Palliative Medicine 2007; 21: 95 99
Dying trajectories in heart failure Merryn Gott and Sarah Barnes Sheffield Institute for Studies on Ageing, University of Sheffield, Sheffield, Chris Parker Nottingham Primary Care Research Partnership, Sheila Payne Lancaster University, David Seamark Peninsula Medical School, University of Exeter, Salah Gariballa Faculty of Medicine, UAE University, Neil Small School of Health Studies, University of Bradford Objectives: To explore dying trajectories in heart failure. Design: Prospective, longitudinal study. Setting: Sixteen GP surgeries in four demographically contrasting areas of the UK. Participants: A total of 27 heart failure patients, /60 years of age, who completed questionnaires for at least five time-points before death. Main outcome measures: Kansas City Cardiomyopathy Questionnaire Physical Limitation Scale. Results: No ‘typical’ dying trajectory could be identified, and only a minority of patients conformed to the theoretical trajectory of dying in heart failure. Conclusions: This study provides the first prospective data regarding physical decline prior to death in heart failure. Findings challenge current efforts to plan and deliver palliative care services on the basis of the theoretical heart failure dying trajectory. Palliative Medicine 2007; 21: 95 99 Key words: dying trajectories; heart failure; older people; primary care
What is already known on this subject Dying trajectories are important for planning palliative care services, and a theoretical model of physical decline prior to death in heart failure has been proposed. However, no prospective data regarding actual dying trajectories in heart failure are available.
What this study adds No typical dying trajectory in heart failure was identified, and only a minority of patients conform to the theoretical trajectory underpinning current service developments.
Background It has been argued that four distinct trajectories ‘each differing in length and slope of functional decline appear to account for most persons’ last phase of life.1 These are described as follows: (1) sudden death with little prior warning and minimal interaction with health services before death; (2) death following a distinct terminal phase of illness occurring after a long period of high functioning and rapid decline, most characteristic of cancer patients; (3) death from organ failure (including COPD and heart failure), where a gradual decline in functional status occurs interspersed with acute periods Address for correspondence: Sarah Barnes, Sheffield Institute for Studies on Ageing, University of Sheffield, Elmfield, Northumberland Road, Sheffield, S10 2TU, UK. E-mail:
[email protected] # 2007 SAGE Publications
of deterioration which could cause death; and (4) death following progressive deterioration accompanying frailty, stroke or dementia. The appeal of constructing theoretical models of dying in this manner is that they can provide a framework for service planning and delivery. Indeed, when Glaser and Strauss introduced the idea of dying trajectories,2 they were referring not only to ‘the physiological unfolding of a patient’s disease but to the total organisation of work done over the course of illness that impact on those involved with that work and its organization’.3 More recently, Lynn and Adamson argued that each trajectory corresponds to a different ‘set of priorities in care’.4 The delivery of specialist palliative care in the UK and hospice care in the US are predicated on the cancer trajectory, whereby intervention is confined predominantly to the ‘terminal phase’. Specialist palliative care, therefore, faces a challenge in adapting the provision of care to patients dying from other conditions. Recently, particular attention has been paid to dying trajectories in heart failure, a condition where specialist palliative care intervention is proposed,5 but few data are available to plan appropriate service models for end of life care. Whilst a small number of studies have been published which empirically describe dying trajectories in heart failure, these have mainly relied on retrospective data.6 9 For example, Teno et al . asked relatives to provide posthumous data regarding physical functioning in the year prior to death amongst 3614 US patients dying from all causes.9 These data were aggregated at a group level to provide trajectories for the most common causes of death, which were heart failure, cancer, CVA, COPD and diabetes. The authors concluded that ‘our findings support previous research that supports the notion of 10.1177/0269216307076348
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dying trajectories and that function declines in the last year of life’.9 The only study where prospective self or proxy-reported data are available for a large sample regarding physical functioning prior to death also aggregated the trajectories according to cause of death.10 The authors concluded that the empirical trajectories they provided were ‘very similar to the previous theoretical model’.10 A similar conclusion was reached in a qualitative study comparing end of life experiences in heart failure (n /20) and lung cancer (n /20).11 However, further data are required. Lynn et al .,4 for example, argue that longitudinal, prospective data gathered at least quarterly are needed regarding physical functioning prior to death for all conditions, including heart failure. Nevertheless, they acknowledge that research of this nature has not been conducted on a large scale due to the costs involved. The current paper provides the only available prospective data regarding the actual trajectories of physical function experienced by people with heart failure prior to death.
