Development of a multivariable predictive model for postoperative nausea and vomiting after cancer surgery in adults
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Publication Date: | 2019 |
Other Authors: | , , , |
Format: | Article |
Language: | eng |
Source: | Revista Brasileira de Anestesiologia (Online) |
Download full: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0034-70942019000400003 |
Summary: | Abstract Background and objectives Predicting postoperative nausea and vomiting risk is the cornerstone for deciding prophylaxis. Apfel's score does not define how long a person must be abstinent from smoking to be considered a non-smoker, and the use of intraoperative spinal opioids as a risk factor for predicting postoperative nausea and vomiting is also not addressed. The aim of this study was to quantify predicting postoperative nausea and vomiting risk by an ordinal smoking status and the use of intraoperative opioids (systemic or neuraxial), and to develop a new predictive model. Methods Patients scheduled for cancer surgery were prospectively evaluated for predicting postoperative nausea and vomiting in the first 24 h after surgery. Results Of 2014 initially included patients, 185 participants were excluded. Smoking status classification was associated with predicting postoperative nausea and vomiting incidence rates of 14.1%, 18.1%, 24.7%, 29.4% and 33.9% for smokers, patients who stopped smoking up to 1 month prior to surgery, one to 6 months prior, more than 6 months prior or patients who never smoked, respectively, which was significant in the multiple comparisons analysis (adjusted p = 0.015). The multiple comparisons-adjusted hypothesis tests for association with predicting postoperative nausea and vomiting for sex, age, previous predicting postoperative nausea and vomiting, chemotherapy-induced nausea, and ordinal smoking status had p-values of <0.001. The type of surgery (p = 0.04), total fentanyl consumption (p = 0.04), both intraoperative and postoperative, were significant predictors. A new model was developed and showed higher discriminative power than Apfel's score (AUC 67.9% vs. 63.7%, p < 0.001). Conclusion Smoking status showed a significant and linear impact on predicting postoperative nausea and vomiting incidence, and we developed a new model that uses unambiguous smoking and opioid predictors. |
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Development of a multivariable predictive model for postoperative nausea and vomiting after cancer surgery in adultsPostoperative nausea and vomitingMultivariable modelCancerSmokingPrognosticAbstract Background and objectives Predicting postoperative nausea and vomiting risk is the cornerstone for deciding prophylaxis. Apfel's score does not define how long a person must be abstinent from smoking to be considered a non-smoker, and the use of intraoperative spinal opioids as a risk factor for predicting postoperative nausea and vomiting is also not addressed. The aim of this study was to quantify predicting postoperative nausea and vomiting risk by an ordinal smoking status and the use of intraoperative opioids (systemic or neuraxial), and to develop a new predictive model. Methods Patients scheduled for cancer surgery were prospectively evaluated for predicting postoperative nausea and vomiting in the first 24 h after surgery. Results Of 2014 initially included patients, 185 participants were excluded. Smoking status classification was associated with predicting postoperative nausea and vomiting incidence rates of 14.1%, 18.1%, 24.7%, 29.4% and 33.9% for smokers, patients who stopped smoking up to 1 month prior to surgery, one to 6 months prior, more than 6 months prior or patients who never smoked, respectively, which was significant in the multiple comparisons analysis (adjusted p = 0.015). The multiple comparisons-adjusted hypothesis tests for association with predicting postoperative nausea and vomiting for sex, age, previous predicting postoperative nausea and vomiting, chemotherapy-induced nausea, and ordinal smoking status had p-values of <0.001. The type of surgery (p = 0.04), total fentanyl consumption (p = 0.04), both intraoperative and postoperative, were significant predictors. A new model was developed and showed higher discriminative power than Apfel's score (AUC 67.9% vs. 63.7%, p < 0.001). Conclusion Smoking status showed a significant and linear impact on predicting postoperative nausea and vomiting incidence, and we developed a new model that uses unambiguous smoking and opioid predictors.Sociedade Brasileira de Anestesiologia2019-08-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0034-70942019000400003Revista Brasileira de Anestesiologia v.69 n.4 2019reponame:Revista Brasileira de Anestesiologia (Online)instname:Sociedade Brasileira de Anestesiologia (SBA)instacron:SBA10.1016/j.bjane.2019.03.006info:eu-repo/semantics/openAccessYamada,Léia Alessandra PintoGuimarães,Gabriel Magalhães NunesSilva,Magda Aparecida SantosSousa,Angela MariaAshmawi,Hazem Adeleng2019-10-08T00:00:00Zoai:scielo:S0034-70942019000400003Revistahttps://www.sbahq.org/revista/https://old.scielo.br/oai/scielo-oai.php||sba2000@openlink.com.br1806-907X0034-7094opendoar:2019-10-08T00:00Revista Brasileira de Anestesiologia (Online) - Sociedade Brasileira de Anestesiologia (SBA)false |
