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Soft tissue oxygen saturation to predict admission from the emergency department: A prospective observational study
Abstract Objective We evaluated a soft tissue oxygen saturation (Sto2) measurement at triage for predicting admission to the hospital in adults presenting to the emergency department (ED) in addition to data routinely gathered at triage. Methods This was a prospective, observational, single center s...
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Published in: | The American journal of emergency medicine 2017-08, Vol.35 (8), p.1111-1117 |
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description | Abstract Objective We evaluated a soft tissue oxygen saturation (Sto2) measurement at triage for predicting admission to the hospital in adults presenting to the emergency department (ED) in addition to data routinely gathered at triage. Methods This was a prospective, observational, single center study of adults presenting to the ED for evaluation. Research assistants obtained thenar eminence Sto2 measurements on patients in ED triage. ED providers not involved in the study then made all management and disposition decisions. We prospectively collected data on each subject's final ED disposition (admission versus discharge). We identified the optimal Sto2 cutoff value for predicting admission. We then used logistic regression modeling to describe the added predictive value of Sto2 beyond routinely collected triage data including Emergency Severity Index level, age, and vital signs. Results We analyzed 2588 adult (> 17 years) subjects with 743 subjects (28.7%) admitted to the hospital. Sto2 < 76% was the optimal diagnostic cutoff for predicting admission. Of subjects with Sto2 < 76%, 158 of 384 (41.1%) underwent admission versus 585 of 2204 (26.5%) subjects with Sto2 ≥ 76. After controlling for age, vital signs, and ESI level in the logistic regression analysis, Sto2 < 76% had an odds ratio of 1.54 (95% confidence interval (CI), 1.19 to 1.98) for predicting admission. Conclusions Sto2 may provide additional prognostic data to routine triage assessment regarding the disposition for undifferentiated adult patients presenting to the ED. |
doi_str_mv | 10.1016/j.ajem.2017.03.013 |
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Methods This was a prospective, observational, single center study of adults presenting to the ED for evaluation. Research assistants obtained thenar eminence Sto2 measurements on patients in ED triage. ED providers not involved in the study then made all management and disposition decisions. We prospectively collected data on each subject's final ED disposition (admission versus discharge). We identified the optimal Sto2 cutoff value for predicting admission. We then used logistic regression modeling to describe the added predictive value of Sto2 beyond routinely collected triage data including Emergency Severity Index level, age, and vital signs. Results We analyzed 2588 adult (> 17 years) subjects with 743 subjects (28.7%) admitted to the hospital. Sto2 < 76% was the optimal diagnostic cutoff for predicting admission. Of subjects with Sto2 < 76%, 158 of 384 (41.1%) underwent admission versus 585 of 2204 (26.5%) subjects with Sto2 ≥ 76. After controlling for age, vital signs, and ESI level in the logistic regression analysis, Sto2 < 76% had an odds ratio of 1.54 (95% confidence interval (CI), 1.19 to 1.98) for predicting admission. Conclusions Sto2 may provide additional prognostic data to routine triage assessment regarding the disposition for undifferentiated adult patients presenting to the ED.