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Methods The sample consisted of decedents from a longitudinal study examining the palliative care needs of 542 community-based heart failure patients, aged /60 years, recruited from GP surgeries in four diverse areas of the UK (more information about the methods used in this study can be found in another publication).12 Study participants completed health-related quality of life questionnaires (Kansas City Cardiomyopathy Questionnaire; KCCQ13 and SF-3614) and self-reported New York Heart Association (NYHA)15 classifications by post, every three months for two years. The KCCQ Physical Limitation Scale was used to measure function at each time point. It consists of six items (Appendix 1), and is transformed to a score of 0100, in which higher scores indicate better health. Trajectories on the KCCQ Physical Limitation Scale were compared with trajectories on the SF-36 Physical Functioning Scale. Trajectories for people with five or more time points (minimum period of one year three months) were examined in further detail to establish if they could be grouped into categories.
Results Some 89 deaths were recorded within the time period of the study (September 2003 to June 2006). Of these, 27 decedents had completed questionnaires for at least five time-points before death. Figure 5 shows the trajectories of KCCQ physical limitation scores for the 27 decedents superimposed from the last score received
Figure 1 Trajectories showing KCCQ physical limitation scores of 27 patients for 24 months prior to death
before death ( 3 months). It can be seen that no clear pattern of trajectories emerged (Figure 1). A comparison of the trajectories from the KCCQ Physical Limitation Scale and the SF-36 Physical Functioning Scale was made. They were similar in peaks and gradients (although SF-36 Physical Functioning Scale was generally scoring lower than KCCQ Physical Limitation Scale because it takes into account co-morbid conditions). Detailed examples of trajectories An exploration of the trajectories identified that the following ‘types’ were present: (1) theoretical frailty trajectory (n /2); (2) theoretical heart failure trajectory (n /6); (3) theoretical cancer trajectory (n /4); (4) improvement prior to death (n /5); (5) fluctuating, but not a downward trend (n /10) (see Figures 2 6 for examples of cases from each of the trajectories). However, within each type there was a lot of variation and individual trajectories may be difficult to categorise. NYHA classifications were self-reported every three months within the time period of the study. Table 1 shows baseline NYHA and the last NYHA recorded prior to death (3 months). Of the 18 patients who selfreported NYHA II at baseline, eight remained at NYHA II in their last recording prior to death, eight had deteriorated to NYHA III, and two had deteriorated to NYHA IV. Of the nine patients who selfreported NYHA III at baseline, eight remained at
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Figure 2 Theoretical frailty trajectory (n /2). Male, aged 92, cause of death myocardial infarction, 0 or one co-morbidity, last recorded NYHA prior to death /3
Figure 4 Theoretical cancer trajectory (n /4). Male, aged 79, cause of death heart failure, 0 or one co-morbidity, last recorded NYHA prior to death /4
NYHA III in their last recording prior to death, and one had deteriorated to NYHA IV. Table 1 also shows the types of trajectory by baseline NYHA, and there was no evidence of any systematic difference in trajectory type according to NYHA category.
