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Symptom control at the end of life is important. This study investigated relationships between age, clinical characteristics and breathlessness sufficient to have people spend at least one half a day in that month in bed or cut down on their usual activities restricting breathlessness during the last year of life.
Monthly telephone interviews were conducted to determine the occurrence of restricting breathlessness. The primary outcome was the percentage of months with restricting breathlessness reported during the last year of life. Frequency increased in the months closer to death irrespective of cause.
Restricting breathlessness was associated with anxiety, 0. Percentage months of restricting breathlessness increased if chronic lung disease was noted at the most recent comprehensive assessment 6. Restricting breathlessness increased in this elderly population in the months preceding death from any cause. Breathlessness should be assessed and managed in the context of poor prognosis. Breathlessness is a frightening symptom which limits all aspects of life and is associated with poor clinical outcomes.
People with breathlessness are more likely to be sent to hospital Bottom cant receive sufficiently primary care, 9 admitted to hospital from the emergency department, 15 experience an in-hospital serious event 16 and have a poorer prognosis.
Despite associations between age and breathlessness, it is unknown whether breathlessness is primarily a feature of disease or of ageing. Using data from a cohort of community dwelling older people, we examined monthly patterns of reported difficulty breathing or shortness of breath sufficient to restrict activities defined as stay in bed at least half a day, or cut down on their usual activities during the Bottom cant receive sufficiently year of life herein as restricting breathlessness.
Based on the literature, we hypothesized that several factors would be Bottom cant receive sufficiently with restricting breathlessness during the last year of life, including the presence of co-morbid disease, cause of death, smoking status, age, sex, anxiety and depression. As this was a cohort of elderly people living at home at study enrolmentthis would include people who were medically fit but may have intercurrent illness, and those with chronic conditions causing breathlessness.
We anticipated that during the last year of life, there would also be people who developed a condition which led to their death. Given the heterogeneity often observed in older persons, we also hypothesized that distinct trajectories of restricting breathlessness during the last year of life could be identified no breathlessness; chronic [present at every month point]; intermittent; and crescendo breathlessness started partway through the year and was continuously present until death.
The study was approved by the human investigational committee at Yale University and participants provided verbal informed consent. This is a secondary analysis of data relating to the last year of life among decedents who had participated in a longitudinal cohort study of initially non-disabled, community-living persons 70 years of age or older when enrolled. Sequential screening and enrollment was conducted between March and October Data collection is ongoing.
Eligible plan members, Those who did not agree to participate were not significantly different in terms of age or sex. Members were excluded if they had: Of these, 50 9. Comprehensive home-based assessments were completed at baseline and at month intervals by trained nurses who used standard instruments to perform all interviews and assessments.
Data were collected on demographic characteristics and nine self-reported chronic conditions diagnosed by a physician hypertension; myocardial infarction; congestive heart failure; stroke; diabetes; arthritis; hip Bottom cant receive sufficiently, chronic lung disease, cancercognition Folstein Mini-Mental State Examination and frailty.
Telephone interviews were conducted monthly. For participants with significant cognitive impairment, data were collected from a proxy. Proxy assessments are valid for many measures, including breathlessness.
Data for this current secondary analysis were collected until June Decedents were identified through local obituary reviews, from the next of kin or another suitable informant during a subsequent telephone interview, or both.
The classification of conditions leading to death is described elsewhere. Frailty, as a condition leading to death, was defined by the phenotype described by Fried et al 32 using data from the comprehensive assessments.
This analysis relates to difficulty breathing that caused restriction in activity during the previous Bottom cant receive sufficiently.
During the monthly interviews, participants were asked if they had stayed in bed at least half a day or cut down on their usual activities due to an illness, injury, or other problem in the preceding month.
Using date of death as the anchor, descriptive statistics presented the number and percentage of participants reporting breathlessness at each month before death.
We calculated the total number of months participants reported restricting breathlessness Bottom cant receive sufficiently the last year of life and evaluated its relationship with the condition leading to death, plotting this relationship as a percentage of the total possible number of months.
If participants died during the first year of follow-up, the denominator was the number of months with available data. We investigated the relationships between percentage months of restricting breathlessness and possible associated variables recorded before the final year the most recent comprehensive assessment prior to the last year of lifeusing two sample t tests or linear regression.
From the monthly follow-up data during the last year of life we calculated the percentage of months for which possible associated variables, and proxy measures were recorded and tested their associations with months of restricting breathlessness using multiple regression. Candidate variables were drawn from the literature and can be seen in table 2. We used multiple regression to investigate demographic and associated clinical factors, which had an effect identified in the unifactorial analysis and Bottom cant receive sufficiently with a plausible biological rationale or have been previously reported in the literature.
At each stage, the variable with the largest non-significant P value was removed and the step repeated until there were no non-significant associated factors.
To assess the effect of using a mixture of participant and proxy measures, the stepwise regression model included the proportion of proxy measures as an associated factor. The appropriateness of the regression model was tested by examining residuals.