The detection of delirium in admitted oncology patients: a scoping review

Development of a Prediction Model for Delirium in Hospitalized Patients with Advanced Cancer

PURPOSE

Delirium is a common neurocognitive disorder in patients with advanced cancer and is associated with poor clinical outcomes. As a potentially reversible phenomenon, early recognition of delirium by identifying the risk factors demands attention. We aimed to develop a model to predict the occurrence of delirium in hospitalized patients with advanced cancer.

MATERIALS AND METHODS

This retrospective study included patients with advanced cancer admitted to the oncology ward of four tertiary cancer centers in Korea for supportive cares and excluded those discharged due to death. The primary endpoint was occurrence of delirium. Sociodemographic characteristics, clinical characteristics, laboratory findings, and concomitant medication were investigated for associating variables. The predictive model developed using multivariate logistic regression was internally validated by bootstrapping.

RESULTS

From January 2019 to December 2020, 2,152 patients were enrolled. The median age of patients was 64 years, and 58.4% were male. A total of 127 patients (5.9%) developed delirium during hospitalization. In multivariate logistic regression, age, body mass index, hearing impairment, previous delirium history, length of hospitalization, chemotherapy during hospitalization, blood urea nitrogen and calcium levels, and concomitant antidepressant use were significantly associated with the occurrence of delirium. The predictive model combining all four categorized variables showed the best performance among the developed models (area under the curve 0.831, sensitivity 80.3%, and specificity 72.0%). The calibration plot showed optimal agreement between predicted and actual probabilities through internal validation of the final model.

CONCLUSION

We proposed a successful predictive model for the risk of delirium in hospitalized patients with advanced cancer.

Postoperative delirium: A tragedy for elderly cancer patients

In this editorial, we comment on the article by Hu et al entitled "Predictive modeling for postoperative delirium in elderly patients with abdominal malignancies using synthetic minority oversampling technique". We wanted to draw attention to the general features of postoperative delirium (POD) as well as the areas where there are uncertainties and contradictions. POD can be defined as acute neurocognitive dysfunction that occurs in the first week after surgery. It is a severe postoperative complication, especially for elderly oncology patients. Although the underlying pathophysiological mechanism is not fully understood, various neuroinflammatory mechanisms and neurotransmitters are thought to be involved. Various assessment scales and diagnostic methods have been proposed for the early diagnosis of POD. As delirium is considered a preventable clinical entity in about half of the cases, various early prediction models developed with the support of machine learning have recently become a hot scientific topic. Unfortunately, a model with high sensitivity and specificity for the prediction of POD has not yet been reported. This situation reveals that all health personnel who provide health care services to elderly patients should approach patients with a high level of awareness in the perioperative period regarding POD.

Machine learning-based model to predict delirium in patients with advanced cancer treated with palliative care: a multicenter, patient-based registry cohort

This study aimed to present a new approach to predict to delirium admitted to the acute palliative care unit. To achieve this, this study employed machine learning model to predict delirium in patients in palliative care and identified the significant features that influenced the model. A multicenter, patient-based registry cohort study in South Korea between January 1, 2019, and December 31, 2020. Delirium was identified by reviewing the medical records based on the criteria of the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition. The study dataset included 165 patients with delirium among 2314 patients with advanced cancer admitted to the acute palliative care unit. Seven machine learning models, including extreme gradient boosting, adaptive boosting, gradient boosting, light gradient boosting, logistic regression, support vector machine, and random forest, were evaluated to predict delirium in patients with advanced cancer admitted to the acute palliative care unit. An ensemble approach was adopted to determine the optimal model. For k-fold cross-validation, the combination of extreme gradient boosting and random forest provided the best performance, achieving the following accuracy metrics: 68.83% sensitivity, 70.85% specificity, 69.84% balanced accuracy, and 74.55% area under the receiver operating characteristic curve. The performance of the isolated testing dataset was also validated, and the machine learning model was successfully deployed on a public website ( http://ai-wm.khu.ac.kr/Delirium/ ) to provide public access to delirium prediction results in patients with advanced cancer. Furthermore, using feature importance analysis, sex was determined to be the top contributor in predicting delirium, followed by a history of delirium, chemotherapy, smoking status, alcohol consumption, and living with family. Based on a large-scale, multicenter, patient-based registry cohort, a machine learning prediction model for delirium in patients with advanced cancer was developed in South Korea. We believe that this model will assist healthcare providers in treating patients with delirium and advanced cancer.

