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A Multivariable Model Predictive of Unplanned Postoperative Intubation in Infant Surgical Patients.
Eisler, Lisa D; Hua, May; Li, Guohua; Sun, Lena S; Kim, Minjae.
Afiliação
  • Eisler LD; From the Department of Anesthesiology, Columbia University Medical Center, New York, New York.
  • Hua M; From the Department of Anesthesiology, Columbia University Medical Center, New York, New York.
  • Li G; Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York.
  • Sun LS; From the Department of Anesthesiology, Columbia University Medical Center, New York, New York.
  • Kim M; Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York.
Anesth Analg ; 129(6): 1645-1652, 2019 12.
Article em En | MEDLINE | ID: mdl-31743186
ABSTRACT

BACKGROUND:

Unplanned postoperative intubation is an important quality indicator, and is associated with significantly increased mortality in children. Infant patients are more likely than older pediatric patients to experience unplanned postoperative intubation, yet the literature provides few characterizations of this outcome in our youngest patients. The objective of this study was to identify risk factors for unplanned postoperative intubation and to develop a scoring system to predict this complication in infants undergoing major surgical procedures.

METHODS:

In this retrospective cohort study, The National Surgical Quality Improvement Program-Pediatric database was surveyed for all infants who underwent noncardiac surgery between January 1, 2012 and December 31, 2015 (derivation cohort, n = 56,962) and between January 1 and December 31, 2016 (validation cohort, n = 20,559). Demographic and perioperative clinical characteristics were examined in association with our primary outcome of unplanned postoperative intubation within 30 days of surgery. Risk factors were analyzed in the derivation cohort (2012-2015 data) using multivariable logistic regression with stepwise selection. Parameters from the final model were used to create a scoring system for predicting unplanned postoperative intubation. Data from the validation cohort were utilized to assess the performance of the scoring system using the area under the receiver operating characteristic curve.

RESULTS:

In the derivation cohort, 2.2% of the infants experienced unplanned postoperative intubation within 30 days of surgery. Of the 14 risk factors identified in multivariable analysis, 10 (age, prematurity, American Society of Anesthesiologists physical status, inpatient status, operative time >120 minutes, cardiac disease, malignancy, hematologic disorder, oxygen supplementation, and nutritional support) were included in the final multivariable logistic regression model to create the risk score. The area under the receiver operating characteristic curve of the final model was 0.86 (95% CI, 0.85-0.87) for the derivation cohort and 0.83 (95% CI, 0.82-0.85) for the validation cohort.

CONCLUSIONS:

About 1 in 50 infants undergoing major surgical procedures experiences unplanned postoperative intubation. Our scoring system based on routinely collected perioperative assessment data can predict risk in infants with good accuracy. Further investigation should assess the clinical utility of the scoring system for risk stratification and improvement in perioperative care quality and patient outcomes.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Complicações Pós-Operatórias / Intubação Intratraqueal / Modelos Teóricos Tipo de estudo: Etiology_studies / Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Female / Humans / Infant / Male / Newborn Idioma: En Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Complicações Pós-Operatórias / Intubação Intratraqueal / Modelos Teóricos Tipo de estudo: Etiology_studies / Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Female / Humans / Infant / Male / Newborn Idioma: En Ano de publicação: 2019 Tipo de documento: Article