Evidence map›Paper›PMID 29237786›Full record

ArticleJournal of clinical microbiology2018

Waltzing around Sacred Cows on the Way to the Future.

Stephen M Brecher

Abstract read
In one paragraph

Article in Journal of clinical microbiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

1 author.

Stephen M BrecherDepartment of Pathology and Laboratory Medicine, VA Boston HealthCare System, West Roxbury, and Department of Pathology and Laboratory Medicine, Boston University School of Medicine, Boston, Massachusetts, USA stephen.brecher@va.gov.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Our mostly manual, agar-based clinical microbiology laboratory is slowly but steadily being redefined by automation and innovation. Ironically, the oldest test, the Gram stain test, is still manually read and interpreted by trained personnel. In a proof-of-concept study, Smith et al. (J. Clin. Microbiol. 56:e01521-17, 2018, https://doi.org/10.1128/JCM.01521-17) used computer imaging with a deep convolutional neural network to examine and interpret Gram-stained slides from positive blood culture bottles. In light of the shortage of medical technologists/microbiologists and the need for results from positive blood culture bottles 24/7, this paper paves the way for the next innovations for the clinical microbiology laboratory of the future.

Indexed as

Automation, LaboratoryGentian VioletPhenazinesBacteriological TechniquesDiagnostic ErrorsHumansMedical Laboratory PersonnelMolecular Diagnostic TechniquesStaining and LabelingGentian VioletGram's stainPhenazines

Identifiers

PMID29237786
PMCPMC5824060

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.