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Performance of surgical site infection risk prediction models in colorectal surgery: external validity assessment from three European national surveillance networks
To assess the validity of multivariable models for predicting risk of surgical site infection (SSI) after colorectal surgery based on routinely collected data in national surveillance networks. Retrospective analysis performed on 3 validation cohorts. Colorectal surgery patients in Switzerland, Fran...
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Published in: | Infection control and hospital epidemiology 2019-09, Vol.40 (9), p.983-990 |
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description | To assess the validity of multivariable models for predicting risk of surgical site infection (SSI) after colorectal surgery based on routinely collected data in national surveillance networks.
Retrospective analysis performed on 3 validation cohorts.
Colorectal surgery patients in Switzerland, France, and England, 2007-2017.
We determined calibration and discrimination (ie, area under the curve, AUC) of the COLA (contamination class, obesity, laparoscopy, American Society of Anesthesiologists [ASA]) multivariable risk model and the National Healthcare Safety Network (NHSN) multivariable risk model in each cohort. A new score was constructed based on multivariable analysis of the Swiss cohort following colorectal surgery, then based on colon and rectal surgery separately.
We included 40,813 patients who had undergone elective or emergency colorectal surgery to validate the COLA score, 45,216 patients to validate the NHSN colon and rectal surgery risk models, and 46,320 patients in the construction of a new predictive model. The COLA score's predictive ability was poor, with AUC values of 0.64 (95% confidence interval [CI], 0.63-0.65), 0.62 (95% CI, 0.58-0.67), 0.60 (95% CI, 0.58-0.61) in the Swiss, French, and English cohorts, respectively. The NHSN colon-specific model (AUC, 0.61; 95% CI, 0.61-0.62) and the rectal surgery-specific model (AUC, 0.57; 95% CI, 0.53-0.61) showed limited predictive ability. The new predictive score showed poor predictive accuracy for colorectal surgery overall (AUC, 0.65; 95% CI, 0.64-0.66), for colon surgery (AUC, 0.65; 95% CI, 0.65-0.66), and for rectal surgery (AUC, 0.63; 95% CI, 0.60-0.66).
Models based on routinely collected data in SSI surveillance networks poorly predict individual risk of SSI following colorectal surgery. Further models that include other more predictive variables could be developed and validated. |
doi_str_mv | 10.1017/ice.2019.163 |
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Retrospective analysis performed on 3 validation cohorts.
Colorectal surgery patients in Switzerland, France, and England, 2007-2017.
We determined calibration and discrimination (ie, area under the curve, AUC) of the COLA (contamination class, obesity, laparoscopy, American Society of Anesthesiologists [ASA]) multivariable risk model and the National Healthcare Safety Network (NHSN) multivariable risk model in each cohort. A new score was constructed based on multivariable analysis of the Swiss cohort following colorectal surgery, then based on colon and rectal surgery separately.
We included 40,813 patients who had undergone elective or emergency colorectal surgery to validate the COLA score, 45,216 patients to validate the NHSN colon and rectal surgery risk models, and 46,320 patients in the construction of a new predictive model. The COLA score's predictive ability was poor, with AUC values of 0.64 (95% confidence interval [CI], 0.63-0.65), 0.62 (95% CI, 0.58-0.67), 0.60 (95% CI, 0.58-0.61) in the Swiss, French, and English cohorts, respectively. The NHSN colon-specific model (AUC, 0.61; 95% CI, 0.61-0.62) and the rectal surgery-specific model (AUC, 0.57; 95% CI, 0.53-0.61) showed limited predictive ability. The new predictive score showed poor predictive accuracy for colorectal surgery overall (AUC, 0.65; 95% CI, 0.64-0.66), for colon surgery (AUC, 0.65; 95% CI, 0.65-0.66), and for rectal surgery (AUC, 0.63; 95% CI, 0.60-0.66).
