Predictors of Post-operative Pain and Opioid Consumption in Patients Undergoing Liver Surgery
Background Post-operative pain management is a critical component of perioperative care. Patients at risk of poorly controlled post-operative pain may benefit from early measures to optimize pain management. We sought to identify risk factors for post-operative pain and opioid consumption in patient...
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| Veröffentlicht in: | World journal of surgery 2019-10, Vol.43 (10), p.2579-2586 |
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| creator | Behman, R. Cleary, S. McHardy, P. Kiss, A. Sawyer, J. Ladak, S. S. J. McCluskey, S. A. Srinivas, C. Katz, J. Coburn, N. Law, C. Wei, A. C. Greig, P. Hallet, J. Clarke, H. Karanicolas, P. J. |
| description | Background
Post-operative pain management is a critical component of perioperative care. Patients at risk of poorly controlled post-operative pain may benefit from early measures to optimize pain management. We sought to identify risk factors for post-operative pain and opioid consumption in patients undergoing liver resection.
Methods
This is a multi-institutional prospective nested cohort study of patients undergoing open liver resection. Opioid consumption and pain scores were collected following surgery. To estimate the effects of patient factors on opioid consumption (oral morphine equivalents—OME) and on pain scores (NRS-11), we used generalized linear models and multivariable linear regression model, respectively.
Results
One hundred and fifty-three patients who underwent open liver resection between 2013 and 2016 were included in the study. The mean patient age was 62.2 years, and 43.3% were female. Younger patients were significantly more likely to use more opioids in the early post-operative period (16.7 OME/10 years,
p
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| doi_str_mv | 10.1007/s00268-019-05050-7 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_2284559316</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2238257539</sourcerecordid><originalsourceid>FETCH-LOGICAL-c4261-e2270678c3964526b5eeb5c4d99d1553825db82f4bb317f05bf353e76a684ebf3</originalsourceid><addsrcrecordid>eNqNkEtr3DAUhUVoSSZJ_0AWQdBNN271lt1dMzR9MJCBNHRVhB_Xg8KM5Ep2y_z73MRJCl2UooUk7nfOPRxCzjh7yxmz7zJjwpQF41XBNJ7CHpAFV1IUQgr5giyYNArfXB6R45xvGePWMHNIjiTnpRXKLMiPdYLOt2NMmcaermMeizhAqkf_C-i69oHWoaNXg4--o8sY8rQbRh8DxckaKQhjpjehg7SJPmzoCnWJXk9pA2l_Sl729TbDq8f7hNxcfvy2_Fysrj59WX5YFa0ShhcghGXGlq2sjNLCNBqg0a3qqqrjWstS6K4pRa-aRnLbM930UkuwpjalAvyckDez75Dizwny6HY-t7Dd1gHilJ0QpdK6ktwg-vov9DZOKWA6pO43WS0rpMRMtSnmnKB3Q_K7Ou0dZ-6-fDeX77B891C-syg6f7Semh10z5KnthF4PwO__Rb2_2Hpvn-9vrhkOOQolrM4oy5gu3-C_yPTHbjcn38</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2238257539</pqid></control><display><type>article</type><title>Predictors of Post-operative Pain and Opioid Consumption in Patients Undergoing Liver Surgery</title><source>MEDLINE</source><source>SpringerNature Journals</source><source>Access via Wiley Online Library</source><creator>Behman, R. ; Cleary, S. ; McHardy, P. ; Kiss, A. ; Sawyer, J. ; Ladak, S. S. J. ; McCluskey, S. A. ; Srinivas, C. ; Katz, J. ; Coburn, N. ; Law, C. ; Wei, A. C. ; Greig, P. ; Hallet, J. ; Clarke, H. ; Karanicolas, P. J.</creator><creatorcontrib>Behman, R. ; Cleary, S. ; McHardy, P. ; Kiss, A. ; Sawyer, J. ; Ladak, S. S. J. ; McCluskey, S. A. ; Srinivas, C. ; Katz, J. ; Coburn, N. ; Law, C. ; Wei, A. C. ; Greig, P. ; Hallet, J. ; Clarke, H. ; Karanicolas, P. J.</creatorcontrib><description>Background
Post-operative pain management is a critical component of perioperative care. Patients at risk of poorly controlled post-operative pain may benefit from early measures to optimize pain management. We sought to identify risk factors for post-operative pain and opioid consumption in patients undergoing liver resection.
