Evidence map›Paper›PMID 28724557›Full record

ReviewJournal of clinical microbiology2017

The Human Virome: Implications for Clinical Practice in Transplantation Medicine.

Susanna K Tan, David A Relman, Benjamin A Pinsky

Abstract readReview
In one paragraph

Review in Journal of clinical microbiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Bacteriophages of the lower urinary tract.Nature reviews. Urology · 2019
    Review
  8. Article
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.

Susanna K TanDepartment of Medicine, Division of Infectious Diseases and Geographic Medicine, Stanford University School of Medicine, Stanford, California, USA susietan@stanford.edu.
David A RelmanDepartment of Medicine, Division of Infectious Diseases and Geographic Medicine, Stanford University School of Medicine, Stanford, California, USA.
Benjamin A PinskyDepartment of Medicine, Division of Infectious Diseases and Geographic Medicine, Stanford University School of Medicine, Stanford, California, USA.ORCID 0000-0001-8751-4810

Funding

Translational CoreU19AI109761 · NIAID · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI LIPKIN, W. IAN · 2014 to 2018
$32.6M
EMERGING INFECTIOUS DISEASEST32AI007502 · NIAID · STANFORD UNIVERSITY · PI Prasanna Jagannathan, DAVID A. RELMAN · 1995 to 2026
$6.8M
Spectrum Stanford Center for Clinical and Translational Research and EducationTL1TR001084 · NCATS · STANFORD UNIVERSITY · PI CULLEN, MARK RICHARD, GREENBERG, HARRY BERNARD · 2013 to 2017
$1.1M
NCATS NIH HHS TL1 TR001084NIAID NIH HHS T32 AI007502NIAID NIH HHS U19 AI109761
6 · The paper itself

Abstract

Advances in DNA sequencing technology have provided an unprecedented opportunity to study the human virome. Transplant recipients and other immunocompromised hosts are at particular risk for developing virus-related pathology; thus, the impact of the virome on health and disease may be even more relevant in this population. Here, we discuss technical considerations in studying the human virome, the current literature on the virome in transplant recipients, and near-future applications of sequence-based findings that can further our understanding of viruses in transplantation medicine.

Indexed as

Immunocompromised HostTransplant RecipientsBase SequenceHigh-Throughput Nucleotide SequencingHumansMicrobiotaOpportunistic InfectionsSequence Analysis, DNAVirusesimmunocompromised hoststransplantationvirome

Identifiers

PMID28724557
PMCPMC5625374

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.