</description><identifier>ISSN: 0735-6757</identifier><identifier>EISSN: 1532-8171</identifier><identifier>DOI: 10.1016/j.ajem.2017.03.013</identifier><identifier>PMID: 28343815</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Adult ; Adults ; Aged ; Ambulatory care ; Clinical decision making ; Confidence intervals ; Critical Illness - therapy ; Data analysis ; Decision making ; Emergency ; Emergency medical care ; Emergency medical services ; Emergency Service, Hospital ; Epidemiology ; Female ; Health care ; Hospital admission tests ; Hospitalization - statistics & numerical data ; Hospitals ; Humans ; Intensive care ; Logistic Models ; Male ; Middle Aged ; Near-infrared ; Observational studies ; Oximetry - methods ; Oxygen ; Oxygen Consumption ; Oxygen content ; Oxygen saturation ; Patients ; Pneumonia ; Predictive Value of Tests ; Prognosis ; Prospective Studies ; Regression analysis ; ROC Curve ; Sepsis ; Severity of Illness Index ; Soft tissue oximetry ; Spectroscopy ; Spectroscopy, Near-Infrared ; Spectrum analysis ; Triage ; Triage - methods ; United States ; Variables</subject><ispartof>The American journal of emergency medicine, 2017-08, Vol.35 (8), p.1111-1117</ispartof><rights>2017</rights><rights>Published by Elsevier Inc.</rights><rights>Copyright Elsevier Limited 2017</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c439t-9d4c1b2950f324e42a07519f50a38ae3b5871b0e788f68f90a5aa1604ef3ffb73</citedby><cites>FETCH-LOGICAL-c439t-9d4c1b2950f324e42a07519f50a38ae3b5871b0e788f68f90a5aa1604ef3ffb73</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/28343815$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Davis, William T</creatorcontrib><creatorcontrib>Lospinso, Josh</creatorcontrib><creatorcontrib>Barnwell, Robert M</creatorcontrib><creatorcontrib>Hughes, John</creatorcontrib><creatorcontrib>Schauer, Steven G</creatorcontrib><creatorcontrib>Smith, Thomas B</creatorcontrib><creatorcontrib>April, Michael D</creatorcontrib><title>Soft tissue oxygen saturation to predict admission from the emergency department: A prospective observational study</title><title>The American journal of emergency medicine</title><addtitle>Am J Emerg Med</addtitle><description>Abstract Objective We evaluated a soft tissue oxygen saturation (Sto2) measurement at triage for predicting admission to the hospital in adults presenting to the emergency department (ED) in addition to data routinely gathered at triage. Methods This was a prospective, observational, single center study of adults presenting to the ED for evaluation. Research assistants obtained thenar eminence Sto2 measurements on patients in ED triage. ED providers not involved in the study then made all management and disposition decisions. We prospectively collected data on each subject's final ED disposition (admission versus discharge). We identified the optimal Sto2 cutoff value for predicting admission. We then used logistic regression modeling to describe the added predictive value of Sto2 beyond routinely collected triage data including Emergency Severity Index level, age, and vital signs. Results We analyzed 2588 adult (> 17 years) subjects with 743 subjects (28.7%) admitted to the hospital. Sto2 < 76% was the optimal diagnostic cutoff for predicting admission. Of subjects with Sto2 < 76%, 158 of 384 (41.1%) underwent admission versus 585 of 2204 (26.5%) subjects with Sto2 ≥ 76. After controlling for age, vital signs, and ESI level in the logistic regression analysis, Sto2 < 76% had an odds ratio of 1.54 (95% confidence interval (CI), 1.19 to 1.98) for predicting admission. Conclusions Sto2 may provide additional prognostic data to routine triage assessment regarding the disposition for undifferentiated adult patients presenting to the ED.</description><subject>Adult</subject><subject>Adults</subject><subject>Aged</subject><subject>Ambulatory care</subject><subject>Clinical decision making</subject><subject>Confidence intervals</subject><subject>Critical Illness - therapy</subject><subject>Data analysis</subject><subject>Decision making</subject><subject>Emergency</subject><subject>Emergency medical care</subject><subject>Emergency medical services</subject><subject>Emergency Service, Hospital</subject><subject>Epidemiology</subject><subject>Female</subject><subject>Health care</subject><subject>Hospital admission tests</subject><subject>Hospitalization - statistics & numerical data</subject><subject>Hospitals</subject><subject>Humans</subject><subject>Intensive care</subject><subject>Logistic Models</subject><subject>Male</subject><subject>Middle Aged</subject><subject>Near-infrared</subject><subject>Observational