Establishment and validation of a delirium prediction model for neurosurgery patients in intensive care

Effect of remimazolam versus propofol anesthesia on postoperative delirium in neurovascular surgery: study protocol for a randomized controlled, non-inferiority trial

BACKGROUND

Remimazolam is a short-acting benzodiazepine newly approved for the induction and maintenance of general anesthesia. Remimazolam emerges as an ideal drug for the neurosurgical population due to its rapid emergence, enabling early neurological assessment, and its ability to maintain perfusion pressure, which is crucial for preventing cerebral ischemia. However, the use of benzodiazepine has been associated with an increased risk of postoperative delirium (POD). There is currently limited evidence about the relationship between remimazolam-based total intravenous anesthesia (TIVA) and POD.

METHODS

In this double-blind, randomized, non-inferiority trial, we plan to include 696 adult patients with American Society of Anesthesiologists physical status class I to III, undergoing elective neurovascular surgery under general anesthesia. After informed consent, the patients will be randomized to receive either remimazolam or propofol-based TIVA with a 1:1 ratio. The primary outcome is the incidence of POD within 5 days after surgery. Secondary outcomes include subtypes, number of positive assessments and severity of POD, emergence agitation, intraoperative awareness and undesirable patient movement, intraoperative hypotension, and postoperative cognitive function. The data will be analyzed in modified intention to treat.

DISCUSSION

This trial will evaluate the effect of remimazolam on the development of POD compared to propofol anesthesia. The results of this trial will provide evidence regarding the choice of optimal anesthetics to minimize the risk of POD in neurosurgical patients.

TRIAL REGISTRATION

The study protocol was prospectively registered at the Clinical trials ( https://clinicaltrials.gov , NCT06115031, principal investigator: Jiseon Jeong; date of first registration: November 2, 2023, before the recruitment of the first participant.

Development and internal validation of a nomogram to predict temporary acute agitated delirium after surgery for chronic subdural hematoma in elderly patients: an analysis of the clinical database

Background

This study aimed to develop a nomogram for predicting temporary acute agitated delirium after surgery in patients with chronic subdural hematoma (CSH) without neurological compromise and hospitalized in the neurosurgery.

Methods

We included 289 patients with chronic subdural hematoma (CSH) from the medical information system of Yuebei People's Hospital of Shaoguan City, Guangdong Province, and collected 16 clinical indicators within 24 h of admission. We used the least absolute shrinkage and selection operator (LASSO) regression to identify risk factors. We established a multivariate logistic regression model and constructed a nomogram. We performed internal validation by 1,000 bootstrap samples; we plotted a receiver operating curve (ROC) and calculated the area under the curve (AUC), sensitivity, and specificity. We also evaluated the calibration of our model by the calibration curve and the Hosmer-Lemeshow goodness-of-fit test (HL test). We performed a decision curve analysis (DCA) and a clinical impact curve (CIC) to assess the net clinical benefit of our model.

Results

The nomogram included alcoholism history, hepatic insufficiency, verbal rating scale for postoperative pain (VRS), pre-hospital modified Rankin Scale (mRS), and preoperative hematoma thickness as predictors. Our model showed satisfactory diagnostic performance with an AUC value of 0.8474 in the validation set. The calibration curve and the HL test showed good agreement between predicted and observed outcomes (p = 0.9288). The DCA and CIC showed that our model had a high predictive ability for the occurrence of postoperative delirium in patients with CSDH.

Conclusion

We identified alcoholism, liver dysfunction, pre-hospital mRS, preoperative hematoma thickness, and postoperative VRS pain as predictors of postoperative delirium in chronic subdural hematoma patients. We developed and validated a multivariate logistic regression model and a nomogram.

Music to prevent deliriUm during neuroSurgerY (MUSYC): a single-centre, prospective randomised controlled trial

OBJECTIVES

Delirium is a serious complication following neurosurgical procedures. We hypothesise that the beneficial effect of music on a combination of delirium-eliciting factors might reduce delirium incidence following neurosurgery and subsequently improve clinical outcomes.

