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Validation of a delirium predictive model in patients admitted to surgical intensive care units: a multicentre
Onuma Chaiwat1,2, Kaweesak Chittawatanarat3,4, Sirirat Mueankwan5
1Department of Anesthesiology, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand onuma.cha@mahidol.ac.th.
Objective:
To internally and externally validate a delirium predictive model for adult patients admitted to intensive care units (ICUs) following surgery.
Design:
A prospective, observational, multicentre study.
Setting:
Three university-affiliated teaching hospitals in Thailand.
Participants:
Adults aged over 18 years were enrolled if they were admitted to a surgical ICU (SICU) and had the surgery within 7 days before SICU admission.
Main Outcome Measures:
Postoperative delirium was assessed using the Thai version of the Confusion Assessment Method for the ICU. The assessments commenced on the first day after the patient's operation and continued for 7 days, or until either discharge from the ICU or the death of the patient. Validation was performed of the previously developed delirium predictive model: age+(5×SOFA)+(15×benzodiazepine use)+(20×DM)+(20×mechanical ventilation)+(20×modified IQCODE>3.42).
Results:
In all, 380 SICU patients were recruited. Internal validation on 150 patients with the mean age of 75±7.5 years resulted in an area under a receiver operating characteristic curve (AUROC) of 0.76 (0.683 to 0.837). External validation on 230 patients with the mean age of 57±17.3 years resulted in an AUROC of 0.85 (0.789 to 0.906). The AUROC of all validation cohorts was 0.83 (0.785 to 0.872). The optimum cut-off value to discriminate between a high and low probability of postoperative delirium in SICU patients was 115. This cut-off offered the highest value for Youden's index (0.50), the best AUROC, and the optimum values for sensitivity (78.9%) and specificity (70.9%).
Conclusions:
The model developed by the previous study was able to predict the occurrence of postoperative delirium in critically ill surgical patients admitted to SICUs.
Trial Registration Number:
Thai Clinical Trail Registry (TCTR20180105001).
