Delirium Screening in Cardiac Surgery (DESCARD): A Useful Tool for Nonpsychiatrists

Intra- and early postoperative predictors of delirium risk in cardiac surgery: results from the prospective observational FINDERI study

BACKGROUND

Postoperative delirium (POD) is a severe complication following cardiac surgery and is associated with increased morbidity and mortality. The impact of intra- and early postoperative factors on the occurrence of POD following cardiac surgery remains controversial. To close this gap, we investigated intra- and early postoperative factors and their predictive values for POD.

METHODS

We performed a prospective observational study that aimed to FIND DElirium RIsk factors (FINDERI) for patients undergoing elective cardiac surgery. POD was assessed using the Confusion Assessment Method algorithm. Intra- and early postoperative factors were extracted from electronic medical records and reviewed by cardiac surgeons. To identify potential predictors of POD, we used univariate and multivariate logistic regression along with machine learning (ML) with ten-fold cross-validation.

RESULTS

In our study cohort of 490 patients, 106 screened positive for POD (21.6%). In the multivariate analysis, we found a positive association between POD occurrence and age ( P < 0.001), duration of surgery ( P = 0.027), combined (versus isolated) surgical procedures ( P = 0.024), opening of the cardiac chambers ( P = 0.046), and ventilation time ( P < 0.001). The ML-based decision tree identified a two level-algorithm including ventilation time and aortic cross-clamping time, with an AUC of 0.7116 ( P = 0.0002) in the validation set. In the ML-based LASSO regression analysis, we identified ventilation time, administration of erythrocyte concentrates (EC), and usage of cardiopulmonary bypass (CPB) as predictors of POD, with an AUC of 0.7407 ( P < 0.0001) in the validation set.

CONCLUSION

The results of this analysis highlight the associations between ventilation time, aortic cross-clamping time, administration of EC, and usage of CPB and POD. Additionally, they suggest that the optimization of surgical protocols has the potential to reduce POD risk in individuals undergoing cardiac surgery.

Preoperative prediction models for postoperative delirium in cardiac surgery patients - a scoping review

BACKGROUND

Postoperative delirium is believed to be preventable in up to 40% of all cases. Researchers have proposed various preoperative risk prediction models for postoperative delirium in patients undergoing cardiac surgery, however, no consensus exists on which model is the most suitable.

AIM

To identify and map existing preoperative risk prediction models, detecting cardiac surgery patients at elevated risk of developing postoperative delirium.

DESIGN

This scoping review considered cohort and case-control studies eligible if they developed or validated preoperative prediction models for postoperative delirium, in adult patients admitted for cardiac surgery via sternotomy.

DATA SOURCES

The primary search was conducted on May 6th, 2022, and a secondary search was conducted on September 18th, 2024. We searched MEDLINE, CINAHL, Embase, and PsycINFO where 2126 references were identified and 15 were included for full-text analysis.

METHOD

This scoping review was conducted in line with the Systematic Reviews and Meta-Analyses extension for Scoping Reviews (the PRISMA-ScR) guideline.

RESULTS

Twelve unique risk prediction models and three validation studies were included in this review, comprising between 77 and 45,744 participants. In total, 157 candidate prognostic variables were investigated of which 40 had a predictive value and thus, were included in the prediction models. The included models revealed an AUC from 0.68-0.93 in the derivation cohorts and 0.61-0.89 in the validation cohorts.

CONCLUSIONS

Twelve unique prediction models and 3 validation studies were identified and mapped. Collectively, the models demonstrated an AUC ranging from 0.61-0.93, indicating a fair to good discrimination performance.

PROTOCOL REGISTRATION

A protocol is registered at Open Science Framework (OSF) https://osf.io/wr93y/?view_only=d129c3bb6be04357bac35c2c41ba2a40.

The Role of Stress Hyperglycemia on Delirium Onset

Delirium is an acute neuropsychiatric syndrome that recognizes one or more underlying causal medical conditions. Stress hyperglycemia usually refers to transient hyperglycemia associated with stress conditions such as stroke, myocardial infarction, and major surgery. Both delirium and stress hyperglycemia share common pathways, such as activation of inflammation. Stress hyperglycemia has been associated with negative outcomes, and recent studies suggested that there is an increased risk of delirium onset in patients with stress hyperglycemia. The purpose of this review is to illustrate the relationship between stress hyperglycemia and delirium. Initially, we illustrate the role of diabetes on delirium onset, summarize the criteria used for the diagnosis of stress hyperglycemia, discuss the impact of stress hyperglycemia on outcome, and focus on the evidence about the relationship between stress hyperglycemia and delirium.

