The Role of Vascular Risk Factors in Post-Stroke Delirium: A Systematic Review and Meta-Analysis

Cerebrovascular pulsatility indicates preoperative subcortical cognitive impairment and an increased risk for postoperative delirium in elderly patients undergoing elective spine surgery

Introduction

Advances in spine surgery enable safe interventions in elderly patients, but perioperative neurocognitive disorders (pNCD), such as post-operative delirium (POD) and cognitive dysfunction (POCD), remain a serious concern. Pre-operative cognitive impairment is a major risk factor for pNCD. Comprehensive pre-operative cognitive assessments are not feasible in clinical practice, making effective screening methods desirable. This study investigates whether pre-operative cerebrovascular duplex sonography can assess subcortical (vascular) cognitive impairment and the risk for POD.

Methods

This prospective single-center study recruited patients aged ≥60 years scheduled for elective spine surgery at a German university hospital. Patients underwent pre-operative assessments including cognitive abilities (CERAD test battery), structural MRI, and cerebrovascular duplex sonography. POD screening was conducted three times daily for at least 3 days. The primary hypothesis, that the mean pulsatility index (PI) of both internal carotid arteries (ICA) predicts POD risk, was tested using logistic regression. Secondary analyses examined the association between POD risk and ICA flow (time-averaged peak velocities, TAPV) and correlations with cognitive profiles and MRI characteristics.

Results

POD occurred in 22% of patients (n = 22/99) within three postoperative days. Patients with POD were significantly older (75.9 ± 5.4 vs. 70.0 ± 6.9 years, p < 0.01) but did not differ by gender (p = 0.51). ICA PI significantly predicted POD risk (OR = 5.46 [95%CI: 1.81-16.49], p = 0.003), which remained significant after adjustment for age and duration of surgery (ORadj = 6.38 [95% CI: 1.77-23.03], p = 0.005). TAPV did not inform the POD risk (p = 0.68). ICA PI Pre-operative cognitive scores were significantly associated with ICA PI (mean CERAD score: r = -0.32, p < 0.001). ICA PI was also significantly associated with total white matter lesion volume (τ = 0.19, p = 0.012) and periventricular white matter lesion volume (τ = 0.21, p = 0.007).

Discussion

This is the first study to demonstrate that cerebrovascular duplex sonography can assess the risk for POD in elderly spine surgery patients. Increased ICA PI may indicate subcortical impairment, larger white matter lesion load, and lower white matter volume, predisposing factors for POD. Pre-operative cerebrovascular duplex sonography of the ICA is widely available, easy-to-use, and efficient, offering a promising screening method for POD risk. Increased ICA PI could supplement established predictors like age to adjust surgical and peri-operative procedures to individual risk profiles.

Prevalence of post-stroke delirium in acute settings: A systematic review and meta-analysis

BACKGROUND

Although post-stroke delirium is a frequent complication in acute settings and has significant long-lasting implications for patients, the prevalence of post-stroke delirium diagnosed according to gold-standard criteria remains uncertain. This highlights the importance of updating the current evidence.

OBJECTIVE

This review aims to provide a precise estimation of the prevalence of delirium in acute post-stroke settings and to explore potential differences in the reported prevalence according to the characteristics of the study and stroke survivors.

DESIGN

Systematic review and meta-analysis.

SETTING AND PARTICIPANTS

Post-stroke survivors with delirium in acute settings.

DATA SOURCES

Five English and two Chinese language databases from inception to June 2023, and the reference lists of published reviews.

METHODS

Studies reporting the prevalence of post-stroke delirium according to the Diagnostic and Statistical Manual of Mental Disorders criteria with the description of assessment method in the absence of interventions for delirium were eligible. Two reviewers independently screened searched records and extracted data from eligible studies. A meta-analysis was conducted using a random-effects model to evaluate the prevalence of post-stroke delirium, and predefined subgroup analyses, sensitivity analyses, and mixed-effects meta-regression were conducted to explore the contribution of heterogeneity.

