4.6 Article

External validation and comparison of two delirium prediction models in patients admitted to the cardiac intensive care unit

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FRONTIERS MEDIA SA
DOI: 10.3389/fcvm.2022.947149

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delirium prediction; prediction model; cardiac intensive care unit; Early PREdiction of DELIRium; PREdiction of DELIRium

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This study externally validated the usefulness of two delirium prediction models, PRE-DELIRIC and E-PRE-DELIRIC, in the cardiac intensive care unit (CICU). The results showed that the PRE-DELIRIC model may have superior predictive performance compared to the E-PRE-DELIRIC model. Further studies are needed to design a specific delirium prediction model for CICU patients.
BackgroundNo data is available on delirium prediction models in the cardiac intensive care unit (CICU), although preexisting delirium prediction models [PREdiction of DELIRium in ICu patients (PRE-DELIRIC) and Early PREdiction of DELIRium in ICu patients (E-PRE-DELIRIC)] were developed and validated based on a population admitted to the general intensive care unit (ICU). Therefore, we externally validated the usefulness of the PRE-DELIRIC and E-PRE-DELIRIC models and compared their predictive performance in patients admitted to the CICU. MethodsA total of 2,724 patients admitted to the CICU were enrolled between September 2012 and December 2018. Delirium was defined as at least one positive Confusion Assessment Method for the ICU (CAM-ICU) which was screened at least once every 8 h. The PRE-DELIRIC value was calculated within 24 h of CICU admission, and the E-PRE-DELIRIC value was calculated at CICU admission. The predictive performance of the models was evaluated by using the area under the receiver operating characteristic (AUROC) curve, and the calibration slope was assessed graphically by plotting. ResultsDelirium occurred in 677 patients (24.8%) when the patients were assessed thrice daily until 7 days of the CICU stay. The AUROC curve for the prediction of delirium was significantly greater for PRE-DELIRIC values [0.84, 95% confidence interval (CI): 0.82-0.86] than for E-PRE-DELIRIC values (0.79, 95% CI: 0.77-0.80) [z score of -6.24 (p < 0.001)]. Net reclassification improvement for the prediction of delirium increased by 0.27 (95% CI: 0.21-0.32, p < 0.001). Calibration was acceptable in the PRE-DELIRIC model (Hosmer-Lemeshow p = 0.170) but not in the E-PRE-DELIRIC model (Hosmer-Lemeshow p < 0.001). ConclusionAlthough both models have good predictive performance for the development of delirium, even in critically ill cardiac patients, the performance of the PRE-DELIRIC model might be superior to that of the E-PRE-DELIRIC model. Further studies are required to confirm our results and design a specific delirium prediction model for CICU patients.

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