Evidence map›Paper›PMID 40236397›Full record

ArticlemedRxiv : the preprint server for health sciences2025

Integrating a host transcriptomic biomarker with a large language model for diagnosis of lower respiratory tract infection.

Hoang Van Phan, Natasha Spottiswoode, Emily C Lydon, Victoria T Chu, Adolfo Cuesta, Alexander D Kazberouk, Natalie L Richmond, Padmini Deosthale, Carolyn S Calfee, Charles R Langelier

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2025. 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

5 · Who and what money

Authors and funding

10 authors.

Hoang Van PhanDepartment of Medicine, Division of Infectious Diseases, University of California San Francisco.
Natasha SpottiswoodeDepartment of Medicine, Division of Infectious Diseases, University of California San Francisco.
Emily C LydonDepartment of Medicine, Division of Infectious Diseases, University of California San Francisco.
Victoria T ChuDepartment of Pediatrics, Division of Infectious Diseases and Global Health, University of California San Francisco.
Adolfo CuestaDepartment of Medicine, Division of Infectious Diseases, University of California San Francisco.
Alexander D KazberoukDepartment of Medicine, University of California San Francisco.
Natalie L RichmondDepartment of Medicine, Division of Infectious Diseases, University of California San Francisco.
Padmini DeosthaleDepartment of Medicine, Division of Infectious Diseases, University of California San Francisco.
Carolyn S CalfeeDepartment of Medicine, Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, University of California San Francisco.
Charles R LangelierDepartment of Medicine, Division of Infectious Diseases, University of California San Francisco.

Funding

BIOLOGY OF INFECTIOUS DISEASES TRAINING PROGRAMT32AI007641 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI MATTHEW G DORSEY · 2000 to 2026
$6.9M
Precision Medicine in the Acute Respiratory Distress SyndromeR35HL140026 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI CALFEE, CAROLYN · 2018 to 2024
$6.8M
Integrated Host-Microbe Metagenomics for Sepsis Pathogen Surveillance, Subphenotyping and Outcome PredictionR01AI185511 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Charles Langelier · 2024 to 2026
$2.0M
Metagenomic surveillance of pathogen and antimicrobial resistance gene transmission in hospitalized neonatesK23AI185326 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI CHU, VICTORIA TIEN-YU · 2024 to 2025
$395k
NHLBI NIH HHS R35 HL140026NIAID NIH HHS K23 AI185326NIAID NIH HHS R01 AI185511NIAID NIH HHS T32 AI007641
6 · The paper itself

Abstract

backgroundLower respiratory tract infections (LRTIs) are a leading cause of mortality worldwide and can be difficult to diagnose in critically ill patients, as non-infectious causes of respiratory failure can present with similar clinical features.

methodsWe developed a LRTI diagnostic method combining the pulmonary transcriptomic biomarker

resultsIn the derivation cohort, a combined classifier incorporating

conclusionsIntegrating a host transcriptional biomarker with EMR text analysis using a large language model may offer a promising new approach to improving the diagnosis of LRTIs in critically ill adults.

Identifiers

PMID40236397
PMCPMC11998817

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.