DESIGN

Prospective randomised controlled trial.

SETTING

Single centre, conducted at the neurosurgical department of the Erasmus Medical Center, Rotterdam, the Netherlands.

PARTICIPANTS

Adult patients undergoing craniotomy were eligible.

INTERVENTIONS

Patients in the intervention group received preferred recorded music before, during and after the operation until day 3 after surgery. Patients in the control group were treated according to standard of clinical care.

PRIMARY AND SECONDARY OUTCOME MEASURES

Primary outcome was presence or absence of postoperative delirium within the first 5 postoperative days measured with the Delirium Observation Screening Scale (DOSS) and, in case of a daily mean score of 3 or higher, a psychiatric evaluation with the latest Diagnostic and Statistical Manual of Mental Disorders (DSM-5) criteria. Secondary outcomes included anxiety, heart rate variability (HRV), depth of anaesthesia, delirium severity and duration, postoperative complications, length of stay and location of discharge.

RESULTS

We enrolled 189 patients (music=95, control=94) from July 2020 through September 2021. Delirium, as assessed by the DOSS, was less common in the music (n=11, 11.6%) than in the control group (n=21, 22.3%, OR:0.49, p=0.048). However, after DSM-5 confirmation, differences in delirium were not significant (4.2% vs 7.4%, OR:0.47, p=0.342). Moreover, music increased the HRV (root mean square of successive differences between normal heartbeats, p=0.012). All other secondary outcomes were not different between groups.

CONCLUSION

Our results support the efficacy of music in reducing the incidence of delirium after craniotomy, as found with DOSS but not after DSM-5 confirmation, substantiated by the effect of music on preoperative autonomic tone. Delirium screening tools should be validated and the long-term implications should be evaluated after craniotomy.

TRIAL REGISTRATION NUMBER

Trialregister.nl: NL8503 and ClinicalTrials.gov: NCT04649450.

Automated machine learning-based model for the prediction of delirium in patients after surgery for degenerative spinal disease

OBJECTIVE

This study used machine learning algorithms to identify critical variables and predict postoperative delirium (POD) in patients with degenerative spinal disease.

METHODS

We included 663 patients who underwent surgery for degenerative spinal disease and received general anesthesia. The LASSO method was used to screen essential features associated with POD. Clinical characteristics, preoperative laboratory parameters, and intraoperative variables were reviewed and were used to construct nine machine learning models including a training set and validation set (80% of participants), and were then evaluated in the rest of the study sample (20% of participants). The area under the receiver-operating characteristic curve (AUROC) and Brier scores were used to compare the prediction performances of different models. The eXtreme Gradient Boosting algorithms (XGBOOST) model was used to predict POD. The SHapley Additive exPlanations (SHAP) package was used to interpret the XGBOOST model. Data of 49 patients were prospectively collected for model validation.

RESULTS

The XGBOOST model outperformed the other classifier models in the training set (area under the curve [AUC]: 92.8%, 95% confidence interval [CI]: 90.7%-95.0%), validation set (AUC: 87.0%, 95% CI: 80.7%-93.3%). This model also achieved the lowest Brier Score. Twelve vital variables, including age, serum albumin, the admission-to-surgery time interval, C-reactive protein level, hypertension, intraoperative blood loss, intraoperative minimum blood pressure, cardiovascular-cerebrovascular disease, smoking, alcohol consumption, pulmonary disease, and admission-intraoperative maximum blood pressure difference, were selected. The XGBOOST model performed well in the prospective cohort (accuracy: 85.71%).

CONCLUSION

A machine learning model and a web predictor for delirium after surgery for the degenerative spinal disease were successfully developed to demonstrate the extent of POD risk during the perioperative period, which could guide appropriate preventive measures for high-risk patients.

