Prognostication in palliative care

Prognostication As an Interactionally Delicate Matter: A Conversation Analytic Study of Hospice Multidisciplinary Team Meetings

Prognostication has been found to be a delicate matter in interactions between palliative care professionals and patients. Studies have investigated how these discussions are managed and how speakers orient to their delicate nature. However, the degree to which prognostication is a delicate matter in discussions between palliative care professionals themselves has yet to be investigated. This study explored how hospice multidisciplinary team (MDT) members oriented to the delicacy of prognostication during their meetings. Video-recordings of 24 hospice MDT meetings were transcribed and analyzed using Conversation Analysis. In-depth analysis of the interactions showed how prognostic discussions were oriented to as delicate. This was displayed through markers such as pauses and self-repair organization including cutting off words and restarts, and through accounts accompanying the prognosis. In this way, it was seen that prognostication was not necessarily straightforward. This was further evidenced when prognostic requests were problematic to respond to. It is noteworthy that prognostic discussions are delicate during hospice MDT meetings. Potential reasons may reach further than the taboo of death and lie within prognostic uncertainty and accountability. Research is warranted to explore what causes this delicacy and whether specific support is needed for hospice staff.

Prognostication After Dialysis Withdrawal

Introduction

Dialysis withdrawal represents an increasingly common cause of death in patients receiving kidney replacement therapy internationally. Prognostic information about stopping dialysis guides clinicians counseling patients and families regarding end-of-life care. However, few studies examine prognostication after withdrawal. We aimed to determine median survival time after withdrawal of dialysis, and to determine which patient and dialysis-related factors are significantly associated with prognosis.

Methods

This retrospective cohort study used registry data. We included all adult patients from the Western Renal Services who were receiving peritoneal dialysis (PD) or hemodialysis prior to death, whose cause of death was documented as "withdrawal from dialysis" and whose date of death was between January 1, 2016 and June 30, 2022. Demographic, clinical, and biochemical data was extracted. The primary outcome was time-to-death, defined as days from last dialysis session to date of death.

Results

Median survival time from last dialysis to death for the PD group (n = 53) was 4 days (interquartile range [IQR]: 3-10 days), not significantly different from the hemodialysis group which was 6 days (IQR: 2-11 days, P = 0.72). For PD, the only variable significantly associated with survival time was reason for withdrawing (P = 0.01). Median survival time was significantly longer for patients withdrawing for psychosocial reasons compared to those withdrawing for other reasons (P = 0.002). For hemodialysis (n = 186), variables significantly associated with survival time from last dialysis to death was reason for withdrawing (P = 0.001), urine production at the time of withdrawal (P = 0.005), serum sodium (P = 0.02) and smoking status (P = 0.009).

Conclusion

Median survival time was longer for withdrawals for psychosocial reasons compared to medical reasons. The data presented could inform withdrawal discussions regarding prognostication and end-of-life planning with patients and family.

Palliative prognostic scores for survival prediction of cancer patients: a systematic review and meta-analysis

BACKGROUND

The palliative prognostic score is the most widely validated prognostic tool for cancer survival prediction, with modified versions available. A systematic evaluation of palliative prognostic score tools is lacking. This systematic review and meta-analysis aimed to evaluate the performance and prognostic utility of palliative prognostic score, delirium-palliative prognostic score, and palliative prognostic score without clinician prediction in predicting 30-day survival of cancer patients and to compare their performance.

METHODS

Six databases were searched for peer-reviewed studies and grey literature published from inception to June 2, 2023. English studies must assess palliative prognostic score, delirium-palliative prognostic score, or palliative prognostic score without clinician-predicted survival for 30-day survival in adults aged 18 years and older with any stage or type of cancer. Outcomes were pooled using the random effects model or summarized narratively when meta-analysis was not possible.

RESULTS

A total of 39 studies (n = 10 617 patients) were included. Palliative prognostic score is an accurate prognostic tool (pooled area under the curve [AUC] = 0.82, 95% confidence interval [CI] = 0.79 to 0.84) and outperforms palliative prognostic score without clinician-predicted survival (pooled AUC = 0.74, 95% CI = 0.71 to 0.78), suggesting that the original palliative prognostic score should be preferred. The meta-analysis found palliative prognostic score and delirium-palliative prognostic score performance to be comparable. Most studies reported survival probabilities corresponding to the palliative prognostic score risk groups, and higher risk groups were statistically significantly associated with shorter survival.

CONCLUSIONS

Palliative prognostic score is a validated prognostic tool for cancer patients that can enhance clinicians' confidence and accuracy in predicting survival. Future studies should investigate if accuracy differs depending on clinician characteristics. Reporting of validation studies must be improved, as most studies were at high risk of bias, primarily because calibration was not assessed.

Could it have been predicted? A retrospective analysis of the last year of life for people who died whilst in an intermediate care centre

Objectives

Intermediate care centres (ICCs) exist in the UK to bridge between acute hospital and home for those with rehabilitation needs. A national study shows 25% of ICC in-patients died within a year of admission. High quality end-of-life care includes early conversations with a person and their loved ones about what matters to them; timely identification of those who are likely to be nearing the end of their life is key.

Methods

This retrospective quantitative review of 98 patient notes reviewed deaths in one NHS trust, comparing 50 deaths in the acute hospital and 48 in the ICC. Data included frailty score, previous hospital admissions, specialist palliative input and conversations between professionals, patients and their loved ones. Supportive and Palliative Care Indicators Tool (SPICT) scores were used to identify those likely to have a poor prognosis.

Results

Results showed statistically significant differences between the groups. The ICC cohort were older with higher clinical frailty scores. They were less likely to have previous hospital admissions but more likely to have poor prognostic features on final admission. Despite this, the possibility of deterioration was discussed them less frequently than the acute hospital cohort, and fewer saw the Palliative care team.

Conclusion

This data suggests support is needed in ICCs to recognise those likely to be nearing end-of-life. One challenge is patients are more likely to be seen as 'well' in a rehabilitation focused environment. This paper suggests a 'proactive approach' trial using SPICT for ongoing assessment of ICC in-patients supporting identification of a deteriorating person and avoid missed opportunities for key conversations.

Can acutely ill patients predict their outcomes? A scoping review

INTRODUCTION

The full impact of an acute illness on subsequent health is seldom explicitly discussed with patients. Patients' estimates of their likely prognosis have been explored in chronic care settings and can contribute to the improvement of clinical outcomes and patient satisfaction. This scoping review aimed to identify studies of acutely ill patients' estimates of their outcomes and potential benefits for their care.

METHODS

A search was conducted in PubMed, Embase, Web of Science and Google Scholar, using terms related to prognostication and acute care. After removal of duplicates, all articles were assessed for relevance by six investigator pairs; disagreements were resolved by a third investigator. Risk of bias was assessed according to the Cochrane Handbook for Systematic Reviews of Interventions.

RESULTS

Our search identified 3265 articles, of which 10 were included. The methods of assessing self-prognostication were very heterogeneous. Patients seem to be able to predict their need for hospital admission in certain settings, but not their length of stay. The severity of their symptoms and the burden of their disease are often overestimated or underestimated by patients. Patients with severe health conditions and their relatives tend to be overoptimistic about the likely outcome.