Methods
This is a multi-institutional prospective nested cohort study of patients undergoing open liver resection. Opioid consumption and pain scores were collected following surgery. To estimate the effects of patient factors on opioid consumption (oral morphine equivalents—OME) and on pain scores (NRS-11), we used generalized linear models and multivariable linear regression model, respectively.
Results
One hundred and fifty-three patients who underwent open liver resection between 2013 and 2016 were included in the study. The mean patient age was 62.2 years, and 43.3% were female. Younger patients were significantly more likely to use more opioids in the early post-operative period (16.7 OME/10 years,
p
< 0.001). Patient factors that were significantly associated with increased NRS-11 pain scores also included younger patient age (difference in pain score of 0.3/10 years with cough and 0.2/10 years at rest,
p
< 0.01 for both) as well as a history of analgesic use (difference in pain score of 0.9 with cough and 0.6 at rest,
p
< 0.01 and
p
= 0.07, respectively).
Conclusion
Younger patients and those with a history of analgesic use are more likely to report higher post-operative pain and require higher doses of opioids. Early identification of these patients, and measures to better manage their pain, may contribute to optimal perioperative care.</description><identifier>ISSN: 0364-2313</identifier><identifier>EISSN: 1432-2323</identifier><identifier>DOI: 10.1007/s00268-019-05050-7</identifier><identifier>PMID: 31187246</identifier><language>eng</language><publisher>Cham: Springer International Publishing</publisher><subject>Abdominal Surgery ; Adult ; Aged ; Analgesics ; Analgesics, Opioid - therapeutic use ; Cardiac Surgery ; Cough ; Critical components ; Female ; General Surgery ; Generalized linear models ; Hepatectomy ; Humans ; Liver ; Male ; Medicine ; Medicine & Public Health ; Middle Aged ; Morphine ; Narcotics ; Opioids ; Optimization ; Original Scientific Report ; Pain ; Pain management ; Pain, Postoperative - drug therapy ; Pain, Postoperative - etiology ; Patients ; Postoperative period ; Prospective Studies ; Regression analysis ; Regression models ; Risk analysis ; Risk factors ; Risk management ; Statistical models ; Surgery ; Thoracic Surgery ; Vascular Surgery</subject><ispartof>World journal of surgery, 2019-10, Vol.43 (10), p.2579-2586</ispartof><rights>Société Internationale de Chirurgie 2019</rights><rights>2019 The Author(s) under exclusive licence to Société Internationale de Chirurgie</rights><rights>World Journal of Surgery is a copyright of Springer, (2019). All Rights Reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4261-e2270678c3964526b5eeb5c4d99d1553825db82f4bb317f05bf353e76a684ebf3</citedby><cites>FETCH-LOGICAL-c4261-e2270678c3964526b5eeb5c4d99d1553825db82f4bb317f05bf353e76a684ebf3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s00268-019-05050-7$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s00268-019-05050-7$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,1417,27924,27925,41488,42557,45574,45575,51319</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/31187246$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Behman, R.</creatorcontrib><creatorcontrib>Cleary, S.</creatorcontrib><creatorcontrib>McHardy, P.</creatorcontrib><creatorcontrib>Kiss, A.</creatorcontrib><creatorcontrib>Sawyer, J.</creatorcontrib><creatorcontrib>Ladak, S. S. J.</creatorcontrib><creatorcontrib>McCluskey, S. A.</creatorcontrib><creatorcontrib>Srinivas, C.</creatorcontrib><creatorcontrib>Katz, J.</creatorcontrib><creatorcontrib>Coburn, N.</creatorcontrib><creatorcontrib>Law, C.</creatorcontrib><creatorcontrib>Wei, A. C.</creatorcontrib><creatorcontrib>Greig, P.</creatorcontrib><creatorcontrib>Hallet, J.</creatorcontrib><creatorcontrib>Clarke, H.</creatorcontrib><creatorcontrib>Karanicolas, P. J.</creatorcontrib><title>Predictors of Post-operative Pain and Opioid Consumption in Patients Undergoing Liver Surgery</title><title>World journal of surgery</title><addtitle>World J Surg</addtitle><addtitle>World J Surg</addtitle><description>Background
Post-operative pain management is a critical component of perioperative care. Patients at risk of poorly controlled post-operative pain may benefit from early measures to optimize pain management. We sought to identify risk factors for post-operative pain and opioid consumption in patients undergoing liver resection.
