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

Figures

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  Figure 1. LASSO model profile plots. A, Coefficient profile plots showing how size of the coefficients of preoperative and intraoperative factors shrinks with increasing value of the λ penalty, with the factors and their regression coefficients selected for the model based on the optimal λ for the LASSO model. B, Penalty plot for the LASSO model; color error bars indicate standard error. C, The optimal λ penalty of the LASSO model with a maximum AUC of 0.785. AUC indicates area under the receiver operating characteristic curve; LASSO, least absolute shrinkage and selection operator.

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  Figure 2. Risk‐based classifier profiles in a derivation cohort. A, Dose‐response relationship between risk score and morbidity from in‐hospital complications and threshold points for classifying patients into risk categorizations. B and C, Adjusted association between the triple‐risk (ie, low, intermediate, high) classifier (B) and the ARIAR‐Risk classifier (C) and probability and OR of in‐hospital complications with 95% CIs. ARIAR‐Risk indicates absolute and relative low risk, intermediate risk, and aggressive and refractory high risk; OR, odds ratio.

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  Figure 3. Comparison of the ARIAR‐Risk classifier and the triple‐risk (ie, low, intermediate, high) classifier. AUC indicates area under the receiver operating characteristic curve. ARIAR‐Risk indicates absolute and relative low risk, intermediate risk, and aggressive and refractory high risk.

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  Figure 4. Derivation and validation of an in‐hospital complications nomogram. A, In‐hospital complications nomogram. This nomogram provides a method to calculate the probability of cumulative incidence of developing postoperative in‐hospital complications after complete repair of tetralogy of Fallot, on the basis of a patient's combination of covariates. AUCs for the derivation cohort (B), internal validation with bootstrapping (C), and external validation cohort (D) of the in‐hospital complications nomogram. Calibration plots for the derivation cohort (E), internal validation with bootstrapping (F), and external validation cohort (G) of the in‐hospital complications nomogram. Shaded area is 95% CIs of the cumulative incidence. Dashed line is the reference line, which would indicate where an ideal nomogram would lie. Decision curves for the in‐hospital complications nomogram in the derivation cohort (H), internal validation with bootstrapping (I), and external validation cohort (J). Gray solid line indicates net benefit of a strategy of treating all patients. Blue dotted line indicates net benefit of treating no patients. Color solid line indicates net benefit of a strategy of treating…

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  Figure 5. Cumulative risks of in‐hospital complications with increasing age at surgery. Kaplan–Meier curves by overall (A), triple‐risk (ie, low, intermediate, high) classifier (B), and ARIAR‐Risk classifier (C). Shaded area is 95% CIs of the cumulative incidence.