Risk Factors for Delirium in the Palliative Care Population: A Systematic Review and Meta-Analysis

Application of machine learning for delirium prediction and analysis of associated factors in hospitalized COVID-19 patients: A comparative study using the Korean Multidisciplinary cohort for delirium prevention (KoMCoDe)

BACKGROUND

The incidence of delirium in hospitalized coronavirus disease 2019 (COVID-19) patients is linked to adverse health outcomes. Predicting the occurrence and risk factors of delirium is key to preventing its sudden onset.

AIMS

To explore the factors associated with delirium in hospitalized COVID-19 patients and to compare the performance of various machine learning (ML) techniques for future use in predicting delirium.

METHODS

We analyzed a dataset of 1,031 cases from two healthcare centers, which included 178 variables such as demographics, clinical data, and medication information. The ML techniques used in this study were extreme gradient boosting (XGB), light gradient boosting machine (LGBM), logistic regression (LR), random forest (RF), and support vector machine (SVM).

RESULTS

The RF model emerged as the most effective for predicting delirium, achieving an area under the curve (AUC) of 0.923. It showed a sensitivity of 0.639, accuracy of 0.900, specificity of 0.934, positive predictive value (PPV) of 0.561, negative predictive value (NPV) of 0.952, and an F1 score of 0.597. The RF model identified key variables related to delirium, including medication type (antipsychotic, sedative, opioid), duration of hospital stay, remdesivir usage, and patient age. The reliability of the model was affirmed through calibration plots and Brier score evaluations.

CONCLUSIONS

This research developed and validated an RF-based ML model for predicting delirium in hospitalized COVID-19 patients. The model demonstrates superior accuracy and reliability compared to other ML methods and would possibly serve as a valuable tool for managing and anticipating delirium in COVID-19 patients, with the potential to enhance patient outcomes.

Prediction model for delirium in advanced cancer patients receiving palliative care: development and validation

BACKGROUND

Delirium is a common and distressing mental disorder in palliative care. To date, no delirium prediction model is available for thepalliative care population. The research aimed to develop and validate a nomogram model for predicting the occurrence of delirium in advanced cancer patients admitted to palliative care units.

METHODS

This was a prospective, multicenter, observational study. Logistic regression was used to identify the independent risk factors for incident delirium among advanced cancer patients in palliative care units. Advanced cancer patients admitted to palliative care units between February 2021 and January 2023 were recruited from four hospitals in Chengdu, Sichuan Province, China. Model performance was evaluated via the area under the receiver operating characteristic curve, calibration plots and decision curve analysis.

RESULTS

There were 592 advanced cancer patients receiving palliative care in the development cohort, 196 in the temporal validation cohort and 65 in the external validation cohort. The final nomogram model included 8 variables (age, the Charlson comorbidity index, cognitive function, the Barthel index, bilirubin, sodium, the opioid morphine equivalent dose and the use of anticholinergic drugs). The model revealed good performance in terms of discrimination, calibration, and clinical practicability, with an area under the receiver operating characteristic curve of 0.846 in the training set, 0.838 after bootstrapping, 0.829 in the temporal validation and 0.803 in the external validation set.

CONCLUSIONS

The model serves as a reliable tool to predict delirium onset for advanced cancer patients in palliative care units, which will facilitate early targeted preventive measures to reduce the burden of delirium.

Barriers to healthcare professionals screening, recognizing, and managing delirium in the adult patients receiving specialist palliative care: a mixed-methods systematic review

BACKGROUND

Delirium frequently occurs in palliative care settings, yet its screening, identification, and management remain suboptimal in clinical practice. This review aims to elucidate the barriers preventing healthcare professionals from effectively screening, recognizing, and managing delirium in adult patients receiving specialist palliative care, with the goal of developing strategies to enhance clinical practice.