CONCLUSION

The understanding of acutely ill patients of their likely outcomes and benefits of treatment has not been adequately studied and is a major knowledge gap. Limited published literature suggests patients may be able to predict their need for hospital admission. Illness perception may influence help-seeking behaviour, speed of recovery and subsequent quality of life. Knowledge of patients' self-prognosis may enhance communication between patients and their physicians, which improves patient-centred care.

'How long do you think?' Unresponsive dying patients in a specialist palliative care service: A consecutive cohort study

BACKGROUND

Predicting length of time to death once the person is unresponsive and deemed to be dying remains uncertain. Knowing approximately how many hours or days dying loved ones have left is crucial for families and clinicians to guide decision-making and plan end-of-life care.

AIM

To determine the length of time between becoming unresponsive and death, and whether age, gender, diagnosis or location-of-care predicted length of time to death.

DESIGN

Retrospective cohort study. Time from allocation of an Australia-modified Karnofsky Performance Status (AKPS) 10 to death was analysed using descriptive narrative. Interval-censored survival analysis was used to determine the duration of patient's final phase of life, taking into account variation across age, gender, diagnosis and location of death.

SETTING/PARTICIPANTS

A total of 786 patients, 18 years of age or over, who received specialist palliative care: as hospice in-patients, in the community and in aged care homes, between January 1st and October 31st, 2022.

RESULTS

The time to death after a change to AKPS 10 is 2 days (n = 382; mean = 2.1; median = 1). Having adjusted for age, cancer, gender, the standard deviation of AKPS for the 7-day period prior to death, the likelihood of death within 2 days is 47%, with 84% of patients dying within 4 days.

CONCLUSION

This study provides valuable new knowledge to support clinicians' confidence when responding to the 'how long' question and can inform decision-making at end-of-life. Further research using the AKPS could provide greater certainty for answering 'how long' questions across the illness trajectory.

Time estimates in prognostic discussions: A conversation analytic study of hospice multidisciplinary team meetings

BACKGROUND

Recommendations state that multidisciplinary team expertise should be utilised for more accurate survival predictions. How the multidisciplinary team discusses prognoses during meetings and how they reference time, is yet to be explored.

AIM

To explore how temporality is conveyed in relation to patients' prognoses during hospice multidisciplinary team meetings.

DESIGN

Video-recordings of 24 hospice multidisciplinary team meetings were transcribed and analysed using Conversation Analysis.

SETTING/PARTICIPANTS

A total of 65 staff participating in multidisciplinary team meetings in a UK hospice from May to December 2021.

RESULTS

Team members conveyed temporality in three different ways. (i) Staff stated that a patient was dying as part of the patient's current health status. These formulations did not include a time reference per se but described the patient's current situation (as dying) instead. (ii) Staff used specific time period references where another specific reference had been provided previously that somehow constrained the timeframe. In these cases, the prognosis would conflict with other proposed care plans. (iii) Staff members used unspecific time period references where the reference appeared vague and there was greater uncertainty about when the patient was expected to die.

CONCLUSIONS

Unspecific time period references are sufficient for achieving meaningful prognostic talk in multidisciplinary teams. In-depth discussion and accurate prediction of patient prognoses are not deemed a priority nor a necessity of these meetings. Providing precise predictions may be too difficult due to uncertainty and accountability. The lack of staff pursuing more specific time references implies shared knowledge between staff and a context-specific use of prognostic estimates.

Prognostic awareness and prognostic information preferences among advanced cancer patients in Kenya

BACKGROUND

 Cancer is the third leading cause of death in Kenya. Yet, little is known about prognostic awareness and preferences for prognostic information.

AIM

 To assess the prevalence of prognostic awareness and preference for prognostic information among advanced cancer patients in Kenya.

SETTING

 Outpatient medical oncology and palliative care clinics and inpatient medical and surgical wards of Moi Teaching and Referral Hospital (MTRH) in Eldoret, Kenya.

METHODS

 The authors surveyed 207 adults with advanced solid cancers. The survey comprised validated measures developed for a multi-site study of end-of-life care in advanced cancer patients. Outcome variables included prognostic awareness and preference for prognostic information.

RESULTS

 More than one-third of participants (36%) were unaware of their prognosis and most (67%) preferred not to receive prognostic information. Increased age (OR = 1.04, 95% CI: 1.02, 1.07) and education level (OR: 1.18, CI: 1.08, 1.30) were associated with a higher likelihood of preference to receive prognostic information, while increased symptom burden (OR= 0.94, CI: 0.90, 0.99) and higher perceived household income levels (lower-middle vs low: OR= 0.19; CI: 0.09, 0.44; and upper middle- or high vs low: OR= 0.22, CI: 0.09, 0.56) were associated with lower odds of preferring prognostic information.

CONCLUSION

 Results reveal low levels of prognostic awareness and little interest in receiving prognostic information among advanced cancer patients in Kenya.Contribution: Given the important role of prognostic awareness in providing patient-centred care, efforts to educate patients in Kenya on the value of this information should be a priority, especially among younger patients.

Prognostic models and factors identifying end-of-life in non-cancer chronic diseases: a systematic review

BACKGROUND

Precise prognostic information, if available, is very helpful for guiding treatment decisions and resource allocation in patients with non-cancer non-communicable chronic diseases (NCDs). This study aimed to systematically review the existing evidence, examining prognostic models and factors for identifying end-of-life non-cancer NCD patients.

METHODS

Electronic databases, including Medline, Embase, CINAHL, Cochrane Library, PsychINFO and other sources, were searched from the inception of these databases up until June 2023. Studies published in English with findings mentioning prognostic models or factors related to identifying end-of-life in non-cancer NCD patients were included. The quality of studies was assessed using the Quality in Prognosis Studies tool.

RESULTS

The analysis included data from 41 studies, with 16 focusing on chronic obstructive pulmonary diseases (COPD), 10 on dementia, 6 on heart failure and 9 on mixed NCDs. Traditional statistical modelling was predominantly used for the identified prognostic models. Common predictors in COPD models included dyspnoea, forced expiratory volume in 1 s, functional status, exacerbation history and body mass index. Models for dementia and heart failure frequently included comorbidity, age, gender, blood tests and nutritional status. Similarly, mixed NCD models commonly included functional status, age, dyspnoea, the presence of skin pressure ulcers, oral intake and level of consciousness. The identified prognostic models exhibited varying predictive accuracy, with the majority demonstrating weak to moderate discriminatory performance (area under the curve: 0.5-0.8). Additionally, most of these models lacked independent external validation, and only a few underwent internal validation.

CONCLUSION

Our review summarised the most relevant predictors for identifying end-of-life in non-cancer NCDs. However, the predictive accuracy of identified models was generally inconsistent and low, and lacked external validation. Although efforts to improve these prognostic models should continue, clinicians should recognise the possibility that disease heterogeneity may limit the utility of these models for individual prognostication; they may be more useful for population level health planning.

