Evidence map›Paper›PMID 31443440›Full record

ArticleViruses2019

A Methodology for Determining Which Diseases Warrant Care in a High-Level Containment Care Unit.

Theodore J Cieslak, Jocelyn J Herstein, Mark G Kortepeter, Angela L Hewlett

Abstract read
In one paragraph

Article in Viruses, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. 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

4 authors.

Theodore J CieslakDepartment of Epidemiology, College of Public Health, University of Nebraska Medical Center, Omaha, NE 68198, USA. ted.cieslak@unmc.edu.
Jocelyn J HersteinDepartment of Environmental, Agricultural & Occupational Health, College of Public Health, University of Nebraska Medical Center, Omaha, NE 68198, USA.
Mark G KortepeterDepartment of Epidemiology, College of Public Health, University of Nebraska Medical Center, Omaha, NE 68198, USA.
Angela L HewlettDepartment of Medicine, Division of Infectious Diseases, College of Medicine, University of Nebraska Medical Center, Omaha, NE 68198, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although the concept of high-level containment care (HLCC or 'biocontainment'), dates back to 1969, the 2014-2016 outbreak of Ebola virus disease (EVD) brought with it a renewed emphasis on the use of specialized HLCC units in the care of patients with EVD. Employment of these units in the United States and Western Europe resulted in a significant decrease in mortality compared to traditional management in field settings. Moreover, this employment appeared to significantly lessen the risk of nosocomial transmission of disease; no secondary cases occurred among healthcare workers in these units. While many now accept the wisdom of utilizing HLCC units and principles in the management of EVD (and, presumably, of other transmissible and highly hazardous viral hemorrhagic fevers, such as those caused by Marburg and Lassa viruses), no consensus exists regarding additional diseases that might warrant HLCC. We propose here a construct designed to make such determinations for existing and newly discovered diseases. The construct examines infectivity (as measured by the infectious dose needed to infect 50% of a given population (ID

Indexed as

Communicable Disease ControlCross InfectionCommunicable DiseasesContainment of BiohazardsHealth PersonnelHemorrhagic Fever, EbolaHemorrhagic Fevers, ViralHumansIntensive Care UnitsbiocontainmentcommunicabilityEbola virus diseasehigh-level containment carehighly hazardous communicable diseaseinfectivity

Identifiers

PMID31443440
PMCPMC6784089

What OpenQuestion holds

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Registered trials

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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.