Models based on routinely collected data in SSI surveillance networks poorly predict individual risk of SSI following colorectal surgery. Further models that include other more predictive variables could be developed and validated.</description><identifier>ISSN: 0899-823X</identifier><identifier>EISSN: 1559-6834</identifier><identifier>DOI: 10.1017/ice.2019.163</identifier><identifier>PMID: 31218977</identifier><language>eng</language><publisher>United States: Cambridge University Press</publisher><subject>Aged ; Aged, 80 and over ; Antibiotics ; Body mass index ; Colonic Diseases - surgery ; Colorectal surgery ; Colorectal Surgery - adverse effects ; Data encryption ; England - epidemiology ; Female ; France - epidemiology ; Health facilities ; Health risks ; Hospitals ; Humans ; Laparoscopy ; Male ; Middle Aged ; Missing data ; Nosocomial infections ; Nursing ; Patients ; Population Surveillance ; Prediction models ; Retrospective Studies ; Risk Assessment - methods ; Surgical outcomes ; Surgical site infections ; Surgical Wound Infection - epidemiology ; Surveillance ; Switzerland - epidemiology ; Validity ; Variables</subject><ispartof>Infection control and hospital epidemiology, 2019-09, Vol.40 (9), p.983-990</ispartof><rights>2019 by The Society for Healthcare Epidemiology of America. All rights reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c319t-40313a51c337a71c0387c0d3db6ac2c83353aadb698ad09b6a8abd44d2bff1533</citedby><cites>FETCH-LOGICAL-c319t-40313a51c337a71c0387c0d3db6ac2c83353aadb698ad09b6a8abd44d2bff1533</cites><orcidid>0000-0002-7265-1887</orcidid></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/31218977$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Grant, Rebecca</creatorcontrib><creatorcontrib>Aupee, Martine</creatorcontrib><creatorcontrib>Buchs, Nicolas C</creatorcontrib><creatorcontrib>Cooper, Kristine</creatorcontrib><creatorcontrib>Eisenring, Marie-Christine</creatorcontrib><creatorcontrib>Lamagni, Theresa</creatorcontrib><creatorcontrib>Ris, Frédéric</creatorcontrib><creatorcontrib>Tanguy, Juliette</creatorcontrib><creatorcontrib>Troillet, Nicolas</creatorcontrib><creatorcontrib>Harbarth, Stephan</creatorcontrib><creatorcontrib>Abbas, Mohamed</creatorcontrib><title>Performance of surgical site infection risk prediction models in colorectal surgery: external validity assessment from three European national surveillance networks</title><title>Infection control and hospital epidemiology</title><addtitle>Infect Control Hosp Epidemiol</addtitle><description>To assess the validity of multivariable models for predicting risk of surgical site infection (SSI) after colorectal surgery based on routinely collected data in national surveillance networks.
Retrospective analysis performed on 3 validation cohorts.
Colorectal surgery patients in Switzerland, France, and England, 2007-2017.
We determined calibration and discrimination (ie, area under the curve, AUC) of the COLA (contamination class, obesity, laparoscopy, American Society of Anesthesiologists [ASA]) multivariable risk model and the National Healthcare Safety Network (NHSN) multivariable risk model in each cohort. A new score was constructed based on multivariable analysis of the Swiss cohort following colorectal surgery, then based on colon and rectal surgery separately.
We included 40,813 patients who had undergone elective or emergency colorectal surgery to validate the COLA score, 45,216 patients to validate the NHSN colon and rectal surgery risk models, and 46,320 patients in the construction of a new predictive model. The COLA score's predictive ability was poor, with AUC values of 0.64 (95% confidence interval [CI], 0.63-0.65), 0.62 (95% CI, 0.58-0.67), 0.60 (95% CI, 0.58-0.61) in the Swiss, French, and English cohorts, respectively. The NHSN colon-specific model (AUC, 0.61; 95% CI, 0.61-0.62) and the rectal surgery-specific model (AUC, 0.57; 95% CI, 0.53-0.61) showed limited predictive ability. The new predictive score showed poor predictive accuracy for colorectal surgery overall (AUC, 0.65; 95% CI, 0.64-0.66), for colon surgery (AUC, 0.65; 95% CI, 0.65-0.66), and for rectal surgery (AUC, 0.63; 95% CI, 0.60-0.66).