Preoperative Delirium Risk Screening in Patients Undergoing a Cardiac Surgery: Results from the Prospective Observational FINDERI Study

OBJECTIVE

Postoperative delirium (POD) is a common complication of cardiac surgery that is associated with higher morbidity, longer hospital stay, cognitive decline, and mortality. Preoperative assessments may help to identify patients´ POD risk. However, a standardized screening assessment for POD risk has not been established.

DESIGN

Prospective observational FINd DElirium RIsk factors (FINDERI) study.

PARTICIPANTS

Patients aged ≥50 years undergoing cardiac surgery.

MEASUREMENTS

The primary aim was to analyze the predictive value of the Delirium Risk Screening Questionnaire (DRSQ) prior to cardiac surgery. Secondary aims are to investigate cognitive, frailty, and geriatric assessments, and to use data-driven machine learning (ML) in predicting POD. Predictive properties were assessed using receiver operating characteristics analysis and multivariate approaches (regularized LASSO regression and decision trees).

RESULTS

We analyzed a data set of 504 patients (68.3 ± 8.2 years, 21.4% women) who underwent cardiac surgery. The incidence of POD was 21%. The preoperatively administered DRSQ showed an area under the curve (AUC) of 0.68 (95% CI 0.62, 0.73), and the predictive OR was 1.25 (95% CI 1.15, 1.35, p <0.001). Using a ML approach, a three-rule decision tree prediction model including DRSQ (score>7), Trail Making Test B (time>118), and Montreal Cognitive Assessment (score ≤ 22) was identified. The AUC of the three-rule decision tree on the training set was 0.69 (95% CI 0.63, 0.75) and 0.62 (95% CI 0.51, 0.73) on the validation set.

CONCLUSION

Both the DRSQ and the three-rule decision tree might be helpful in predicting POD risk before cardiac surgery.

Association between Preoperative Glucose Dysregulation and Delirium after Non-Cardiac Surgery

This study aimed to investigate the association between glucose dysregulation and delirium after non-cardiac surgery. Among a total of 203,787 patients who underwent non-cardiac surgery between January 2011 and June 2019 at our institution, we selected 61,805 with available preoperative blood glucose levels within 24 h before surgery. Patients experiencing glucose dysregulation were divided into three groups: hyperglycemia, hypoglycemia, and both. We compared the incidence of postoperative delirium within 30 days after surgery between exposed and unexposed patients according to the type of glucose dysregulation. The overall incidence of hyperglycemia, hypoglycemia, and both was 5851 (9.5%), 1452 (2.3%), and 145 (0.2%), respectively. The rate of delirium per 100 person-months of the exposed group was higher than that of the unexposed group in all types of glucose dysregulation. After adjustment, the hazard ratios of glucose dysregulation in the development of delirium were 1.35 (95% CI, 1.18-1.56) in hyperglycemia, 1.36 (95% CI, 1.06-1.75) in hypoglycemia, and 3.14 (95% CI, 1.27-7.77) in both. The subgroup analysis showed that exposure to hypoglycemia or both to hypo- and hyperglycemia was not associated with delirium in diabetic patients, but hyperglycemia was consistently associated with postoperative delirium regardless of the presence of diabetes. Preoperative glucose dysregulation was associated with increased risk of delirium after non-cardiac surgery. Our findings may be helpful for preventing postoperative delirium, and further investigations are required to verify the association and mechanisms for the effect we observed.

Dynamic predictive scores for cardiac surgery-associated agitated delirium: a single-center retrospective observational study

BACKGROUND

Prevention, screening, and early treatment are the aims of postoperative delirium management. The scoring system is an objective and effective tool to stratify potential delirium risk for patients undergoing cardiac surgery.

METHODS

Patients who underwent cardiac surgery between January 1, 2012, and January 1, 2019, were enrolled in our retrospective study. The patients were divided into a derivation cohort (n = 45,744) and a validation cohort (n = 11,436). The AD predictive systems were formulated using multivariate logistic regression analysis at three time points: preoperation, ICU admittance, and 24 h after ICU admittance.

RESULTS

The prevalence of AD after cardiac surgery in the whole cohort was 3.6% (2,085/57,180). The dynamic scoring system included preoperative LVEF ≤ 45%, serum creatinine > 100 µmol/L, emergency surgery, coronary artery disease, hemorrhage volume > 600 mL, intraoperative platelet or plasma use, and postoperative LVEF ≤ 45%. The area under the receiver operating characteristic curve (AUC) values for AD prediction were 0.68 (preoperative), 0.74 (on the day of ICU admission), and 0.75 (postoperative). The Hosmer‒Lemeshow test indicated that the calibration of the preoperative prediction model was poor (P = 0.01), whereas that of the pre- and intraoperative prediction model (P = 0.49) and the pre, intra- and postoperative prediction model (P = 0.35) was good.