A Prospective Study with Patients and Families on the Usefulness of Accurate Prognosis for Palliative Care Patients

Prediction of life expectancy in terminally ill patients is an important end-of-life care issue for patients, families and mental health workers during the last days of life. This study was conducted to examine the importance/usefulness for patients/families to have an accurate prognosis and its impact on planning their activities prior to death. All patients admitted during a period of one year were included. Patients' and families' viewpoints on the usefulness of an accurate prognosis was documented at admission. There were 285 patients in the cohort. The median time to death was 8 days. Most families (83%) rated the importance of an accurate prognosis as moderately (13%) to very much useful (70%). A total of 42% of patients were able to complete e the questionnaire. Among these, 58% found it moderately to very much useful. For families, having an accurate prognosis influenced the planning of visits (69%), communication/closure (42%) and spiritual needs/funeral arrangements (31%). Patients identified planning of visits (10%), communication/closure (12%), and goals/accomplishments (9%) as very important. Discussing the prognosis and its impact is very helpful for the mental health professionals to have open and honest conversations with patients/families to identify, prioritize and adapt treatment to achieve goals prior to death.

Understanding the Utility of Less Than Six-Month Prognosis Using Administrative Data Among U.S. Nursing Home Residents With Cancer

Background

There is a dearth of studies evaluating the utility of reporting prognostication among nursing home (NH) residents with cancer.

Objective

To study factors associated with documented less than six-month prognosis, and its relationship with end-of-life (EOL) care quality measures among residents with cancer.

Methods

The Surveillance, Epidemiology, and End Results linked with Medicare, and the Minimum Data Set databases was used to identify 20,397 NH residents in the United States with breast, colorectal, lung, pancreatic, or prostate cancer who died between July 2016 and December 2018. Of these, 2205 residents (10.8%) were documented with less than six-month prognosis upon NH admission. Main outcomes were more than one hospitalization, more than one emergency department visit, and any intensive care unit admission within the last 30 days of life as aggressive EOL care markers, as well as admission to hospice, receipt of advance care planning and palliative care, and survival. Specificity and sensitivity of prognosis were assessed using six-month mortality as the outcome. Propensity score matching adjusted for selection biases, and logistic regression examined association.

Results

Specificity and sensitivity of documented less than six-month prognosis for mortality were 94.2% and 13.7%, respectively. Residents with documented less than six-month prognosis had greater odds of being admitted to hospice than those without (adjusted odds ratio: 3.27, 95% confidence interval: 2.86-3.62), and lower odds to receive aggressive EOL care.

Conclusion

In this cohort study, documented less than six-month prognosis was associated with less aggressive EOL care. Despite its high specificity, however, low sensitivity limits its utility to operationalize care on a larger population of residents with terminal illness.

How clinicians recognise people who are dying: An integrative review

BACKGROUND

Timely recognition of dying is important for high quality end-of-life care however, little is known about how clinicians recognise dying. Late recognition is common and can lead to futile treatment that can prolong or increase suffering and prevent a change in the focus of care.

AIM

To explore how clinicians caring for dying people recognise that they are in the last days or hours of life, as well as the factors that influence the recognition of dying.

DESIGN

A systematically constructed integrative review of the literature.

METHODS

Medline, Scopus, Cumulative Index to Nursing and Allied Health Literature, PsycInfo and Allied and Complementary Medicine were searched in July 2022. Papers were included if they were original research, discussed how clinicians recognise dying, available in English language and published in 2012 or later. A constant comparison approach was applied to the analysis and synthesis of the literature.

RESULTS

24 papers met the inclusion criteria. There were 3 main categories identified: 'Clues and signals' refers to prompts and signs that lead a clinician to believe a person is dying, incorporating the sub-categories 'knowing the patient over time', and 'intuition and experience'. 'Recognition by others' is where clinicians come to recognise someone is dying through others. This can be through a change in the context of care such as a tool or care plan or by communication with the team. 'Culture, system and practice' refers to the cultural beliefs of a setting that influences awareness of dying and denial of death as a possibility and avoidance of naming death and dying directly. System and practice of the setting also impact on recognition of dying. This involves work pace and intensity, shift systems and timing of senior reviews of patients. Uncertainty and its impact on recognition of dying are evident throughout the findings of this review. The seeking of certainty and the absence of the possibility of dying contributes to late recognition of dying.

DISCUSSION

Recognition of dying is a complex process that occurs over time, involving a combination of intuition and gathering of information, that is influenced by contextual factors. A culture where dying is not openly acknowledged or even named explicitly contributes to late recognition of dying. A shared language and consistent terminology for explicitly naming dying are needed. Uncertainty is intrinsic to the recognition of dying and therefore a shift to recognising the possibility of dying rather than seeking certainty is needed.

REGISTRATION

(PROSPERO) CRD42022360900. Registered September 2022.

Predicting 60-Day Mortality in a Home-Care Service: Development of a New Inter-RAI 49-Frailty Index in Patients with Chronic Disease and without a Cancer Diagnosis

OBJECTIVE

Frailty Index (FI) is used to define the level of frailty in various clinical settings. Fifteen- and 26-item FIs have been demonstrated to predict 1-year mortality and intensity of care in home care (HC) and palliative home care (PHC). The objective of this study was to develop a new FI to predict the 60-day risk of death or transition to a PHC service after the initiation of an HC service in patients with chronic disease and without a cancer diagnosis.

DESIGN

Retrospective cohort study.

SETTING AND PARTICIPANTS

Patients 18 years and older followed in an HC service of a "Frailty Department-Local Palliative Care Network" from January 1, 2017, to October 31, 2021.

METHODS

A 49-item FI (FI-49) was developed selecting variables within the standardized international Residential Assessment Instrument assessments (interRAI-HC) and compared to existing FIs with 15 and 26 variables.

RESULTS

A total of 2099 patients were included in the study with a median age of 80.0 years (IQR: 72.0-86.0) and a predominantly female population (62.4%). Among these patients, 8% died or were transferred to PHC within the 60-day follow-up. The FI-49 demonstrated a higher ability to predict 60-day mortality (C index 0.8165, 95% CI 0.7848-0.8481) compared to the 26- and 15-item FI. An FI-49 cutoff of 0.33 was also selected to provide clinicians with a more practical approach (C-index of 0.7044, 95% CI 0.6796-0.7292).

CONCLUSION AND IMPLICATION

The FI-49 is a good predictor of short-term mortality or transition to palliative care among older patients referred to an HC service. The automatic calculation of this tool could facilitate more appropriate care planning and the correct allocation of healthcare resources, especially considering the rapid ageing of the population.

Indian Society of Critical Care Medicine and Indian Association of Palliative Care Expert Consensus and Position Statements for End-of-life and Palliative Care in the Intensive Care Unit

End-of-life care (EOLC) exemplifies the joint mission of intensive and palliative care (PC) in their human-centeredness. The explosion of technological advances in medicine must be balanced with the culture of holistic care. Inevitably, it brings together the science and the art of medicine in their full expression. High-quality EOLC in the ICU is grounded in evidence, ethical principles, and professionalism within the framework of the Law. Expert professional statements over the last two decades in India were developed while the law was evolving. Recent landmark Supreme Court judgments have necessitated a review of the clinical pathway for EOLC outlined in the previous statements. Much empirical and interventional evidence has accumulated since the position statement in 2014. This iteration of the joint Indian Society of Critical Care Medicine-Indian Association of Palliative Care (ISCCM-IAPC) Position Statement for EOLC combines contemporary evidence, ethics, and law for decision support by the bedside in Indian ICUs.