METHODS

A mixed-methods systematic review was conducted (PROSPERO: CRD42024563666). Literature was sourced from PubMed, Web of Science, Embase, CINAHL, The Cochrane Library, and Clinical Trials databases from their inception to November 16, 2024, without language restrictions. Studies that were primary quantitative, qualitative, and mixed-methods research, and reported the barriers to healthcare professionals' screening, recognition, and management of delirium in adult patients receiving specialist palliative care (including inpatient hospice/hospital care, consultation teams, and outpatient/community services) were included. Studies were excluded if they did not permit barrier factor extraction, had duplicate or incomplete data, or were case reports or conference abstracts. The Mixed Methods Appraisal Tool (MMAT) version 2018 was employed to evaluate the methodological quality of included studies. Data synthesis used the convergent-integrated JBI mixed-methods approach.

RESULTS

21 articles that meet the selection criteria have been identified, with 11 quantitative, 8 qualitative and 2 mixed-methods, collectively involving 857 patients and 649 healthcare professionals. Four themes were identified from the includes studies: (1) Individual level: knowledge and understanding gaps among healthcare professionals; (2) Operational level: implementation challenges in clinical practice; (3) Organizational level: structural and resource deficiencies; (4) Contextual level: specific impacts of situational factors.

CONCLUSION

The systematic review uncovered a complex interplay of barriers spanning individual, operational, organizational, and contextual levels in palliative settings. To address these challenges, recommended strategies include developing targeted training programs, implementing standardized delirium assessment tools, improving guideline accessibility, and promoting interdisciplinary collaboration to enhance delirium screening and management in palliative care.

Assessing the relationship between the distress levels in patients with irreversible terminal delirium and the good quality of death from the perspective of bereaved family

BACKGROUND

Research on achieving a good death for terminally delirious patients is scarce, with limited knowledge about the level of good death and influencing factors. This study investigates the level of good death among delirium patients, factors influencing it, and the correlation between distress, end-of-life care needs, and achieving a good death by surveying bereaved family members of deceased patients in Chinese hospitals.

METHODS

This cross-sectional study from January 2022 to January 2024 was conducted among bereaved family members of patients using an online questionnaire. The questionnaires consisted of (1) participants' demographic and disease-related questionnaires; (2) the Good Death Inventory (GDI) China version; (3) Terminal Delirium-Related Distress Scale (TTDS) China version; (4) the Care Evaluation Scale - short form (CES) China version. All data were analyzed using descriptive statistics, and the associated factors influencing good death were analyzed by multiple linear regression analyses.

RESULT

A total of 263 subjects were enrolled. More males (63.5%) participated than females (36.5%), the mean age was 75.35 ± 13.90 years. Good quality of death was significantly and negatively related to the distress in patients with irreversible terminal delirium (r = -0.458, P<0.01).The multiple linear regression model indicates that TDDS score, CES score, types of diseases, smoking history, nutritional deficiency are important factor affecting the good quality of death.

CONCLUSIONS

The good quality of death from the perspective of bereaved family, a negative correlation was found between the distress in patients with irreversible terminal delirium and good death. Medical staff should be more aware of good quality of death in patients, future research should expand sample sizes to include more demographic data, and explore the concept of a good death across different cultural contexts.

Non-invasive technology to assess hydration status in advanced cancer to explore relationships between fluid status and symptoms: an observational study using bioelectrical impedance analysis

BACKGROUND

Oral fluid intake decreases in advanced cancer in the dying phase of illness. There is inadequate evidence to support the assessment, and management, of hydration in the dying. Bioelectrical impedance analysis (BIA) is a body composition assessment tool. BIA has the potential to inform clinal management in advanced cancer, by examining the relationships between hydration status and clinical variables.

AIM

BIA was used to determine the association between hydration status, symptoms, clinical signs, quality-of-life and survival in advanced cancer, including those who are dying (i.e. in the last week of life).

MATERIALS AND METHODS

We conducted a prospective observational study of people with advanced cancer in three centres. Advance consent methodology was used to conduct hydration assessments in the dying. Total body water was estimated using the BIA Impedance index (Height - H (m)2 /Resistance - R (Ohms)). Backward regression was used to identify factors (physical signs, symptoms, quality of life) that predicted H2/R. Participants in the last 7 days of life were further assessed with BIA to assess hydration changes, and its relationship with clinical outcomes.

