Evidence map›Paper›PMID 33047099›Full record

ArticleiScience2020

Multi-Biomarker Prediction Models for Multiple Infection Episodes Following Blunt Trauma.

Amy Tsurumi, Patrick J Flaherty, Yok-Ai Que, Colleen M Ryan, April E Mendoza, Marianna Almpani, Arunava Bandyopadhaya, Asako Ogura, Yashoda V Dhole, Laura F Goodfield and 2 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in iScience, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
–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

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. 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

12 authors.

Amy TsurumiDepartment of Surgery, Massachusetts General Hospital, and Harvard Medical School, 50 Blossom St., Their 340, Boston, MA 02114, USA.
Patrick J FlahertyDepartment of Mathematics and Statistics, University of Massachusetts at Amherst, Amherst, MA 01003, USA.
Yok-Ai QueDepartment of Intensive Care Medicine, Inselspital, Bern University Hospital, University of Bern, Switzerland, 3010 Bern, Switzerland.
Colleen M RyanDepartment of Surgery, Massachusetts General Hospital, and Harvard Medical School, 50 Blossom St., Their 340, Boston, MA 02114, USA.
April E MendozaDepartment of Surgery, Massachusetts General Hospital, and Harvard Medical School, 50 Blossom St., Their 340, Boston, MA 02114, USA.
Marianna AlmpaniDepartment of Surgery, Massachusetts General Hospital, and Harvard Medical School, 50 Blossom St., Their 340, Boston, MA 02114, USA.
Arunava BandyopadhayaDepartment of Surgery, Massachusetts General Hospital, and Harvard Medical School, 50 Blossom St., Their 340, Boston, MA 02114, USA.
Asako OguraDepartment of Surgery, Massachusetts General Hospital, and Harvard Medical School, 50 Blossom St., Their 340, Boston, MA 02114, USA.
Yashoda V DholeDepartment of Surgery, Massachusetts General Hospital, and Harvard Medical School, 50 Blossom St., Their 340, Boston, MA 02114, USA.
Laura F GoodfieldDepartment of Surgery, Massachusetts General Hospital, and Harvard Medical School, 50 Blossom St., Their 340, Boston, MA 02114, USA.
Ronald G TompkinsDepartment of Surgery, Massachusetts General Hospital, and Harvard Medical School, 50 Blossom St., Their 340, Boston, MA 02114, USA.
Laurence G RahmeDepartment of Surgery, Massachusetts General Hospital, and Harvard Medical School, 50 Blossom St., Their 340, Boston, MA 02114, USA.

Funding

Inflammation and the Response to InjuryU54GM062119 · NIGMS · MASSACHUSETTS GENERAL HOSPITAL · PI SCHOENFELD, DAVID ALAN · 2001 to 2010
$78.6M
Predictive Approaches and Technology Development for Identification of Susceptibility to Multiple Independent Infections in Trauma PatientsR56AI155505 · NIAID · MASSACHUSETTS GENERAL HOSPITAL · PI RAHME, LAURENCE G · 2021 to 2021
$845k
NIAID NIH HHS R56 AI155505NIGMS NIH HHS U54 GM062119
6 · The paper itself

Abstract

Severe trauma predisposes patients to multiple independent infection episodes (MIIEs), leading to augmented morbidity and mortality. We developed a method to identify increased MIIE risk before clinical signs appear, which is fundamentally different from existing approaches entailing infections' detection after their establishment. Applying machine learning algorithms to genome-wide transcriptome data from 128 adult blunt trauma patients' (42 MIIE cases and 85 non-cases) leukocytes collected ≤48 hr of injury and ≥3 days before any infection, we constructed a 15-transcript and a 26-transcript multi-biomarker panel model with the least absolute shrinkage and selection operator (LASSO) and Elastic Net, respectively, which accurately predicted MIIE (Area Under Receiver Operating Characteristics Curve [AUROC] [95% confidence intervals, CI]: 0.90 [0.84-0.96] and 0.92 [0.86-0.96]) and significantly outperformed clinical models. Gene Ontology and network analyses found various pathways to be relevant. External validation found our model to be generalizable. Our unique precision medicine approach can be applied to a wide range of patient populations and outcomes.

Indexed as

Artificial IntelligenceTraumaVirology

Identifiers

PMID33047099
PMCPMC7539926

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.