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Factors predictive of poor behavioral compliance during inhaled induction in children
Anna M Varughese1, Todd G Nick, Joel Gunter
1Department of Anesthesiology, Cincinnati Children's Hospital Medical Center, 3333 Burnet Avenue, Cincinnati, OH 45229, USA. anna.varughese@cchmc.org
Insights
Younger children, shorter prep times, and higher anxiety predict poor behavioral compliance during anesthesia induction. Preoperative tours can help mitigate risks associated with prior anesthesia experiences in children.
Area of Science:
- Pediatric Anesthesiology
- Child Psychology
- Health Services Research
Background:
- Preoperative identification of children at risk for emotional distress and poor behavioral compliance during inhaled anesthesia induction is crucial for targeted interventions.
- Understanding predictive factors enhances the quality of the anesthetic experience for pediatric patients.
Purpose of the Study:
- To identify patient, procedural, and healthcare system factors predicting poor behavioral compliance during inhaled anesthesia induction in children.
- To develop a predictive model for identifying children at risk of distress during anesthesia induction.
Main Methods:
- A study of 861 children aged 1-13 years undergoing inhaled anesthesia induction with parents present.
- Behavioral compliance assessed using the Induction Compliance Checklist (ICC); ICC >= 4 defined as poor compliance.
- Multivariable ordinal logistic regression used to model behavioral compliance, with model performance evaluated by the c-statistic.
Main Results:
- Twenty-one percent of children exhibited poor behavioral compliance.
- Factors increasing odds of poor compliance: younger age (<4 years), shorter preoperative preparation time, and high preoperative anxiety.
- Previous anesthesia experience increased odds in school-age children, but this was ameliorated by attending a preoperative tour.
Conclusions:
- Age, previous anesthesia, preoperative tour attendance, preparation time, and preoperative anxiety levels are predictive of poor behavioral compliance.
- A predictive algorithm using these factors can help identify children benefiting from interventions.
- This approach can also help avoid unnecessary interventions for low-risk children.
Background:
Preoperative identification of children at risk of emotional distress and poor behavioral compliance during inhaled induction of anesthesia allows targeted interventions to reduce distress, thereby enhancing the quality of the anesthetic experience. We sought to identify patient, procedural, and health care system factors predictive of poor behavioral compliance during induction.
Methods:
We studied 861 developmentally appropriate children ages 1-13 yr, The American Society of Anesthesiologists physical status I to III, presenting for inhaled induction of anesthesia. All inductions were performed in an induction room with parent(s) present. Behavioral compliance was assessed using the Induction Compliance Checklist (ICC), an observational scale consisting of 10 behaviors scored as the number of behaviors observed during induction; ICC > or =4 was considered poor behavioral compliance. A multivariable ordinal logistic regression model for behavioral compliance was generated and the performance of the multivariable model was evaluated by the c statistic.
Results:
Twenty-one percent of children exhibited poor behavioral compliance on induction. Factors increasing the odds of poor behavioral compliance were younger age (< 4 yr, P < 0.0001), shorter preoperative preparation time (P = 0.004), and high anxiety levels in the preoperative clinic (modified-Yale preoperative anxiety scale > 40; P = 0.016). Previous anesthesia experience increased the odds in school-age children (P = 0.046); this effect was ameliorated in children attending the preoperative tour (P = 0.018). The model using these factors demonstrated moderate discrimination between children with poor compliance and those with perfect compliance (ICC = 0) (c statistic = 0.75).
Conclusions:
Factors predictive of poor behavioral compliance were age, previous anesthesia, preoperative tour attendance, preoperative preparation time and anxiety levels in the preoperative clinic. These factors, bundled into a predictive algorithm, may help identify children who could benefit from behavioral or pharmacological interventions and avoid use of interventions to those at low risk.
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