Prediction model for delirium in patients with cardiovascular surgery: development and validation

Evaluation of postoperative delirium in cardiac surgery patients with the SDACS screening tool: a multicenter-multiphase study

OBJECTIVE

Postoperative delirium is a prevalent complication in cardiac surgery patients, highlighting the importance of early risk factor identification for optimal management. This study aimed to pinpoint risk factors and devise a novel screening tool, the Screening Tool for Delirium After Cardiac Surgery (SDACS), to predict postoperative delirium in cardiac surgery patients after the first day.

MATERIALS AND METHODS

This study employed a multiphase design consisting of three phases. In the first phase, through a scoping review of 38 finally selected published papers, 136 potential risk factors for identifying delirium after cardiac surgery were identified. These risk factors were then incorporated into three Delphi rounds of expert panels to develop a screening tool for postoperative delirium. Finally, 76 potential risk factors were examined on 920 cardiac surgery patients at three academic institutions between 2020 and 2023 (third phase of the study). All predictors were included into a screening instrument (SDACS), and the regression coefficient of each predictor was transformed into a risk score.

RESULTS

Delirium was diagnosed in 53% (n = 488) of 920 patients. Four independent predictors of delirium were identified: chronic opioid use (OR: 4.605, 95% CI: 2.163-9.804), hearing impairment (OR: 6.926, 95% CI: 3.630-12.215), benzodiazepine history (OR: 8.506, 95% CI: 5.651-11.805), and poor sleep quality on the first night after cardiac surgery (OR: 9.081, 95% CI: 6.225-12.248). The cross-validated area under receiver operating characteristics curve (AUC) for the screening instrument was 0.897 (95% CI: 0.876-0.916; P < 0.001).

CONCLUSION

Chronic opioid use, hearing impairment, benzodiazepine history, and poor sleep quality post-surgery are linked to postoperative delirium in cardiac surgery patients. The SDACS screening tool effectively forecasts this syndrome early, offering bedside nurses a valuable tool for prompt intervention and improved patient outcomes. The SDACS screening tool aids in early delirium risk assessment, enabling timely interventions and better patient outcomes. By predicting postoperative delirium accurately, nurses can address risk factors proactively, potentially reducing its incidence and severity, leading to improved postoperative outcomes for patients.

Prediction model for delirium in advanced cancer patients receiving palliative care: development and validation

BACKGROUND

Delirium is a common and distressing mental disorder in palliative care. To date, no delirium prediction model is available for thepalliative care population. The research aimed to develop and validate a nomogram model for predicting the occurrence of delirium in advanced cancer patients admitted to palliative care units.

METHODS

This was a prospective, multicenter, observational study. Logistic regression was used to identify the independent risk factors for incident delirium among advanced cancer patients in palliative care units. Advanced cancer patients admitted to palliative care units between February 2021 and January 2023 were recruited from four hospitals in Chengdu, Sichuan Province, China. Model performance was evaluated via the area under the receiver operating characteristic curve, calibration plots and decision curve analysis.

RESULTS

There were 592 advanced cancer patients receiving palliative care in the development cohort, 196 in the temporal validation cohort and 65 in the external validation cohort. The final nomogram model included 8 variables (age, the Charlson comorbidity index, cognitive function, the Barthel index, bilirubin, sodium, the opioid morphine equivalent dose and the use of anticholinergic drugs). The model revealed good performance in terms of discrimination, calibration, and clinical practicability, with an area under the receiver operating characteristic curve of 0.846 in the training set, 0.838 after bootstrapping, 0.829 in the temporal validation and 0.803 in the external validation set.

CONCLUSIONS

The model serves as a reliable tool to predict delirium onset for advanced cancer patients in palliative care units, which will facilitate early targeted preventive measures to reduce the burden of delirium.

Practical prognostic tools to predict the risk of postoperative delirium in older patients undergoing cardiac surgery: visual and dynamic nomograms

PURPOSE

Postoperative Delirium (POD) has an incidence of up to 65% in older patients undergoing cardiac surgery. We aimed to develop two dynamic nomograms to predict the risk of POD in older patients undergoing cardiac surgery.

