Evidence map›Paper›PMID 34548250›Full record

ArticleJournal of the American Society of Cytopathology

Financial and educational impact of the COVID-19 pandemic in an academic hospital-based tertiary cytopathology practice.

Kanish Mirchia, Kamal Khurana

Abstract read
In one paragraph

Article in Journal of the American Society of Cytopathology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Kanish MirchiaDepartment of Pathology, State University of New York, Upstate Medical University, Syracuse, New York.
Kamal KhuranaDepartment of Pathology, State University of New York, Upstate Medical University, Syracuse, New York. Electronic address: KhuranaK@upstate.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe ongoing COVID-19 pandemic has led to a dramatic shift in volumes and practice patterns for hospitals around the globe. We analyzed its effect on the cytopathology subspecialty practice and resident education at our institution.

designSpecimen volumes were analyzed for the cytology practice for 2019 and 2020. Patient registration and elective and scheduled surgery volumes were also included in the analysis for 2020. The impact of innovative concepts, such as virtual teaching, on resident teaching was evaluated using a survey consisting of 5 multiple choice questions with 4 possible responses each.

resultsThe total number of specimens decreased by 28% in March 2020 (P < 0.00001), with a continuing decline in April (66% decrease year-over-year, P < 0.00001), followed by recovery in May and return to baseline within June 2020. Specimen volumes continued to show an upward trend thereafter. Improved specimen volumes correlated with patient registration and surgical volumes. The majority of residents considered virtual teaching conferences (75%) and self-study sets (58%) as beneficial and did not view absence of one-on-one microscope learning (58%) as significantly affecting their education.

conclusionThe recovery curve for our cytopathology service was V-shaped, essentially the most ideal response to an economic downturn. The majority of residents viewed virtual teaching conferences and self-study sets favorably and did not regard absence of one-on-one microscope learning as adversely affecting their education.

Indexed as

COVID-19CytodiagnosisEducation, Medical, GraduateHumansInternship and ResidencyPathologySARS-CoV-2AcademicCoronavirusCovid-19CytologyEconomic recoveryEducational

Identifiers

PMID34548250
PMCPMC8410219

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.