CONCLUSIONS

Using perioperative data, we developed a dynamic scoring system for predicting the risk of AD following cardiac surgery. The dynamic scoring system may improve the early recognition of and the interventions for AD.

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.

The effect of foot reflexology massage on delirium and sleep quality following cardiac surgery: A randomized clinical trial

BACKGROUND

Delirium is the most common neurologic disorder after cardiac surgery and affects both short and long-term outcomes. This study was conducted to evaluate the effect of foot reflexology massage on the incidence of delirium and sleep quality in patients undergoing cardiac surgery.

METHODS

In this randomized clinical trial, 60 patients who were candidates for CABG surgery were randomly assigned into two equal groups (n = 30); intervention and control groups. In the intervention group, foot reflexology massage was done on each foot for 15 min, for two consecutive days. Delirium observation screening scale, the Richard Campbell sleep questionnaire (RSCQ), and pain intensity using VAS were compared.

RESULTS

in the second postoperative day, delirium was observed in 8 (26.7 %) and 7 (23.3 %) of patients in the intervention and control groups, respectively (p > 0.05). The measured odds ratio for the effect of massage on delirium is 0.83 (95 %CI 0.71-2.69, p = 0.76). The difference in RSCQ scores was not significant between groups of intervention and control (68.32 ± 10.41 VS. 62.80 ± 11.86, P = 0.06). The pain intensity was lower in the intervention group (P < 0.001).

CONCLUSION

Foot reflexology was not effective in reducing delirium and improving the sleep quality, but the pain intensity was decreased. It seems that the precise pathology and predicting model of delirium should be identified, and appropriate interventions should be planned accordingly.

Emergence Delirium in Elderly Patients as a Potential Predictor of Subsequent Postoperative Delirium: A Descriptive Correlational Study

PURPOSE

This study aimed to investigate the incidence of emergence delirium (ED) in elderly patients under general anesthesia and to determine the correlation between ED and delirium at five subsequent postoperative days.

DESIGN

This research is a descriptive correlational study.

METHODS

A total of 168 aged patients undergoing elective general anesthesia were recruited from a comprehensive tertiary teaching hospital with 2,400 beds in Southern China from April 2018 to September 2018. The Nursing Delirium Screening Scale was used to assess delirium at 30 and 60 minutes after extubation or on discharge from the postanesthesia care unit. Patients were assessed for delirium at postoperative days one through five using the same method. Patients' demographic information, including cognitive function, were collected.

FINDINGS

Among the 168 aged patients, 58 suffered from ED (34.5%), including the 79.3% for the 46 patients who experienced postoperative delirium (POD). A positive correlation existed between ED and POD (χ² = 111.744; P < .01). Logistic regression analysis included seven variables: age, preoperative Mini-Mental State Examination score, underlying diseases, American Society of Anesthesiologists grade, surgery duration, postoperative complications, and the presence of ED. Age and ED were concluded to be independent predictive factors of POD.

CONCLUSIONS

ED in the first hour after tracheal tube removal is a predictor of delirium at five subsequent postoperative days. Accurate and timely assessment of recovery period can effectively guide the treatment and rehabilitation of POD and maximize prevention of adverse consequences.

Efficacy of Intervention for Prevention of Postoperative Delirium after Spine Surgery

Introduction

Delirium after spine surgery is an important complication; identification of risk factors associated with postoperative delirium (PD) is essential for reducing its incidence. Prophylactic intervention for PD has been reported to be effective. This study aimed to identify risk factors for PD and determine the efficacy of a prevention program using a delirium risk scoring system for PD after spine surgery.

Methods

This study was conducted in two stages. First, 294 patients (167 males, 127 females) who underwent spine surgery from 2013 to 2014 were assessed to examine the incidence and risk factors of PD and to establish a novel PD screening tool (Group A). Second, preoperative intervention was performed on 265 patients who underwent surgery from 2016 to 2017 (Group B) for the purpose of preventing PD using a delirium risk scoring system. Outcomes, including PD incidence and rates of adverse events, were compared between Group A and Group B.