Delirium During Critical Illness and Subsequent Change of Treatment in Patients With Cancer: A Mediation Analysis

OBJECTIVES

To assess whether delirium during ICU stay is associated with subsequent change in treatment of cancer after discharge.

DESIGN

Retrospective cohort study.

SETTING

A 50-bed ICU in a dedicated cancer center.

PATIENTS

Patients greater than or equal to 18 years old with a previous proposal of cancer treatment (chemotherapy, target therapy, hormone therapy, immunotherapy, radiotherapy, oncologic surgery, and bone marrow transplantation).

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

We considered delirium present if Confusion Assessment Method for the ICU was positive. We assessed the association between delirium and modification of the treatment after discharge. We also performed a mediation analysis to assess both the direct and indirect (i.e., mediated by the development of functional dependence after discharge) of delirium on modification of cancer treatment and whether the modification of cancer treatment was associated with mortality at 1 year. We included 1,134 patients, of whom, 189 (16.7%) had delirium. Delirium was associated with the change in cancer treatment (adjusted odds ratio [OR], 3.80; 95% CI, 2.72-5.35). The association between delirium in ICU and change of treatment was both direct and mediated by the development of functional dependence after discharge. The proportion of the total effect of delirium on change of treatment mediated by the development of functional dependence after discharge was 33.0% (95% CI, 21.7-46.0%). Change in treatment was associated with increased mortality at 1 year (adjusted OR, 2.68; 95% CI, 2.01-3.60).

CONCLUSIONS

Patients who had delirium during ICU stay had a higher rate of modification of cancer treatment after discharge. The effect of delirium on change in cancer treatment was only partially mediated by the development of functional dependence after discharge. Change in cancer treatment was associated with increased 1-year mortality.

Incidence of delirium in older people with cancer: Systematic review and meta-analysis

PURPOSE

Delirium is a prevalent neuropsychiatric syndrome in older people with cancer. However, there are no meta-analyses assessing its incidence exclusively in this population. This study aims to assess the incidence proportion of delirium in older people with cancer in the hospital area.

METHODS

A systematic review and meta-analysis were carried out. MEDLINE, Scopus, and EBSCO were searched from inception to December 2021. PRISMA guidelines were followed. Inclusion criteria were original peer-reviewed studies with experimental (randomised controlled trials), observational, and cross-sectional designs assessing delirium older inpatients (≥65 years) with oncological diseases in medical and post-surgical hospital areas and using validated screening or diagnostic methods. A web-based system was used to manage the screening process. Study quality was assessed with Joanna Briggs Institute Critical Appraisal tools. The statistical analysis was performed in RevMan v5.4.0 (Cochrane Collaboration, Oxford, UK), using a random-effects model to calculate incidence and 95% confidence intervals (CIs).

RESULTS

Based on 37 included articles, the incidence proportion of delirium ranged from 3.8% to 61.4%, in a total of 11,847 older patients with cancer. Meta-analysis showed a pooled incidence of 22.6% (95% confidence interval 18.5%, 26.7%; I2 = 97%, p < 0.001). The main tools for detection were the Diagnostic Statistical Manual criteria and the Confusion Assessment Methods scale.

CONCLUSIONS

The incidence proportion of delirium in older inpatients with cancer is 22.6%. Incidence in the medical setting was higher than in the post-surgical areas. There is a need for high-quality studies examining delirium in older people with cancer.

Delirium in patients with musculoskeletal tumours: incidence and risk factors - single-centre prospective study

OBJECTIVES

Delirium, a neurocognitive disorder, typically occurs in older patients and those with advanced cancer. Although there have been numerous reports on delirium in patients with cancer in various conditions, there are no reports that specifically focus on patients with musculoskeletal tumours. This prospective study aimed to investigate the incidence, risk factors and prognostic implications of delirium in patients with musculoskeletal tumours.

