Computerized decision support system improves fluid resuscitation following severe burns: An original study
OBJECTIVE:Several formulas have been developed to guide resuscitation in severely burned patients during the initial 48 hrs after injury. These approaches require manual titration of fluid that may result in human error during this process and lead to suboptimal outcomes. The goal of this study was...
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| Veröffentlicht in: | Critical care medicine 2011-09, Vol.39 (9), p.2031-2038 |
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| creator | Salinas, José Chung, Kevin K Mann, Elizabeth A Cancio, Leopoldo C Kramer, George C Serio-Melvin, Maria L Renz, Evan M Wade, Charles E Wolf, Steven E |
| description | OBJECTIVE:Several formulas have been developed to guide resuscitation in severely burned patients during the initial 48 hrs after injury. These approaches require manual titration of fluid that may result in human error during this process and lead to suboptimal outcomes. The goal of this study was to analyze the efficacy of a computerized open-loop decision support system for burn resuscitation compared to historical controls.
DESIGN:Fluid infusion rates and urinary output from 39 severely burned patients with >20% total body surface area burns were recorded upon admission (Model group). A fluid-response model based on these data was developed and incorporated into a computerized open-loop algorithm and computer decision support system. The computer decision support system was used to resuscitate 32 subsequent patients with severe burns (computer decision support system group) and compared with the Model group.
SETTING:Burn intensive care unit of a metropolitan Level 1 Trauma center.
PATIENTS:Acute burn patients with >20% total body surface area requiring active fluid resuscitation during the initial 24 to 48 hours after burn.
MEASUREMENTS AND MAIN RESULTS:We found no significant difference between the Model and computer decision support system groups in age, total body surface area, or injury mechanism. Total crystalloid volume during the first 48 hrs post burn, total crystalloid intensive care unit volume, and initial 24-hr crystalloid intensive care unit volume were all lower in the computer decision support system group. Infused volume per kilogram body weight (mL/kg) and per percentage burn (mL/kg/total body surface area) were also lower for the computer decision support system group. The number of patients who met hourly urinary output goals was higher in the computer decision support system group.
CONCLUSIONS:Implementation of a computer decision support system for burn resuscitation in the intensive care unit resulted in improved fluid management of severely burned patients. All measures of crystalloid fluid volume were reduced while patients were maintained within urinary output targets a higher percentage of the time. The addition of computer decision support system technology improved patient care. |
| doi_str_mv | 10.1097/CCM.0b013e31821cb790 |
| format | Article |
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DESIGN:Fluid infusion rates and urinary output from 39 severely burned patients with >20% total body surface area burns were recorded upon admission (Model group). A fluid-response model based on these data was developed and incorporated into a computerized open-loop algorithm and computer decision support system. The computer decision support system was used to resuscitate 32 subsequent patients with severe burns (computer decision support system group) and compared with the Model group.
SETTING:Burn intensive care unit of a metropolitan Level 1 Trauma center.
PATIENTS:Acute burn patients with >20% total body surface area requiring active fluid resuscitation during the initial 24 to 48 hours after burn.
MEASUREMENTS AND MAIN RESULTS:We found no significant difference between the Model and computer decision support system groups in age, total body surface area, or injury mechanism. Total crystalloid volume during the first 48 hrs post burn, total crystalloid intensive care unit volume, and initial 24-hr crystalloid intensive care unit volume were all lower in the computer decision support system group. Infused volume per kilogram body weight (mL/kg) and per percentage burn (mL/kg/total body surface area) were also lower for the computer decision support system group. The number of patients who met hourly urinary output goals was higher in the computer decision support system group.