Models based on routinely collected data in SSI surveillance networks poorly predict individual risk of SSI following colorectal surgery. Further models that include other more predictive variables could be developed and validated.</description><subject>Aged</subject><subject>Aged, 80 and over</subject><subject>Antibiotics</subject><subject>Body mass index</subject><subject>Colonic Diseases - surgery</subject><subject>Colorectal surgery</subject><subject>Colorectal Surgery - adverse effects</subject><subject>Data encryption</subject><subject>England - epidemiology</subject><subject>Female</subject><subject>France - epidemiology</subject><subject>Health facilities</subject><subject>Health risks</subject><subject>Hospitals</subject><subject>Humans</subject><subject>Laparoscopy</subject><subject>Male</subject><subject>Middle Aged</subject><subject>Missing data</subject><subject>Nosocomial infections</subject><subject>Nursing</subject><subject>Patients</subject><subject>Population Surveillance</subject><subject>Prediction models</subject><subject>Retrospective Studies</subject><subject>Risk Assessment - methods</subject><subject>Surgical outcomes</subject><subject>Surgical site infections</subject><subject>Surgical Wound Infection - epidemiology</subject><subject>Surveillance</subject><subject>Switzerland - epidemiology</subject><subject>Validity</subject><subject>Variables</subject><issn>0899-823X</issn><issn>1559-6834</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><recordid>eNpdkU1v1DAQhi1ERZeFG2dkiQsHstiZZG1zq6ryIVVqDyBxi7z2BNwm8TJ2Cvt_-kNx2MKBkzWjZ1691sPYCyk2Ukj1Njjc1EKajdzCI7aSbWuqrYbmMVsJbUyla_h6yp6mdCOEUMbIJ-wUZC21UWrF7q-R-kijnRzy2PM007fg7MBTyMjD1KPLIU6cQrrle0IfjvMYPQ6pANzFIVKhlptyjHR4x_FXRprK5s4OwYd84DYlTGnEKfOe4sjzd0LkFzPFPdqJT3ZJPUbcYRiGP30mzD8j3aZn7KS3Q8LnD--afXl_8fn8Y3V59eHT-dll5UCaXDUCJNhWOgBllXQCtHLCg99traudBmjB2jIZbb0wZavtzjeNr3d9L1uANXt9zN1T_DFjyt0YksOlDcY5dXXdNLKtW6MK-uo_9CbOy5cLpXTTwFaWOmv25kg5iikR9t2ewmjp0EnRLfa6Yq9b7HXFXsFfPoTOuxH9P_ivLvgNcV6aYQ</recordid><startdate>201909</startdate><enddate>201909</enddate><creator>Grant, Rebecca</creator><creator>Aupee, Martine</creator><creator>Buchs, Nicolas C</creator><creator>Cooper, Kristine</creator><creator>Eisenring, Marie-Christine</creator><creator>Lamagni, Theresa</creator><creator>Ris, Frédéric</creator><creator>Tanguy, Juliette</creator><creator>Troillet, Nicolas</creator><creator>Harbarth, Stephan</creator><creator>Abbas, Mohamed</creator><general>Cambridge University Press</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>7X7</scope><scope>7XB</scope><scope>88C</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>K9-</scope><scope>K9.</scope><scope>KB0</scope><scope>M0R</scope><scope>M0S</scope><scope>M0T</scope><scope>M1P</scope><scope>NAPCQ</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>S0X</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-7265-1887</orcidid></search><sort><creationdate>201909</creationdate><title>Performance of surgical site infection risk prediction models in colorectal surgery: external validity assessment from three European national surveillance networks</title><author>Grant, Rebecca ; Aupee, Martine ; Buchs, Nicolas C ; Cooper, Kristine ; Eisenring, Marie-Christine ; Lamagni, Theresa ; Ris, Frédéric ; Tanguy, Juliette ; Troillet, Nicolas ; Harbarth, Stephan ; Abbas, Mohamed</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c319t-40313a51c337a71c0387c0d3db6ac2c83353aadb698ad09b6a8abd44d2bff1533</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Aged</topic><topic>Aged, 80 and over</topic><topic>Antibiotics</topic><topic>Body mass index</topic><topic>Colonic Diseases - surgery</topic><topic>Colorectal surgery</topic><topic>Colorectal Surgery - adverse effects</topic><topic>Data encryption</topic><topic>England - epidemiology</topic><topic>Female</topic><topic>France - epidemiology</topic><topic>Health facilities</topic><topic>Health risks</topic><topic>Hospitals</topic><topic>Humans</topic><topic>Laparoscopy</topic><topic>Male</topic><topic>Middle Aged</topic><topic>Missing data</topic><topic>Nosocomial infections</topic><topic>Nursing</topic><topic>Patients</topic><topic>Population Surveillance</topic><topic>Prediction models</topic><topic>Retrospective Studies</topic><topic>Risk Assessment - methods</topic><topic>Surgical outcomes</topic><topic>Surgical site infections</topic><topic>Surgical Wound Infection - epidemiology</topic><topic>Surveillance</topic><topic>Switzerland - epidemiology</topic><topic>Validity</topic><topic>Variables</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Grant, Rebecca</creatorcontrib><creatorcontrib>Aupee, Martine</creatorcontrib><creatorcontrib>Buchs, Nicolas