Development and validation of a cellular host response test as an early diagnostic for sepsis
Sepsis must be diagnosed quickly to avoid morbidity and mortality. However, the clinical manifestations of sepsis are highly variable and emergency department (ED) clinicians often must make rapid, impactful decisions before laboratory results are known. We previously developed a technique that allo...
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Published in | PloS one Vol. 16; no. 4; p. e0246980 |
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Main Authors | , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
United States
Public Library of Science
15.04.2021
Public Library of Science (PLoS) |
Subjects | |
Online Access | Get full text |
ISSN | 1932-6203 1932-6203 |
DOI | 10.1371/journal.pone.0246980 |
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Abstract | Sepsis must be diagnosed quickly to avoid morbidity and mortality. However, the clinical manifestations of sepsis are highly variable and emergency department (ED) clinicians often must make rapid, impactful decisions before laboratory results are known. We previously developed a technique that allows the measurement of the biophysical properties of white blood cells as they are stretched through a microfluidic channel. In this study we describe and validate the resultant output as a model and score—the IntelliSep Index (ISI)—that aids in the diagnosis of sepsis in patients with suspected or confirmed infection from a single blood draw performed at the time of ED presentation. By applying this technique to a high acuity cohort with a 23.5% sepsis incidence (
n
= 307), we defined specific metrics—the aspect ratio and visco-elastic inertial response—that are more sensitive than cell size or cell count in predicting disease severity. The final model was trained and cross-validated on the high acuity cohort, and the performance and generalizability of the model was evaluated on a separate low acuity cohort with a 6.4% sepsis incidence (
n
= 94) and healthy donors (
n
= 72). For easier clinical interpretation, the ISI is divided into three interpretation bands of Green, Yellow, and Red that correspond to increasing disease severity. The ISI agreed with the diagnosis established by retrospective physician adjudication, and accurately identified subjects with severe illness as measured by SOFA, APACHE-II, hospital-free days, and intensive care unit admission. Measured using routinely collected blood samples, with a short run-time and no requirement for patient or laboratory information, the ISI is well suited to aid ED clinicians in rapidly diagnosing sepsis. |
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AbstractList | Sepsis must be diagnosed quickly to avoid morbidity and mortality. However, the clinical manifestations of sepsis are highly variable and emergency department (ED) clinicians often must make rapid, impactful decisions before laboratory results are known. We previously developed a technique that allows the measurement of the biophysical properties of white blood cells as they are stretched through a microfluidic channel. In this study we describe and validate the resultant output as a model and score-the IntelliSep Index (ISI)-that aids in the diagnosis of sepsis in patients with suspected or confirmed infection from a single blood draw performed at the time of ED presentation. By applying this technique to a high acuity cohort with a 23.5% sepsis incidence (n = 307), we defined specific metrics-the aspect ratio and visco-elastic inertial response-that are more sensitive than cell size or cell count in predicting disease severity. The final model was trained and cross-validated on the high acuity cohort, and the performance and generalizability of the model was evaluated on a separate low acuity cohort with a 6.4% sepsis incidence (n = 94) and healthy donors (n = 72). For easier clinical interpretation, the ISI is divided into three interpretation bands of Green, Yellow, and Red that correspond to increasing disease severity. The ISI agreed with the diagnosis established by retrospective physician adjudication, and accurately identified subjects with severe illness as measured by SOFA, APACHE-II, hospital-free days, and intensive care unit admission. Measured using routinely collected blood samples, with a short run-time and no requirement for patient or laboratory information, the ISI is well suited to aid ED clinicians in rapidly diagnosing sepsis. Sepsis must be diagnosed quickly to avoid morbidity and mortality. However, the clinical manifestations of sepsis are highly variable