Evidence map›Paper›PMID 34373501›Full record

SynthesisScientific reports2021

Detection of three pandemic causing coronaviruses from non-respiratory samples: systematic review and meta-analysis.

Chandan Mishra, Suneeta Meena, Jitendra Kumar Meena, Suman Tiwari, Purva Mathur

Abstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

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

  1. Pooled it
  2. Article
  3. Predicting pathogen evolution and immune evasion in the age of artificial intelligence.Computational and structural biotechnology journal · 2025
    Review
  4. Article
  5. Review
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.

Chandan MishraDepartment of Laboratory Medicine, All India Institute of Medical Sciences, Delhi, India.
Suneeta MeenaDepartment of Laboratory Medicine, All India Institute of Medical Sciences, Delhi, India. suneetameena@gmail.com.
Jitendra Kumar MeenaPreventive Oncology, NCI Jhajjar, All India Institute of Medical Sciences, Delhi, India.
Suman TiwariDepartment of Anaesthesia and Intensive Care, VMMC and Safdarjung Hospital, Delhi, India.
Purva MathurDepartment of Laboratory Medicine, JPNATC, All India Institute of Medical Sciences, Delhi, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

SARS-CoV-2 has posed an unprecedented challenge to the world. Pandemics have been caused previously by viruses of this family like Middle East Respiratory Corona Virus (MERS CoV), Severe Acute Respiratory Syndrome Corona Virus (SARS CoV). Although these viruses are primarily respiratory viruses, but they have been isolated from non-respiratory samples as well. Presently, the detection rate of SARS-CoV-2 RNA from different clinical specimens using Real Time Reverse Transcriptase Polymerized Chain Reaction (qRT-PCR) after onset of symptoms is not yet well established. Therefore, the aim of this systematic review was to establish the profile of detecting SARS-CoV-2, MERS CoV, SARS CoV from different types of clinical specimens other than the respiratory using a standard diagnostic test (qRT-PCR). A total of 3429 non-respiratory specimens were recorded: SARS CoV (total sample-802), MERS CoV (total sample-155), SARS CoV-2 (total sample-2347). Out of all the samples studied high positive rate was seen for saliva with 96.7% (14/14; 95% CI 87.6-100.0%) for SARS CoV and 57.5% (58/250; 95% CI - 1.2 to 116.2%) for SARS CoV-2, while low detection rate in urine samples for SARS CoV-2 with 2.2% (8/318; 95% CI 0.6-3.7%) and 9.6% (12/61; 95% CI - 0.9 to 20.1%) for SARS CoV but there was relatively higher positivity in urine samples for MERS CoV with detection rate of 32.4% (2/38; 95% CI - 37.3 to 102.1%). In Stool sample positivity was 54.9% (396/779; 95% CI 41.0-68.8%), 45.2% (180/430; 95% CI 28.1-62.3%) and 34.7% (4/38; 95% CI - 29.5 to 98.9%) for SARS CoV-2, MERS CoV, and SARS CoV, respectively. In blood sample the positivity was 33.3% (7/21; 95% CI 13.2-53.5%), 23.7% (42/277; 95% CI 10.5-36.9%) and 2.5% (2/81; 95% CI 0.00-5.8%) for MERS CoV, SARS CoV-2 and SARS CoV respectively. SARS-CoV-2 along with previous two pandemic causing viruses from this family, were highly detected stool and saliva. A low positive rate was recorded in blood samples. Viruses were also detected in fluids along with unusual samples like semen and vaginal secretions thus highlighting unique pathogenic potential of SARS-CoV-2.

Indexed as

COVID-19FecesHumansMiddle East Respiratory Syndrome CoronavirusPandemicsReverse Transcriptase Polymerase Chain ReactionRNA, ViralSalivaSARS-CoV-2Severe acute respiratory syndrome-related coronavirusRNA, Viral

Identifiers

PMID34373501
PMCPMC8352881

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.