How to cite this article

Mani RK, Bhatnagar S, Butola S, Gursahani R, Mehta D, Simha S, et al. Indian Society of Critical Care Medicine and Indian Association of Palliative Care Expert Consensus and Position Statements for End-of-life and Palliative Care in the Intensive Care Unit. Indian J Crit Care Med 2024;28(3):200-250.

Palliative medicine trainees be should learn about frailty: meta-synthesis and Delphi study to establish curriculum content

OBJECTIVES

Frailty is common and highly associated with morbidity and mortality, a fact that has been highlighted by COVID-19. Understanding how to provide palliative care for frail individuals is an international priority, despite receiving limited mention in Palliative Medicine curricula or examinations worldwide. This study aimed to synthesise evidence and establish expert consensus on what should be included in a Palliative-Medicine Specialist Training Curriculum for frailty.

METHODS

Literature Meta-synthesis conducted by palliative medicine, frailty and education experts produced a draft curriculum with Bologna based Learning-Outcomes. A Delphi study asked experts to rate the importance of Learning-Outcomes for specialist-training completion and propose additional Learning-Outcomes. This process was repeated until 70% consensus was achieved for over 90% of Learning-Outcomes. Experts divided Learning-Outcomes into specific (for inclusion in a frailty subsection) or generic (applicable to other palliative conditions). The Delphi panel was Subject Matter Experts: Palliative-Medicine Consultants (n=14) and Trainees (n=10), representing hospital, community, hospice and care home services and including committee members of key national training organisations. A final reviewing panel of Geriatric Medicine Specialists including experts in research methodology, national training requirements and frailty were selected.

RESULTS

The meta-synthesis produced 114 Learning-Outcomes. The Delphi Study and Review by Geriatric Medicine experts resulted in 46 essential and 33 desirable Learning-Outcomes.

CONCLUSIONS

This frailty curriculum is applicable internationally and highlights the complex and unique palliative needs of frail patients. Future research is required to inform implementation, educational delivery and service provision.

Prescribing and deprescribing in older people with life-limiting illnesses receiving hospice care at the end of life: A longitudinal, retrospective cohort study

BACKGROUND

Although prescribing and deprescribing practices in older people have been the subject of much research generally, there are limited data in older people at the end of life. This highlights the need for research to determine prescribing and deprescribing patterns, as a first step to facilitate guideline development for medicines optimisation in this vulnerable population.

AIMS

To examine prescribing and deprescribing patterns in older people at the end of life and to determine the prevalence of potentially inappropriate medication use.

DESIGN

A longitudinal, retrospective cohort study where medical records of eligible participants were reviewed, and data extracted. Medication appropriateness was assessed using two sets of consensus-based criteria; the STOPPFrail criteria and criteria developed by Morin et al.

SETTING/PARTICIPANTS

Decedents aged 65 years and older admitted continuously for at least 14 days before death to three inpatient hospice units across Northern Ireland, who died between 1st January and 31st December 2018, and who had a known diagnosis, known cause of death and prescription data. Unexpected/sudden deaths were excluded.

RESULTS

Polypharmacy was reported to be continued until death in 96.2% of 106 decedents (mean age of 75.6 years). Most patients received at least one potentially inappropriate medication at the end of life according to the STOPPFrail and the criteria developed by Morin et al. (57.5 and 69.8% respectively). Limited prevalence of proactive deprescribing interventions was observed.

CONCLUSIONS

In the absence of systematic rationalisation of drug treatments, a substantial proportion of older patients continued to receive potentially inappropriate medication until death.

A review of the utility of prognostic tools in predicting 6-month mortality in cancer patients, conducted in the context of voluntary assisted dying

BACKGROUND

Eligibility to access the Victorian voluntary assisted dying (VAD) legislation requires that people have a prognosis of 6 months or less (or 12 months or less in the setting of a neurodegenerative diagnosis). Yet prognostic determination is frequently inaccurate and prompts clinician discomfort. Based on functional capacity and clinical and biochemical markers, prognostic tools have been developed to increase the accuracy of life expectancy predictions.

AIMS

This review of prognostic tools explores their accuracy to determine 6-month mortality in adults when treated under palliative care with a primary diagnosis of cancer (the diagnosis of a large proportion of people who are requesting VAD).

METHODS

A systematic search of the literature was performed on electronic databases Medline, Embase and Cinahl.

RESULTS

Limitations of prognostication identified include the following: (i) prognostic tools still provide uncertain prognoses; (ii) prognostic tools have greater accuracy predicting shorter prognoses, such as weeks to months, rather than 6 months; and (iii) functionality was often weighted significantly when calculating prognoses. Challenges of prognostication identified include the following: (i) the area under the curve (a value that represents how well a model can distinguish between two outcomes) cannot be directly interpreted clinically and (ii) difficulties exist related to determining appropriate thresholds of accuracy in this context.

CONCLUSIONS

Prognostication is a significant aspect of VAD, and the utility of the currently available prognostic tools appears limited but may prompt discussions about prognosis and alternative means (other than prognostic estimates) to identify those eligible for VAD.

What outcomes do studies use to measure the impact of prognostication on people with advanced cancer? Findings from a systematic review of quantitative and qualitative studies

BACKGROUND

Studies evaluating the impact of prognostication in advanced cancer patients vary in the outcomes they measure, and there is a lack of consensus about which outcomes are most important.

AIM

To identify outcomes previously reported in prognostic research with people with advanced cancer, as a first step towards constructing a core outcome set for prognostic impact studies.

DESIGN

A systematic review was conducted and analysed in two subsets: one qualitative and one quantitative. (PROSPERO ID: CRD42022320117; 29/03/2022).

DATA SOURCES

Six databases were searched from inception to September 2022. We extracted data describing (1) outcomes used to measure the impact of prognostication and (2) patients' and informal caregivers' experiences and perceptions of prognostication in advanced cancer. We classified findings using the Core Outcome Measures in Effectiveness Trials (COMET) initiative taxonomy, along with a narrative description. We appraised retrieved studies for quality, but quality was not a basis for exclusion.

RESULTS

We identified 42 eligible studies: 32 quantitative, 6 qualitative, 4 mixed methods. We extracted 70 outcomes of prognostication in advanced cancer and organised them into 12 domains: (1) survival; (2) psychiatric outcomes; (3) general outcomes; (4) spiritual/religious/existential functioning/wellbeing, (5) emotional functioning/wellbeing; (6) cognitive functioning; (7) social functioning; (8) global quality of life; (9) delivery of care; (10) perceived health status; (11) personal circumstances; and (12) hospital/hospice use.

CONCLUSION

Outcome reporting and measurement varied markedly across the studies. A standardised approach to outcome reporting in studies of prognosis is necessary to enhance data synthesis, improve clinical practice and better align with stakeholders' priorities.

