Evidence map›Paper›PMID 32617371›Full record

ArticleOpen forum infectious diseases2020

Previously Derived Host Gene Expression Classifiers Identify Bacterial and Viral Etiologies of Acute Febrile Respiratory Illness in a South Asian Population.

L Gayani Tillekeratne, Sunil Suchindran, Emily R Ko, Elizabeth A Petzold, Champica K Bodinayake, Ajith Nagahawatte, Vasantha Devasiri, Ruvini Kurukulasooriya, Bradly P Nicholson, Micah T McClain and 6 more

Abstract read
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Article in Open forum infectious diseases, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

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3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

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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

16 authors.

L Gayani TillekeratneDepartment of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.ORCID 0000-0001-6012-7271
Sunil SuchindranCenter for Applied Genomics and Precision Medicine, Durham, North Carolina, USA.
Emily R KoDepartment of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.
Elizabeth A PetzoldCenter for Applied Genomics and Precision Medicine, Durham, North Carolina, USA.
Champica K BodinayakeDuke Global Health Institute, Durham, North Carolina, USA.
Ajith NagahawatteDuke Global Health Institute, Durham, North Carolina, USA.
Vasantha DevasiriDepartment of Pediatrics, Faculty of Medicine, University of Ruhuna, Galle, Sri Lanka.
Ruvini KurukulasooriyaDepartment of Microbiology, Faculty of Medicine, University of Ruhuna, Galle, Sri Lanka.
Bradly P NicholsonInstitute for Medical Research, Inc., Durham, North Carolina, USA.
Micah T McClainDepartment of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.
Thomas W BurkeDepartment of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.
Ephraim L TsalikDepartment of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.
Ricardo HenaoDepartment of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.
Geoffrey S GinsburgDepartment of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.
Megan E RellerDepartment of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.
Christopher W WoodsDepartment of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.

Funding

Novel Diagnostics to Improve Antimicrobial Stewardship for Acute Respiratory Tract Infections in Resource-Limited SettingsK23AI125677 · NIAID · DUKE UNIVERSITY · PI TILLEKERATNE, GAYANI · 2017 to 2021
$905k
NIAID NIH HHS K23 AI125677
6 · The paper itself

Abstract

backgroundPathogen-based diagnostics for acute respiratory infection (ARI) have limited ability to detect etiology of illness. We previously showed that peripheral blood-based host gene expression classifiers accurately identify bacterial and viral ARI in cohorts of European and African descent. We determined classifier performance in a South Asian cohort.

methodsPatients ≥15 years with fever and respiratory symptoms were enrolled in Sri Lanka. Comprehensive pathogen-based testing was performed. Peripheral blood ribonucleic acid was sequenced and previously developed signatures were applied: a pan-viral classifier (viral vs nonviral) and an ARI classifier (bacterial vs viral vs noninfectious).

resultsRibonucleic acid sequencing was performed in 79 subjects: 58 viral infections (36 influenza, 22 dengue) and 21 bacterial infections (10 leptospirosis, 11 scrub typhus). The pan-viral classifier had an overall classification accuracy of 95%. The ARI classifier had an overall classification accuracy of 94%, with sensitivity and specificity of 91% and 95%, respectively, for bacterial infection. The sensitivity and specificity of C-reactive protein (>10 mg/L) and procalcitonin (>0.25 ng/mL) for bacterial infection were 100% and 34%, and 100% and 41%, respectively.

conclusionsPreviously derived gene expression classifiers had high predictive accuracy at distinguishing viral and bacterial infection in South Asian patients with ARI caused by typical and atypical pathogens.

Indexed as

antimicrobial stewardshipdiagnostic testgene expressionrespiratory tract infectionSri Lanka

Identifiers

PMID32617371
PMCPMC7314590

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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.