CONCLUSIONS:Implementation of a computer decision support system for burn resuscitation in the intensive care unit resulted in improved fluid management of severely burned patients. All measures of crystalloid fluid volume were reduced while patients were maintained within urinary output targets a higher percentage of the time. The addition of computer decision support system technology improved patient care.</description><identifier>ISSN: 0090-3493</identifier><identifier>EISSN: 1530-0293</identifier><identifier>DOI: 10.1097/CCM.0b013e31821cb790</identifier><identifier>PMID: 21532472</identifier><identifier>CODEN: CCMDC7</identifier><language>eng</language><publisher>Hagerstown, MD: by the Society of Critical Care Medicine and Lippincott Williams & Wilkins</publisher><subject>Adult ; Algorithms ; Anesthesia. Intensive care medicine. Transfusions. Cell therapy and gene therapy ; Biological and medical sciences ; Burns - therapy ; Decision Making, Computer-Assisted ; Emergency and intensive cardiocirculatory care. Cardiogenic shock. Coronary intensive care ; Female ; Fluid Therapy - methods ; Humans ; Intensive care medicine ; Intensive Care Units ; Male ; Medical sciences ; Middle Aged ; Rehydration Solutions - administration & dosage ; Rehydration Solutions - therapeutic use ; Resuscitation - methods</subject><ispartof>Critical care medicine, 2011-09, Vol.39 (9), p.2031-2038</ispartof><rights>2011 by the Society of Critical Care Medicine and Lippincott Williams & Wilkins</rights><rights>2015 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3850-f86df96593cd2f349daaeea7cd5bc9fb46a323aaf38e410737e461aff6a426743</citedby><cites>FETCH-LOGICAL-c3850-f86df96593cd2f349daaeea7cd5bc9fb46a323aaf38e410737e461aff6a426743</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27901,27902</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=24444101$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/21532472$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Salinas, José</creatorcontrib><creatorcontrib>Chung, Kevin K</creatorcontrib><creatorcontrib>Mann, Elizabeth A</creatorcontrib><creatorcontrib>Cancio, Leopoldo C</creatorcontrib><creatorcontrib>Kramer, George C</creatorcontrib><creatorcontrib>Serio-Melvin, Maria L</creatorcontrib><creatorcontrib>Renz, Evan M</creatorcontrib><creatorcontrib>Wade, Charles E</creatorcontrib><creatorcontrib>Wolf, Steven E</creatorcontrib><title>Computerized decision support system improves fluid resuscitation following severe burns: An original study</title><title>Critical care medicine</title><addtitle>Crit Care Med</addtitle><description>OBJECTIVE:Several formulas have been developed to guide resuscitation in severely burned patients during the initial 48 hrs after injury. These approaches require manual titration of fluid that may result in human error during this process and lead to suboptimal outcomes. The goal of this study was to analyze the efficacy of a computerized open-loop decision support system for burn resuscitation compared to historical controls.
DESIGN:Fluid infusion rates and urinary output from 39 severely burned patients with >20% total body surface area burns were recorded upon admission (Model group). A fluid-response model based on these data was developed and incorporated into a computerized open-loop algorithm and computer decision support system. The computer decision support system was used to resuscitate 32 subsequent patients with severe burns (computer decision support system group) and compared with the Model group.
SETTING:Burn intensive care unit of a metropolitan Level 1 Trauma center.
PATIENTS:Acute burn patients with >20% total body surface area requiring active fluid resuscitation during the initial 24 to 48 hours after burn.
MEASUREMENTS AND MAIN RESULTS:We found no significant difference between the Model and computer decision support system groups in age, total body surface area, or injury mechanism. Total crystalloid volume during the first 48 hrs post burn, total crystalloid intensive care unit volume, and initial 24-hr crystalloid intensive care unit volume were all lower in the computer decision support system group. Infused volume per kilogram body weight (mL/kg) and per percentage burn (mL/kg/total body surface area) were also lower for the computer decision support system group. The number of patients who met hourly urinary output goals was higher in the computer decision support system group.