Developing a Core Outcome Set for Prognostic Research in Palliative Cancer Care: Protocol for a Mixed Methods Study

BACKGROUND

Studies exploring the impact of receiving end-of-life prognoses in patients with advanced cancer use a variety of different measures to evaluate the outcomes, and thus report often conflicting findings. The standardization of outcomes reported in studies of prognostication in palliative cancer care could enable uniform assessment and reporting, as well as intertrial comparisons. A core outcome set promotes consistency in outcome selection and reporting among studies within a particular population. We aim to develop a set of core outcomes to be used to measure the impact of end-of-life prognostication in palliative cancer care.

OBJECTIVE

This protocol outlines the proposed methodology to develop a core outcome set for measuring the impact of end-of-life prognostication in palliative cancer care.

METHODS

We will adopt a mixed methods approach consisting of 3 phases using methodology recommended by the Core Outcome Measure in Effectiveness Trials (COMET) initiative. In phase I, we will conduct a systematic review to identify existing outcomes that prognostic studies have previously used, so as to inform the development of items and domains for the proposed core outcome set. Phase II will consist of semistructured interviews with patients with advanced cancer who are receiving palliative care, informal caregivers, and clinicians, to explore their perceptions and experiences of end-of-life prognostication. Outcomes identified in the interviews will be combined with those found in existing literature and taken forward to phase III, a Delphi survey, in which we will ask patients, informal caregivers, clinicians, and relevant researchers to rate these outcomes until consensus is achieved as to which are considered to be the most important for inclusion in the core outcome set. The resulting, prioritized outcomes will be discussed in a consensus meeting to agree and endorse the final core outcome set.

RESULTS

Ethical approval was received for this study in September 2022. As of July 2023, we have completed and published the systematic review (phase I) and have started recruitment for phase II. Data analysis for phase II has not yet started. We expect to complete the study by October 2024.

CONCLUSIONS

This protocol presents the stepwise approach that will be taken to develop a core outcome set for measuring the impact of end-of-life prognostication in palliative cancer care. The final core outcome set has the potential for translation into clinical practice, allowing for consistent evaluation of emerging prognostic algorithms and improving communication of end-of-life prognostication. This study will also potentially facilitate the design of future clinical trials of the impact of end-of-life prognostication in palliative care that are acceptable to key stakeholders.

TRIAL REGISTRATION

Core Outcome Measures in Effectiveness Trials 2136; https://www.comet-initiative.org/Studies/Details/2136.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/49774.

Digital health and inpatient palliative care: a cohort-controlled study

OBJECTIVES

End of life has unacceptable levels of hospital admission and death. We aimed to determine the association of a novel digital specific system (Proactive Risk-Based and Data-Driven Assessment of Patients at the End of Life, PRADA) to modify such events.

METHODS

A cohort-controlled study of those discharged alive, who died within 90 days of discharge, comparing PRADA (n=114) with standard care (n=3730).

RESULTS

At 90 days, the PRADA group were more likely to die (78.9% vs 46.2%, p<0.001), had a shorter time to death (58±90 vs 178±186 days, p<0.001) but readmission (20.2% vs 37.9%, p<0.001) or death in hospital (4.4% vs 28.9%, p<0.001) was lower with reduced risk for a combined 90-day outcome of postdischarge non-elective admission or hospital death (OR 0.45, 95% CI 0.27-0.74, p<0.001). Tightening criteria with 1:1 matching (n=83 vs 83) showed persistent significant findings in PRADA contact with markedly reduced adverse events (OR 0.15, 95% CI 0.02-0.96, p<0.05).

CONCLUSIONS

Being seen in hospital by a specialist palliative care team using the PRADA tool was associated with significantly improved postdischarge outcomes pertaining to those destined to die after discharge.

Deep Learning Prediction Model for Patient Survival Outcomes in Palliative Care Using Actigraphy Data and Clinical Information

(1) Background: Predicting the survival of patients in end-of-life care is crucial, and evaluating their performance status is a key factor in determining their likelihood of survival. However, the current traditional methods for predicting survival are limited due to their subjective nature. Wearable technology that provides continuous patient monitoring is a more favorable approach for predicting survival outcomes among palliative care patients. (2) Aims and objectives: In this study, we aimed to explore the potential of using deep learning (DL) model approaches to predict the survival outcomes of end-stage cancer patients. Furthermore, we also aimed to compare the accuracy of our proposed activity monitoring and survival prediction model with traditional prognostic tools, such as the Karnofsky Performance Scale (KPS) and the Palliative Performance Index (PPI). (3) Method: This study recruited 78 patients from the Taipei Medical University Hospital's palliative care unit, with 66 (39 male and 27 female) patients eventually being included in our DL model for predicting their survival outcomes. (4) Results: The KPS and PPI demonstrated an overall accuracy of 0.833 and 0.615, respectively. In comparison, the actigraphy data exhibited a higher accuracy at 0.893, while the accuracy of the wearable data combined with clinical information was even better, at 0.924. (5) Conclusion: Our study highlights the significance of incorporating clinical data alongside wearable sensors to predict prognosis. Our findings suggest that 48 h of data is sufficient for accurate predictions. The integration of wearable technology and the prediction model in palliative care has the potential to improve decision making for healthcare providers and can provide better support for patients and their families. The outcomes of this study can possibly contribute to the development of personalized and patient-centered end-of-life care plans in clinical practice.

Palliative profile, one-year mortality and quality of life in older inpatients according to Be-PICT: a multicenter prospective cohort study

BACKGROUND

A palliative care approach (PCA), including advanced care planning (ACP), should be considered for patients with limited life expectancy. The Belgian Palliative Care Indicators Tool (Be-PICT) has been released to help identify patients who may benefit from such approach. This study aimed at measuring 1-year mortality and describe the quality of life in older inpatients, according to baseline Be-PICT results.

METHODS

Prospective multicentre cohort study in older patients (≥ 75 years) admitted at geriatrics and cardiology wards of four Belgian hospitals. The palliative profile was defined as a positive Be-PICT.1, defined by the presence of its three criteria, i.e. a negative physician's answer to the surprise question 'would you be surprised if this patient dies in the 6-12 next months?', ≥ 1 poor health indicator and ≥ 1 life-limiting condition.

RESULTS

Of the 379 patients (50% aged ≥85 years; 51% female), 52 (14%) presented a palliative profile and 83 (23%) died within 1 year. Be-PICT.1 showed the following characteristics to predict 1-year mortality: sensitivity 0.54, specificity 0.83, positive and negative predictive values 0.48 and 0.86, positive and negative likelihood ratios 3.22 and 0.55. The patients with a palliative profile were at higher mortality risk (hazard ratio 4.79 p < 0.001) and 1-year mortality rate (45%). Not using the SQ allowed to improve sensitivity to include a larger number of patients who may benefit from ACP and PCA.

CONCLUSIONS

Be-PICT.1 is a simple case-finding tool to identify older inpatients being at high mortality risk and candidates for ACP and PCA.

