Development of a Model Identifying Fontan Patients at High Risk for Failed Early Extubation in the Operating Room

Atsushi Kawaguchi1, Dominic Cave1, Qi Liu2

  • 1Department of Pediatrics, Pediatric Critical Care Medicine, University of Alberta, Alberta, Canada.

Insights

A predictive model was developed to identify children at high risk for failed early extubation after the Fontan procedure. Key predictors include concomitant procedures, bypass time, and absence of fenestration, aiding clinical decision-making.

Area of Science:

  • Pediatric Cardiac Surgery
  • Critical Care Medicine
  • Cardiovascular Research

Background:

  • The Fontan procedure is a complex surgery for single-ventricle congenital heart defects.
  • Early extubation in the operating room (OR) is a desirable strategy but carries risks.
  • Identifying high-risk patients for failed early extubation is crucial for improving outcomes.

Purpose of the Study:

  • To identify patients at high risk for failed early extubation in the OR following the Fontan procedure.
  • To develop a predictive model for failed early extubation to aid clinical decision-making.

Main Methods:

  • Retrospective review of 75 patients (0-17 years) undergoing the Fontan procedure (2008-2011).
  • Comparison of patients requiring reintubation versus those not reintubated after OR extubation.
  • Development of a two-stage logistic regression predictive model using pre/perioperative and postoperative predictors.

Main Results:

  • The first-stage model identified concomitant procedure, total bypass time (≥99 minutes), and absence of fenestration as significant predictors.
  • The second-stage model incorporated chest-tube fluid loss (CTFL ≥9.9 mL/kg/first 6 hours).
  • The sequential prediction model achieved a net sensitivity of 87.5% and specificity of 77.6%.

Conclusions:

  • A validated predictive model for failed early extubation in Fontan patients was developed.
  • The model's sensitivity and specificity suggest clinical utility.
  • Further validation with larger, independent samples is recommended.
Abstract

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