and emergency department (ED) clinicians often must make rapid, impactful decisions before laboratory results are known. We previously developed a technique that allows the measurement of the biophysical properties of white blood cells as they are stretched through a microfluidic channel. In this study we describe and validate the resultant output as a model and score-the IntelliSep Index (ISI)-that aids in the diagnosis of sepsis in patients with suspected or confirmed infection from a single blood draw performed at the time of ED presentation. By applying this technique to a high acuity cohort with a 23.5% sepsis incidence (n = 307), we defined specific metrics-the aspect ratio and visco-elastic inertial response-that are more sensitive than cell size or cell count in predicting disease severity. The final model was trained and cross-validated on the high acuity cohort, and the performance and generalizability of the model was evaluated on a separate low acuity cohort with a 6.4% sepsis incidence (n = 94) and healthy donors (n = 72). For easier clinical interpretation, the ISI is divided into three interpretation bands of Green, Yellow, and Red that correspond to increasing disease severity. The ISI agreed with the diagnosis established by retrospective physician adjudication, and accurately identified subjects with severe illness as measured by SOFA, APACHE-II, hospital-free days, and intensive care unit admission. Measured using routinely collected blood samples, with a short run-time and no requirement for patient or laboratory information, the ISI is well suited to aid ED clinicians in rapidly diagnosing sepsis.Sepsis must be diagnosed quickly to avoid morbidity and mortality. However, the clinical manifestations of sepsis are highly variable and emergency department (ED) clinicians often must make rapid, impactful decisions before laboratory results are known. We previously developed a technique that allows the measurement of the biophysical properties of white blood cells as they are stretched through a microfluidic channel. In this study we describe and validate the resultant output as a model and score-the IntelliSep Index (ISI)-that aids in the diagnosis of sepsis in patients with suspected or confirmed infection from a single blood draw performed at the time of ED presentation. By applying this technique to a high acuity cohort with a 23.5% sepsis incidence (n = 307), we defined specific metrics-the aspect ratio and visco-elastic inertial response-that are more sensitive than cell size or cell count in predicting disease severity. The final model was trained and cross-validated on the high acuity cohort, and the performance and generalizability of the model was evaluated on a separate low acuity cohort with a 6.4% sepsis incidence (n = 94) and healthy donors (n = 72). For easier clinical interpretation, the ISI is divided into three interpretation bands of Green, Yellow, and Red that correspond to increasing disease severity. The ISI agreed with the diagnosis established by retrospective physician adjudication, and accurately identified subjects with severe illness as measured by SOFA, APACHE-II, hospital-free days, and intensive care unit admission. Measured using routinely collected blood samples, with a short run-time and no requirement for patient or laboratory information, the ISI is well suited to aid ED clinicians in rapidly diagnosing sepsis. Sepsis must be diagnosed quickly to avoid morbidity and mortality. However, the clinical manifestations of sepsis are highly variable and emergency department (ED) clinicians often must make rapid, impactful decisions before laboratory results are known. We previously developed a technique that allows the measurement of the biophysical properties of white blood cells as they are stretched through a microfluidic channel. In this study we describe and validate the resultant output as a model and score—the IntelliSep Index (ISI)—that aids in the diagnosis of sepsis in patients with suspected or confirmed infection from a single blood draw performed at the time of ED presentation. By applying this technique to a high acuity cohort with a 23.5% sepsis incidence ( n = 307), we defined specific metrics—the aspect ratio and visco-elastic inertial response—that are more sensitive than cell size or cell count in predicting disease severity. The final model was trained and cross-validated on the high acuity cohort, and the performance and generalizability of the model was evaluated on a separate low acuity cohort with a 6.4% sepsis incidence ( n = 94) and healthy donors ( n = 72). For easier clinical interpretation, the ISI is divided into three interpretation bands of Green, Yellow, and Red that correspond to increasing disease severity. The ISI agreed with the diagnosis established by retrospective physician adjudication, and accurately identified subjects with severe illness as measured by SOFA, APACHE-II, hospital-free days, and intensive care unit admission. Measured using routinely collected blood samples, with a short run-time and no requirement for patient or laboratory information, the ISI is well suited to aid ED clinicians in rapidly diagnosing sepsis. |