Discussion Whilst these data are derived from a relatively small sample of patients, to the best of our knowledge they represent the only prospective trajectory data regarding
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Figure 3 Theoretical heart failure trajectory (n /6). Male, aged 77, cause of death ischemic heart disease, two or more co-morbidities, last recorded NYHA prior to death /3
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Figure 5 Improvement before death (n /5). Female, aged 95, cause of death heart failure, two or more co-morbidities, last recorded NYHA prior to death /2
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M Gott et al. Table 1 Comparison of baseline and final NYHA classifications with trajectory types
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Figure 6 Fluctuating, but not a downward trend (n /10). Male, aged 79, cause of death heart failure, 0 or one comorbidity, last recorded NYHA prior to death /3
physical function prior to death in heart failure. We did not observe a ‘typical’ heart failure trajectory, and the theoretical trajectory model proposed only represents the experiences of a small minority of patients. The main study limitation was that the sample size was relatively small and biased in favour of those who were able to complete a questionnaire within the three months prior to death. Given that our findings challenge the theoretical heart failure dying trajectory upon which current service developments are being planned, there is an urgent need for more research to map dying trajectories within larger patient samples, and gather proxy data when patients are too ill to participate themselves. No prospective studies mapping dying trajectories in heart failure could be identified, and it is unsurprising that our findings differ from those of previous studies which have analysed data at a group level,10 rather than considered individual trajectories. There is a need to reconsider current efforts to plan and deliver services in heart failure on the basis of the theorised trajectory until further evidence is available.1 There is a real danger that resources will be inappropriately allocated and services developed which only meet the needs of a minority of patients. Developing palliative care services in heart failure must remain a priority,16 but further research is needed to underpin service development. 1
Dr Keri Thomas, personal communication.
Acknowledgements We would like to thank all participating GP practices and patients. The study was funded by the Department of Health. The study received ethical approval from the Cardiff MREC.
References 1 Lunney JR, Lynn J, Hogan C. Profiles of older Medicare decedents. J Am Geriatr Soc 2002; 50(6): 1008 12. 2 Glaser BG, Strauss AL. Time for dying . Aldine, 1968. 3 Strauss AL, Fagerhaugh S, Suczek B, Weiner C. Sentimental work in the technologized hospital. Soc Health Illn 1981; 4: 254 78. 4 Lynn J, Adamson DM. Living well at the end of life. Adapting health care to serious chronic illness in old age. Rand Health, 2003. 5 Department of Health. National service framework: older people. HMSO, 2001. 6 Morris JN, Suissa S, Sherwood S, Wright SM, Greer D. Last days: a study of quality of life of terminally ill cancer patients. J Chronic Dis 1986; 39: 47 62. 7 Lawton M, Moss M, Glicksman A. The quality of the last year of life of older persons. Milbank Q 1990; 68: 1 28. 8 Brock DB, Foley DJ. Demography and epidemiology of dying in the US with emphasis on death of older persons. Hosp J 1998; 13(49): 49 60. 9 Teno JM, Weitzen S, Fennell ML, Mor V. Dying trajectory in the last year of life: does cancer trajectory fit other diseases? J Palliat Med 2001; 4(4): 457 64. 10 Lunney JR, Lynn J, Foley DJ, Lipson S, Guralnik JM. Patterns of functional decline at the end of life. J Am Med Assoc 2003; 289(18): 2387 92. 11 Murray SA, Boyd K, Kendall M, Worth A, Benton TF, Clausen H. Dying of lung cancer or cardiac failure: prospective qualitative interview study of patients and their carers in the community. Br Med J 2002; 325: 929 32. 12 Barnes S, Gott M, Payne SA, Parker C, Seamark DA, Gariballa SE, Small NA. Recruiting older people into a
Dying trajectories in heart failure large community-based study of heart failure. Chronic Illn 2005; 1: 321 29. 13 Green CP, Porter CB, Bresnahan DR, Spertus JA. Development and evaluation of the Kansas City cardiomyopathy questionnaire: a new health status measure for heart failure. J Am Coll Cardiol 2000; 35(5): 1245 55. 14 Ware JE. SF-36 health survey: manual and interpretation guide. The Health Institute, New England Medical Center, 1993.
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