Identifying Novel Sepsis Subphenotypes Using Temperature Trajectories
Sepsis is a heterogeneous syndrome, and identifying clinically relevant subphenotypes is essential. To identify novel subphenotypes in hospitalized patients with infection using longitudinal temperature trajectories. In the model development cohort, inpatient admissions meeting criteria for infectio...
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Veröffentlicht in: | American journal of respiratory and critical care medicine 2019-08, Vol.200 (3), p.327-335 |
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creator | Bhavani, Sivasubramanium V Carey, Kyle A Gilbert, Emily R Afshar, Majid Verhoef, Philip A Churpek, Matthew M |
description | Sepsis is a heterogeneous syndrome, and identifying clinically relevant subphenotypes is essential.
To identify novel subphenotypes in hospitalized patients with infection using longitudinal temperature trajectories.
In the model development cohort, inpatient admissions meeting criteria for infection in the emergency department and receiving antibiotics within 24 hours of presentation were included. Temperature measurements within the first 72 hours were compared between survivors and nonsurvivors. Group-based trajectory modeling was performed to identify temperature trajectory groups, and patient characteristics and outcomes were compared between the groups. The model was then externally validated at a second hospital using the same inclusion criteria.
A total of 12,413 admissions were included in the development cohort, and 19,053 were included in the validation cohort. In the development cohort, four temperature trajectory groups were identified: "hyperthermic, slow resolvers" (
= 1,855; 14.9% of the cohort); "hyperthermic, fast resolvers" (
= 2,877; 23.2%); "normothermic" (
= 4,067; 32.8%); and "hypothermic" (
= 3,614; 29.1%). The hypothermic subjects were the oldest and had the most comorbidities, the lowest levels of inflammatory markers, and the highest in-hospital mortality rate (9.5%). The hyperthermic, slow resolvers were the youngest and had the fewest comorbidities, the highest levels of inflammatory markers, and a mortality rate of 5.1%. The hyperthermic, fast resolvers had the lowest mortality rate (2.9%). Similar trajectory groups, patient characteristics, and outcomes were found in the validation cohort.
We identified and validated four novel subphenotypes of patients with infection, with significant variability in inflammatory markers and outcomes. |
doi_str_mv | 10.1164/rccm.201806-1197OC |
format | Article |
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To identify novel subphenotypes in hospitalized patients with infection using longitudinal temperature trajectories.
In the model development cohort, inpatient admissions meeting criteria for infection in the emergency department and receiving antibiotics within 24 hours of presentation were included. Temperature measurements within the first 72 hours were compared between survivors and nonsurvivors. Group-based trajectory modeling was performed to identify temperature trajectory groups, and patient characteristics and outcomes were compared between the groups. The model was then externally validated at a second hospital using the same inclusion criteria.
A total of 12,413 admissions were included in the development cohort, and 19,053 were included in the validation cohort. In the development cohort, four temperature trajectory groups were identified: "hyperthermic, slow resolvers" (
= 1,855; 14.9% of the cohort); "hyperthermic, fast resolvers" (
= 2,877; 23.2%); "normothermic" (
= 4,067; 32.8%); and "hypothermic" (
= 3,614; 29.1%). The hypothermic subjects were the oldest and had the most comorbidities, the lowest levels of inflammatory markers, and the highest in-hospital mortality rate (9.5%). The hyperthermic, slow resolvers were the youngest and had the fewest comorbidities, the highest levels of inflammatory markers, and a mortality rate of 5.1%. The hyperthermic, fast resolvers had the lowest mortality rate (2.9%). Similar trajectory groups, patient characteristics, and outcomes were found in the validation cohort.
We identified and validated four novel subphenotypes of patients with infection, with significant variability in inflammatory markers and outcomes.</description><identifier>ISSN: 1073-449X</identifier><identifier>EISSN: 1535-4970</identifier><identifier>DOI: 10.1164/rccm.201806-1197OC</identifier><identifier>PMID: 30789749</identifier><language>eng</language><publisher>United States: American Thoracic Society</publisher><subject>Aged ; Antibiotics ; Body Temperature ; Cohort Studies ; Cytokines ; Demographics ; Female ; Fever ; Fever - diagnosis ; Fever - etiology ; Fever - therapy ; Hospital Mortality ; Hospitalization ; Humans ; Immunology ; Infections ; Intensive care ; Laboratories ; Male ; Medicine ; Middle Aged ; Mortality ; Original ; Patients ; Pediatrics ; Physiology ; Sepsis ; Sepsis - complications ; Sepsis - mortality ; Sepsis - therapy ; Time Factors ; Vital signs</subject><ispartof>American journal of respiratory and critical care medicine, 2019-08, Vol.200 (3), p.327-335</ispartof><rights>Copyright American Thoracic Society Aug 1, 2019</rights><rights>Copyright © 2019 by the American Thoracic Society 2019</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><orcidid>0000-0002-9640-6720 ; 0000-0002-1502-5468</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,780,784,885,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/30789749$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Bhavani, Sivasubramanium V</creatorcontrib><creatorcontrib>Carey, Kyle A</creatorcontrib><creatorcontrib>Gilbert, Emily R</creatorcontrib><creatorcontrib>Afshar, Majid</creatorcontrib><creatorcontrib>Verhoef, Philip A</creatorcontrib><creatorcontrib>Churpek, Matthew M</creatorcontrib><title>Identifying Novel Sepsis Subphenotypes Using Temperature Trajectories</title><title>American journal of respiratory and critical care medicine</title><addtitle>Am J Respir Crit Care Med</addtitle><description>Sepsis is a heterogeneous syndrome, and identifying clinically relevant subphenotypes is essential.
