Predictors of perioperative complications in paediatric cranial vault reconstruction surgery

a multicentre observational study from the Pediatric Craniofacial Collaborative Group

the Pediatric Craniofacial Collaborative Group

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Background: The current incidence of major complications in paediatric craniofacial surgery in North America has not been accurately defined. In this report, the Pediatric Craniofacial Collaborative Group evaluates the incidence and determines the independent predictors of major perioperative complications using a multicentre database. Methods: The Pediatric Craniofacial Surgery Perioperative Registry was queried for subjects undergoing complex cranial vault reconstruction surgery over a 5-year period. Major perioperative complications were identified through a structured a priori consensus process. Logistic regression was applied to identify predictors of a major perioperative complication with bootstrapping to evaluate discrimination accuracy and provide internal validity of the multivariable model. Results: A total of 1814 patients from 33 institutions in the US and Canada were analysed; 15% were reported to have a major perioperative complication. Multivariable predictors included ASA physical status 3 or 4 (P=0.005), craniofacial syndrome (P=0.008), antifibrinolytic administered (P=0.003), blood product transfusion >50 ml kg –1 (P<0.001), and surgery duration over 5 h (P<0.001). Bootstrapping indicated that the predictive algorithm had good internal validity and excellent discrimination and model performance. A perioperative complication was estimated to increase the hospital length of stay by an average of 3 days (P<0.001). Conclusions: The predictive algorithm can be used as a prognostic tool to risk stratify patients and thereby potentially reduce morbidity and mortality. Craniofacial teams can utilise these predictors of complications to identify high-risk patients. Based on this information, further prospective quality improvement initiatives may decrease complications, and reduce morbidity and mortality.

Original languageEnglish (US)
Pages (from-to)215-223
Number of pages9
JournalBritish Journal of Anaesthesia
Volume122
Issue number2
DOIs
StatePublished - Feb 1 2019
Externally publishedYes

Fingerprint

Multicenter Studies
Observational Studies
Pediatrics
Length of Stay
Morbidity
Antifibrinolytic Agents
Mortality
Incidence
North America
Quality Improvement
Blood Transfusion
Canada
Registries
Logistic Models
Databases

Keywords

  • craniosynostosis
  • multivariable model
  • paediatrics
  • perioperative complications
  • perioperative outcome
  • predictive algorithm
  • risk assessment

ASJC Scopus subject areas

  • Anesthesiology and Pain Medicine

Cite this

Predictors of perioperative complications in paediatric cranial vault reconstruction surgery : a multicentre observational study from the Pediatric Craniofacial Collaborative Group. / the Pediatric Craniofacial Collaborative Group.

In: British Journal of Anaesthesia, Vol. 122, No. 2, 01.02.2019, p. 215-223.

Research output: Contribution to journalArticle

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abstract = "Background: The current incidence of major complications in paediatric craniofacial surgery in North America has not been accurately defined. In this report, the Pediatric Craniofacial Collaborative Group evaluates the incidence and determines the independent predictors of major perioperative complications using a multicentre database. Methods: The Pediatric Craniofacial Surgery Perioperative Registry was queried for subjects undergoing complex cranial vault reconstruction surgery over a 5-year period. Major perioperative complications were identified through a structured a priori consensus process. Logistic regression was applied to identify predictors of a major perioperative complication with bootstrapping to evaluate discrimination accuracy and provide internal validity of the multivariable model. Results: A total of 1814 patients from 33 institutions in the US and Canada were analysed; 15{\%} were reported to have a major perioperative complication. Multivariable predictors included ASA physical status 3 or 4 (P=0.005), craniofacial syndrome (P=0.008), antifibrinolytic administered (P=0.003), blood product transfusion >50 ml kg –1 (P<0.001), and surgery duration over 5 h (P<0.001). Bootstrapping indicated that the predictive algorithm had good internal validity and excellent discrimination and model performance. A perioperative complication was estimated to increase the hospital length of stay by an average of 3 days (P<0.001). Conclusions: The predictive algorithm can be used as a prognostic tool to risk stratify patients and thereby potentially reduce morbidity and mortality. Craniofacial teams can utilise these predictors of complications to identify high-risk patients. Based on this information, further prospective quality improvement initiatives may decrease complications, and reduce morbidity and mortality.",
keywords = "craniosynostosis, multivariable model, paediatrics, perioperative complications, perioperative outcome, predictive algorithm, risk assessment",
author = "{the Pediatric Craniofacial Collaborative Group} and Goobie, {S. M.} and D. Zurakowski and Isaac, {K. V.} and Taicher, {B. M.} and Fernandez, {P. G.} and Derderian, {C. K.} and M. Hetmaniuk and Stricker, {P. A.} and Christopher Abruzzese and Jesus Apuya and Amy Beethe and Hubert Benzon and Wendy Binstock and Alyssa Brzenskim and Stefan Budac and Veronica Busso and Surendrasingh Chhabada and Franklin Chiao and Franklyn Cladis and Danielle Claypool and Michael Collins and Rachel Dabek and Nicholas Dalesio and Ricardo Falconl and Allison Fernandez and Patrick Fernandez and John Fiadjoe and Meera Gangadharan and Katherine Gentry and Chris Glover and Goobie, {Susan M.} and Amanda Gosman and Shannon Grap and Heike Gries and Allison Griffin and Charles Haberkern and John Hajduk and Rebecca Hall and Jennifer Hansen and Mali Hetmaniuk and Vincent Hsieh and Henry Huang and Pablo Ingelmo and Iskra Ivanova and Ranu Jain and Michelle Kars and Courtney Kowalczyk-Derderian and Jane Kugler and Kristen Labovsky and Brian Masel",
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T1 - Predictors of perioperative complications in paediatric cranial vault reconstruction surgery

T2 - a multicentre observational study from the Pediatric Craniofacial Collaborative Group

AU - the Pediatric Craniofacial Collaborative Group

AU - Goobie, S. M.

