Evidence map›Paper›PMID 32927419›Full record

ReviewJournal of pharmaceutical and biomedical analysis2020

Quantitative microsampling for bioanalytical applications related to the SARS-CoV-2 pandemic: Usefulness, benefits and pitfalls.

Michele Protti, Roberto Mandrioli, Laura Mercolini

Open access · greenAbstract readReview
In one paragraph

Review in Journal of pharmaceutical and biomedical analysis, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.8field-weighted citation impact, top 14% 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

9 citing papers in PubMed, 37 citations in OpenAlex.

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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.

Michele ProttiResearch Group of Pharmaco-Toxicological Analysis (PTA Lab), Department of Pharmacy and Biotechnology (FaBiT), Alma Mater Studiorum - University of Bologna, Via Belmeloro 6, 40126 Bologna, Italy.
Roberto MandrioliDepartment for Life Quality Studies, Alma Mater Studiorum - University of Bologna, Corso d'Augusto 237, 47921 Rimini, Italy.
Laura MercoliniResearch Group of Pharmaco-Toxicological Analysis (PTA Lab), Department of Pharmacy and Biotechnology (FaBiT), Alma Mater Studiorum - University of Bologna, Via Belmeloro 6, 40126 Bologna, Italy. Electronic address: laura.mercolini@unibo.it.
University of Bologna · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The multiple pathological effects of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, and its total novelty, mean that currently a lot of diagnostic and therapeutic tools, established and tentative alike, are needed to treat patients in a timely, effective way. In order to make these tools more reliable, faster and more feasible, biological fluid microsampling techniques could provide many advantages. In this review, the most important microsampling techniques are considered (dried matrix spots, volumetric absorptive microsampling, microfluidics and capillary microsampling, solid phase microextraction) and their respective advantages and disadvantages laid out. Moreover, currently available microsampling applications of interest for SARS-CoV-2 therapy are described, in order to make them as much widely known as possible, hopefully providing useful information to researchers and clinicians alike.

Indexed as

Blood Specimen CollectionChemistry Techniques, AnalyticalCoronavirus InfectionsCOVID-19Dried Blood Spot TestingHumansPandemicsPneumonia, ViralSolid Phase MicroextractionTandem Mass SpectrometryDBSDMSMicrosamplingSARS-CoV-2VAMS

Identifiers

PMID32927419
PMCPMC7456588
OpenAlexW3081183907

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.