RESULTS

One hundred and twenty-five people participated (males n = 74 (59.2%), females, n = 51 (40.8%)). We used backward regression analysis to describe a statistical model to predict hydration status in advanced cancer. The model demonstrated that 'less hydration' (lower H2/R) was associated with female sex (Beta = -0.39, p < 0.001), increased appetite (Beta = -0.12, p = 0.09), increased dehydration assessment scale score (dry mouth, dry axilla, sunken eyes - Beta = -0.19, p = 0.006), and increased breathlessness (Beta = -0.15, p = 0.03). 'More hydration' (higher H2/R) was associated with oedema (Beta = 0.49, p < 0.001). In dying participants (n = 18, 14.4%), hydration status (H2/R) was not significantly different compared to their baseline measurements (n = 18, M = 49.6, SD = 16.0 vs. M = 51.0, SD = 12.1; t(17) = 0.64, p = 0.53) and was not significantly associated with agitation (rs = -0.85, p = 0.74), pain (rs = 0.31, p = 0.23) or respiratory tract secretions (rs = -0.34, p = 0.19).

CONCLUSIONS

This is the first study to use bioimpedance to report a model (using clinical factors) to predict hydration status in advanced cancer. Our data demonstrates the feasibility of using an advance consent method to conduct research in dying people. This method can potentially improve the evidence base (and hence, quality of care) for the dying. Future BIA research can involve hydration assessment of cancers (according to type and stage) and associated variables (e.g., stage of illness, ethnicity and gender). Further work can use BIA to identify clinically relevant outcomes for hydration studies and establish a core outcome set to evaluate how hydration affects symptoms and quality-of-life in cancer.

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.

Risk factors for delirium in advanced cancer patients: A systematic review and meta-analysis

PURPOSE

To systematically collect published research in order to identify and quantify risk factors for delirium in advanced cancer patients.

METHODS

The Cochrane Library, PubMed, Proquest, CINAHL, Web of Science, Ovid MEDLINE, Embase, Scopus, Chinese Wanfang Data, Chinese Periodical Full-text Database (VIP), Chinese Biomedical Literature Database (CBM), and Chinese National Knowledge Infrastructure (CNKI) were systematically searched for cohort or case-control studies reporting individual risk factors for delirium among advanced-stage cancer patients published prior to March 2022. The Newcastle-Ottawa Scale was used to assess the methodological quality of included studies. The pooled adjusted odds ratio (aOR) and its 95% confidence interval were calculated using the RevMan 5.4 software package.

RESULTS

A total of 15 studies with data from 3106 advanced cancer patients were included in our analysis. Nine studies were high-quality and six were of moderate quality. Pooled analyses revealed that 11 risk factors were statistically significant. High-intensity risk factors included sleep disturbance, infection, cachexia and the Palliative Prognostic Index; medium-intensity risk factors included male sex, renal failure, dehydration and drowsiness; low-intensity risk factors included age, total bilirubin and opioid use. Antibiotic use was found to have been a protective factor.

CONCLUSIONS

We identified 12 independent risk factors that were significantly associated with delirium in advanced cancer patients and provide an evidence-based foundation to implement appropriate preventive strategies.

A Review of Clinical Signs and Symptoms of Imminent End-of-Life in Individuals With Advanced Illness

Background: World population is not only aging but suffering from serious chronic illnesses, requiring an increasing need for end-of-life care. However, studies show that many healthcare providers involved in the care of dying patients sometimes express challenges in knowing when to stop non-beneficial investigations and futile treatments that tend to prolong undue suffering for the dying person. Objective: To evaluate the clinical signs and symptoms that show end-of-life is imminent in individuals with advanced illness. Design: Narrative review. Methods: Computerized databases, including PubMed, Embase, Medline,CINAHL, PsycInfo, and Google Scholar were searched from 1992 to 2022 for relevant original papers written in or translated into English language that investigated clinical signs and symptoms of imminent death in individuals with advanced illness. Results: 185 articles identified were carefully reviewed and only those that met the inclusion criteria were included for review. Conclusion: While it is often difficult to predict the timing of death, the ability of healthcare providers to recognize the clinical signs and symptoms of imminent death in terminally-ill individuals may lead to earlier anticipation of care needs and better planning to provide care that is tailored to individual's needs, and ultimately results in better end-of-life care, as well as a better bereavement adjustment experience for the families.