AU - Zurakowski, D.

AU - Isaac, K. V.

AU - Taicher, B. M.

AU - Fernandez, P. G.

AU - Derderian, C. K.

AU - Hetmaniuk, M.

AU - Stricker, P. A.

AU - Abruzzese, Christopher

AU - Apuya, Jesus

AU - Beethe, Amy

AU - Benzon, Hubert

AU - Binstock, Wendy

AU - Brzenskim, Alyssa

AU - Budac, Stefan

AU - Busso, Veronica

AU - Chhabada, Surendrasingh

AU - Chiao, Franklin

AU - Cladis, Franklyn

AU - Claypool, Danielle

AU - Collins, Michael

AU - Dabek, Rachel

AU - Dalesio, Nicholas

AU - Falconl, Ricardo

AU - Fernandez, Allison

AU - Fernandez, Patrick

AU - Fiadjoe, John

AU - Gangadharan, Meera

AU - Gentry, Katherine

AU - Glover, Chris

AU - Goobie, Susan M.

AU - Gosman, Amanda

AU - Grap, Shannon

AU - Gries, Heike

AU - Griffin, Allison

AU - Haberkern, Charles

AU - Hajduk, John

AU - Hall, Rebecca

AU - Hansen, Jennifer

AU - Hetmaniuk, Mali

AU - Hsieh, Vincent

AU - Huang, Henry

AU - Ingelmo, Pablo

AU - Ivanova, Iskra

AU - Jain, Ranu

AU - Kars, Michelle

AU - Kowalczyk-Derderian, Courtney

AU - Kugler, Jane

AU - Labovsky, Kristen

AU - Masel, Brian

PY - 2019/2/1

Y1 - 2019/2/1

N2 - Background: The current incidence of major complications in paediatric craniofacial surgery in North America has not been accurately defined. In this report, the Pediatric Craniofacial Collaborative Group evaluates the incidence and determines the independent predictors of major perioperative complications using a multicentre database. Methods: The Pediatric Craniofacial Surgery Perioperative Registry was queried for subjects undergoing complex cranial vault reconstruction surgery over a 5-year period. Major perioperative complications were identified through a structured a priori consensus process. Logistic regression was applied to identify predictors of a major perioperative complication with bootstrapping to evaluate discrimination accuracy and provide internal validity of the multivariable model. Results: A total of 1814 patients from 33 institutions in the US and Canada were analysed; 15% were reported to have a major perioperative complication. Multivariable predictors included ASA physical status 3 or 4 (P=0.005), craniofacial syndrome (P=0.008), antifibrinolytic administered (P=0.003), blood product transfusion >50 ml kg –1 (P<0.001), and surgery duration over 5 h (P<0.001). Bootstrapping indicated that the predictive algorithm had good internal validity and excellent discrimination and model performance. A perioperative complication was estimated to increase the hospital length of stay by an average of 3 days (P<0.001). Conclusions: The predictive algorithm can be used as a prognostic tool to risk stratify patients and thereby potentially reduce morbidity and mortality. Craniofacial teams can utilise these predictors of complications to identify high-risk patients. Based on this information, further prospective quality improvement initiatives may decrease complications, and reduce morbidity and mortality.

AB - Background: The current incidence of major complications in paediatric craniofacial surgery in North America has not been accurately defined. In this report, the Pediatric Craniofacial Collaborative Group evaluates the incidence and determines the independent predictors of major perioperative complications using a multicentre database. Methods: The Pediatric Craniofacial Surgery Perioperative Registry was queried for subjects undergoing complex cranial vault reconstruction surgery over a 5-year period. Major perioperative complications were identified through a structured a priori consensus process. Logistic regression was applied to identify predictors of a major perioperative complication with bootstrapping to evaluate discrimination accuracy and provide internal validity of the multivariable model. Results: A total of 1814 patients from 33 institutions in the US and Canada were analysed; 15% were reported to have a major perioperative complication. Multivariable predictors included ASA physical status 3 or 4 (P=0.005), craniofacial syndrome (P=0.008), antifibrinolytic administered (P=0.003), blood product transfusion >50 ml kg –1 (P<0.001), and surgery duration over 5 h (P<0.001). Bootstrapping indicated that the predictive algorithm had good internal validity and excellent discrimination and model performance. A perioperative complication was estimated to increase the hospital length of stay by an average of 3 days (P<0.001). Conclusions: The predictive algorithm can be used as a prognostic tool to risk stratify patients and thereby potentially reduce morbidity and mortality. Craniofacial teams can utilise these predictors of complications to identify high-risk patients. Based on this information, further prospective quality improvement initiatives may decrease complications, and reduce morbidity and mortality.

KW - craniosynostosis

KW - multivariable model

KW - paediatrics

KW - perioperative complications

KW - perioperative outcome

KW - predictive algorithm

KW - risk assessment

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U2 - 10.1016/j.bja.2018.10.061

DO - 10.1016/j.bja.2018.10.061

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EP - 223

JO - British Journal of Anaesthesia

JF - British Journal of Anaesthesia

SN - 0007-0912

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ER -