RESULTS

Twenty-nine eligible studies involving 8839 survivors were included. In acute settings, the overall weighted prevalence of post-stroke delirium was 25 % (95 % CI, 20-30; I2, 95 %). Subgroup analyses revealed age-dependent variations in delirium prevalence, with rates of 20 %, 25 %, and 34 % for ages 60-64, 65-74, and 75-79, respectively. Delirium prevalence varied by assessment duration (7 days: 31 %, >7 days: 24 %, <7 days: 20 %). Initial screening significantly reduced reported prevalence to 15 %, compared with 30 % when no initial screening was conducted. Delirium prevalence was lower when nurses were involved in assessments (13 % vs. 29 %). No significant effects were detected for economic status, publication year, female percentage, onset-to-admission time, stroke type, and assessment frequency. Meta-regression analysis revealed that higher delirium prevalence was associated with increased survivors' age (β = 0.051; 95 % CI, -0.0002 to 0.103; P = 0.05; R2 = 13.36 %).

CONCLUSION

A high prevalence of post-stroke delirium was observed in acute settings. Nurses are required to integrate and coordinate the prevention, early detection, and management of delirium following stroke into their nursing practice, particularly for older stroke survivors. The findings necessitate the need for incorporating specialized training within nursing education to identify and manage the delirium effectively and accurately. This reinforces the pivotal role of nurses in the early detection and prevention of delirium within the acute stroke care continuum.

REGISTRATION

The protocol was registered on PROSPERO (CRD42022352097).

TWEETABLE ABSTRACT

Evidence suggests 25 % prevalence of post-stroke delirium in acute settings, with higher rates in older patients, emphasizing the need for prevention, early detection, and management in nursing practice.

A machine learning-based prediction model for postoperative delirium in cardiac valve surgery using electronic health records

BACKGROUND

Previous models for predicting delirium after cardiac surgery remained inadequate. This study aimed to develop and validate a machine learning-based prediction model for postoperative delirium (POD) in cardiac valve surgery patients.

METHODS

The electronic medical information of the cardiac surgical intensive care unit (CSICU) was extracted from a tertiary and major referral hospital in southern China over 1 year, from June 2019 to June 2020. A total of 507 patients admitted to the CSICU after cardiac valve surgery were included in this study. Seven classical machine learning algorithms (Random Forest Classifier, Logistic Regression, Support Vector Machine Classifier, K-nearest Neighbors Classifier, Gaussian Naive Bayes, Gradient Boosting Decision Tree, and Perceptron.) were used to develop delirium prediction models under full (q = 31) and selected (q = 19) feature sets, respectively.

RESULT

The Random Forest classifier performs exceptionally well in both feature datasets, with an Area Under the Curve (AUC) of 0.92 for the full feature dataset and an AUC of 0.86 for the selected feature dataset. Additionally, it achieves a relatively lower Expected Calibration Error (ECE) and the highest Average Precision (AP), with an AP of 0.80 for the full feature dataset and an AP of 0.73 for the selected feature dataset. To further evaluate the best-performing Random Forest classifier, SHAP (Shapley Additive Explanations) was used, and the importance matrix plot, scatter plots, and summary plots were generated.

CONCLUSIONS

We established machine learning-based prediction models to predict POD in patients undergoing cardiac valve surgery. The random forest model has the best predictive performance in prediction and can help improve the prognosis of patients with POD.

Post-stroke delirium and challenges for the rehabilitation setting: A narrative review

INTRODUCTION

Post-stroke delirium (PSD) is a common yet underrecognized complication following stroke, with its effect on stroke rehabilitation being the subject of limited attention. The objective of this narrative review is to provide an overview of core issues in PSD including epidemiology, diagnostic challenges, and management considerations, with an emphasis on the rehabilitation phase.

METHODS

Ovid Medline and Google Scholar were searched through February 2023 using keywords related to delirium, rehabilitation, and the post-stroke period. Only studies conducted on adults (≥18 years) and written in the English language were included.

