Evidence map›Paper›PMID 34195053›Full record

ArticleTropical parasitology

Molecular diagnosis of infectious parasites in the post-COVID-19 era.

Subhash Chandra Parija, Abhijit Poddar

Open access · hybridAbstract read
In one paragraph

Article in Tropical parasitology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.8field-weighted citation impact, top 18% 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

7 citing papers in PubMed, 13 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

2 authors at 1 institution in 1 country.

Subhash Chandra ParijaVice Chancellor, Sri Balaji Vidyapeeth University, Puducherry, India.
Abhijit PoddarScientist, Sri Balaji Vidyapeeth University, Puducherry, India.
Sri Balaji Vidyapeeth University · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The endemicity of several parasitic diseases across the globe and recent evidence of distress among COVID-19 patients with preexisting parasitic infections requires strengthening One Health framework and advanced strategies for parasitic detection. Owing to the greater sensitivity and accuracy, molecular technologies such as conventional polymerase chain reaction (PCR), reverse transcription (RT)-PCR, nested PCR, loop-mediated isothermal amplification (LAMP), and xMAP technology have been extensively studied for parasitic diagnosis. Varieties of genes have been targeted for primer development where 18S rRNA, internal transcribed spacer regions, and mitochondrial DNAs coding for cytochrome, and other enzymes have been widely used. More recent, low-cost sequencing and advances in big data management have resulted in a slow but steady rise of next-generation sequencing-based approaches for parasite diagnosis. However, except for few parasites of global concerns such as

Indexed as

Molecular diagnosisparasitespost-COVID-19zoonotic disease

Identifiers

PMID34195053
PMCPMC8213111
OpenAlexW3160814841

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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.