Results

A logistic regression analysis revealed that psychiatric disorders (odds ratio [OR] = 10.3, P < 0.001), benzodiazepine use (OR = 4.9, P < 0.001), age > 70 years (OR = 4.2, P < 0.001), hearing loss (OR = 3.7, P = 0.001), and admission to intensive care unit (ICU) (OR = 3.7, P = 0.006) were independent risk factors associated with PD. Based on these results, we established a novel delirium screening tool after spine surgery. PD incidence was significantly higher in Group A than in Group B (22% vs. 13%, P = 0.0008). The occurrence of dangerous behavioral symptoms was significantly higher in Group A than in Group B (66% vs. 40%, P = 0.02). The catheter problem tended to be higher in Group A than in Group B (19% vs. 9%, P = 0.245).

Conclusions

In this study, psychiatric disorders, benzodiazepine use, age > 70 years, hearing loss, and admission to ICU were independent risk factors associated with PD. With the introduction of the delirium risk score, the onset of delirium was delayed, and adverse outcomes of delirium were reduced.

The relationship of delirium and risk factors for cardiology intensive care unit patients with the nursing workload

AIMS AND OBJECTIVES

To evaluate the relationship of delirium and risk factors for cardiology intensive care unit (ICU) patients with the nursing workload.

BACKGROUND

Delirium is a common syndrome in patients with cardiac problems. The risk factors causing delirium and the presence and type of delirium affect the nurse workload and patient care quality adversely.

DESIGN

This cross-sectional study was conducted with 133 patients staying at the cardiology ICU of a university hospital between 5 January-31 March 2017.

METHOD

The study data were collected using the Patient Information Form, Delirium Risk Factors' Form and Therapeutic Intervention Scoring System-28 (TISS-28) scale to identify the nurse workload. The statistical analysis of the data was performed using frequency, chi-square, Mann-Whitney U, correlation and regression analyses.

RESULTS

It was found that patients who developed delirium were 65 years or older, they had more nasogastric/total parenteral nutrition (NG/TPN), benzodiazepine and physical restraints in comparison with those with no delirium development, and that the prevalence of hypoxia and hypoalbuminemia were higher in these patients. The mean TISS-28 score was higher in patients with delirium, compared with those without delirium. There was a positive correlation between the mean Acute Physiology and Chronic Health Evaluation II (APACHE II) scores and the mean TISS-28 score of the patients. The mean TISS-28 score was found to significantly increase with being at the age of 65 and above and the administration of mechanical ventilation. The patients with delirium required a mean of 60-min additional care.

CONCLUSIONS

Our study results suggest that the presence of delirium and the delirium risk factors, irrespective of delirium, increase the nurse workload.

RELEVANCE TO CLINICAL PRACTICE

An effective management of delirium risk factors can improve the patient care quality by reducing delirium occurrence and nurse workload.

Neurocognitive Function after Cardiac Surgery: From Phenotypes to Mechanisms

For half a century, it has been known that some patients experience neurocognitive dysfunction after cardiac surgery; however, defining its incidence, course, and causes remains challenging and controversial. Various terms have been used to describe neurocognitive dysfunction at different times after cardiac surgery, ranging from "postoperative delirium" to "postoperative cognitive dysfunction or decline." Delirium is a clinical diagnosis included in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5). Postoperative cognitive dysfunction is not included in the DSM-5 and has been heterogeneously defined, though a recent international nomenclature effort has proposed standardized definitions for it. Here, the authors discuss pathophysiologic mechanisms that may underlie these complications, review the literature on methods to prevent them, and discuss novel approaches to understand their etiology that may lead to novel treatment strategies. Future studies should measure both delirium and postoperative cognitive dysfunction to help clarify the relationship between these important postoperative complications.

Postoperative delirium

Delirium can be defined as an ‘acute brain dysfunction.’ Compared to dementia, which is a disease that deteriorates the brain function chronically, delirium shows very similar symptoms but is mostly ameliorated when the causative factors are normalized. Due to the heterogeneity in etiologies and symptoms, people including health care workers often mistake delirium for dementia or other psychiatric disorders. Delirium has attracted global interest increasingly and a vast amount of research on its management has been conducted. Experts in the field have constantly suggested that systematic intervention should be implemented through a team-based multicomponent approach aimed to reduce the incidence and duration of delirium. Surgery involves many health care workers with different expertise who are not familiar with delirium. For a team-based approach on the management of delirium, it is vital that all medical personnel concerned have a common understanding of delirium and keep in constant communication. Postoperative delirium is a common complication and exerts an enormous burden on patients, their families, hospitals, and public resources. To alleviate this burden, this article aimed to review general features and the latest evidence-based knowledge of delirium with a focus on postoperative delirium.

