Evidence map›Paper›PMID 22648675›Full record

ArticleJournal of general internal medicine2012

Chapter 7: grading a body of evidence on diagnostic tests.

Sonal Singh, Stephanie M Chang, David B Matchar, Eric B Bass

Abstract read
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In one paragraph

Article in Journal of general internal medicine, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 11 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed, 11 pooled it
–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

24 citing papers in PubMed, 11 syntheses or guidelines pooled it.

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  10. C-reactive protein for diagnosing late-onset infection in newborn infants.The Cochrane database of systematic reviews · 2019
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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.

Sonal SinghDepartment of Medicine, Johns Hopkins University School of Medicine, 624 N Broadway, Baltimore, MD 21205, USA. Ssingh31@jhu.edu
Stephanie M Chang
David B Matchar
Eric B Bass

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionGrading the strength of a body of diagnostic test evidence involves challenges over and above those related to grading the evidence from health care intervention studies. This chapter identifies challenges and outlines principles for grading the body of evidence related to diagnostic test performance. CHALLENGES: Diagnostic test evidence is challenging to grade because standard tools for grading evidence were designed for questions about treatment rather than diagnostic testing; and the clinical usefulness of a diagnostic test depends on multiple links in a chain of evidence connecting the performance of a test to changes in clinical outcomes. PRINCIPLES: Reviewers grading the strength of a body of evidence on diagnostic tests should consider the principle domains of risk of bias, directness, consistency, and precision, as well as publication bias, dose response association, plausible unmeasured confounders that would decrease an effect, and strength of association, similar to what is done to grade evidence on treatment interventions. Given that most evidence regarding the clinical value of diagnostic tests is indirect, an analytic framework must be developed to clarify the key questions, and strength of evidence for each link in that framework should be graded separately. However if reviewers choose to combine domains into a single grade of evidence, they should explain their rationale for a particular summary grade and the relevant domains that were weighed in assigning the summary grade.

Indexed as

Guidelines as TopicReview Literature as TopicDiagnostic Techniques and ProceduresEvidence-Based MedicineHumansOutcome and Process Assessment, Health CarePublication Bias

Identifiers

PMID22648675
PMCPMC3364356

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.