Perioperative neurocognitive disorders: A narrative review focusing on diagnosis, prevention, and treatment

Perioperative neurocognitive disorders (NCDs) refer to neurocognitive abnormalities detected during the perioperative periods, including preexisting cognitive impairment, preoperative delirium, delirium occurring up to 7 days after surgery, delayed neurocognitive recovery, and postoperative NCD. The Diagnostic and Statistical Manual of Mental Disorders‐5th edition (DSM‐5) is the golden standard for diagnosing perioperative NCDs. Given the impracticality of using the DSM‐5 by non‐psychiatric practitioners, many diagnostic tools have been developed and validated for different clinical scenarios. The etiology of perioperative NCDs is multifactorial and includes predisposing and precipitating factors. Identifying these risk factors is conducive to preoperative risk stratification and perioperative risk reduction. Prevention for perioperative NCDs should include avoiding possible contributors and implementing nonpharmacologic and pharmacological interventions. The former generally includes avoiding benzodiazepines, anticholinergics, prolonged liquid fasting, deep anesthesia, cerebral oxygen desaturation, and intraoperative hypothermia. Nonpharmacologic measures include preoperative cognitive prehabilitation, comprehensive geriatric assessment, implementing fast‐track surgery, combined use of regional block, and sleep promotion. Pharmacological measures including dexmedetomidine, nonsteroidal anti‐inflammatory drugs, and acetaminophen are found to have beneficial effects. Nonpharmacological treatments are the first‐line measures for established perioperative NCDs. Pharmacological treatments are still limited to severely agitated or distressed patients.

Risk Factors and a Nomogram Model Establishment for Postoperative Delirium in Elderly Patients Undergoing Arthroplasty Surgery: A Single-Center Retrospective Study

Objective

To explore the related risk factors of postoperative delirium (POD) after hip or knee arthroplasty in elderly orthopedic patients and the predictive value of related risk factors. Material and Methods. In total, 309 patients (≥60 years) who received knee and hip arthroplasty between January 2017 and May 2020 were consecutively selected into the POD and nonpostoperative delirium (NPOD) groups. Group bias was eliminated through propensity score matching. Univariate and multivariable logistic analysis was used to determine the risk factors for POD. The nomogram was made by R.

Results

58 patients were included in each group after propensity score matching; multivariable analysis demonstrated that LDH (OR = 4.364, P = 0.017), CHE (OR = 4.640, P = 0.004), Cystatin C (OR = 5.283, P = 0.006), arrhythmia (OR = 5.253, P = 0.002), and operation duration (OR = 1.017, P = 0.050) were independent risk factors of POD. LDH, CHE, Cystatin C, and arrhythmia were used to construct a nomogram to predict the POD. The nomogram was well calibrated and had moderate discriminative ability (AUC = 0.821, 95% CI: 0.760~0.883). Decision curve analysis demonstrated that the nomogram was clinically useful.

Conclusions

Our study revealed that arrhythmia, operation duration, the increase of lactate dehydrogenase and Cystatin C, and the decrease of cholinesterase were reliable factors for predicting postoperative delirium after elderly hip and knee arthroplasty. Meanwhile, the nomogram we developed can assist the clinician to filtrate potential patients with postoperative delirium.

Delirium in neurosurgery: a systematic review and meta-analysis

Delirium is a frequent occurring complication in surgical patients. Nevertheless, a scientific work-up of the clinical relevance of delirium after intracranial surgery is lacking. We conducted a systematic review (CRD42020166656) to evaluate the current diagnostic work-up, incidence, risk factors and health outcomes of delirium in this population. Five databases (Embase, Medline, Web of Science, PsycINFO, Cochrane Central) were searched from inception through March 31st, 2021. Twenty-four studies (5589 patients) were included for qualitative analysis and twenty-one studies for quantitative analysis (5083 patients). Validated delirium screening tools were used in 70% of the studies, consisting of the Confusion Assessment Method (intensive care unit) (45%), Delirium Observation Screening Scale (5%), Intensive Care Delirium Screening Checklist (10%), Neelon and Champagne Confusion Scale (5%) and Nursing Delirium Screening Scale (5%). Incidence of post-operative delirium after intracranial surgery was 19%, ranging from 12 to 26% caused by variation in clinical features and delirium assessment methods. Meta-regression for age and gender did not show a correlation with delirium. We present an overview of risk factors and health outcomes associated with the onset of delirium. Our review highlights the need of future research on delirium in neurosurgery, which should focus on optimizing diagnosis and assessing prognostic significance and management.

