Evidence map›Paper›PMID 42647646›Full record

ArticleScience advances2026

Rapid and robust diagnosis of bloodstream infections by single-cell analysis.

Siew Mei Chin, Emma Epiphaniou, Evgenii Kovtunov, Kathleen E Mach, Joseph C Liao, April M Bobenchik, Samuel Yang, Pak Kin Wong

Abstract read
In one paragraph

Article in Science advances, 2026. 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
–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

0 citing papers in PubMed.

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

8 authors.

Siew Mei ChinDepartment of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA.ORCID 0009-0004-4089-8465
Emma EpiphaniouDepartment of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA.
Evgenii KovtunovDepartment of Pathology and Laboratory Medicine, Penn State College of Medicine, Hershey, PA 17033, USA.ORCID 0000-0002-3506-080X
Kathleen E MachDepartment of Urology, Stanford University School of Medicine, Stanford, CA 94305, USA.ORCID 0000-0003-1197-4073
Joseph C LiaoDepartment of Urology, Stanford University School of Medicine, Stanford, CA 94305, USA.ORCID 0000-0003-2448-5463
April M BobenchikDepartment of Pathology and Laboratory Medicine, Penn State College of Medicine, Hershey, PA 17033, USA.
Samuel YangDepartment of Emergency Medicine, Stanford University School of Medicine, Palo Alto, CA 94304, USA.ORCID 0000-0003-1123-9036
Pak Kin WongDepartment of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA.ORCID 0000-0001-7388-2110

Funding

Changing Cultures in Sepsis: Rapid single-cell pathogen identification and antibiotic susceptibility testing directly from whole bloodR01AI153133 · NIAID · STANFORD UNIVERSITY · PI WONG, PAK KIN, YANG, SAMUEL · 2020 to 2024
$3.7M
NIAID NIH HHS R01 AI153133
6 · The paper itself

Abstract

Sepsis, a common consequence of bloodstream infection (BSI), is a leading cause of global mortality and morbidity. Diagnosis is challenging and slow due to extremely low pathogen loads and reliance on time-consuming blood culture, necessitating empiric therapy that worsens outcomes and antimicrobial resistance. Here, we introduce sedimentation-assisted tandem rocking and enrichment for analysis and monitoring (STREAM), a platform that efficiently isolates and enriches pathogens near their natural doubling times directly from whole blood. By integrating STREAM with single-cell analysis, we achieved rapid and robust diagnosis of BSI from whole-blood samples. Using molecularly barcoded sequential fluorescence in situ hybridization, pathogen identification in 104 positive blood culture samples showed 96.15% concordance with clinical laboratory results. Gel-based single-cell antimicrobial susceptibility testing yields 97.96% essential agreement and 93.9% categorical agreement across 219 drug-dose combinations. The platform enabled comprehensive BSI diagnosis directly from whole blood, achieving a detection limit as low as 0.1 to 1 CFU/ml and delivering full diagnostic results within 6.75 to 17 hours.

Indexed as

BacteremiaSepsisSingle-Cell AnalysisHumansIn Situ Hybridization, FluorescenceMicrobial Sensitivity Tests

Identifiers

PMID42647646
PMCPMC13510697

What Socratic 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 Socratic graph.