Evidence map›Paper›PMID 30215227›Full record

ArticleAnnals of laboratory medicine2019

Evaluation of the SD Bioline Strep A Ultra Test in Relation With Number of Colony Forming Units and Color Intensity.

Sang Hyuk Ma, Won Hee Choi, Hyunwoong Park, Sunjoo Kim

Open access · diamondAbstract readEvaluation Study
In one paragraph

Article in Annals of laboratory medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.7field-weighted citation impact, top 25% 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

0 citing papers in PubMed, 3 citations in OpenAlex.

No citing paper in PubMed yet.

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 at 3 institutions in 1 country.

Sang Hyuk MaDepartment of Pediatrics, Changwon Fatima Hospital, Changwon, Korea.
Won Hee ChoiDepartment of Nursing Science, Kyungsung University, Busan, Korea.
Hyunwoong ParkDepartment of Laboratory Medicine, Seoul National University Boramae Medical Center, Seoul, Korea.
Sunjoo KimDepartment of Laboratory Medicine, Gyeongsang National University College of Medicine, Jinju, Korea.ORCID https://orcid.org/0000-0001-8099-8891
Gyeongsang National University · KRKyungsung University · KRSeoul National University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe SD Bioline Strep A Ultra (SD, Yongin, Korea) is a recently developed rapid antigen detection test (RADT) for diagnosing bacterial pharyngitis caused by Group A

methodsThree throat swabs each were taken from 343 children with pharyngitis who visited pediatric clinics. We evaluated the performance of SD Bioline Strep A Ultra and compared its positive rate with the number of colony forming units, using the Fisher exact test.

resultsThe sensitivity, specificity, positive predictive value, and negative predictive value (95% confidence interval) were 97.4% (94.0-99.1%), 90.8% (85.0-94.9%), 93.0% (88.5-96.1%), and 96.5% (92.0-98.9%), respectively. Positive rate significantly differed by number of colony forming units (

conclusionsSD Bioline Strep A Ultra showed excellent performance, and its positive rate differed by the number of colony counts. This RADT could be used as a sensitive and semi-quantitative method detecting bacterial pharyngitis.

Indexed as

AdolescentAntigens, BacterialArea Under CurveChildChild, PreschoolColorFemaleHumansInfantMalePharynxReagent Kits, DiagnosticROC CurveSensitivity and SpecificityStreptococcal InfectionsStreptococcus pyogenesAntigens, BacterialReagent Kits, DiagnosticEvaluationGroup A StreptococcusPharyngitisRapid antigen detection test

Identifiers

PMID30215227
PMCPMC6143457
OpenAlexW2891367182

What OpenQuestion holds

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LicenceCC BY-NC
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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.