Methods
This is a multi-institutional prospective nested cohort study of patients undergoing open liver resection. Opioid consumption and pain scores were collected following surgery. To estimate the effects of patient factors on opioid consumption (oral morphine equivalents—OME) and on pain scores (NRS-11), we used generalized linear models and multivariable linear regression model, respectively.
Results
One hundred and fifty-three patients who underwent open liver resection between 2013 and 2016 were included in the study. The mean patient age was 62.2 years, and 43.3% were female. Younger patients were significantly more likely to use more opioids in the early post-operative period (16.7 OME/10 years,
p
< 0.001). Patient factors that were significantly associated with increased NRS-11 pain scores also included younger patient age (difference in pain score of 0.3/10 years with cough and 0.2/10 years at rest,
p
< 0.01 for both) as well as a history of analgesic use (difference in pain score of 0.9 with cough and 0.6 at rest,
p
< 0.01 and
p
= 0.07, respectively).
Conclusion
Younger patients and those with a history of analgesic use are more likely to report higher post-operative pain and require higher doses of opioids. Early identification of these patients, and measures to better manage their pain, may contribute to optimal perioperative care.</description><subject>Abdominal Surgery</subject><subject>Adult</subject><subject>Aged</subject><subject>Analgesics</subject><subject>Analgesics, Opioid - therapeutic use</subject><subject>Cardiac Surgery</subject><subject>Cough</subject><subject>Critical components</subject><subject>Female</subject><subject>General Surgery</subject><subject>Generalized linear models</subject><subject>Hepatectomy</subject><subject>Humans</subject><subject>Liver</subject><subject>Male</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Middle Aged</subject><subject>Morphine</subject><subject>Narcotics</subject><subject>Opioids</subject><subject>Optimization</subject><subject>Original Scientific Report</subject><subject>Pain</subject><subject>Pain management</subject><subject>Pain, Postoperative - drug therapy</subject><subject>Pain, Postoperative - etiology</subject><subject>Patients</subject><subject>Postoperative period</subject><subject>Prospective Studies</subject><subject>Regression analysis</subject><subject>Regression models</subject><subject>Risk analysis</subject><subject>Risk factors</subject><subject>Risk management</subject><subject>Statistical models</subject><subject>Surgery</subject><subject>Thoracic Surgery</subject><subject>Vascular Surgery</subject><issn>0364-2313</issn><issn>1432-2323</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>eNqNkEtr3DAUhUVoSSZJ_0AWQdBNN271lt1dMzR9MJCBNHRVhB_Xg8KM5Ep2y_z73MRJCl2UooUk7nfOPRxCzjh7yxmz7zJjwpQF41XBNJ7CHpAFV1IUQgr5giyYNArfXB6R45xvGePWMHNIjiTnpRXKLMiPdYLOt2NMmcaermMeizhAqkf_C-i69oHWoaNXg4--o8sY8rQbRh8DxckaKQhjpjehg7SJPmzoCnWJXk9pA2l_Sl729TbDq8f7hNxcfvy2_Fysrj59WX5YFa0ShhcghGXGlq2sjNLCNBqg0a3qqqrjWstS6K4pRa-aRnLbM930UkuwpjalAvyckDez75Dizwny6HY-t7Dd1gHilJ0QpdK6ktwg-vov9DZOKWA6pO43WS0rpMRMtSnmnKB3Q_K7Ou0dZ-6-fDeX77B891C-syg6f7Semh10z5KnthF4PwO__Rb2_2Hpvn-9vrhkOOQolrM4oy5gu3-C_yPTHbjcn38</recordid><startdate>20191015</startdate><enddate>20191015</enddate><creator>Behman, R.</creator><creator>Cleary, S.</creator><creator>McHardy, P.</creator><creator>Kiss, A.</creator><creator>Sawyer, J.</creator><creator>Ladak, S. S. J.</creator><creator>McCluskey, S. A.