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Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
A Risk Prediction Nomogram Model for Postoperative Pulmonary Complications in Children Aged 0-6 years
Qian Wang1, Yanhong Li1, Kuangyu Zhao1
1Department of Anesthesiology and Perioperative Medicine, People's Hospital of Zhengzhou University, Henan Provincial People's Hospital, Zhengzhou, Henan, People's Republic of China.
Insights
This study identified key risk factors for postoperative pulmonary complications in young children, developing a predictive model to guide preoperative interventions and improve patient outcomes.
Area of Science:
- Pediatric Anesthesiology
- Respiratory Medicine
- Clinical Risk Prediction
Background:
- Postoperative pulmonary complications (PPCs) are frequent in pediatric surgical patients.
- Existing risk models lack specificity for children, hindering targeted preoperative interventions.
- This study addresses the need for a child-specific risk prediction model for PPCs.
Purpose of the Study:
- To identify independent risk factors associated with PPCs in children aged 0-6 years.
- To develop and validate a nomogram-based risk prediction model for PPCs in this pediatric population.
- To enhance preoperative risk assessment and facilitate timely interventions.
Main Methods:
- Retrospective review of 1545 pediatric patients (ASA I-II) undergoing surgery with mechanical ventilation.
- Univariate and multivariate logistic regression analyses to determine independent risk factors for PPCs.
- Construction and validation of a nomogram prediction model using discovery and test cohorts, evaluated with ROC and calibration curves.
Main Results:
- The incidence of PPCs was 13.4% (211/1545 patients).
- Independent risk factors identified: younger age, longer mechanical ventilation duration, specific airway devices, higher ASA physical status, and type of surgery.
- The prediction model demonstrated good discriminant validity (AUC 0.762-0.818) and calibration in both cohorts.
Conclusions:
- Age, ventilation parameters, ASA status, and surgical type are significant predictors of PPCs in children.
- The developed nomogram model effectively predicts PPC risk in pediatric surgical patients.
- This model can aid clinicians in identifying high-risk children and implementing preemptive strategies.
Background:
Postoperative pulmonary complications (PPCs) in children are common. However, few models tailored specifically for children are available to identify risk factors for PPCs and enable preoperative interventions. This study aimed to identify independent risk factors for PPCs in children and establish a risk prediction model.
Methods:
The clinical data of pediatric patients aged 0-6 years with an American Society of Anesthesiologists (ASA) physical status of I or II, and had undergone surgery with mechanical ventilation at Henan Provincial People's Hospital between January 2020 and December 2021 were retrospectively reviewed. Univariate and multivariate logistic regression analyses were employed to identify risk factors for PPCs. The corresponding nomogram prediction model was constructed based on the regression coefficients. The receiver operating characteristic curve and calibration curve were used respectively to evaluate the discriminant validity and calibration of the prediction model.
Results:
Among 1545 patients included, 211 (13.4%) developed PPCs (156 of 1082 patients in the discovery cohort and 55 of 463 patients in the test cohort). In the multivariate logistic regression analysis, age (odds ratio [OR] 0.87, 95% confidence interval [CI] 0.79-0.96, P=0.007), mechanical ventilation time (OR 1.36, 95% CI 1.20-1.55, P<0.001), airway device (OR 1.67, 95% CI 1.04-2.68, P=0.033), ASA physical status (OR 1.96, 95% CI 1.34-2.88, P=0.001), and type of surgery (the total effect, P=0.004) were identified as the independent risk factors for PPCs in the discovery cohort. The prediction model showed good discrimination and calibration performance in both the discovery and test cohorts. The corresponding area under the curve was 0.762 (95% CI: 0.722, 0.803) and 0.818 (95% CI: 0.760, 0.875), respectively.
Conclusion:
We identified age, ventilation device and duration, ASA physical status, and surgical site as independent risk factors for PPCs in children aged 0-6 years. The predictive model performed well and demonstrated a certain capability in predicting the risk of PPCs.