CONCLUSIONS:Implementation of a computer decision support system for burn resuscitation in the intensive care unit resulted in improved fluid management of severely burned patients. All measures of crystalloid fluid volume were reduced while patients were maintained within urinary output targets a higher percentage of the time. The addition of computer decision support system technology improved patient care.</description><subject>Adult</subject><subject>Algorithms</subject><subject>Anesthesia. Intensive care medicine. Transfusions. Cell therapy and gene therapy</subject><subject>Biological and medical sciences</subject><subject>Burns - therapy</subject><subject>Decision Making, Computer-Assisted</subject><subject>Emergency and intensive cardiocirculatory care. Cardiogenic shock. Coronary intensive care</subject><subject>Female</subject><subject>Fluid Therapy - methods</subject><subject>Humans</subject><subject>Intensive care medicine</subject><subject>Intensive Care Units</subject><subject>Male</subject><subject>Medical sciences</subject><subject>Middle Aged</subject><subject>Rehydration Solutions - administration & dosage</subject><subject>Rehydration Solutions - therapeutic use</subject><subject>Resuscitation - methods</subject><issn>0090-3493</issn><issn>1530-0293</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kU1v1DAQhi0EokvhHyDkC-KU4q98cauiQpGKeinnyHHGrakTB0_c1fbX49UuReLQuczlmZlXzxDynrMzztr6c9f9OGMD4xIkbwQ3Q92yF2TDS8kKJlr5kmwYa1khVStPyBvEX4xxVdbyNTkRmRKqFhty34VpSStE9wgjHcE4dGGmmJYlxJXiDleYqJuWGB4AqfXJjTQCJjRu1euetcH7sHXzLUV4gAh0SHHGL_R8piG6WzdrT3FN4-4teWW1R3h37Kfk59eLm-6yuLr-9r07vyqMbEpW2KYabVuVrTSjsDn-qDWArs1YDqa1g6q0FFJrKxtQnNWyBlVxbW2llahqJU_Jp8PeHPp3Alz7yaEB7_UMIWHfNEoJ2XKeSXUgTQyIEWy_RDfpuOs56_eW-2y5_99yHvtwPJCGCcanob9aM_DxCGg02tuo5yz2H6dycba_3xy4bfD5B3jv0xZifwfar3fPZ_gDWRebPQ</recordid><startdate>201109</startdate><enddate>201109</enddate><creator>Salinas, José</creator><creator>Chung, Kevin K</creator><creator>Mann, Elizabeth A</creator><creator>Cancio, Leopoldo C</creator><creator>Kramer, George C</creator><creator>Serio-Melvin, Maria L</creator><creator>Renz, Evan M</creator><creator>Wade, Charles E</creator><creator>Wolf, Steven E</creator><general>by the Society of Critical Care Medicine and Lippincott Williams & Wilkins</general><general>Lippincott Williams & Wilkins</general><scope>IQODW</scope><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>7X8</scope></search><sort><creationdate>201109</creationdate><title>Computerized decision support system improves fluid resuscitation following severe burns: An original study</title><author>Salinas, José ; Chung, Kevin K ; Mann, Elizabeth A ; Cancio, Leopoldo C ; Kramer, George C ; Serio-Melvin, Maria L ; Renz, Evan M ; Wade, Charles E ; Wolf, Steven E</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3850-f86df96593cd2f349daaeea7cd5bc9fb46a323aaf38e410737e461aff6a426743</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Adult</topic><topic>Algorithms</topic><topic>Anesthesia. Intensive care medicine. Transfusions. Cell therapy and gene therapy</topic><topic>Biological and medical sciences</topic><topic>Burns - therapy</topic><topic>Decision Making, Computer-Assisted</topic><topic>Emergency and intensive cardiocirculatory care. Cardiogenic shock. Coronary intensive care</topic><topic>Female</topic><topic>Fluid Therapy - methods</topic><topic>Humans</topic><topic>Intensive care medicine</topic><topic>Intensive Care Units</topic><topic>Male</topic><topic>Medical sciences</topic><topic>Middle Aged</topic><topic>Rehydration Solutions - administration & dosage</topic><topic>Rehydration Solutions - therapeutic use</topic><topic>Resuscitation - methods</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Salinas, José</creatorcontrib><creatorcontrib>Chung, Kevin K</creatorcontrib><creatorcontrib>Mann, Elizabeth A</creatorcontrib><creatorcontrib>Cancio, Leopoldo C</creatorcontrib><creatorcontrib>Kramer, George C</creatorcontrib><creatorcontrib>Serio-Melvin, Maria L</creatorcontrib><creatorcontrib>Renz, Evan M</creatorcontrib><creatorcontrib>Wade, Charles E</creatorcontrib><creatorcontrib>Wolf, Steven