Cardiac Delirium Index for Predicting the Occurrence of Postoperative Delirium in Adult Patients After Coronary Artery Bypass Grafting

Platelet Dynamics in Neurodegenerative Disorders: Investigating the Role of Platelets in Neurological Pathology

Background: Neurological disorders, particularly those associated with aging, pose significant challenges in early diagnosis and treatment. The identification of specific biomarkers, such as platelets (PLTs), has emerged as a promising strategy for early detection and intervention in neurological health. This systematic review aims to explore the intricate relationship between PLT dynamics and neurological health, focusing on their potential role in cognitive functions and the pathogenesis of cognitive disorders. Methods: Adhering to PRISMA guidelines, a comprehensive search strategy was employed in the PubMed and Scholar databases to identify studies on the role of PLTs in neurological disorders published from 2013 to 2023. The search criteria included studies focusing on PLTs as biomarkers in neurological disorders, their dynamics, and their potential in monitoring disease progression and therapy effectiveness. Results: The systematic review included 104 studies, revealing PLTs as crucial biomarkers in neurocognitive disorders, acting as inflammatory mediators. The findings suggest that PLTs share common features with altered neurons, which could be utilised for monitoring disease progression and evaluating the effectiveness of treatments. PLTs are identified as significant biomarkers for detecting neurological disorders in their early stages and understanding the pathological events leading to neuronal death. Conclusions: The systematic review underscores the critical role of PLTs in neurological disorders, highlighting their potential as biomarkers for the early detection and monitoring of disease progression. However, it also emphasises the need for further research to solidify the use of PLTs in neurological disorders, aiming to enhance early diagnosis and intervention strategies.

Neutrophil to Lymphocyte Ratio and Periprosthetic Joint Infection: A Systematic Review and Meta-Analysis

BACKGROUND

The neutrophil-to-lymphocyte ratio (NLR) has shown promising results as a diagnostic tool for periprosthetic joint infection (PJI) after total joint arthroplasty. We conducted a systematic review and meta-analysis to determine the utility of NLR in the diagnosis of PJI.

METHODS

We searched PubMed, Scopus, and Web of Science from inception up to 2022 and evaluated the quality of the included literature.

RESULTS

Based on the 12 eligible studies, NLR levels were significantly higher in patients who had PJI compared to those who had aseptic loosening (standard mean difference (SMD) = 1.05, 95% Confidence Interval (CI) = 0.71 to 1.40, P < .001). In the subgroup analysis according to type of PJI, NLR levels were significantly higher in patients who had either acute (SMD = 1.04, 95% CI = 0.05 to 2.03, P < .001) or chronic PJI (SMD = 1.08, 95% CI = 0.55 to 1.61, P < .001), compared to those who had aseptic loosening. According to type of arthroplasty, NLR levels were significantly higher in patients who had either total knee arthroplasty (SMD = 1.81, 95% CI = 1.48 to 2.13, P < .001) or total hip arthroplasty (SMD = 1.76, 95% CI = 1.54 to 1.98, P < .001) compared to aseptic loosening. The pooled sensitivity of the 12 studies was 0.73 (95% CI, 0.65 to 0.79), and the pooled specificity was 0.75 (95% CI, 0.71 to 0.78). The pooled positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio of NLR were 2.94 (95% CI = 2.44 to 3.54), 0.35 (95% CI = 0.27 to 0.46), and 8.26 (95% CI = 5.42 to 12.58), respectively.

CONCLUSION

In summary, this meta-analysis indicates that NLR is a reliable marker in the diagnosis of PJI.

Dynamic Nomogram for Predicting the Risk of Perioperative Neurocognitive Disorders in Adults

BACKGROUND

Simple and rapid tools for screening high-risk patients for perioperative neurocognitive disorders (PNDs) are urgently needed to improve patient outcomes. We developed an online tool with machine-learning algorithms using routine variables based on multicenter data.

