Evidence map›Paper›PMID 37138045›Full record

ArticleScientific reports2023

Underscoring the effect of swab type, workflow, and positive sample order on swab pooling for COVID-19 surveillance testing.

Maxwell J Kalinowski, Devon R Hartigan, Neal M Lojek, Bryan O Buchholz, Chiara E Ghezzi

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 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
0.4field-weighted citation impact, top 42% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  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

5 authors at 1 institution in 1 country.

Maxwell J Kalinowski *Department of Biomedical Engineering, University of Massachusetts-Lowell, 1 University Avenue, Lowell, MA, 01854, USA.
Devon R Hartigan *Department of Biomedical Engineering, University of Massachusetts-Lowell, 1 University Avenue, Lowell, MA, 01854, USA.
Neal M LojekDepartment of Biomedical Engineering, University of Massachusetts-Lowell, 1 University Avenue, Lowell, MA, 01854, USA.
Bryan O BuchholzDepartment of Biomedical Engineering, University of Massachusetts-Lowell, 1 University Avenue, Lowell, MA, 01854, USA.
Chiara E GhezziDepartment of Biomedical Engineering, University of Massachusetts-Lowell, 1 University Avenue, Lowell, MA, 01854, USA. Chiara_ghezzi@uml.edu.
University of Massachusetts Lowell · US

Funding

The Center for Advancing Point of Care in Heart, Lung, Blood and Sleep DiseasesU54HL143541 · NHLBI · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI BRYAN O BUCHHOLZ, Nathaniel Scott Hafer · 2018 to 2026
$141.0M
NHLBI NIH HHS U54 HL143541
6 · The paper itself

Abstract

Sample pooling is a promising strategy to facilitate COVID-19 surveillance testing for a larger population in comparison to individual single testing due to resource and time constraints. Increased surveillance testing capacity will reduce the likelihood of outbreaks as the general population is returning to work, school, and other gatherings. We have analyzed the impact of three variables on the effectiveness of pooling test samples: swab type, workflow, and positive sample order. We investigated the performance of several commercially available swabs (Steripack polyester flocked, Puritan nylon flocked, Puritan foam) in comparison to a new injected molded design (Yukon). The bench-top performance of collection swab was conducted with a previously developed anterior nasal cavity tissue model, based on a silk-glycerol sponge to mimic soft tissue mechanics and saturated with a physiologically relevant synthetic nasal fluid spiked with heat-inactivated SARS-CoV-2. Overall, we demonstrated statistically significant differences in performance across the different swab types. A characterization of individual swab uptake (gravimetric analysis) and FITC microparticle release suggests that differences in absorbance and retention drive the observed differences in Ct of the pooled samples. We also proposed two distinct pooling workflows to encompass different community collection modes and analyzed the difference in resulting positive pools as an effect of workflow, swab type, and positive sample order. Overall, swab types with lower volume retention resulted in reduced false negative occurrence, also observed for collection workflows with limited incubation times. Concurrently, positive sample order did have a significant impact on pooling test outcome, particularly in the case of swab type with great volume retention. We demonstrated that the variables investigated here affect the results of pooled COVID-19 testing, and therefore should be considered while designing pooled surveillance testing.

Indexed as

COVID-19COVID-19 TestingHumansSARS-CoV-2Specimen HandlingWorkflow

Identifiers

PMID37138045
PMCPMC10155136
OpenAlexW4367843724

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.