METHODS

In this single institutional study, 148 patients with musculoskeletal oncology were enrolled. The estimated risk factors included age, sex, alcohol abuse, performance status (PS), dietary status, admission route, tumour malignancy, oncological stage and blood test results. The significance of delirium in survival was also examined.

RESULTS

Only 18 patients with malignant tumours had delirium (12.2%). Based on univariate analysis, older age, poor PS, dietary status, admission from another hospital, malignant tumour, carcinoma rather than sarcoma, anaemia and some laboratory abnormalities were found to be significant risk factors for delirium. Multivariate analysis showed that poor PS was significantly correlated with delirium. Additionally, delirium was significantly correlated with poor survival.

CONCLUSIONS

The incidence of delirium among patients with musculoskeletal tumours was 12.2% and was observed only in patients with malignant tumours. PS is a significant risk factor for delirium. Delirium is correlated with poor prognosis.

Preventing and treating delirium in clinical settings for older adults

Delirium is a serious consequence of many acute or worsening chronic medical conditions, a side effect of medications, and a precipitant of worsening functional and cognitive status in older adults. It is a syndrome characterized by fluctuations in cognition and impaired attention that develops over a short period of time in response to an underlying medical condition, a substance (prescribed, over the counter, or recreational), or substance withdrawal and can be multi-factorial. We present a narrative review of the literature on nonpharmacologic and pharmacologic approaches to prevention and treatment of delirium with a focus on older adults as a vulnerable population. Older adult patients are most at risk due to decreasing physiologic reserves, with delirium rates of up to 80% in critical care settings. Presentation of delirium can be hyperactive, hypoactive, or mixed, making identification and study challenging as patients with hypoactive delirium are less likely to come to attention in an inpatient or long-term care setting. Studies of delirium focus on prevention and treatment with nonpharmacological or medication interventions, with the preponderance of evidence favoring multi-component nonpharmacological approaches to prevention as the most effective. Though use of antipsychotic medication in delirium is common, existing evidence does not support routine use, showing no clear benefit in clinically significant outcome measures and with evidence of harm in some studies. We therefore suggest that antipsychotics be used to treat agitation, psychosis, and distress associated with delirium at the lowest effective doses and shortest possible duration and not be considered a treatment of delirium itself. Future studies may clarify the use of other agents, such as melatonin and melatonin receptor agonists, alpha-2 receptor agonists, and anti-epileptics.

The Confusion Assessment Method Could Be More Accurate than the Memorial Delirium Assessment Scale for Diagnosing Delirium in Older Cancer Patients: An Exploratory Study

BACKGROUND

Older people with cancer carry a high risk of delirium, an underdiagnosed syndrome due to its diagnostic complexity and often subtle presentation. Tools based on the Diagnostic and Statistical Manual of Mental Disorders (DSM) are available to different health professionals. Our aim is to assess the prevalence of delirium in older people with cancer in an inpatient unit and the accuracy of the Confusion Assessment Method (CAM) and Memorial Delirium Assessment Scale (MDAS).

METHODS

This exploratory, cross-sectional study included people aged 65 years or older with a diagnosis of cancer and admitted to the medical oncology unit from June 2021 to December 2022. The diagnostic accuracy of CAM and MDAS was analyzed against the gold standard medical diagnosis based on DSM-5 criteria by two medical oncologists. The cutoff point for the MDAS was determined using a receiver-operating characteristics (ROC) curve.

RESULTS

Among the 75 included patients (mean age 71.6 years, standard deviation 4.1; 52% males), the prevalence of delirium was 62.7%. The most prevalent types of cancer in patients with delirium were hematological and lung cancer. The scale with the highest diagnostic accuracy was the CAM, with a sensitivity of 100% and specificity of 86%, followed by the MDAS, with a sensitivity of 88% and specificity of 30%. The presence of cognitive impairment hindered the detection of delirium.