dc.title.none.fl_str_mv |
Development of a multivariable predictive model for postoperative nausea and vomiting after cancer surgery in adults |
title |
Development of a multivariable predictive model for postoperative nausea and vomiting after cancer surgery in adults |
spellingShingle |
Development of a multivariable predictive model for postoperative nausea and vomiting after cancer surgery in adults Yamada,Léia Alessandra Pinto Postoperative nausea and vomiting Multivariable model Cancer Smoking Prognostic |
title_short |
Development of a multivariable predictive model for postoperative nausea and vomiting after cancer surgery in adults |
title_full |
Development of a multivariable predictive model for postoperative nausea and vomiting after cancer surgery in adults |
title_fullStr |
Development of a multivariable predictive model for postoperative nausea and vomiting after cancer surgery in adults |
title_full_unstemmed |
Development of a multivariable predictive model for postoperative nausea and vomiting after cancer surgery in adults |
title_sort |
Development of a multivariable predictive model for postoperative nausea and vomiting after cancer surgery in adults |
author |
Yamada,Léia Alessandra Pinto |
author_facet |
Yamada,Léia Alessandra Pinto Guimarães,Gabriel Magalhães Nunes Silva,Magda Aparecida Santos Sousa,Angela Maria Ashmawi,Hazem Adel |
author_role |
author |
author2 |
Guimarães,Gabriel Magalhães Nunes Silva,Magda Aparecida Santos Sousa,Angela Maria Ashmawi,Hazem Adel |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Yamada,Léia Alessandra Pinto Guimarães,Gabriel Magalhães Nunes Silva,Magda Aparecida Santos Sousa,Angela Maria Ashmawi,Hazem Adel |
dc.subject.por.fl_str_mv |
Postoperative nausea and vomiting Multivariable model Cancer Smoking Prognostic |
topic |
Postoperative nausea and vomiting Multivariable model Cancer Smoking Prognostic |
description |
Abstract Background and objectives Predicting postoperative nausea and vomiting risk is the cornerstone for deciding prophylaxis. Apfel's score does not define how long a person must be abstinent from smoking to be considered a non-smoker, and the use of intraoperative spinal opioids as a risk factor for predicting postoperative nausea and vomiting is also not addressed. The aim of this study was to quantify predicting postoperative nausea and vomiting risk by an ordinal smoking status and the use of intraoperative opioids (systemic or neuraxial), and to develop a new predictive model. Methods Patients scheduled for cancer surgery were prospectively evaluated for predicting postoperative nausea and vomiting in the first 24 h after surgery. Results Of 2014 initially included patients, 185 participants were excluded. Smoking status classification was associated with predicting postoperative nausea and vomiting incidence rates of 14.1%, 18.1%, 24.7%, 29.4% and 33.9% for smokers, patients who stopped smoking up to 1 month prior to surgery, one to 6 months prior, more than 6 months prior or patients who never smoked, respectively, which was significant in the multiple comparisons analysis (adjusted p = 0.015). The multiple comparisons-adjusted hypothesis tests for association with predicting postoperative nausea and vomiting for sex, age, previous predicting postoperative nausea and vomiting, chemotherapy-induced nausea, and ordinal smoking status had p-values of <0.001. The type of surgery (p = 0.04), total fentanyl consumption (p = 0.04), both intraoperative and postoperative, were significant predictors. A new model was developed and showed higher discriminative power than Apfel's score (AUC 67.9% vs. 63.7%, p < 0.001). Conclusion Smoking status showed a significant and linear impact on predicting postoperative nausea and vomiting incidence, and we developed a new model that uses unambiguous smoking and opioid predictors. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-08-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0034-70942019000400003 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0034-70942019000400003 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1016/j.bjane.2019.03.006 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Sociedade Brasileira de Anestesiologia |
publisher.none.fl_str_mv |
Sociedade Brasileira de Anestesiologia |
dc.source.none.fl_str_mv |
Revista Brasileira de Anestesiologia v.69 n.4 2019 reponame:Revista Brasileira de Anestesiologia (Online) instname:Sociedade Brasileira de Anestesiologia (SBA) instacron:SBA |
instname_str |
Sociedade Brasileira de Anestesiologia (SBA) |
instacron_str |
SBA |
institution |
SBA |
reponame_str |
Revista Brasileira de Anestesiologia (Online) |
collection |
Revista Brasileira de Anestesiologia (Online) |
repository.name.fl_str_mv |
Revista Brasileira de Anestesiologia (Online) - Sociedade Brasileira de Anestesiologia (SBA) |
repository.mail.fl_str_mv |
||sba2000@openlink.com.br |
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1752126630470352896 |