Evidence map›Paper›PMID 37744098›Full record

ArticleFrontiers in fungal biology2021

Development of a Sensitive and Specific Novel qPCR Assay for Simultaneous Detection and Differentiation of Mucormycosis and Aspergillosis by Melting Curve Analysis.

Mragnayani Pandey, Immaculata Xess, Janya Sachdev, Usha Yadav, Gagandeep Singh, Dibyabhaba Pradhan, Ashit Bhushan Xess, Bhaskar Rana, Lalit Dar, Sameer Bakhshi and 7 more

Abstract read
In one paragraph

Article in Frontiers in fungal biology, 2021. 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
–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

7 citing papers in PubMed.

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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

17 authors.

Mragnayani PandeyDepartment of Microbiology, All India Institute of Medical Sciences, New Delhi, India.
Immaculata XessDepartment of Microbiology, All India Institute of Medical Sciences, New Delhi, India.
Janya SachdevDepartment of Microbiology, All India Institute of Medical Sciences, New Delhi, India.
Usha YadavDepartment of Microbiology, All India Institute of Medical Sciences, New Delhi, India.
Gagandeep SinghDepartment of Microbiology, All India Institute of Medical Sciences, New Delhi, India.
Dibyabhaba PradhanICMR Computational Genomics Centre Informatics, Systems & Research Management Division Indian Council of Medical Research, All India Institute of Medical Sciences, New Delhi, India.
Ashit Bhushan XessDepartment of Microbiology, All India Institute of Medical Sciences, New Delhi, India.
Bhaskar RanaDepartment of Microbiology, All India Institute of Medical Sciences, New Delhi, India.
Lalit DarDepartment of Microbiology, All India Institute of Medical Sciences, New Delhi, India.
Sameer BakhshiDepartment of Medical Oncology, All India Institute of Medical Sciences, New Delhi, India.
Rachna SethDepartment of Pediatrics, All India Institute of Medical Sciences, New Delhi, India.
Manoranjan MahapatraDepartment of Hematology, All India Institute of Medical Sciences, New Delhi, India.
Viveka P JyotsnaDepartment of Endocrinology, All India Institute of Medical Sciences, New Delhi, India.
Arun Kumar JainDepartments of Environmental Toxicology and Bioinformatics, ICMR-National Institute of Pathology Sri Ramachari Bhawan, Safdarjang Hospital Campus, New Delhi, India.
Rakesh KumarDepartment of Otorhinolaryngology, All India Institute of Medical Sciences, New Delhi, India.
Reshu AgarwalDepartment of Microbiology, All India Institute of Medical Sciences, New Delhi, India.
Prashant ManiDepartment of Microbiology, All India Institute of Medical Sciences, New Delhi, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Molecular diagnostic assays can expedite the diagnosis of fungal infections, and subsequently help in early interventions and appropriate management of patients. The aim of this study was to develop a single set of primers for a real-time quantitative polymerase chain reaction (qPCR) assay to detect and identify commonly reported, clinically relevant molds i.e.,

Indexed as

invasive aspergillosisinvasive fusariosisinvasive mucormycosismelting curve analysisreal-time PCR

Identifiers

PMID37744098
PMCPMC10512281

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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.