CONCLUSIONS

The CAM scale was more accurate than the MDAS pre-existing cognitive impairment in our sample. Further studies are needed to analyze the diagnostic accuracy of delirium tools in older populations with cancer and in the presence of cognitive impairment.

Delirium as a Risk Factor for Mortality in Critically Ill Patients With Cancer

PURPOSE

Although delirium is known to negatively affect critically ill patients, little data exist on delirium in critically ill patients with cancer.

METHODS

We analyzed 915 critically ill patients with cancer between January and December 2018. Delirium screening was performed using the Confusion Assessment Method for the intensive care unit (ICU), performed twice daily. Confusion Assessment Method-ICU incorporates four features of delirium: acute fluctuations in mental status, inattention, disorganized thinking, and altered levels of consciousness. Multivariable analysis controlling for admitting service, pre-ICU hospital length of stay (LOS), metastatic disease, CNS involvement, Mortality Probability Model II score on ICU admission, mechanical ventilation, and others was performed to determine precipitating factors for delirium, ICU, and hospital mortality and LOS.

RESULTS

Delirium occurred in 40.5% (n = 317) of patients; 43.8% (n = 401) were female; the median age was 64.9 (interquartile range, 54.6-73.2) years; 70.8% (n = 647) were White, 9.3% (n = 85) were Black, and 8.9% (n = 81) were Asian. The most common cancer types were hematologic (25.7%, n = 244) and gastrointestinal (20.9%, n = 191). Delirium was independently associated with age (OR, 1.01; 95% CI, 1.00 to 1.02; P = .038), longer pre-ICU hospital LOS (OR, 1.04; 95% CI, 1.02 to 1.06; P < .001), not resuscitating on admission (OR, 2.18; 95% CI, 1.07 to 4.44; P = .032), CNS involvement (OR, 2.25; 95% CI, 1.20 to 4.20; P = .011), higher Mortality Probability Model II score (OR, 1.02; 95% CI, 1.01 to 1.02; P < .001), mechanical ventilation (OR, 2.67; 95% CI, 1.84 to 3.87; P < .001), and sepsis diagnosis (OR, 0.65; 95% CI, 0.43 to 0.99; P = .046). Delirium was also independently associated with higher ICU mortality (OR, 10.75; 95% CI, 5.91 to 19.55; P < .001), hospital mortality (OR, 5.84; 95% CI, 4.03 to 8.46; P < .001), and ICU LOS (estimate, 1.67; 95% CI, 1.54 to 1.81; P < .001).

CONCLUSION

Delirium significantly worsens outcome in critically ill patients with cancer. Delirium screening and management should be integrated into the care of this patient subgroup.

Accuracy of Delirium Screening Tools in Older People with Cancer-A Systematic Review

BACKGROUND

The increase in life expectancy worldwide has led to a larger population of older people, which in turn entails a rising prevalence of cancer. One of the main complications of cancer is delirium, especially in advanced stages.

OBJECTIVE

To determine which delirium screening instrument is the most accurate in older people with cancer.

METHODS

A systematic review was designed. A literature search was performed in MEDLINE, EBSCO and SCOPUS; additional records were identified by handsearching. Selection criteria were studies involving people with cancer and a mean sample age of 60 years or older, assessing delirium, and reporting the metric properties of the assessment instrument. Studies with post-surgical patients and substance abuse delirium were excluded.

RESULTS

From 2001 to 2021, 14 eligible studies evaluated 13 different assessment tools, reporting an incidence of delirium ranging from 14.3% to 68.3%. The Delirium Observation Screening Scale (DOSS) showed the best metric properties, followed by the Nursing Delirium Screening Scale (NuDESC), Confusion Assessment Method (CAM) and Memorial Delirium Assessment Scale (MDAS). Only two studies were considered to be at low risk of bias using the QUADAS-2 Tool. No study exclusively examined this population group.

CONCLUSIONS

Screening tools for delirium are heterogeneous for older people with cancer, and there is a need to analyze metric properties exclusively in the older population. Registered on PROSPERO ID: CRD42022303530.