Prognostication in Advanced Cancer by Combining Actigraphy-Derived Rest-Activity and Sleep Parameters with Routine Clinical Data: An Exploratory Machine Learning Study

Survival prediction is integral to oncology and palliative care, yet robust prognostic models remain elusive. We assessed the feasibility of combining actigraphy, sleep diary data, and routine clinical parameters to prognosticate. Fifty adult outpatients with advanced cancer and estimated prognosis of <1 year were recruited. Patients were required to wear an Actiwatch® (wrist actigraph) for 8 days, and complete a sleep diary. Univariate and regularised multivariate regression methods were used to identify predictors from 66 variables and construct predictive models of survival. A total of 49 patients completed the study, and 34 patients died within 1 year. Forty-two patients had disrupted rest-activity rhythms (dichotomy index (I < O ≤ 97.5%) but I < O did not have prognostic value in univariate analyses. The Lasso regularised derived algorithm was optimal and able to differentiate participants with shorter/longer survival (log rank p < 0.0001). Predictors associated with increased survival time were: time of awakening sleep efficiency, subjective sleep quality, clinician’s estimate of survival and global health status score, and haemoglobin. A shorter survival time was associated with self-reported sleep disturbance, neutrophil count, serum urea, creatinine, and C-reactive protein. Applying machine learning to actigraphy and sleep data combined with routine clinical data is a promising approach for the development of prognostic tools.

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.

An online randomised controlled trial of prognosticating imminent death in advanced cancer patients: Clinicians give greater weight to advice from a prognostic algorithm than from another clinician with a different profession

BACKGROUND

A second opinion or a prognostic algorithm may increase prognostic accuracy. This study assessed the level to which clinicians integrate advice perceived to be coming from another clinician or a prognostic algorithm into their prognostic estimates, and how participant characteristics and nature of advice received affect this.

METHODS

An online double-blind randomised controlled trial was conducted. Palliative doctors, nurses and other types of healthcare professionals were randomised into study arms differing by perceived source of advice (algorithm or another clinician). In fact, the advice was the same in both arms (emanating from the PiPS-B14 prognostic model). Each participant reviewed five patient summaries. For each summary, participants: (1) provided an initial probability estimate of two-week survival (0% 'certain death'-100% 'certain survival'); (2) received advice (another estimate); (3) provided a final estimate. Weight of Advice (WOA) was calculated for each summary (0 '100% advice discounting' - 1 '0% discounting') and multilevel linear regression analyses were conducted.

CLINICAL TRIAL REGISTRATION NUMBER

NCT04568629.

RESULTS

A total of 283 clinicians were included in the analysis. Clinicians integrated advice from the algorithm more than advice from another clinician (WOA difference = -0.12 [95% CI -0.18, -0.07], p < 0.001). There was no interaction between study arm and participant profession, years of palliative care or overall experience. Advice of intermediate strength (75%) was given a lower WOA (0.31) than advice received at either the 50% (WOA 0.40) or 90% level (WOA 0.43). The overall interaction between strength of advice and study arm on WOA was significant (p < 0.001).

CONCLUSION

Clinicians adjusted their prognostic estimates more when advice was perceived to come from a prognostic algorithm than from another clinician. Research is needed to understand how clinicians make prognostic decisions and how algorithms are used in clinical practice.

A Consensus Definition of End of Life from an International and Interdisciplinary Perspective: A Delphi Panel Study

Background: Those working in the field of palliative care have recognized that many terms are being used synonymously and that clear definitions (or any definitions) for many of these terms are lacking. The synonymous use of the terms palliative and end of life (EOL) can especially lead to conflicts in clinical practice, such as a tardy referral to palliative care. Such conflicts may then result in poorer treatment of patients, for instance, pain management. In research, the lack of clear definitions or even of any established definition for central concepts, such as EOL, weakens study validity and research outcomes. Objective: The aim of this study was to establish a concise definition for the EOL phase. Design: A modified Delphi study design was chosen. A structured questionnaire based on a previously conducted concept analysis about the EOL was used. Setting: A panel of international and interdisciplinary experts was established. Between 34 (1st round) and 21 (4th round) individuals participated in the anonymous online expert panel. Results: After four panel rounds, we were able to provide a definition which covers physical and psychosocial aspects that should be considered at the beginning of the EOL phase and possible predictions about the remaining time. The definition also covers aspects of EOL care, such as considerations related to the individual's dignity, spirituality, and maintenance of relationships. Conclusion: EOL is a term which is defined by considering multiple aspects that affect the process of identifying the EOL phase, the EOL phase itself and the resulting care options.

Integrating palliative surgery and palliative care

We report a challenging patient journey at a rural New Zealand hospital affiliated with a hospice programme. This case illustrates the complexities and rewards of achieving a valuable and sensible collaboration among various teams to ensure the best possible outcome for surgical patients receiving palliative care.

Clinical frailty and performance scale translation in palliative care: scoping review

BACKGROUND

Frailty is associated with advancing age and increases the risk of adverse outcomes and death. Routine assessment of frailty is becoming more common in a number of healthcare settings, but not in palliative care, where performance scales (eg, the Australia-modified Karnofsky Performance Status Scale (AKPS)) are more commonly employed. A shared understanding of performance and frailty measures could aid interspecialty collaboration in both end-of-life care research and clinical practice.

AIMS

To identify and synthesise evidence comparing measures of performance routinely collected in palliative care with the Clinical Frailty Scale (CFS), and create a conversion chart to support interspecialty communication.

METHODS

A scoping literature review with comprehensive searches of PubMed, Web of Science, Ovid SP, the Cochrane Library and reference lists. Eligible articles compared the CFS with the AKPS, Palliative Performance Scale (PPS), Karnofsky Performance Scale or Eastern Cooperative Oncology Group Performance Status or compared these performance scales, in patients aged >18 in any setting.

RESULTS

Searches retrieved 3124 articles. Two articles directly compared CFS to the PPS. Thirteen studies translated between different performance scores, facilitating subsequent conversion to CFS, specifically: AKPS/PPS 10/20=very severe frailty, AKPS/PPS 30=severe frailty, AKPS/PPS 40/50=moderate frailty, AKPS/PPS60=mild frailty.

CONCLUSION

We present a tool for converting between the CFS and performance measures commonly used in palliative care. A small number of studies provided evidence for the direct translation between CFS and the PPS. Therefore, more primary evidence is needed from a wider range of population settings, and performance measures to support this conversion.

Intelligent Palliative Care Based on Patient-Reported Outcome Measures

CONTEXT

The growth of patient reported outcome measures data in palliative care provides an opportunity for machine learning to identify patterns in patient responses signifying different phases of illness.

OBJECTIVES

The study will explore if machine learning and network analysis can identify phases in patient palliative status through symptoms reported on the Integrated Palliative Care Outcome Scale (IPOS).

METHODS

A partly cross-sectional and partially longitudinal observational study was undertaken using the Australasian Karnofsky Performance Scale (AKPS); Integrated Palliative Care Outcome Scale (IPOS); Phase of Illness (POI). Patient palliative records (n = 1507, 65% stable, 20% unstable, 9% deteriorating, 2% terminal) from 804 adult patients enrolled in a New Zealand palliative care service were analysed using a combination of statistical, machine learning and network analysis techniques.

RESULTS

Data from IPOS showed considerable variation with phase. Also, network analysis showed clear associations between items by phase. Six machine learning techniques identified the most important variables for predicting possible transition between phases of illness. Network analysis for all patients showed that Poor Appetite and Loss of Energy were central IPOS items, with Loss of Energy linked to Drowsiness, Shortness of Breath and Lack of Mobility on the one hand, and Poor Appetite linked to Nausea, Vomiting, Constipation and Sore and Dry Mouth on the other.