Development of an early prediction model for postoperative delirium in neurosurgical patients admitted to the ICU after elective craniotomy (E-PREPOD-NS): A secondary analysis of a prospective cohort study

Postoperative delirium (POD) is a significant clinical problem in neurosurgical patients after intracranial surgery. Identification of high-risk patients may optimize perioperative management, but an adequate risk model for use at early phase after operation has not been developed. In the secondary analysis of a prospective cohort study, 800 adult patients admitted to the ICU after elective intracranial surgeries were included. The POD was diagnosed as Confusion Assessment Method for the ICU positive on postoperative day 1 to 3. Multivariate logistic regression analysis was used to develop early prediction model (E-PREPOD-NS) and the final model was validated with 200 bootstrap samples. The incidence of POD in this cohort was19.6%. We identified nine variables independently associated with POD in the final model: advanced age (OR 3.336, CI 1.765-6.305, 1 point), low education level (OR 2.528, 1.446-4.419, 1), smoking history (OR 2.582, 1.611-4.140, 1), diabetes (OR 2.541, 1.201-5.377, 1), supra-tentorial lesions (OR 3.424, 2.021-5.802, 1), anesthesia duration > 360 min (OR 1.686, 1.062-2.674, 0.5), GCS < 9 at ICU admission (OR 6.059, 3.789-9.690, 1.5), metabolic acidosis (OR 13.903, 6.248-30.938, 2.5), and neurosurgical drainage tube (OR 1.924, 1.132-3.269, 0.5). The area under the receiver operator curve (AUROC) of the risk score for prediction of POD was 0.865 (95% CI 0.835-0.895). The AUROC was 0.851 after internal validation (95% CI 0.791-0.912). The model showed good calibration. The E-PREPOD-NS model can predict POD in patients admitted to the ICU after elective intracranial surgery with good accuracy. External validation is needed in the future.

Factors Influencing the Physical Restraint of Patients in the Neurosurgical Intensive Care Unit

The purpose of this study was to investigate the current status of physical restraint of patients in the neurosurgical intensive care unit (NSICU) and analyze the factors influencing this measure using a cross-sectional study design. A total of 312 patients from four tertiary hospitals in NSICU were investigated in Beijing, China. The rate of physical restraint of patients in the NSICU was 42.9%. In 41.8% of cases, nurses performed physical restraint based on experience, and 45.5% of patients had physical restraint-related nursing records. Binary logistic regression analyses revealed that physical restraint was associated with delirium, mild-to-moderate disturbance of consciousness, history of extubation, surgery, and use of sedatives within 24 hour. Analysis of related factors can provide a reference for nurses and managers to improve physical restraint strategies.

Management of post-operative delirium following stereoelectroencephalography electrode placement for drug resistant epilepsy: Lessons learned from two case reports

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Post-operative delirium poses unique challenges in neurosurgical patients.

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Substance use is a modifiable risk factor for post-operative delirium after SEEG.

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SEEG patients have increased risk of harm when experiencing post-operative delirium.

Post-operative delirium (POD) represents a unique challenge in the care of any surgical patient but is especially challenging in neurosurgical inpatient management due to a host of potentially significant predisposing factors. Patients undergoing stereoencephalography (SEEG) for diagnosis of drug resistant epilepsy are at unique risk due to safety concerns, yet POD has been underdiscussed in this population. Patients should be counseled pre-operatively about their risk and subsequent steps be taken post-operatively. We present two cases of POD status-post SEEG and propose a mechanism by which future post-operative care be coordinated by the physician, patient, and patient’s family.