An association between cancer type and delirium incidence in Japanese elderly patients: A retrospective longitudinal study

OBJECTIVE

There is not a known elevated prevalence of delirium in older adult cancer patients. However, it is unknown if the incidence of delirium varies by cancer type among older adult patients. Therefore, this study aimed to examine the association between the incidence of delirium and cancer type among older adult patients using a Japanese hospital-based administrative claims database.

METHODS

A total of 76,868 patients over 65 years of age or older, first diagnosed with cancer on an initial date of hospitalization between April 2008 and December 2019, were included in this retrospective longitudinal study. Delirium was defined by the World Health Organization's International Statistical Classification of Diseases and Related Health Problems (ICD-10) codes or antipsychotic medication use. Cox proportional hazard models were performed to estimate the risk of delirium incidence according to 22 cancer types during the one-year hospitalization period.

RESULTS

The incidence rates of delirium were 17.1% for men and 15.3% for women. Compared to gastric cancer, the risk of delirium was significantly higher for pancreatic cancer (HR: 1.26, 95% CI: 1.11-1.42 for men; HR: 1.27, 95% CI: 1.11-1.45 for women), leukemia (HR: 1.24, 95% CI: 1.09-1.41 for men; HR: 1.20, 95% CI: 1.03-1.41 for women), and oropharyngeal cancer (HR: 1.30, 95% CI: 1.10-1.54 for men; HR: 1.32; 95% CI: 1.02-1.72 for women) after adjusting for age, initial hospitalization year, antipsychotic medications, and surgery.

CONCLUSIONS

As compared to gastric cancer, patients with pancreatic cancer, leukemia, oropharyngeal cancer were found to have a higher risk of developing delirium. Our study findings suggested that the risk of delirium incidence may vary by cancer type.

Psychological Aspects of Care in Cancer Patients in the Last Weeks/Days of Life

Palliative care is comprised of an interdisciplinary team (IDT) approach with members from different disciplines who collaboratively work together to reduce multidimensional components of pain and suffering and improve quality of life for patients coping with a terminal illness. Psychosocial team members are integral to the palliative care IDT and provide expertise in assessment and empirically validated interventions to address psychological distress. The following paper will provide a review of different facets of psychological distress experienced by advanced cancer patients such as psychological disorders, existential distress, spiritual distress, caregiver distress, parental distress, and grief. Finally, an overview of commonly used screening and assessment tools as well as psychological interventions relevant for the palliative care population is presented.

The Dilemma of Treating Delirium: the Conundrum of Drug Management

OPINION STATEMENT

Delirium is a common medical complication in people living with cancer, particularly with more advanced disease. Delirium is associated with significant symptom burden which causes distress and impacts quality of life. As recommended by international guidelines, a high degree of suspicion is needed to ensure delirium is detected early. Attention to collateral history can provide clues to changes in cognition and attention. Non-pharmacological approaches that can be considered essential elements of care are effective in reducing the risk of delirium. Delirium screening using a validated measure is recommended as even expert clinicians can underdiagnose or miss delirium. The diagnostic assessment requires consideration of the cancer diagnosis and comorbidities, in the context of potential reversibility, goals of care, and patient preferences. The gold standard approach based on expert consensus is to institute management for delirium precipitants supported by non-pharmacological essential care, with the support of an interdisciplinary team. Medication management should be used sparingly and for a limited period of time wherever possible for severe perceptual disturbance or agitation which has not improved with non-pharmacological approaches. Clinicians should be familiar with the registered indication for medications and seek informed consent for off-label use. All interventions put in place to manage delirium need to consider net clinical benefit, including harms such as sedation and loss of capacity for meaningful interaction. Clear communication and explanation are needed regularly, with the person with delirium as far as possible and with surrogate decision makers. Delirium can herald a poor prognosis and this needs to be considered and be discussed as appropriate in shared decision-making. Recall after delirium has resolved is common, and opportunity to talk about this experience and the related distress should be offered during the period after recovery.