METHODS

This was a single-center retrospective cohort study, which included 531 older patients who underwent cardiac surgery from July 2021 to June 2022 at Nanjing First Hospital, China. Univariable and multivariable logistic regression were used to identify the significant predictors used when constructing the models. We evaluated the performances and accuracy, validated, and estimated the clinical utility and net benefit of the models using the receiver operating characteristic (ROC), the 10-fold cross-validation, and decision curve analysis (DCA).

RESULTS

A total of 30% of the patients developed POD, the significant predictors in the preoperative model were ASA ( p < 0.001 OR = 3.220), cerebrovascular disease (p < 0.001 OR = 2.326), Alb (p < 0.037 OR = 0.946), and URE (p < 0.001 OR = 1.137), while for the postoperative model they were ASA (p = 0.044, OR = 1.737), preoperative MMSE score (p = 0.005, OR = 0.782), URE (p = 0.017 OR = 1.092), CPB duration (p < 0.001 OR = 1.010) and APACHE II (p < 0.001, OR = 1.353). The preoperative and postoperative models achieved satisfactory predictive performances, with AUC values of 0.731 and 0.799, respectively. The web calculators can be accessed at https://xxh152.shinyapps.io/Pre-POD/ and https://xxh152.shinyapps.io/Post-POD/ .

CONCLUSION

We established two nomogram models based on the preoperative and postoperative time points to predict POD risk and guide the flexible implementation of possible interventions at different time points.

Development of an individualized model for predicting postoperative delirium in elderly patients with hepatocellular carcinoma

Postoperative delirium (POD) is a common complication in older patients with hepatocellular carcinoma (HCC) that adversely impacts clinical outcomes. We aimed to evaluate the risk factors for POD and to construct a predictive nomogram. Data for a total of 1481 older patients (training set: n=1109; validation set: n=372) who received liver resection for HCC were retrospectively retrieved from two prospective databases. The receiver operating characteristic (ROC) curve, calibration plot, and decision curve analysis (DCA) were used to evaluate the performance. The rate of POD was 13.3% (148/1109) in the training set and 16.4% (61/372) in the validation set. Multivariate analysis of the training set revealed that factors including age, history of cerebrovascular disease, American Society of Anesthesiologists (ASA) classification, albumin level, and surgical approach had significant effects on POD. The area under the ROC curves (AUC) for the nomogram, incorporating the aforementioned predictors, was 0.798 (95% CI 0.752-0.843) and 0.808 (95% CI 0.754-0.861) for the training and validation sets, respectively. The calibration curves of both sets showed a degree of agreement between the nomogram and the actual probability. DCA demonstrated that the newly established nomogram was highly effective for clinical decision-making. We developed and validated a nomogram with high sensitivity to assist clinicians in estimating the individual risk of POD in older patients with HCC.

Effects of short-term preoperative intranasal dexmedetomidine plus conventional treatment on delirium following cardiac surgery in patients with sleep disorders

STUDY OBJECTIVES

To assess whether preoperative dexmedetomidine (DEX) nasal drips combined with conventional treatment could mitigate the occurrence of postoperative delirium (POD).

DESIGN

A prospective randomised controlled study.

SETTING

The cardiac surgery intensive care unit (CSICU) and patient hospitalisation ward at a university hospital.

PARTICIPANTS

A total of 100 patients (aged ≥60 years) undergoing cardiac surgery at a university hospital between 7 January 2022, and 30 November 2022 met the eligibility criteria and were included in the study.

INTERVENTIONS

Patients with sleep disorders (Pittsburgh Sleep Quality Index ≥8) were divided into two groups: Group A (the placebo group, n=50), receiving a short-term preoperative placebo combined with conventional treatment and Group B (the DEX group, n=50), receiving short-term preoperative DEX combined with conventional treatment.

MEASUREMENTS AND RESULTS

The Confusion Assessment Method for the ICU (CAM-ICU) was used for POD assessment in the CSICU, while the CAM was employed to assess delirium in the patient ward. Group B demonstrated a reduced incidence of POD compared to Group A (12% vs. 30%, odds ratio: 0.318, 95% confidence interval: 0.112-0.905, p=0.027).

CONCLUSION

The combined treatment involving DEX demonstrated a decreased incidence of POD in elderly individuals with sleep disorders undergoing cardiac surgery compared to the placebo combination treatment.

TRIAL REGISTRATION

URL: www.chictr.org.cn with registration number ChiCTR 2100043968, registered on 06/03/2021.