METHODS

The entire dataset was composed of 49,768 surgical patients from 3 representative academic hospitals in China. Surgical patients older than 45 years, those undergoing general anesthesia, and those without a history of PND were enrolled. When the patient's discharge diagnosis was PND, the patient was in the PND group. Patients in the non-PND group were randomly extracted from the big data platform according to the surgical type, age, and source of data in the PND group with a ratio of 3:1. After data preprocessing and feature selection, general linear model (GLM), artificial neural network (ANN), and naive Bayes (NB) were used for model development and evaluation. Model performance was evaluated by the area under the receiver operating characteristic curve (ROCAUC), the area under the precision-recall curve (PRAUC), the Brier score, the index of prediction accuracy (IPA), sensitivity, specificity, etc. The model was also externally validated on the multiparameter intelligent monitoring in intensive care (MIMIC) Ⅳ database. Afterward, we developed an online visualization tool to preoperatively predict patients' risk of developing PND based on the models with the best performance.

RESULTS

A total of 1051 patients (242 PND and 809 non-PND) and 2884 patients (6.2% patients with PND) were analyzed on multicenter data (model development, test [internal validation], external validation-1) and MIMIC Ⅳ dataset (external validation-2). The model performance based on GLM was much better than that based on ANN and NB. The best-performing GLM model on validation-1 dataset achieved ROCAUC (0.874; 95% confidence interval [CI], 0.833-0.915), PRAUC (0.685; 95% CI, 0.584-0.786), sensitivity (72.6%; 95% CI, 61.4%-81.5%), specificity (84.4%; 95% CI, 79.3%-88.4%), Brier score (0.131), and IPA (44.7%), and of which the ROCAUC (0.761, 95% CI, 0.712-0.809), the PRAUC (0.475, 95% CI, 0.370-0.581), Brier score (0.053), and IPA (76.8%) on validation-2 dataset. Afterward, we developed an online tool (https://pnd-predictive-model-dynnom.shinyapps.io/ DynNomapp/) with 10 routine variables for preoperatively screening high-risk patients.

CONCLUSIONS

We developed a simple and rapid online tool to preoperatively screen patients' risk of PND using GLM based on multicenter data, which may help medical staff's decision-making regarding perioperative management strategies to improve patient outcomes.

Neutrophil to lymphocyte ratio and platelet to lymphocyte ratio as prognostic predictors for delirium in critically ill patients: a systematic review and meta-analysis

INTRODUCTION

In this systematic review and meta-analysis, we aim to analyze the current literature to evaluate neutrophil to lymphocyte ratio (NLR) and platelet to lymphocyte ratio (PLR) values among critically ill patients who develop delirium as compared to those who do not.

METHODS

PubMed, Web of Science, and Scopus were used to conduct a systematic search for relevant publications published before June 12, 2022. The Newcastle-Ottawa scale was used for quality assessment. Because a significant level of heterogeneity was found, we used the random-effects model to generate pooled effects.

RESULTS

Twenty-four studies including 11,579 critically ill patients, of whom 2439 were diagnosed with delirium, were included in our meta-analysis. Compared with the non-delirious group, the delirious group's NLR levels were significantly higher (WMD = 2.14; CI 95% = 1.48-2.80, p < 0.01). In the subgroup analysis according to the type of critical condition, the NLR levels in patients of delirious group were significantly more than those of non-delirious group in studies on POD, PSD and PCD (WMD = 1.14, CI 95% = 0.38-1.91, p < 0.01, WMD = 1.38, CI 95% = 1.04-1.72, p < 0.001, and WMD = 4.22, CI 95% = 3.47-4.98, p < 0.001, respectively). However, compared with the non-delirious group, the delirious group's PLR levels were not significantly different (WMD = 1.74; CI 95% = -12.39-15.86, p = 0.80).

CONCLUSION

Our findings support NLR to be a promising biomarker that can be readily integrated into clinical settings to aid in the prediction and prevention of delirium.

