Evidence map›Paper›PMID 30305386›Full record

ArticleJournal of clinical microbiology2019

Designing Studies Acceptable for Abstraction and Inclusion in Evidence-Based Laboratory Practice Guidelines.

Michael A Saubolle, Alice S Weissfeld, Colleen S Kraft

Abstract read
In one paragraph

Article in Journal of clinical microbiology, 2019. 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. Article
  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

3 authors.

Michael A SaubolleDivision of Infectious Diseases, Laboratory Sciences of Arizona, Banner-University Medical Center Phoenix, Phoenix, Arizona, USA mike.saubolle@bannerhealth.com.
Alice S WeissfeldMicrobiology Specialists Inc., Houston, Texas, USA.
Colleen S KraftDepartment of Pathology and Laboratory Medicine, Division of Infectious Diseases, Emory University, Atlanta, Georgia, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Expansion of technologies, changing infrastructure, and dwindling resources have produced the need for health care reform and changes in clinical laboratories. The health care model will have to shift increasingly from a fee-for-service model to a value-based model. Laboratories will have to focus more on evidence-based outcome studies evaluating the effects of their preanalytical and postanalytical practices on real patient outcomes. Although well-designed clinical trials and multicenter studies are needed to determine the effects of laboratory processes on outcomes, there has been concern that too few well-designed studies have been published. To help improve the quality of study design and to facilitate reporting transparency, several method statements have been developed. The Standards for Reporting of Diagnostic Accuracy Studies (STARD) initiative was recently updated, listing 30 items deemed crucial for transparent reporting of studies, thereby allowing the creation of a robust database for clinical practice guidelines. Three methods describing the assessment of the quality of data on which to base recommendations for such guidelines are also available. Close attention must be given to study design so that parameters ensuring study quality are met, thereby allowing inclusion of the study data in the formulation of evidence-based laboratory best practices guidelines.

Indexed as

Clinical Studies as TopicEvidence-Based PracticeGuidelines as TopicHumansLaboratoriesQuality ControlResearch DesignResearch Reportabstractionclinical outcomesevidence-basedguidelineslaboratory medicine best practicesstudy design

Identifiers

PMID30305386
PMCPMC6425160

What OpenQuestion holds

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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.