RESULTS

PSD affects approximately 25% of stroke patients, and often persists well into the post-acute phase, with a negative impact on rehabilitation outcomes including lengths of stay, function, and cognition. Certain stroke and patient characteristics can help predict risk for PSD. The diagnosis of delirium becomes more challenging when superimposed on stroke deficits (such as attentional impairment or other cognitive, psychiatric, or behavioural disorders), leading to underdiagnosis, overdiagnosis, or misdiagnosis. Particularly in patients with post-stroke language or cognitive disorders, common screening tools are less accurate. The multidisciplinary rehabilitation team should be involved in management of PSD as rehabilitative activities can be beneficial for patients who can participate safely. Addressing barriers to effective delirium care at various levels of the health care system can improve rehabilitation trajectories for these patients.

CONCLUSIONS

PSD is a disease entity commonly encountered in the rehabilitation setting, but it is challenging to diagnose and manage. New delirium screening tools and management approaches specific for the post-stroke and rehabilitation settings are needed.

A predictive scoring system for postoperative delirium in the elderly patients with intertrochanteric fracture

OBJECTIVE

To establish a scoring system to predict the postoperative delirium in elderly patients with intertrochanteric fracture.

MATERIALS AND METHODS

We retrospectively reviewed 159 elderly patients with a diagnosis of intertrochanteric fracture and underwent closed reduction and intramedullary nail fixation, and then divided them into two groups including the delirium group (23 cases) or non-delirium group (136 cases) in our hospital from January 2017 to December 2019. The following clinical characteristics were recorded and analyzed: age, gender, fracture classification, body mass index (BMI), history of diabetes mellitus, history of stroke, preoperative albumin, preoperative hemoglobin (Hb), preoperative arterial partial pressure of oxygen (PaO₂), time between admission and surgery, lower limb thrombosis, American Society of Anesthesiologists (ASA) grade, operative time, operative blood loss, and intraoperative blood transfusion. The prevalence of these clinical characteristics in delirium group was evaluated, and the scoring system was established using logistic regression analysis. The performance of the scoring system was also prospectively validated.

RESULTS

The predictive scoring system was based on five clinical characteristics confirmed as significant predictors of postoperative delirium, namely, age > 75 years, history of stroke, preoperative Hb ≤ 100 g/L, preoperative PaO₂ ≤ 60 mmHg, and time between admission to surgery > 3 days. Delirium group showed a significant higher score than non-delirium (6.26 vs. 2.29, P < 0.001), and the optimal cut-off value for the scoring system was 4 points. The sensitivity and specificity of the scoring system for predicting postoperative delirium were 82.61% and 81.62% in derivation set, respectively, and 72.71% and 75.00% in validation set.

CONCLUSION

The predictive scoring system confirmed with achieve satisfactory sensitivity and specificity in predicting postoperative delirium in the elderly with intertrochanteric fracture. The risk of postoperative delirium in patients with the score of 5 to 11 is high, while the score of 0 to 4 is low.

Effects of Melatonin Administration on Post-Stroke Delirium in Patients with Intracerebral Hemorrhage

Post-stroke delirium (PSD) after intracerebral hemorrhage (ICH) is considered to be even more detrimental compared to that after ischemic stroke. Treatment options for post-ICH PSD remain limited. This study aimed at investigating to what extent prophylactic melatonin administration may have beneficial effects on post-ICH PSD. We performed a mono-centric, non-randomized, non-blinded, prospective cohort study, including 339 consecutive ICH patients admitted to the Stroke Unit (SU) from December 2015 to December 2020. The cohort consisted of ICH patients who underwent standard care (defined as the control group) and ICH patients who additionally received prophylactic melatonin (2 mg per day, at night) within 24 h of ICH onset until the discharge from the SU. The primary endpoint was post-ICH PSD prevalence. The secondary endpoints were: (i) PSD duration and (ii) the duration of SU stay. The PSD prevalence was higher in the melatonin treated cohort compared to the propensity score-matched (PSM) control group. Post-ICH PSD patients receiving melatonin had shorter SU-stay durations, and shorter PSD durations, although not statistically significant. This study shows no efficacy in limiting post-ICH PSD with preventive melatonin administration.