</creator><creator>Srinivas, C.</creator><creator>Katz, J.</creator><creator>Coburn, N.</creator><creator>Law, C.</creator><creator>Wei, A. C.</creator><creator>Greig, P.</creator><creator>Hallet, J.</creator><creator>Clarke, H.</creator><creator>Karanicolas, P. J.</creator><general>Springer International Publishing</general><general>Springer Nature B.V</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>7QO</scope><scope>7T5</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8FD</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>H94</scope><scope>K9.</scope><scope>M0S</scope><scope>M1P</scope><scope>P64</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope></search><sort><creationdate>20191015</creationdate><title>Predictors of Post-operative Pain and Opioid Consumption in Patients Undergoing Liver Surgery</title><author>Behman, R. ; Cleary, S. ; McHardy, P. ; Kiss, A. ; Sawyer, J. ; Ladak, S. S. J. ; McCluskey, S. A. ; Srinivas, C. ; Katz, J. ; Coburn, N. ; Law, C. ; Wei, A. C. ; Greig, P. ; Hallet, J. ; Clarke, H. ; Karanicolas, P. J.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4261-e2270678c3964526b5eeb5c4d99d1553825db82f4bb317f05bf353e76a684ebf3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Abdominal Surgery</topic><topic>Adult</topic><topic>Aged</topic><topic>Analgesics</topic><topic>Analgesics, Opioid - therapeutic use</topic><topic>Cardiac Surgery</topic><topic>Cough</topic><topic>Critical components</topic><topic>Female</topic><topic>General Surgery</topic><topic>Generalized linear models</topic><topic>Hepatectomy</topic><topic>Humans</topic><topic>Liver</topic><topic>Male</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Middle Aged</topic><topic>Morphine</topic><topic>Narcotics</topic><topic>Opioids</topic><topic>Optimization</topic><topic>Original Scientific Report</topic><topic>Pain</topic><topic>Pain management</topic><topic>Pain, Postoperative - drug therapy</topic><topic>Pain, Postoperative - etiology</topic><topic>Patients</topic><topic>Postoperative period</topic><topic>Prospective Studies</topic><topic>Regression analysis</topic><topic>Regression models</topic><topic>Risk analysis</topic><topic>Risk factors</topic><topic>Risk management</topic><topic>Statistical models</topic><topic>Surgery</topic><topic>Thoracic Surgery</topic><topic>Vascular Surgery</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Behman, R.</creatorcontrib><creatorcontrib>Cleary, S.</creatorcontrib><creatorcontrib>McHardy, P.</creatorcontrib><creatorcontrib>Kiss, A.</creatorcontrib><creatorcontrib>Sawyer, J.</creatorcontrib><creatorcontrib>Ladak, S. S. J.</creatorcontrib><creatorcontrib>McCluskey, S. A.</creatorcontrib><creatorcontrib>Srinivas, C.</creatorcontrib><creatorcontrib>Katz, J.</creatorcontrib><creatorcontrib>Coburn, N.</creatorcontrib><creatorcontrib>Law, C.</creatorcontrib><creatorcontrib>Wei, A. C.</creatorcontrib><creatorcontrib>Greig, P.</creatorcontrib><creatorcontrib>Hallet, J.</creatorcontrib><creatorcontrib>Clarke, H.</creatorcontrib><creatorcontrib>Karanicolas, P. J.</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>Biotechnology Research Abstracts</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>ProQuest Pharma Collection</collection><collection>Technology Research 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>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Biotechnology and BioEngineering Abstracts</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><jtitle>World journal of surgery</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Behman, R.