10 and 57% of respondents thought VM will become an acceptable sole diagnostic tool in most centers within 5 and 10 years, respectively. These findings are irrespective of the fact that overall, 90% of respondents reported being familiar with VM use. DISCUSSION: VM technology is unlikely to substitute CM in diagnostic oral and maxillofacial histopathology practice among future OMFP practitioners in the foreseeable future.

Identifiers

PMID29607083
PMCPMC5842823
OpenAlexW2740871063

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.