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Published on: September 15, 2023
Optimal postoperative delirium prediction after coronary artery bypass grafting surgery: a prospective cohort study
Ying Ma1, Dongxin Sui2, Shaozhong Yang3
1Department of Geriatric Medicine, Qilu Hospital (Qingdao), Cheeloo College of Medicine, Shandong University, Qingdao, China.
Insights
The Age-adjusted Charlson Comorbidity Index (ACCI) predicts postoperative delirium (POD) in patients undergoing off-pump coronary artery bypass grafting (OPCABG) surgery. Higher ACCI scores correlate with increased POD incidence, indicating its predictive value.
Area of Science:
- Cardiology
- Neurosurgery
- Geriatrics
Background:
- Postoperative delirium (POD) is a significant complication following off-pump coronary artery bypass grafting (OPCABG) surgery.
- POD is associated with adverse outcomes including mortality, cognitive decline, and increased healthcare costs.
- The Age-adjusted Charlson Comorbidity Index (ACCI) is a validated predictor of mortality and survival.
Purpose of the Study:
- To evaluate the predictive capability of the ACCI for the occurrence of POD in patients undergoing OPCABG.
- To determine if ACCI is an independent risk factor for POD in this patient population.
Main Methods:
- A prospective cohort study included 89 patients undergoing OPCABG surgery.
- Patients were stratified into low-ACCI (0-3) and high-ACCI (≥4) groups.
- POD was diagnosed using the Confusion Assessment Method (CAM-ICU and CAM) within 7 days post-surgery; ROC curve analysis was employed.
Main Results:
- The incidence of POD was significantly higher in the high-ACCI group (45.5%) compared to the low-ACCI group (15.6%).
- Multivariate logistic regression identified ACCI as an independent risk factor for POD (OR, 2.433; P = 0.001).
- The ACCI demonstrated good predictive accuracy for POD with an AUC of 0.738.
Conclusions:
- Patients with a high ACCI score exhibit a greater risk of developing POD after OPCABG.
- The ACCI is an independent predictor of POD in patients undergoing OPCABG surgery.
- The ACCI serves as a valuable tool for predicting POD in patients undergoing OPCABG.
Background:
Postoperative delirium (POD) presents as a serious neuropsychiatric syndrome in patients undergoing off-pump coronary artery bypass grafting (OPCABG) surgery. This is correlated with higher mortality, cognitive decline, and increased costs. The Age-adjusted Charlson Comorbidity Index (ACCI) is recognized as an independent predictor for mortality and survival rate. The purpose of our study is to estimate the predictive value of the ACCI on the POD in patients undergoing OPCABG surgery.
Methods:
This prospective cohort study enrolled patients undergoing OPCABG surgery between December 2020 and May 2021 in Qilu Hospital. Patients were divided into the low-ACCI group (score, 0-3) and the high-ACCI group (score ≥4) according to their ACCI scores. The Confusion Assessment Method for the Intensive Care Unit (CAM-ICU) and CAM were used to diagnose POD within 7 days after surgery. The general, laboratory, and clinical data of the patients were recorded and collected. The characteristic ROC curve was applied to further assess the predictive value of the ACCI for POD in patients following OPCABG surgery.
Results:
A total of 89 patients were enrolled, including 45 patients in the low-ACCI group and 44 patients in the high-ACCI group. The incidence of POD was higher in the high-ACCI group than in the low-ACCI group (45.5% vs. 15.6%, P = 0.003). Multivariate logistic regression analyses showed that the ACCI (OR, 2.433; 95% CI, 1.468-4.032; P = 0.001) was an independent risk factor for POD. The ACCI accurately predicted POD in patients following OPCABG surgery with an AUC of 0.738, and the Hosmer-Lemeshow goodness of fit test yielded X2 = 5.391 (P = 0.145).
Conclusion:
The high-ACCI group showed a high incidence of POD. The ACCI was an independent factor associated with POD in patients following OPCABG surgery. In addition, the ACCI could accurately predict POD in patients following OPCABG surgery.
Clinical Trial Registration:
ClinicalTrials.gov, identifier CHiCTR2100052811.