</au><au>Cleary, S.</au><au>McHardy, P.</au><au>Kiss, A.</au><au>Sawyer, J.</au><au>Ladak, S. S. J.</au><au>McCluskey, S. A.</au><au>Srinivas, C.</au><au>Katz, J.</au><au>Coburn, N.</au><au>Law, C.</au><au>Wei, A. C.</au><au>Greig, P.</au><au>Hallet, J.</au><au>Clarke, H.</au><au>Karanicolas, P. J.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Predictors of Post-operative Pain and Opioid Consumption in Patients Undergoing Liver Surgery</atitle><jtitle>World journal of surgery</jtitle><stitle>World J Surg</stitle><addtitle>World J Surg</addtitle><date>2019-10-15</date><risdate>2019</risdate><volume>43</volume><issue>10</issue><spage>2579</spage><epage>2586</epage><pages>2579-2586</pages><issn>0364-2313</issn><eissn>1432-2323</eissn><abstract>Background
Post-operative pain management is a critical component of perioperative care. Patients at risk of poorly controlled post-operative pain may benefit from early measures to optimize pain management. We sought to identify risk factors for post-operative pain and opioid consumption in patients undergoing liver resection.
Methods
This is a multi-institutional prospective nested cohort study of patients undergoing open liver resection. Opioid consumption and pain scores were collected following surgery. To estimate the effects of patient factors on opioid consumption (oral morphine equivalents—OME) and on pain scores (NRS-11), we used generalized linear models and multivariable linear regression model, respectively.
Results
One hundred and fifty-three patients who underwent open liver resection between 2013 and 2016 were included in the study. The mean patient age was 62.2 years, and 43.3% were female. Younger patients were significantly more likely to use more opioids in the early post-operative period (16.7 OME/10 years,
p
< 0.001). Patient factors that were significantly associated with increased NRS-11 pain scores also included younger patient age (difference in pain score of 0.3/10 years with cough and 0.2/10 years at rest,
p
< 0.01 for both) as well as a history of analgesic use (difference in pain score of 0.9 with cough and 0.6 at rest,
p
< 0.01 and
p
= 0.07, respectively).
Conclusion
Younger patients and those with a history of analgesic use are more likely to report higher post-operative pain and require higher doses of opioids. Early identification of these patients, and measures to better manage their pain, may contribute to optimal perioperative care.</abstract><cop>Cham</cop><pub>Springer International Publishing</pub><pmid>31187246</pmid><doi>10.1007/s00268-019-05050-7</doi><tpages>8</tpages></addata></record> |
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| subjects | Abdominal Surgery Adult Aged Analgesics Analgesics, Opioid - therapeutic use Cardiac Surgery Cough Critical components Female General Surgery Generalized linear models Hepatectomy Humans Liver Male Medicine Medicine & Public Health Middle Aged Morphine Narcotics Opioids Optimization Original Scientific Report Pain Pain management Pain, Postoperative - drug therapy Pain, Postoperative - etiology Patients Postoperative period Prospective Studies Regression analysis Regression models Risk analysis Risk factors Risk management Statistical models Surgery Thoracic Surgery Vascular Surgery |
| title | Predictors of Post-operative Pain and Opioid Consumption in Patients Undergoing Liver Surgery |
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