Effects of inflammation and oxidative stress on postoperative delirium in cardiac surgery

The past decade has witnessed unprecedented medical progress, which has translated into cardiac surgery being increasingly common and safe. However, complications such as postoperative delirium remain a major concern. Although the pathophysiological changes of delirium after cardiac surgery remain poorly understood, it is widely thought that inflammation and oxidative stress may be potential triggers of delirium. The development of delirium following cardiac surgery is associated with perioperative risk factors. Multiple interventions are being explored to prevent and treat delirium. Therefore, research on the potential role of biomarkers in delirium as well as identification of perioperative risk factors and pharmacological interventions are necessary to mitigate the development of delirium.

Outcomes of postoperative delirium in patients undergoing cardiac surgery: A systematic review and meta-analysis

Background

Postoperative delirium (POD) is an acute brain dysfunction that is frequently observed in patients undergoing cardiac surgery. Increasing evidence indicates POD is related to higher mortality among cardiac surgical patients, but the results remain controversial. Moreover, a quantitative evaluation of the influence of POD on hospital days, intensive care unit (ICU) time, and mechanical ventilation (MV) time has not been performed.

Objective

This study aimed to evaluate the correlation between POD and outcomes in patients undergoing cardiac surgery by a systematic review and meta-analysis.

Materials and methods

A total of 7 electronic databases (Cochrane Library, PubMed, EMBASE, CINAHL Complete, MEDLINE, Wan-fang database, and China National Knowledge Infrastructure) were searched from January 1980 to July 20, 2021, with language restrictions to English and Chinese, to estimate the impact of the POD on outcome in patients who underwent cardiac surgery. The meta-analysis was registered with PROSPERO (Registration: CRD42021228767).

Results

Forty-two eligible studies with 19785 patients were identified. 3368 (17.0%) patients were in the delirium group and 16417 (83%) were in the non-delirium group. The meta-analysis showed that compared to patients without POD, patients with POD had 2.77-fold higher mortality (OR = 2.77, 95% CI 1.86-4.11, P < 0.001), 5.70-fold higher MV (>24h) rate (OR = 5.70, 95% CI 2.93-11.09, P < 0.001); and longer MV time (SMD = 0.83, 95% CI 0.57-1.09, P < 0.001), ICU time (SMD = 0.91, 95% CI 0.60-1.22, P < 0.001), hospital days (SMD = 0.62, 95% CI 0.48-0.76, P < 0.001).

Conclusion

The synthesized evidence suggests that POD is causally related to the increased risk of mortality, prolonged length of ICU and hospital stay, and a longer duration of MV time. Future research should focus on the interventions for POD, to reduce the incidence.

Systematic review registration

[www.crd.york.ac.uk/PROSPERO], identifier [CRD42021228767].

Risk assessment of perioperative neurocognitive disorders, where are we now?

PURPOSE OF REVIEW

Perioperative neurocognitive disorders (PNDs) are among the most frequent complications after surgery and are associated with considerable morbidity and mortality. We analysed the recent literature regarding risk assessment of PND.

RECENT FINDINGS

Certain genetic variants of the cholinergic receptor muscarinic 2 and 4, as well as a marked degree of frailty but not the kind of anaesthesia (general or spinal) are associated with the risk to develop postoperative delirium (POD). Models predict POD with a discriminative power, for example, area under the receiver operating characteristics curve between 0.52 and 0.94.

SUMMARY

Advanced age as well as preexisting cognitive, functional and sensory deficits remain to be the main risk factors for the development of PND. Therefore, aged patients should be routinely examined for both preexisting and new developing deficits, as recommended in international guidelines. Appropriate tests should have a high discrimination rate, be feasible to be administered by staff that do not require excessive training, and only take a short time to be practical for a busy outpatient clinic. Models to predict PND, should be validated appropriately (and externally if possible) and should not contain a too large number of predictors to prevent overfitting of models.

White-Cell Derived Inflammatory Biomarkers in Prediction of Postoperative Delirium in Elderly Patients Undergoing Surgery for Lower Limb Fracture Under Non-General Anaesthesia

Purpose

The aim of this study was to investigate whether white-cell derived biomarkers could serve as potential markers in prediction of postoperative delirium (POD) after lower limb fracture.

