Evidence map›Paper›PMID 34888402›Full record

ArticleOpen forum infectious diseases2021

Comparing the Diagnostic Accuracy of Clinician Judgment to a Novel Host Response Diagnostic for Acute Respiratory Illness.

Ian S Jaffe, Anja K Jaehne, Eugenia Quackenbush, Emily R Ko, Emanuel P Rivers, Micah T McClain, Geoffrey S Ginsburg, Christopher W Woods, Ephraim L Tsalik

Open access · goldAbstract read
In one paragraph

Article in Open forum infectious diseases, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 44% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. Review
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

9 authors at 4 institutions in 1 country.

Ian S JaffeDuke Center for Applied Genomics & Precision Medicine, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.
Anja K JaehneDepartment of Emergency Medicine, Henry Ford Hospital, Wayne State University, Detroit, Michigan, USA.
Eugenia QuackenbushDepartment of Emergency Medicine, University of North Carolina Medical Center, Chapel Hill, North Carolina, USA.
Emily R KoDuke Center for Applied Genomics & Precision Medicine, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.
Emanuel P RiversDepartment of Emergency Medicine, Henry Ford Hospital, Wayne State University, Detroit, Michigan, USA.
Micah T McClainDuke Center for Applied Genomics & Precision Medicine, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.
Geoffrey S GinsburgDuke Center for Applied Genomics & Precision Medicine, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.
Christopher W WoodsDuke Center for Applied Genomics & Precision Medicine, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.
Ephraim L TsalikDuke Center for Applied Genomics & Precision Medicine, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.
Duke University · USDurham VA Health Care System · USHenry Ford Hospital · USWayne State University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDifficulty discriminating bacterial from viral infections drives antibacterial misuse. Host gene expression tests discriminate bacterial and viral etiologies, but their clinical utility has not been evaluated.

methodsHost gene expression and procalcitonin levels were measured in 582 emergency department participants with suspected infection. We also recorded clinician diagnosis and clinician-recommended treatment. These 4 diagnostic strategies were compared with clinical adjudication as the reference. To estimate the clinical impact of host gene expression, we calculated the change in overall Net Benefit (∆NB; the difference in Net Benefit comparing 1 diagnostic strategy with a reference) across a range of prevalence estimates while factoring in the clinical significance of false-positive and -negative errors.

resultsGene expression correctly classified bacterial, viral, or noninfectious illness in 74.1% of subjects, similar to the other strategies. Clinical diagnosis and clinician-recommended treatment revealed a bias toward overdiagnosis of bacterial infection resulting in high sensitivity (92.6% and 94.5%, respectively) but poor specificity (67.2% and 58.8%, respectively), resulting in a 33.3% rate of inappropriate antibacterial use. Gene expression offered a more balanced sensitivity (79.0%) and specificity (80.7%), which corresponded to a statistically significant improvement in average weighted accuracy (79.9% vs 71.5% for procalcitonin and 76.3% for clinician-recommended treatment;

conclusionsHost gene expression-based tests to distinguish bacterial and viral infection can facilitate appropriate treatment, improving patient outcomes and mitigating the antibacterial resistance crisis.

Indexed as

bacterial infectionclinical decision-makingdiagnostic testgene expressionprocalcitonin

Identifiers

PMID34888402
PMCPMC8651161
OpenAlexW4200007818

What OpenQuestion holds

Textmetadata
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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.