CONCLUSION

These preliminary results, when coupled with the latest technological developments in mobile apps and wearable technology, could point the way to increased use of digital therapeutics in continuous palliative care monitoring.

Enhancing Palliative Care for Patients With Advanced Heart Failure Through Simple Prognostication Tools: A Comparison of the Surprise Question, the Number of Previous Heart Failure Hospitalizations, and the Seattle Heart Failure Model for Predicting 1-Year Survival

Background

Score-based survival prediction in patients with advanced heart failure (HF) is complicated. Easy-to-use prognostication tools could inform clinical decision-making and palliative care delivery.

Objective

To compare the prognostic utility of the Seattle HF model (SHFM), the surprise question (SQ), and the number of HF hospitalizations (NoH) within the last 12 months for predicting 1-year survival in patients with advanced HF.

Methods

We retrospectively analyzed data from a cluster-randomized controlled trial of advanced HF patients, predominantly with reduced ejection fraction. Primary outcome was the prognostic discrimination of SHFM, SQ (“Would you be surprised if this patient were to die within 1 year?”) answered by HF cardiologists, and NoH, assessed by receiver operating characteristic (ROC) curve analysis. Optimal cut-offs were calculated using Youden’s index (SHFM: <86% predicted 1-year survival; NoH ≥ 2).

Results

Of 535 subjects, 82 (15.3%) had died after 1-year of follow-up. SHFM, SQ, and NoH yielded a similar area under the ROC curve [SHFM: 0.65 (0.60–0.71 95% CI); SQ: 0.58 (0.54–0.63 95% CI); NoH: 0.56 (0.50–0.62 95% CI)] and similar sensitivity [SHFM: 0.76 (0.65–0.84 95% CI); SQ: 0.84 (0.74–0.91 95% CI); NoH: 0.56 (0.45–0.67 95% CI)]. As compared to SHFM, SQ had lower specificity [SQ: 0.33 (0.28–0.37 95% CI) vs. SHFM: 0.55 (0.50–0.60 95% CI)] while NoH had similar specificity [0.56 (0.51–0.61 95% CI)]. SQ combined with NoH showed significantly higher specificity [0.68 (0.64–0.73 95% CI)].

Conclusion

SQ and NoH yielded comparable utility to SHFM for 1-year survival prediction among advanced HF patients, are easy-to-use and could inform bedside decision-making.

Prognostic decision-making about imminent death within multidisciplinary teams: a scoping review

OBJECTIVE

To summarise evidence on how multidisciplinary team (MDTs) make decisions about identification of imminently dying patients.

DESIGN

Scoping review.

SETTING

Any clinical setting providing care for imminently dying patients, excluding studies conducted solely in acute care settings.

DATA SOURCES

The databases AMED, CINAHL, Embase, MEDLINE, PsychINFO and Web of Science were searched from inception to May 2021.Included studies presented original study data written in English and reported on the process or content of MDT discussions about identifying imminently dying adult patients.

RESULTS

40 studies were included in the review. Studies were primarily conducted using interviews and qualitative analysis of themes.MDT members involved in decision-making were usually doctors and nurses. Some decisions focused on professionals recognising that patients were dying, other decisions focused on initiating specific end-of-life care pathways or clarifying care goals. Most decisions provided evidence for a partial collaborative approach, with information-sharing being more common than joint decision-making. Issues with decision-making included disagreement between staff members and the fact that doctors were often regarded as final or sole decision-makers.

CONCLUSIONS

Prognostic decision-making was often not the main focus of included studies. Based on review findings, research explicitly focusing on MDT prognostication by analysing team discussions is needed. The role of allied and other types of healthcare professionals in prognostication needs further investigation as well. A focus on specialist palliative care settings is also necessary.

Identification of Palliative Care Needs in Cancer Patients in a Surgical Emergency Center

BACKGROUND

Advanced cancer is associated with a significant symptom burden, and timely identification of palliative care (PC) needs, and provision of appropriate PC can improve treatment outcomes, reduce healthcare cost, and enhance patient and family satisfaction with care. Several tools have been used to identify PC needs in different clinical settings and patient groups.

OBJECTIVE

The primary objective was to determine the prevalence and associated characteristics of PC needs among cancer patients admitted to the surgical emergency center (SEC) of a large academic hospital in South Africa (SA). The association between PC needs and early death were explored as a secondary outcome.

DESIGN

This was a cross-sectional observational study that included all patients with known malignancy admitted through the SEC for acute surgical emergencies. The validated Supportive and Palliative Care Indicators Tool (SPICT™) was applied to patients' files on admission to the SEC. In addition, attending physicians were asked to estimate the 1 year survival probability of these patients by answering The Surprise Question (SQ).

SETTING

A tertiary level, public, academic hospital in Cape Town, SA.

RESULTS

One hundred and twelve admissions were included with a median age of 58 years. Fifty-two admissions (46.4%) were for metastatic patients and 60.7% were known with palliative treatment intent. The prevalence of SPICT- and SQ-defined PC needs was 46.4% and 54.7% respectively. Pain was the most prevalent presenting symptom and bowel obstruction the most prevalent presenting diagnosis. SPICT-positivity was a significant predictor of death before discharge and death within 6 months of first admission. Proportional agreement in predicting for PC needs of greater than 70% was shown between the two tools.

CONCLUSION

Patients with PC needs comprise a significant proportion of SEC cancer admissions. This study shows the clear need for investment in staff and infrastructure to provide integrated palliative and end-of-life care as part of surgical services. The SPICT^TM and SQ were shown to predict for early death in this cohort. Further validation of PC needs assessment tools is needed to guide the cost-effective implementation of PC services in low resource settings.

'I Don't Have a Crystal Ball' - Why Do Doctors Tend to Avoid Prognostication?

Uncertainty, fear to harm the patient, discomfort handling the discussion and lack of time are the most cited barriers to prognostic disclosure. Physicians can be reassured that patients desire the truth about prognosis and can manage the discussion without harm, including the uncertainty of the information, if approached in a sensitive manner. Conversational guides could provide support in preparing such difficult conversations. Communicating 'with realism and hope' is possible, and anxiety is normal for both patients and clinicians during prognostic disclosure. As a clinician pointed out: 'I had asked a mentor once if it ever got easier. - No. But you get better at it.'

Challenges and facilitators in delivering optimal care at the End of Life for older patients: a scoping review on the clinicians' perspective

The concepts and elements determining quality of care at the End of Life may vary across professional groups but there is consensus that high-quality care at the End of Life is beneficial for the patient, families, health systems and society at large. This scoping review aimed to elucidate gaps in the delivery of this specific type of care in older people from the clinicians' perspective, and to identify potential solutions to both improve this care and promote work satisfaction by the involved clinicians. Twelve studies published since 2010 with data from 18 countries identified four major gaps: (1) Core clinical competencies; (2) Shared decision-making; (3) Health care system, environmental context, and resources; and (4) Organisational leadership, culture and legislation. Multiple suggestions for staff communications training, multidisciplinary mentoring, and advance care planning alignment with patient wishes were identified. However, a clear picture arose of consistently unmet needs that have been previously highlighted in research for more than a decade. This indicates poor uptake of previous recommendations and highlights the difficulties in changing the service culture to ensure provision of optimal services at the End of Life. Future investigations on the reasons for poor uptake and identification of effective approaches to execute the agreed recommendations are warranted.