studies</subject><subject>Oximetry - methods</subject><subject>Oxygen</subject><subject>Oxygen Consumption</subject><subject>Oxygen content</subject><subject>Oxygen saturation</subject><subject>Patients</subject><subject>Pneumonia</subject><subject>Predictive Value of Tests</subject><subject>Prognosis</subject><subject>Prospective Studies</subject><subject>Regression analysis</subject><subject>ROC Curve</subject><subject>Sepsis</subject><subject>Severity of Illness Index</subject><subject>Soft tissue oximetry</subject><subject>Spectroscopy</subject><subject>Spectroscopy, Near-Infrared</subject><subject>Spectrum analysis</subject><subject>Triage</subject><subject>Triage - methods</subject><subject>United States</subject><subject>Variables</subject><issn>0735-6757</issn><issn>1532-8171</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><recordid>eNp9kkuLFDEUhYMoTs_oH3AhATduqs2zkhIRhmF8wICL0XVIpW40ZT3aJNVY_96UPSrMwlUgnPNx7zkXoWeU7Cmh9at-b3sY94xQtSd8Tyh_gHZUclZpquhDtCOKy6pWUp2h85R6QigVUjxGZ0xzwTWVO5RuZ59xDiktgOef61eYcLJ5iTaHecJ5xocIXXAZ224squ3Tx3nE-RtgGCEWg1txBwcb8whTfo0vi2VOB3A5HAuzTRCPv2l2wCkv3foEPfJ2SPD07r1AX95df776UN18ev_x6vKmcoI3uWo64WjLGkk8ZwIEs0RJ2nhJLNcWeCu1oi0BpbWvtW-IldbSmgjw3PtW8Qv08sQt8_xYIGVTNnAwDHaCeUmGak2FqJuaFOmLe9J-XmKZuKgaJiQTWm9AdlK5smCK4M0hhtHG1VBitkpMb7ZKzFaJIdyUSorp-R16aUfo_lr-dFAEb04CKFkcA0STXCiplthjCdF0c_g__-09uxvCFJwdvsMK6d8eJjFDzO12FNtNUMULpaH8F9cfszA</recordid><startdate>20170801</startdate><enddate>20170801</enddate><creator>Davis, William T</creator><creator>Lospinso, Josh</creator><creator>Barnwell, Robert M</creator><creator>Hughes, John</creator><creator>Schauer, Steven G</creator><creator>Smith, Thomas B</creator><creator>April, Michael D</creator><general>Elsevier Inc</general><general>Elsevier Limited</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7RV</scope><scope>7T5</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>H94</scope><scope>K9.</scope><scope>KB0</scope><scope>M0S</scope><scope>M1P</scope><scope>M2O</scope><scope>MBDVC</scope><scope>NAPCQ</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>Q9U</scope><scope>7X8</scope></search><sort><creationdate>20170801</creationdate><title>Soft tissue oxygen saturation to predict admission from the emergency department: A prospective observational study</title><author>Davis, William T ; Lospinso, Josh ; Barnwell, Robert M ; Hughes, John ; Schauer, Steven G ; Smith, Thomas B ; April, Michael D</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c439t-9d4c1b2950f324e42a07519f50a38ae3b5871b0e788f68f90a5aa1604ef3ffb73</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Adult</topic><topic>Adults</topic><topic>Aged</topic><topic>Ambulatory care</topic><topic>Clinical decision making</topic><topic>Confidence intervals</topic><topic>Critical Illness - therapy</topic><topic>Data analysis</topic><topic>Decision making</topic><topic>Emergency</topic><topic>Emergency medical care</topic><topic>Emergency medical services</topic><topic>Emergency Service, Hospital</topic><topic>Epidemiology</topic><topic>Female</topic><topic>Health care</topic><topic>Hospital admission tests</topic><topic>Hospitalization - statistics & numerical data</topic><topic>Hospitals</topic><topic>Humans</topic><topic>Intensive care</topic><topic>Logistic Models</topic><topic>Male</topic><topic>Middle Aged</topic><topic>Near-infrared</topic><topic>Observational studies</topic><topic>Oximetry - methods</topic><topic>Oxygen</topic><topic>Oxygen Consumption</topic><topic>Oxygen content</topic><topic>Oxygen saturation</topic><topic>Patients</topic><topic>Pneumonia</topic><topic>Predictive Value of Tests</topic><topic>Prognosis</topic><topic>Prospective Studies</topic><topic>Regression analysis</topic><topic>ROC Curve</topic><topic>Sepsis</topic><topic>Severity of Illness Index</topic><topic>Soft tissue oximetry</topic><topic>Spectroscopy</topic><topic>Spectroscopy, Near-Infrared</topic><topic>Spectrum analysis</topic><topic>Triage</topic><topic>Triage - methods</topic><topic>United States</topic><topic>Variables</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Davis, William