Impact of COVID-19 on the End-of-Life Care of Cancer Patients Who Died in a Korean Tertiary Hospital: A Retrospective Study

Purpose

Social distancing and strict visitor restrictions at hospitals have been national policies since the onset of the coronavirus disease 2019 (COVID-19) pandemic. This has challenged the concept of a good death in comfort with the opportunity to say goodbye. Little is known about how these measures have influenced end-of-life (EOL) care among cancer patients who die in acute care hospitals. This study examined changes in the EOL care of cancer patients during the COVID-19 pandemic.

Methods

We retrospectively analyzed 1,456 adult cancer patients who died in 2019 (n=752) and 2020 (n=704) at a tertiary hospital. Data on EOL care-symptom control and comfort care in an imminently dying state, preparation for death, place of death, and aggressive care in the last month-were reviewed.

Results

The 1,456 patients had a median age of 67 years, and 62.5% were men. Patients who died in 2020 were more likely to experience agitation or delirium before death (17.2% vs. 10.9%), to use inotropes/vasopressors near death (59.2% vs. 52.3%), and to receive cardiopulmonary resuscitation in their last months (16.3% vs. 12.5%) than those who died in 2019. Additionally, the number of deaths in the emergency room doubled in 2020 compared to 2019 (from 7.1% to 14.1%).

Conclusion

This study suggests that EOL care for cancer patients who died in a tertiary hospital deteriorated during the COVID-19 pandemic. The implementation of medical care at the EOL and the preferred place of death should be discussed carefully in advance for high-quality EOL care.

A simple risk score list can be used to predict the occurrence of delirium in patients admitted to inpatient hospice care: A medical record study

OBJECTIVE

This study aimed to examine whether the 10-item Risk Score List (RSL) accurately predicts delirium in patients admitted to inpatient hospice care and whether this instrument can be simplified. Determining the risk for developing delirium can help to treat these patients in a timely manner.

METHODS

This was a retrospective medical record study in patients who died in 2019 or 2020 in three hospices. Predictive values were examined using Cox regression analysis, crosstabs, and C-statistic.

RESULTS

In total, 240 patients were included. Median age at admission was 78 (IQR 70-84) years. Primary diagnosis most often was cancer (n = 186, 78%); 173 (72%) patients had an increased risk of delirium according to RSL, of whom 120 (69%) developed delirium. Overall, 147 (61%) patients developed delirium. The RSL significantly predicted future delirium (HR 3.25, CI 1.87-5.65, p < 0.01) and had a sensitivity of 85%, a specificity of 43%, positive predictive value of 62%, negative predictive value of 73%, and a C-statistic of 0.64. Simplifying the RSL to four items still significantly predicted future delirium, with similar predictive values.

CONCLUSION

Delirium occurs in more than half of patients admitted to hospice care. The RSL can be simplified to four items, without compromising on predictive accuracy.

Successful Management of a Patient With a History of Postoperative Delirium Undergoing Cardiac Surgery With an Erector Spinae Plane Block and Multimodal Analgesia: A Case Report

Perioperative delirium is an acute confusional state with fluctuating levels of consciousness, which can be precipitated by opioid-based anesthetics and inadequate pain control, especially in patients undergoing cardiac surgery. We seek to minimize opioid usage to avoid postoperative delirium in a patient with multiple risk factors undergoing aortic valve replacement. We used cardiac enhanced recovery after surgery protocols (ERAS-C), which include multimodal analgesia and regional anesthesia via bilateral erector spinae plane (ESP) blocks. Our observations suggest that bilateral ESP blocks and cardiac ERAS protocols offer a potential option to manage pain and control risk factors in patients at high risk of postoperative delirium undergoing cardiac surgery.