End-Of-Life Care in the Time of COVID-19: Communication Matters More Than Ever

CONTEXT

The COVID-19 pandemic resulted in visitation restrictions across most health care settings, necessitating the use of remote communication to facilitate communication among families, patients and health care teams.

OBJECTIVE

To examine the impact of remote communication on families' evaluation of end-of-life care during the COVID-19 pandemic.

METHODS

Retrospective, cross-sectional, mixed methods study using data from an after-death survey administered from March 17-June 30, 2020. The primary outcome was the next of kin's global assessment of care during the Veteran's last month of life.

RESULTS

Data were obtained from the next-of-kin of 328 Veterans who died in an inpatient unit (i.e., acute care, intensive care, nursing home, hospice units) in one of 37 VA medical centers with the highest numbers of COVID-19 cases. The adjusted percentage of bereaved families reporting excellent overall end-of-life care was statistically significantly higher among those reporting Very Effective remote communication compared to those reporting that remote communication was Mostly, Somewhat, or Not at All Effective (69.5% vs. 35.7%). Similar differences were observed in evaluations of remote communication effectiveness with the health care team. Overall, 81.3% of family members who offered positive comments about communication with either the Veteran or the health care team reported excellent overall end-of-life care vs. 28.4% who made negative comments.

CONCLUSIONS

Effective remote communication with the patient and the health care team was associated with significantly better ratings of the overall experience of end-of-life care by bereaved family members. Our findings offer timely insights into the importance of remote communication strategies.

The Prognosis in Palliative care Study II (PiPS2): A prospective observational validation study of a prognostic tool with an embedded qualitative evaluation

Background

Prognosis in Palliative care Study (PiPS) models predict survival probabilities in advanced cancer. PiPS-A (clinical observations only) and PiPS-B (additionally requiring blood results) consist of 14- and 56-day models (PiPS-A14; PiPS-A56; PiPS-B14; PiPS-B56) to create survival risk categories: days, weeks, months. The primary aim was to compare PIPS-B risk categories against agreed multi-professional estimates of survival (AMPES) and to validate PiPS-A and PiPS-B. Secondary aims were to assess acceptability of PiPS to patients, caregivers and health professionals (HPs).

Methods and findings

A national, multi-centre, prospective, observational, cohort study with nested qualitative sub-study using interviews with patients, caregivers and HPs. Validation study participants were adults with incurable cancer; with or without capacity; recently referred to community, hospital and hospice palliative care services across England and Wales. Sub-study participants were patients, caregivers and HPs. 1833 participants were recruited. PiPS-B risk categories were as accurate as AMPES [PiPS-B accuracy (910/1484; 61%); AMPES (914/1484; 61%); p = 0.851]. PiPS-B14 discrimination (C-statistic 0.837) and PiPS-B56 (0.810) were excellent. PiPS-B14 predictions were too high in the 57–74% risk group (Calibration-in-the-large [CiL] -0.202; Calibration slope [CS] 0.840). PiPS-B56 was well-calibrated (CiL 0.152; CS 0.914). PiPS-A risk categories were less accurate than AMPES (p<0.001). PiPS-A14 (C-statistic 0.825; CiL -0.037; CS 0.981) and PiPS-A56 (C-statistic 0.776; CiL 0.109; CS 0.946) had excellent or reasonably good discrimination and calibration. Interviewed patients (n = 29) and caregivers (n = 20) wanted prognostic information and considered that PiPS may aid communication. HPs (n = 32) found PiPS user-friendly and considered risk categories potentially helpful for decision-making. The need for a blood test for PiPS-B was considered a limitation.

Conclusions

PiPS-B risk categories are as accurate as AMPES made by experienced doctors and nurses. PiPS-A categories are less accurate. Patients, carers and HPs regard PiPS as potentially helpful in clinical practice.

Study registration

ISRCTN13688211.

Oral dryness and moisture degree at the lingual but not buccal mucosa predict prognosis in end-of-life cancer patients

PURPOSE

The aim of this study is to investigate the association of oral dryness with overall survival and determine the threshold points of moisture degree for predicting 7-day survival in palliative care patients.

METHODS

A total of 147 consecutive palliative care patients were included between January 2017 and November 2018. Oral dryness at the lingual and buccal mucosa was measured using an oral moisture-checking device. Overall survival was compared between patients with and without oral dryness using Kaplan-Meier curves with a log-rank test. Prediction accuracy was evaluated by the receiver operating characteristic (ROC) curve and the area under the curve (AUC).

RESULTS

Median survival (95% confidence interval) in patients with oral dryness at the lingual mucosa was shorter than that in patients without oral dryness (17 [11-24] days vs. 28 [22-37] days, log-rank test, p <0.001), but not at the buccal mucosa. Time-dependent ROC revealed that the AUCs for 7-, 14-, 21-, and 28-day survival predictions were 0.72, 0.68, 0.61, and 0.59 with a cutoff value of 19.2%, respectively. The prevalence of performance status (PS) 4 and oxygen administration in the 7-day death group were higher than those in the non-7-day death group. A stratified analysis indicated that moisture degree <19.2% showed fair predictive performance with an AUC of 0.74 and 0.74, in the case of PS ≤3 or without oxygen administration.

CONCLUSION

Oral dryness was associated with increased risk of mortality in palliative care patients. Moisture degree <19.2% at the lingual mucosa predicted less than 7-day survival.

Changing patterns of mortality during the COVID-19 pandemic: Population-based modelling to understand palliative care implications

BACKGROUND

COVID-19 has directly and indirectly caused high mortality worldwide.

AIM

To explore patterns of mortality during the COVID-19 pandemic and implications for palliative care, service planning and research.

DESIGN

Descriptive analysis and population-based modelling of routine data.

PARTICIPANTS AND SETTING

All deaths registered in England and Wales between 7 March and 15 May 2020. We described the following mortality categories by age, gender and place of death: (1) baseline deaths (deaths that would typically occur in a given period); (2) COVID-19 deaths and (3) additional deaths not directly attributed to COVID-19. We estimated the proportion of people who died from COVID-19 who might have been in their last year of life in the absence of the pandemic using simple modelling with explicit assumptions.

RESULTS

During the first 10 weeks of the pandemic, there were 101,614 baseline deaths, 41,105 COVID-19 deaths and 14,520 additional deaths. Deaths in care homes increased by 220%, while home and hospital deaths increased by 77% and 90%, respectively. Hospice deaths fell by 20%. Additional deaths were among older people (86% aged ⩾ 75 years), and most occurred in care homes (56%) and at home (43%). We estimate that 22% (13%-31%) of COVID-19 deaths occurred among people who might have been in their last year of life in the absence of the pandemic.

CONCLUSION

The COVID-19 pandemic has led to a surge in palliative care needs. Health and social care systems must ensure availability of palliative care to support people with severe COVID-19, particularly in care homes.