T</creatorcontrib><creatorcontrib>Lospinso, Josh</creatorcontrib><creatorcontrib>Barnwell, Robert M</creatorcontrib><creatorcontrib>Hughes, John</creatorcontrib><creatorcontrib>Schauer, Steven G</creatorcontrib><creatorcontrib>Smith, Thomas B</creatorcontrib><creatorcontrib>April, Michael D</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Proquest Nursing & Allied Health Source</collection><collection>Immunology Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>AIDS and Cancer Research Abstracts</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>Research Library</collection><collection>Research Library (Corporate)</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 Basic</collection><collection>MEDLINE - Academic</collection><jtitle>The American journal of emergency medicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Davis, William T</au><au>Lospinso, Josh</au><au>Barnwell, Robert M</au><au>Hughes, John</au><au>Schauer, Steven G</au><au>Smith, Thomas B</au><au>April, Michael D</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Soft tissue oxygen saturation to predict admission from the emergency department: A prospective observational study</atitle><jtitle>The American journal of emergency medicine</jtitle><addtitle>Am J Emerg Med</addtitle><date>2017-08-01</date><risdate>2017</risdate><volume>35</volume><issue>8</issue><spage>1111</spage><epage>1117</epage><pages>1111-1117</pages><issn>0735-6757</issn><eissn>1532-8171</eissn><abstract>Abstract Objective We evaluated a soft tissue oxygen saturation (Sto2) measurement at triage for predicting admission to the hospital in adults presenting to the emergency department (ED) in addition to data routinely gathered at triage. Methods This was a prospective, observational, single center study of adults presenting to the ED for evaluation. Research assistants obtained thenar eminence Sto2 measurements on patients in ED triage. ED providers not involved in the study then made all management and disposition decisions. We prospectively collected data on each subject's final ED disposition (admission versus discharge). We identified the optimal Sto2 cutoff value for predicting admission. We then used logistic regression modeling to describe the added predictive value of Sto2 beyond routinely collected triage data including Emergency Severity Index level, age, and vital signs. Results We analyzed 2588 adult (> 17 years) subjects with 743 subjects (28.7%) admitted to the hospital. Sto2 < 76% was the optimal diagnostic cutoff for predicting admission. Of subjects with Sto2 < 76%, 158 of 384 (41.1%) underwent admission versus 585 of 2204 (26.5%) subjects with Sto2 ≥ 76. After controlling for age, vital signs, and ESI level in the logistic regression analysis, Sto2 < 76% had an odds ratio of 1.54 (95% confidence interval (CI), 1.19 to 1.98) for predicting admission. Conclusions Sto2 may provide additional prognostic data to routine triage assessment regarding the disposition for undifferentiated adult patients presenting to the ED.</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>28343815</pmid><doi>10.1016/j.ajem.2017.03.013</doi><tpages>7</tpages></addata></record> |
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subjects | Adult Adults Aged Ambulatory care Clinical decision making Confidence intervals Critical Illness - therapy Data analysis Decision making Emergency Emergency medical care Emergency medical services Emergency Service, Hospital Epidemiology Female Health care Hospital admission tests Hospitalization - statistics & numerical data Hospitals Humans Intensive care Logistic Models Male Middle Aged Near-infrared Observational studies Oximetry - methods Oxygen Oxygen Consumption Oxygen content Oxygen saturation Patients Pneumonia Predictive Value of Tests Prognosis Prospective Studies Regression analysis ROC Curve Sepsis Severity of Illness Index Soft tissue oximetry Spectroscopy Spectroscopy, Near-Infrared Spectrum analysis Triage Triage - methods United States Variables |
title | Soft tissue oxygen saturation to predict admission from the emergency department: A prospective observational study |
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