To identify novel subphenotypes in hospitalized patients with infection using longitudinal temperature trajectories.
In the model development cohort, inpatient admissions meeting criteria for infection in the emergency department and receiving antibiotics within 24 hours of presentation were included. Temperature measurements within the first 72 hours were compared between survivors and nonsurvivors. Group-based trajectory modeling was performed to identify temperature trajectory groups, and patient characteristics and outcomes were compared between the groups. The model was then externally validated at a second hospital using the same inclusion criteria.
A total of 12,413 admissions were included in the development cohort, and 19,053 were included in the validation cohort. In the development cohort, four temperature trajectory groups were identified: "hyperthermic, slow resolvers" (
= 1,855; 14.9% of the cohort); "hyperthermic, fast resolvers" (
= 2,877; 23.2%); "normothermic" (
= 4,067; 32.8%); and "hypothermic" (
= 3,614; 29.1%). The hypothermic subjects were the oldest and had the most comorbidities, the lowest levels of inflammatory markers, and the highest in-hospital mortality rate (9.5%). The hyperthermic, slow resolvers were the youngest and had the fewest comorbidities, the highest levels of inflammatory markers, and a mortality rate of 5.1%. The hyperthermic, fast resolvers had the lowest mortality rate (2.9%). Similar trajectory groups, patient characteristics, and outcomes were found in the validation cohort.
We identified and validated four novel subphenotypes of patients with infection, with significant variability in inflammatory markers and outcomes.</description><subject>Aged</subject><subject>Antibiotics</subject><subject>Body Temperature</subject><subject>Cohort Studies</subject><subject>Cytokines</subject><subject>Demographics</subject><subject>Female</subject><subject>Fever</subject><subject>Fever - diagnosis</subject><subject>Fever - etiology</subject><subject>Fever - therapy</subject><subject>Hospital Mortality</subject><subject>Hospitalization</subject><subject>Humans</subject><subject>Immunology</subject><subject>Infections</subject><subject>Intensive care</subject><subject>Laboratories</subject><subject>Male</subject><subject>Medicine</subject><subject>Middle Aged</subject><subject>Mortality</subject><subject>Original</subject><subject>Patients</subject><subject>Pediatrics</subject><subject>Physiology</subject><subject>Sepsis</subject><subject>Sepsis - complications</subject><subject>Sepsis - mortality</subject><subject>Sepsis - therapy</subject><subject>Time Factors</subject><subject>Vital signs</subject><issn>1073-449X</issn><issn>1535-4970</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><recordid>eNpdkEtLAzEUhYMotlb_gAsZcONmNLnJJJmNIMVHodhFW3A3ZDK37ZR5mcwI_fdOsYq6ugfu4eOcQ8glo7eMSXHnrC1vgTJNZchYrGbjIzJkEY9CESt63GuqeChE_DYgZ95vKWWgGT0lA06VjpWIh-RxkmHV5qtdXq2D1_oDi2COjc99MO_SZoNV3e4a9MHS7w0LLBt0pu0cBgtntmjb2uXoz8nJyhQeLw53RJZPj4vxSzidPU_GD9OwARBtmCmRxVxmoC0FaSFbIZpIcxsjZ4qjyFIKGIGxKpVaAaSCG5AKmaGaGsZH5P6L23RpiZntoztTJI3LS-N2SW3y5O-nyjfJuv5IpNS0L90Dbg4AV7936NukzL3FojAV1p1PgOkokpoB7a3X_6zbunNVXy8B6NcDIfgeePU70U-U74X5J15qf9Q</recordid><startdate>20190801</startdate><enddate>20190801</enddate><creator>Bhavani, Sivasubramanium V</creator><creator>Carey, Kyle A</creator><creator>Gilbert, Emily R</creator><creator>Afshar, Majid</creator><creator>Verhoef, Philip A</creator><creator>Churpek, Matthew M</creator><general>American Thoracic Society</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>3V.</scope><scope>7RV</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AN0</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>K9.</scope><scope>KB0</scope><scope>M0S</scope><scope>M1P</scope><scope>NAPCQ</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0002-9640-6720</orcidid><orcidid>https://orcid.org/0000-0002-1502-5468</orcidid></search><sort><creationdate>20190801</creationdate><title>Identifying Novel Sepsis Subphenotypes Using Temperature Trajectories</title><author>Bhavani, Sivasubramanium V ; Carey, Kyle A ; Gilbert, Emily R ; Afshar, Majid ; Verhoef, Philip A ; Churpek, Matthew M</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-p224t-d74d936d28c026c2dfeea583c9e3173e4db02e52ac7b68722b43a267e1a080a13</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Aged</topic><topic>Antibiotics</topic><topic>Body Temperature</topic><topic>Cohort Studies</topic><topic>Cytokines</topic><topic>Demographics</topic><topic>Female</topic><topic>Fever</topic><topic>Fever - diagnosis</topic><topic>Fever - etiology</topic><topic>Fever - therapy</topic><topic>Hospital Mortality</topic><topic>Hospitalization</topic><topic>Humans</topic><topic>Immunology</topic><topic>Infections</topic><topic>Intensive