Evidence map›Paper›PMID 17158858›Full record

ReviewArchives of disease in childhood2007

Quantifying how tests reduce diagnostic uncertainty.

Malcolm G Coulthard

Open access · bronzeAbstract readReview
In one paragraph

Review in Archives of disease in childhood, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.7field-weighted citation impact, top 13% of its field
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

7 citing papers in PubMed, 36 citations in OpenAlex.

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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

1 author at 1 institution in 1 country.

Malcolm G CoulthardRoyal Victoria Infirmary, Newcastle NE1 4LP, UK. malcolm.coulthard@nuth.nhs.uk
Royal Victoria Infirmary · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDiagnostic tests are commonly evaluated from sensitivity and specificity, which are robust and independent of prevalence, but clinically not intuitive. Many clinicians prefer to use positive and negative predictive values (PPV and NPV), but they are frequently applied as if they are independent of prevalence, whereas this may make an important difference. METHODS AND

resultsWe present graphs that allow easy reference to appropriate values and demonstrate that PPV and NPV are not independent of prevalence. PPV and NPV figures reflect the prior probability of the case having a positive diagnosis, estimated clinically from the history, examination and other results, as well as the impact of the test result. To avoid the common error of allowing for prior probability twice, and to interpret the impact of the test result alone, we present graphs of the proportionate reduction in uncertainty score (PRU), calculated from sensitivity, specificity and prevalence. These plots show the extent to which either a positive or negative test result affects the remaining degree of uncertainty about a diagnosis in either direction, according to likely clinical prevalence.

conclusionsPRU plots demonstrate the discriminatory value of tests more clearly than sensitivity and specificity from which they are derived, and should be published alongside them.

Indexed as

Diagnostic Tests, RoutineChildHumansPredictive Value of TestsPrevalenceSensitivity and SpecificityUncertaintyUrinary Tract Infections

Identifiers

PMID17158858
PMCPMC2083733
OpenAlexW2153380226

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.