Evidence map›Paper›PMID 33501458›Full record

ArticlemedRxiv : the preprint server for health sciences2021

Meta-Analysis of Robustness of COVID-19 Diagnostic Kits During Early Pandemic.

Chandrakumar Shanmugam, Michael Behring, Vishwas Luthra, Sixto M Leal, Sameer Al Diffalha, Sooryanarayana Varambally, George J Netto, Upender Manne

Open access · greenAbstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2021. 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, 1 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors at 3 institutions in 2 countries.

Chandrakumar ShanmugamORCID 0000-0002-4782-4512
Sameer Al Diffalha
Sooryanarayana VaramballyORCID 0000-0002-2277-1127
University of Alabama at Birmingham · USDr. NTR University of Health Sciences · INInstitute of Medical Sciences · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAccurate detection of severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) is necessary to mitigate the coronavirus disease-19 (COVID-19) pandemic. However, the test reagents and assay platforms are varied and may not be sufficiently robust to diagnose COVID-19.

methodsWe reviewed 85 studies (21,530 patients), published from five regions of the world, to highlight issues involved in the diagnosis of COVID-19 in the early phase of the pandemic, following the standards outlined in the PRISMA statement. All relevant articles, published up to May 31, 2020, in PubMed, BioRiXv, MedRiXv, and Google Scholar, were included. We evaluated the qualitative (9749 patients) and quantitative (10,355 patients) performance of RT-PCR and serologic diagnostic tests for real-world samples, and assessed the concordance (5,538 patients) between methods in meta-analyses.

resultsThe RT-PCR tests exhibited heterogeneity in the primers and reagents used. Of 1,957 positive RT-PCR COVID-19 participants, 1,585 had positive serum antibody (IgM +/- IgG) tests (sensitivity 0.81, 95%CI 0.66-.90). While 3,509 of 3581 participants RT-PCR negative for COVID-19 were found negative by serology testing (specificity 0.98, 95%CI 0.94-0.99). The chemiluminescent immunoassay exhibited the highest sensitivity, followed by ELISA and lateral flow immunoassays. Serology tests had higher sensitivity and specificity for laboratory-approval than for real-world reporting data.

conclusionsThe robustness of the assays/platforms is influenced by variability in sampling and reagents. Serological testing complements and may minimize false negative RT-PCR results. Lack of standardized assay protocols in the early phase of pandemic might have contributed to the spread of COVID-19.

Identifiers

PMID33501458
PMCPMC7836130
OpenAlexW3123950505

What OpenQuestion holds

Textmetadata
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.