care</topic><topic>Laboratories</topic><topic>Male</topic><topic>Medicine</topic><topic>Middle Aged</topic><topic>Mortality</topic><topic>Original</topic><topic>Patients</topic><topic>Pediatrics</topic><topic>Physiology</topic><topic>Sepsis</topic><topic>Sepsis - complications</topic><topic>Sepsis - mortality</topic><topic>Sepsis - therapy</topic><topic>Time Factors</topic><topic>Vital signs</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Bhavani, Sivasubramanium V</creatorcontrib><creatorcontrib>Carey, Kyle A</creatorcontrib><creatorcontrib>Gilbert, Emily R</creatorcontrib><creatorcontrib>Afshar, Majid</creatorcontrib><creatorcontrib>Verhoef, Philip A</creatorcontrib><creatorcontrib>Churpek, Matthew M</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>ProQuest Central (Corporate)</collection><collection>Nursing & Allied Health Database</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Public Health Database</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>British Nursing Database</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Nursing & Allied Health Premium</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>American journal of respiratory and critical care medicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Bhavani, Sivasubramanium V</au><au>Carey, Kyle A</au><au>Gilbert, Emily R</au><au>Afshar, Majid</au><au>Verhoef, Philip A</au><au>Churpek, Matthew M</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Identifying Novel Sepsis Subphenotypes Using Temperature Trajectories</atitle><jtitle>American journal of respiratory and critical care medicine</jtitle><addtitle>Am J Respir Crit Care Med</addtitle><date>2019-08-01</date><risdate>2019</risdate><volume>200</volume><issue>3</issue><spage>327</spage><epage>335</epage><pages>327-335</pages><issn>1073-449X</issn><eissn>1535-4970</eissn><abstract>Sepsis is a heterogeneous syndrome, and identifying clinically relevant subphenotypes is essential.
To identify novel subphenotypes in hospitalized patients with infection using longitudinal temperature trajectories.
In the model development cohort, inpatient admissions meeting criteria for infection in the emergency department and receiving antibiotics within 24 hours of presentation were included. Temperature measurements within the first 72 hours were compared between survivors and nonsurvivors. Group-based trajectory modeling was performed to identify temperature trajectory groups, and patient characteristics and outcomes were compared between the groups. The model was then externally validated at a second hospital using the same inclusion criteria.
A total of 12,413 admissions were included in the development cohort, and 19,053 were included in the validation cohort. In the development cohort, four temperature trajectory groups were identified: "hyperthermic, slow resolvers" (
= 1,855; 14.9% of the cohort); "hyperthermic, fast resolvers" (
= 2,877; 23.2%); "normothermic" (
= 4,067; 32.8%); and "hypothermic" (
= 3,614; 29.1%). The hypothermic subjects were the oldest and had the most comorbidities, the lowest levels of inflammatory markers, and the highest in-hospital mortality rate (9.5%). The hyperthermic, slow resolvers were the youngest and had the fewest comorbidities, the highest levels of inflammatory markers, and a mortality rate of 5.1%. The hyperthermic, fast resolvers had the lowest mortality rate (2.9%). Similar trajectory groups, patient characteristics, and outcomes were found in the validation cohort.
We identified and validated four novel subphenotypes of patients with infection, with significant variability in inflammatory markers and outcomes.</abstract><cop>United States</cop><pub>American Thoracic Society</pub><pmid>30789749</pmid><doi>10.1164/rccm.201806-1197OC</doi><tpages>9</tpages><orcidid>https://orcid.org/0000-0002-9640-6720</orcidid><orcidid>https://orcid.org/0000-0002-1502-5468</orcidid><oa>free_for_read</oa></addata></record> |
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source | MEDLINE; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; American Thoracic Society (ATS) Journals Online; Alma/SFX Local Collection |
subjects | Aged Antibiotics Body Temperature Cohort Studies Cytokines Demographics Female Fever Fever - diagnosis Fever - etiology Fever - therapy Hospital Mortality Hospitalization Humans Immunology Infections Intensive care Laboratories Male Medicine Middle Aged Mortality Original Patients Pediatrics Physiology Sepsis Sepsis - complications Sepsis - mortality Sepsis - therapy Time Factors Vital signs |
title | Identifying Novel Sepsis Subphenotypes Using Temperature Trajectories |
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