Patients and Methods

Elderly patients with surgery for lower limb fracture under non-general anaesthesia were included. Neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR) and platelet-to-white cell ratio (PWR), which were most recently measured preceding surgery and measured within 24h after surgery, were calculated. Delirium was measured with Confusion Assessment Method (CAM) once daily from preoperative day 1 to postoperative day 3 or hospital discharge.

Results

The incidence of POD was 32.6% (60/184). Between patients with and those without POD, there were significant differences in preoperative hematological biomarkers (neutrophil count, lymphocyte count, NLR and PWR) and postoperative hematological biomarkers (white cell count, neutrophil count, lymphocyte count, NLR, PLR and PWR). More obvious changes before and after operation for NLR, PLR and C-reactive protein (CRP) were found in patients with POD. Multivariate logistic regression showed that benzodiazepines (OR, 7.912; 95% CI, 1.884–33.230; p = 0.005), change of CRP (OR, 1.017; 95% CI, 1.007–1.027; p = 0.001) and postoperative NLR (OR, 1.358; 95% CI, 1.012–1.823; p = 0.041) were associated with POD. When the changes of NLR, PLR and PWR entered multivariate logistic regression, older age (OR, 1.073; 95% CI, 1.001–1.149; p = 0.046), benzodiazepines (OR, 6.811; 95% CI, 1.652–28.081; p = 0.008), greater change of CRP (OR, 1.015; 95% CI, 1.006–1.023; p = 0.001) and greater change of NLR (OR, 1.266; 95% CI, 1.035–1.549; p = 0.022) were associated with increased risk of POD. Postoperative NLR had high accuracy to predict POD with area under curve (AUC) of 0.790 (95% CI 0.708 to 0.872).

Conclusion

Age, benzodiazepines, postoperative NLR, change of NLR and change of CRP were independent predictable markers for POD in elderly patients undergoing surgery for lower limb fracture under non-general anaesthesia. Early postoperative NLR may help to recognize POD as soon as possible.

Intraoperative Glycemic Variability and Mean Glucose are Predictors for Postoperative Delirium After Cardiac Surgery: A Retrospective Cohort Study

Purpose

Postoperative delirium (POD) is a common but serious complication after cardiac surgery and is associated with various short- and long-term outcomes. In this study, we investigated the effects of intraoperative glycemic variability (GV) and other glycemic variables on POD after cardiac surgery.

Patients and Methods

A retrospective single-center cohort analysis was conducted using data from electronic medical record from 2018 to 2020. A total of 705 patients undergoing coronary artery bypass graft surgery and/or valve surgery, and/or aortic replacement surgery were included in the analysis. Intraoperative GV was assessed with a coefficient of variation (CV), which was defined as the standard deviation of five intraoperative blood glucose measurements divided by the mean. POD assessment was performed three times a day in the ICU and twice a day in the ward until discharge by trained medical staff. POD was diagnosed if any of the Confusion Assessment Method for the Intensive Care Unit was positive in the ICU, and the Confusion Assessment Method was positive in the ward. Multivariable logistic regression was used to identify associations between intraoperative GV and POD.

Results

POD occurred in 306 (43.4%) patients. When intraoperative glycemic CV was compared as a continuous variable, the delirium group had higher intraoperative glycemic CV than the non-delirium group (22.59 [17.09, 29.68] vs 18.19 [13.00, 23.35], p < 0.001), and when intraoperative glycemic CV was classified as quartiles, the incidence of POD increased as intraoperative glycemic CV quartiles increased (first quartile 29.89%; second quartile 36.67%; third quartile 44.63%; and fourth quartile 62.64%, p < 0.001). In the multivariable logistic regression model, patients in the third quartile of intraoperative glycemic CV were 1.833 times (OR 1.833, 95% CI: 1.132–2.967, p = 0.014), and patients in the fourth quartile of intraoperative glycemic CV were 3.645 times (OR 3.645, 95% CI: 2.235–5.944, p < 0.001) more likely to develop POD than those in the first quartile of intraoperative glycemic CV.

Conclusion

Intraoperative blood glucose fluctuation, manifested by intraoperative GV, is associated with POD after cardiac surgery. Patients with a higher intraoperative GV have an increased risk of POD.