Audience | Academic |
Author | Guillou, Lionel Shah, Ajay M. Tse, Henry T. K. O’Neal, Hollis R. Thomas, Christopher B. Sheybani, Roya Jensen, Anne E. Caffery, Terrell S. Di Carlo, Dino |
AuthorAffiliation | 3 Louisiana State University Health Sciences Center, Baton Rouge, Louisiana, United States of America Heidelberg University Hospital, GERMANY 1 Cytovale, Inc., San Francisco, California, United States of America 2 Department of Bioengineering, University of California, Los Angeles, California, United States of America |
AuthorAffiliation_xml | – name: 1 Cytovale, Inc., San Francisco, California, United States of America – name: Heidelberg University Hospital, GERMANY – name: 2 Department of Bioengineering, University of California, Los Angeles, California, United States of America – name: 3 Louisiana State University Health Sciences Center, Baton Rouge, Louisiana, United States of America |
Author_xml | – sequence: 1 givenname: Lionel surname: Guillou fullname: Guillou, Lionel – sequence: 2 givenname: Roya surname: Sheybani fullname: Sheybani, Roya – sequence: 3 givenname: Anne E. surname: Jensen fullname: Jensen, Anne E. – sequence: 4 givenname: Dino surname: Di Carlo fullname: Di Carlo, Dino – sequence: 5 givenname: Terrell S. surname: Caffery fullname: Caffery, Terrell S. – sequence: 6 givenname: Christopher B. surname: Thomas fullname: Thomas, Christopher B. – sequence: 7 givenname: Ajay M. surname: Shah fullname: Shah, Ajay M. – sequence: 8 givenname: Henry T. K. orcidid: 0000-0002-0542-2312 surname: Tse fullname: Tse, Henry T. K. – sequence: 9 givenname: Hollis R. surname: O’Neal fullname: O’Neal, Hollis R. |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/33857126$$D View this record in MEDLINE/PubMed |
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CitedBy_id | crossref_primary_10_1038_s41551_023_01015_3 crossref_primary_10_1063_5_0252985 crossref_primary_10_1007_s44258_023_00008_w crossref_primary_10_1111_acem_14923 crossref_primary_10_1146_annurev_biophys_030822_030629 crossref_primary_10_1016_j_bpj_2023_12_008 crossref_primary_10_1080_14737159_2024_2408743 crossref_primary_10_1039_D1LC00731A crossref_primary_10_1128_cmr_00078_24 crossref_primary_10_1016_j_bpj_2022_03_021 crossref_primary_10_1002_smll_202107305 crossref_primary_10_1097_CCE_0000000000000942 crossref_primary_10_1097_CCE_0000000000000460 crossref_primary_10_1002_emp2_12984 crossref_primary_10_1016_j_ebiom_2022_104394 crossref_primary_10_1056_AIoa2400867 crossref_primary_10_1371_journal_pone_0264220 crossref_primary_10_1038_s41378_023_00541_z crossref_primary_10_3389_frlct_2024_1328004 crossref_primary_10_1016_j_amjms_2022_02_008 crossref_primary_10_1097_CCE_0000000000001026 crossref_primary_10_1039_D2LC00904H crossref_primary_10_1093_clinchem_hvad097_414 crossref_primary_10_1097_CCE_0000000000001228 crossref_primary_10_1038_s41551_023_01110_5 |
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Copyright | COPYRIGHT 2021 Public Library of Science 2021 Guillou et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. 2021 Guillou et al 2021 Guillou et al |
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Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 Competing Interests: Authors LG, RS, AEJ, DDC, AMS, and HTKT are affiliated with Cytovale and have an equity interest in the company whose device is the subject of this study. The other authors declare that they have no competing financial interests. The system that is the subject of this study is for investigational use only (not yet cleared for commercial use) and is covered by the following patents: 8,361,415; 8,935,098; 2,619,545; and 9,897,532. This does not alter the authors adherence to PLOS ONE policies on sharing data and materials. |
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Bundle (SEP-1) Sepsis Quality Measure publication-title: Clin Infect Dis |
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Title | Development and validation of a cellular host response test as an early diagnostic for sepsis |
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