Do Risk Prediction Models for Postoperative Delirium Consider Patients' Preoperative Medication Use?

BACKGROUND

Medicines are potentially modifiable risk factors for postoperative delirium. However, the extent to which preoperative medicines are included in risk prediction models (RPMs) is unknown.

OBJECTIVE

This systematic review aimed to assess the extent of inclusion of preoperative medications in RPMs for postoperative delirium.

METHODS

Articles were systematically searched from MEDLINE, EMBASE and CINAHL using Medical Subject Headings (MeSH) where possible and keywords for postoperative delirium and prediction model. Studies published until May 2017 with a primary outcome of postoperative delirium that developed an RPM containing preoperative patient information were considered. Where a study had two cohorts, a derivation and a validation cohort, findings from the derivation cohort were extracted and reported.

RESULTS

Eighteen prospective and one retrospective cohort studies were included for review. Of the 19 studies, only nine considered preoperative medication data, with medications appearing as predictor variables in five models. There was wide variability in the factors included in the final models, with the most frequent predictors being age and cognitive impairment, appearing in 13 (68%) and 11 (58%) RPMs, respectively.

CONCLUSION

While medications are commonly cited risk factors for delirium, they are not adequately considered when developing RPMs. Future studies aiming to develop an RPM for postoperative delirium should include preoperative medication data as a potential predictor variable because of the modifiable nature of medication use and its impact on other factors commonly in models, such as cognition.

Perioperative hyperglycemia and neurocognitive outcome after surgery: a systematic review

INTRODUCTION

Preliminary evidence suggest a possible relationship between perioperative hyperglycemia, postoperative delirium (POD) or cognitive dysfunction (POCD). We aim to present the available clinical evidence related to chronic (i.e. diabetes mellitus) or acute perioperative hyperglycemia as risk factors for POD/POCD.

EVIDENCE ACQUISITION

A literature search of EMBASE (via Ovid, 1974-present) online medical database and MEDLINE (via PubMed or Ovid, 1946-present) was performed. All types of clinical studies including randomized controlled trials, prospective, as well as retrospective cohort studies were screened. Clinical studies that reported original information on the relationship between diabetes mellitus (DM) and/or acute perioperative abnormal glucose levels and POD or POCD were selected. Reviews and editorials (i.e. articles not presenting original preclinical or clinical research) were excluded and case-reports were not considered for analysis.

EVIDENCE SYNTHESIS

Our search resulted in 2356 papers for screening, from which we selected 29 studies that met our inclusion criteria. DM was investigated in 24 observational papers, acute perioperative hyperglycemia in six observational studies and two randomized controlled trials examined the effect of perioperative glucose lowering on POD/POCD. Diabetes was associated with POD or POCD in 18/24 observational studies and 6/6 of the included observational studies found that perioperative hyperglycemia was associated with POD/POCD, independent of diabetes. The two randomized controlled trials had a different trial design and reported conflicting results.

CONCLUSIONS

According to the available evidence, DM and acute perioperative hyperglycemia may be associated with an increased risk for POD/POCD. These conclusions are based mostly on observational studies and deserve more and dedicated research. This systematic review may direct the design of future studies.

The Polish language version of the Confusion Assessment Method - a questionnaire for the screening of consciousness disorders

Confusion on a somatic basis is a dangerous problem mainly related with aging of the population. Data says that consciousness disorders concern 10-15% of patients in general wards, and up to 50% of patients admitted to geriatric wards. The persistence of the symptoms of confusion results in increase of agitation, disorganization, fear, which increases the risk of self-injuries of patients, it causes the need for parenteral feeding and hydratation, as well as maintaining water balance, and also disturbs cooperation, worsening the course and prognosis of the primary disease. It is believed that consciousness disorders are one of the most difficult diagnostic problems and the most difficult therapy problem among psychotic disorders. So far in Poland there have been no screening evaluation tools to assess the occurrence of confusion on the somatic basis. The purpose of this paper is to introduce the Polish translation of the widely used scale to assess consciousness disorders, intended also for middle personnel of health care - Confusion Assessment Method (CAM). Numerous studies over 16 years established the position of CAM as an exceptionally effective standardized diagnostic test, specifying the sensitivity of 94-100%, specificity from 90-95%, positive predictive value of 91-94%, negative predictive value of 90-100%. The questionnaire and instructions of its interpretation have been translated by doctors with active help from the original creators of CAM. Further studies are required in order to validate and determine the effectiveness of the newly formed diagnostic tool.