Evidence map›Paper›PMID 26251049›Full record

ArticleClinical infectious diseases : an official publication of the Infectious Diseases Society of America2015

How next-generation sequencing and multiscale data analysis will transform infectious disease management.

Theodore R Pak, Andrew Kasarskis

Abstract read
In one paragraph

Article in Clinical infectious diseases : an official publication of the Infectious Diseases Society of America, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Next-Generation Sequencing Coupled WithFrontiers in veterinary science · 2019
    Review
  10. Genomic Surveillance Reveals Diversity of Multidrug-Resistant Organism Colonization and Infection: A Prospective Cohort Study in Liver Transplant Recipients.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2018
    Article
  11. Review
  12. Article
  13. Article
  14. Review
  15. Community-Acquired CavitaryCase reports in infectious diseases · 2017
    Article
  16. Antimicrobial resistance and infection control · 2017
    Article
  17. Review
  18. Article
  19. Advanced Molecular Detection of Malarone Resistance.Antimicrobial agents and chemotherapy · 2016
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Theodore R PakIcahn Institute and Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York.
Andrew KasarskisIcahn Institute and Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent reviews have examined the extent to which routine next-generation sequencing (NGS) on clinical specimens will improve the capabilities of clinical microbiology laboratories in the short term, but do not explore integrating NGS with clinical data from electronic medical records (EMRs), immune profiling data, and other rich datasets to create multiscale predictive models. This review introduces a range of "omics" and patient data sources relevant to managing infections and proposes 3 potentially disruptive applications for these data in the clinical workflow. The combined threats of healthcare-associated infections and multidrug-resistant organisms may be addressed by multiscale analysis of NGS and EMR data that is ideally updated and refined over time within each healthcare organization. Such data and analysis should form the cornerstone of future learning health systems for infectious disease.

Indexed as

Communicable DiseasesComputational BiologyDisease ManagementGenomicsHigh-Throughput Nucleotide SequencingMeta-Analysis as TopicSequence Analysis, DNAElectronic Health RecordsHumansSoftwareelectronic medical recordshealthcare-associated infectionshospital-acquired infectionsmultiscale analysiswhole genome sequencing

Identifiers

PMID26251049
PMCPMC4643486

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.