E</creatorcontrib><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Critical care medicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Salinas, José</au><au>Chung, Kevin K</au><au>Mann, Elizabeth A</au><au>Cancio, Leopoldo C</au><au>Kramer, George C</au><au>Serio-Melvin, Maria L</au><au>Renz, Evan M</au><au>Wade, Charles E</au><au>Wolf, Steven E</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Computerized decision support system improves fluid resuscitation following severe burns: An original study</atitle><jtitle>Critical care medicine</jtitle><addtitle>Crit Care Med</addtitle><date>2011-09</date><risdate>2011</risdate><volume>39</volume><issue>9</issue><spage>2031</spage><epage>2038</epage><pages>2031-2038</pages><issn>0090-3493</issn><eissn>1530-0293</eissn><coden>CCMDC7</coden><abstract>OBJECTIVE:Several formulas have been developed to guide resuscitation in severely burned patients during the initial 48 hrs after injury. These approaches require manual titration of fluid that may result in human error during this process and lead to suboptimal outcomes. The goal of this study was to analyze the efficacy of a computerized open-loop decision support system for burn resuscitation compared to historical controls.
DESIGN:Fluid infusion rates and urinary output from 39 severely burned patients with >20% total body surface area burns were recorded upon admission (Model group). A fluid-response model based on these data was developed and incorporated into a computerized open-loop algorithm and computer decision support system. The computer decision support system was used to resuscitate 32 subsequent patients with severe burns (computer decision support system group) and compared with the Model group.
SETTING:Burn intensive care unit of a metropolitan Level 1 Trauma center.
PATIENTS:Acute burn patients with >20% total body surface area requiring active fluid resuscitation during the initial 24 to 48 hours after burn.
MEASUREMENTS AND MAIN RESULTS:We found no significant difference between the Model and computer decision support system groups in age, total body surface area, or injury mechanism. Total crystalloid volume during the first 48 hrs post burn, total crystalloid intensive care unit volume, and initial 24-hr crystalloid intensive care unit volume were all lower in the computer decision support system group. Infused volume per kilogram body weight (mL/kg) and per percentage burn (mL/kg/total body surface area) were also lower for the computer decision support system group. The number of patients who met hourly urinary output goals was higher in the computer decision support system group.
CONCLUSIONS:Implementation of a computer decision support system for burn resuscitation in the intensive care unit resulted in improved fluid management of severely burned patients. All measures of crystalloid fluid volume were reduced while patients were maintained within urinary output targets a higher percentage of the time. The addition of computer decision support system technology improved patient care.</abstract><cop>Hagerstown, MD</cop><pub>by the Society of Critical Care Medicine and Lippincott Williams & Wilkins</pub><pmid>21532472</pmid><doi>10.1097/CCM.0b013e31821cb790</doi><tpages>8</tpages></addata></record> |
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| ispartof | Critical care medicine, 2011-09, Vol.39 (9), p.2031-2038 |
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| subjects | Adult Algorithms Anesthesia. Intensive care medicine. Transfusions. Cell therapy and gene therapy Biological and medical sciences Burns - therapy Decision Making, Computer-Assisted Emergency and intensive cardiocirculatory care. Cardiogenic shock. Coronary intensive care Female Fluid Therapy - methods Humans Intensive care medicine Intensive Care Units Male Medical sciences Middle Aged Rehydration Solutions - administration & dosage Rehydration Solutions - therapeutic use Resuscitation - methods |
| title | Computerized decision support system improves fluid resuscitation following severe burns: An original study |
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