C</creatorcontrib><creatorcontrib>Cooper, Kristine</creatorcontrib><creatorcontrib>Eisenring, Marie-Christine</creatorcontrib><creatorcontrib>Lamagni, Theresa</creatorcontrib><creatorcontrib>Ris, Frédéric</creatorcontrib><creatorcontrib>Tanguy, Juliette</creatorcontrib><creatorcontrib>Troillet, Nicolas</creatorcontrib><creatorcontrib>Harbarth, Stephan</creatorcontrib><creatorcontrib>Abbas, Mohamed</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 Database</collection><collection>Health Medical collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Healthcare Administration Database (Alumni)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>ProQuest 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)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Databases</collection><collection>ProQuest One Community College</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>Consumer Health Database (Alumni Edition)</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>ProQuest Consumer Health Database</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>ProQuest Healthcare Administration Database</collection><collection>PML(ProQuest Medical Library)</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>SIRS Editorial</collection><collection>MEDLINE - Academic</collection><jtitle>Infection control and hospital epidemiology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Grant, Rebecca</au><au>Aupee, Martine</au><au>Buchs, Nicolas C</au><au>Cooper, Kristine</au><au>Eisenring, Marie-Christine</au><au>Lamagni, Theresa</au><au>Ris, Frédéric</au><au>Tanguy, Juliette</au><au>Troillet, Nicolas</au><au>Harbarth, Stephan</au><au>Abbas, Mohamed</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Performance of surgical site infection risk prediction models in colorectal surgery: external validity assessment from three European national surveillance networks</atitle><jtitle>Infection control and hospital epidemiology</jtitle><addtitle>Infect Control Hosp Epidemiol</addtitle><date>2019-09</date><risdate>2019</risdate><volume>40</volume><issue>9</issue><spage>983</spage><epage>990</epage><pages>983-990</pages><issn>0899-823X</issn><eissn>1559-6834</eissn><abstract>To assess the validity of multivariable models for predicting risk of surgical site infection (SSI) after colorectal surgery based on routinely collected data in national surveillance networks.
Retrospective analysis performed on 3 validation cohorts.
Colorectal surgery patients in Switzerland, France, and England, 2007-2017.
We determined calibration and discrimination (ie, area under the curve, AUC) of the COLA (contamination class, obesity, laparoscopy, American Society of Anesthesiologists [ASA]) multivariable risk model and the National Healthcare Safety Network (NHSN) multivariable risk model in each cohort. A new score was constructed based on multivariable analysis of the Swiss cohort following colorectal surgery, then based on colon and rectal surgery separately.
We included 40,813 patients who had undergone elective or emergency colorectal surgery to validate the COLA score, 45,216 patients to validate the NHSN colon and rectal surgery risk models, and 46,320 patients in the construction of a new predictive model. The COLA score's predictive ability was poor, with AUC values of 0.64 (95% confidence interval [CI], 0.63-0.65), 0.62 (95% CI, 0.58-0.67), 0.60 (95% CI, 0.58-0.61) in the Swiss, French, and English cohorts, respectively. The NHSN colon-specific model (AUC, 0.61; 95% CI, 0.61-0.62) and the rectal surgery-specific model (AUC, 0.57; 95% CI, 0.53-0.61) showed limited predictive ability. The new predictive score showed poor predictive accuracy for colorectal surgery overall (AUC, 0.65; 95% CI, 0.64-0.66), for colon surgery (AUC, 0.65; 95% CI, 0.65-0.66), and for rectal surgery (AUC, 0.63; 95% CI, 0.60-0.66).
Models based on routinely collected data in SSI surveillance networks poorly predict individual risk of SSI following colorectal surgery. Further models that include other more predictive variables could be developed and validated.</abstract><cop>United States</cop><pub>Cambridge University Press</pub><pmid>31218977</pmid><doi>10.1017/ice.2019.163</doi><tpages>8</tpages><orcidid>https://orcid.org/0000-0002-7265-1887</orcidid></addata></record> |
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subjects | Aged Aged, 80 and over Antibiotics Body mass index Colonic Diseases - surgery Colorectal surgery Colorectal Surgery - adverse effects Data encryption England - epidemiology Female France - epidemiology Health facilities Health risks Hospitals Humans Laparoscopy Male Middle Aged Missing data Nosocomial infections Nursing Patients Population Surveillance Prediction models Retrospective Studies Risk Assessment - methods Surgical outcomes Surgical site infections Surgical Wound Infection - epidemiology Surveillance Switzerland - epidemiology Validity Variables |
title | Performance of surgical site infection risk prediction models in colorectal surgery: external validity assessment from three European national surveillance networks |
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