Evidence map›Paper›PMID 31574959›Full record

ReviewBiosensors2019

Advances in Directly Amplifying Nucleic Acids from Complex Samples.

Faye M Walker, Kuangwen Hsieh

Abstract readReview
In one paragraph

Review in Biosensors, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed, 1 pooled it
–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

30 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. The diagnostic accuracy of seven commercial molecularExpert review of molecular diagnostics · 2021
    Pooled it
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  14. Mimicking anbioRxiv : the preprint server for biology · 2024
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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

2 authors.

Faye M WalkerRaytheon Company, Waltham, MA 02451, USA. faye.m.walker@raytheon.com.
Kuangwen HsiehDepartment of Mechanical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA. khsieh4@jhu.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Advances in nucleic acid amplification technologies have revolutionized diagnostics for systemic, inherited, and infectious diseases. Current assays and platforms, however, often require lengthy experimental procedures and multiple instruments to remove contaminants and inhibitors from clinically-relevant, complex samples. This requirement of sample preparation has been a bottleneck for using nucleic acid amplification tests (NAATs) at the point of care (POC), though advances in "lab-on-chip" platforms that integrate sample preparation and NAATs have made great strides in this space. Alternatively, direct NAATs-techniques that minimize or even bypass sample preparation-present promising strategies for developing POC diagnostic tools for analyzing real-world samples. In this review, we discuss the current status of direct NAATs. Specifically, we surveyed potential testing systems published from 1989 to 2017, and analyzed their performances in terms of robustness, sensitivity, clinical relevance, and suitability for POC diagnostics. We introduce bubble plots to facilitate our analysis, as bubble plots enable effective visualization of the performances of these direct NAATs. Through our review, we hope to initiate an in-depth examination of direct NAATs and their potential for realizing POC diagnostics, and ultimately transformative technologies that can further enhance healthcare.

Indexed as

Biosensing TechniquesMolecular Diagnostic TechniquesNucleic Acid Amplification TechniquesBlood Chemical AnalysisFecesPoint-of-Care SystemsSalivaSputumUrinalysisbubble plotdisease diagnosticsnucleic acid testingsample preparation

Identifiers

PMID31574959
PMCPMC6955841

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.