Evidence map›Paper›PMID 32634229›Full record

ReviewLaboratory medicine2020

Laboratory Assay Evaluation Demystified: A Review of Key Factors Influencing Interpretation of Test Results Using Different Assays for SARS-CoV-2 Infection Diagnosis.

Huy P Pham, Elizabeth M Staley, Dheeraj Raju, Maximo J Marin, Chong H Kim

Abstract readReview
In one paragraph

Review in Laboratory medicine, 2020. 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. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Huy P PhamDepartment of Pathology, University of Southern California, Los Angeles.
Elizabeth M StaleyDepartment of Laboratory Medicine, University of Washington, Seattle.
Dheeraj RajuCancer Treatment Centers of America, Boca Raton, Florida.
Maximo J MarinDepartment of Pathology, University of Southern California, Los Angeles.
Chong H KimDepartment of Clinical Pharmacy, University of Colorado Anschutz Medical Campus, Aurora.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Laboratory tests are an integral part of the diagnosis and management of patients; however, these tests are far from perfect. Their imperfections can be due to patient health condition, specimen collection, and/or technological difficulty with performing the assay and/or interpretation. To be useful clinically, testing requires calculation of positive predictive values (PPVs) and negative predictive values (NPVs). During the current global pandemic of COVID-19 (coronavirus disease 2019), multiple assays with unknown clinical sensitivity and specificity have been rapidly developed to aid in the diagnosis of the disease. Due to a lack of surveillance testing, the prevalence of COVID-19 remains unknown. Hence, using this situation as an clinical example, the goal of this article is to clarify the key factors that influence the PPV and NPV yielded by diagnostic testing, By doing so, we hope to offer health-care providers information that will help them better understand the potential implications of utilizing these test results in clinical patient management.

Indexed as

Coronavirus InfectionsCOVID-19Data Interpretation, StatisticalDiagnostic ErrorsHumansMolecular Diagnostic TechniquesPandemicsPneumonia, ViralSensitivity and Specificityclinical interpretationnegative predictive valuepositive predictive valuesensitivityspecificitytest parameters

Identifiers

PMID32634229
PMCPMC7454829

What OpenQuestion holds

Textmetadata
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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.