Evidence map›Paper›PMID 27657881›Full record

ArticlePloS one

Dynamic Computational Model of Symptomatic Bacteremia to Inform Bacterial Separation Treatment Requirements.

Sinead E Miller, Charleson S Bell, Mark S McClain, Timothy L Cover, Todd D Giorgio

Open access · goldAbstract read
In one paragraph

Article in PloS one. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.5field-weighted citation impact, top 35% 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

2 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. 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

5 authors at 3 institutions in 1 country.

Sinead E MillerDepartment of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, United States of America.
Charleson S BellDepartment of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, United States of America.
Mark S McClainDepartment of Medicine, Division of Infectious Disease, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America.ORCID http://orcid.org/0000-0002-9857-4883
Timothy L CoverDepartment of Medicine, Division of Infectious Disease, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America.
Todd D GiorgioDepartment of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, United States of America.
Vanderbilt University · USVanderbilt University Medical Center · USVA Tennessee Valley Healthcare System · US

Funding

Role of Iron and B-Catenin Activation in Gastric CarcinogenesisP01CA116087 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI RICHARD M. PEEK · 2009 to 2026
$27.5M
NCI NIH HHS P01 CA116087
6 · The paper itself

Abstract

The rise of multi-drug resistance has decreased the effectiveness of antibiotics, which has led to increased mortality rates associated with symptomatic bacteremia, or bacterial sepsis. To combat decreasing antibiotic effectiveness, extracorporeal bacterial separation approaches have been proposed to capture and separate bacteria from blood. However, bacteremia is dynamic and involves host-pathogen interactions across various anatomical sites. We developed a mathematical model that quantitatively describes the kinetics of pathogenesis and progression of symptomatic bacteremia under various conditions, including bacterial separation therapy, to better understand disease mechanisms and quantitatively assess the biological impact of bacterial separation therapy. Model validity was tested against experimental data from published studies. This is the first multi-compartment model of symptomatic bacteremia in mammals that includes extracorporeal bacterial separation and antibiotic treatment, separately and in combination. The addition of an extracorporeal bacterial separation circuit reduced the predicted time of total bacteria clearance from the blood of an immunocompromised rodent by 49%, compared to antibiotic treatment alone. Implementation of bacterial separation therapy resulted in predicted multi-drug resistant bacterial clearance from the blood of a human in 97% less time than antibiotic treatment alone. The model also proposes a quantitative correlation between time-dependent bacterial load among tissues and bacteremia severity, analogous to the well-known 'area under the curve' for characterization of drug efficacy. The engineering-based mathematical model developed may be useful for informing the design of extracorporeal bacterial separation devices. This work enables the quantitative identification of the characteristics required of an extracorporeal bacteria separation device to provide biological benefit. These devices will potentially decrease the bacterial load in blood. Additionally, the devices may achieve bacterial separation rates that allow consequent acceleration of bacterial clearance in other tissues, inhibiting the progression of symptomatic bacteremia, including multi-drug resistant variations.

Identifiers

PMID27657881
PMCPMC5033423
OpenAlexW2523254241

What OpenQuestion holds

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LicenceCC BY
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.