Derivation and Validation of a Nomogram to Predict In‐Hospital Complications in Children with Tetralogy of Fallot Repaired at an Older Age

Abstract

Background

We aimed to develop and validate a prediction model for in‐hospital complications in children with tetralogy of Fallot repaired at an older age.

Methods and Results

A total of 513 pediatric patients from the Tianjin data set formed a derivation cohort, and 158 pediatric patients from the Hefei and Xiamen data sets formed validation cohorts. We applied least absolute shrinkage and selection operator analysis for variable selection and logistic regression coefficients for risk scoring. We classified patients into different risk categorizations by threshold analysis and investigated the association with in‐hospital complications using logistic regression. In‐hospital complications were defined as death, need for extensive pharmacologic support (vasoactive‐inotrope score of ≥20), and need for mechanical circulatory support. We developed a nomogram based on risk classifier and independent baseline variables using a multivariable logistic model. Based on risk scores weighted by 11 preoperative and 4 intraoperative selected variables, we classified patients as low, intermediate, and high risk in the derivation cohort. With reference to the low‐risk group, the intermediate‐ and high‐risk groups conferred significantly higher in‐hospital complication risks (adjusted odds ratio: 2.721 [95% CI, 1.267–5.841], P=0.0102; 9.297 [95% CI, 4.601–18.786], P<0.0001). A nomogram integrating the ARIAR‐Risk classifier (absolute and relative low risk, intermediate risk, and aggressive and refractory high risk) with age and mean blood pressure showed good discrimination and goodness‐of‐fit for derivation (area under the receiver operating characteristic curve: 0.785 [95% CI, 0.731–0.839]; Hosmer‐Lemeshow test, P=0.544) and external validation (area under the receiver operating characteristic curve: 0.759 [95% CI, 0.636–0.881]; Hosmer‐Lemeshow test, P=0.508).

Conclusions

A risk‐classifier–oriented nomogram is a reliable prediction model for in‐hospital complications in children with tetralogy of Fallot repaired at an older age, and strengthens risk/benefit–based decision‐making.