Survival time tool to guide care planning in people with dementia

Haaksma, Miriam L.; Eriksdotter, Maria; Rizzuto, Debora; Leoutsakos, Jeannie Marie S.; Rikkert, Marcel G M Olde; Melis, René J. F.; García-Ptacek, Sara

doi:10.1212/wnl.0000000000008745

Cited by 47 publications

(59 citation statements)

References 36 publications

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“…This is not surprising as clinicians' difficulties to estimate survival time in people with dementia is well recognized in the literature. 34 Finally, the preferences of healthcare professionals in hospitals were found to be almost identical to those reported in a recent study in which the general public was questioned, 28 suggesting that clinicians' decisions will be easily understood and supported by laypersons. This might not only reduce the distress of hospital professionals when making difficult decisions, but also might encourage adopting a more transparent and accountable triaging process.…”

Section: Discussionmentioning

confidence: 52%

Examining hospital staff members' preferences for allocating a ventilator to a COVID-19 patient with and without Alzheimer's disease

Idilbi

AboJabel

2021

Geriatric Nursing

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Section: Discussionmentioning

confidence: 52%

Examining hospital staff members' preferences for allocating a ventilator to a COVID-19 patient with and without Alzheimer's disease

Idilbi

AboJabel

2021

Geriatric Nursing

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“…Common reasons included lack of information on discrimination and calibration, lack of internal validation, insufficient numbers of events, lack of accounting for missing data or using complete case analysis, and selecting final candidates based on the results of univariate p value testing (more details available in Supplementary Table 2). Of the 16 studies reporting model development, 2 had low risk of bias for ≥18 PROBAST signaling questions [17,18], 7 had low risk of bias for 15-17 signaling questions [9,10,12,[19][20][21], and 7 had low risk of bias for <15 signaling questions [11, 13-16, 22, 23]. The two highest quality studies were the Advanced Dementia Prognostic Tool (ADEPT) [17], derived to predict risk of death at 6 months among persons with advanced dementia in nursing homes, and a prognostic model for risk of death at 6 months among persons with dementia seen in outpatient primary care or dementia specialty clinics contributing data to a nationwide registry [18].…”

Section: Resultsmentioning

confidence: 99%

Mortality Risk Models for Persons with Dementia: A Systematic Review

Smith

Ismail

2021

JAD

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Background: Persons with dementia have higher mortality than the general population. Objective, standardized predictions of mortality risk in persons with dementia could help with planning resources for care close to the end of life. Objective: To systematically review prediction models for risk of death in persons with dementia. Methods: The Medline and PsycInfo databases were searched on November 29, 2020, for prediction models estimating the risk of death in persons with dementia. Study quality was assessed using the Prediction model Risk Of Bias ASsessment Tool. Results: The literature search identified 2,828 studies, of which 18 were included. These studies described 16 different prediction models with c statistics mostly ranging from 0.67 to 0.79. Five models were externally validated, of which four were applicable. There were two models that were both applicable and had reasonably low risk of bias. One model predicted risk of death at six months in persons with advanced dementia residing in a nursing home. The other predicted risk of death at three years in persons seen in primary care practice or a dementia specialty clinic, derived from a nationwide registry in Sweden but not externally validated. Conclusion: Valid, applicable models with low risk of bias were found in two settings: advanced dementia in a nursing home and outpatient practices. The outpatient model requires external validation. Better models are needed for persons with mild to moderate dementia in nursing homes, a common demographic. These models may be useful for educating persons living with dementia and care partners and directing resources for end of life care. Registration: The study protocol is registered on PROSPERO as RD4202018076.

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“…People with AD and severe asthma/COPD may not be able to use acetylcholinesterase inhibitors due to possible worsening of asthma/ COPD and therefore they would not have been captured in our study population. Asthma and COPD are part of Comorbidity Indices [ 37 , 38 ] used in several studies [ 16 , 17 ], but by reporting comorbidities in this way makes it impossible to see an association between individual comorbidities and mortality. We found a 4.9-month shorter median survival time of people with a history of asthma/COPD in the AD cohort and a 7-month shorter survival time in the non-AD cohort.…”

Section: Discussionmentioning

confidence: 99%

The effect of comorbidities on survival in persons with Alzheimer’s disease: a matched cohort study

2021

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Background Alzheimer’s disease (AD) is one of the leading causes of death world-wide, but little is known on the role of comorbidities on mortality among people with AD. We studied how comorbidities and age at AD diagnosis impact the survival of people with AD. Methods The Medication Use and Alzheimer’s disease (MEDALZ) cohort study included 70,718 community-dwelling persons in Finland with AD diagnosis from 2005 to 2011 and were matched 1:1 (age, gender, and hospital district) to people without AD (mean age 80 years, 65% women, and the mean follow-up 4.9 and 5.6 years, respectively). Covariates (age, gender, and socioeconomic position), comorbidities (cardiovascular disease, stroke, diabetes, asthma/ chronic obstructive pulmonary disease (COPD), hip fracture, cancer treatment, and mental or behavioral disorders excluding dementia) and survival data were obtained from nationwide registers. Cox proportional hazard models were used to compare risk of death between people with and without AD. Results During the follow-up period a greater proportion of the AD cohort died compared to the non-AD cohort (63% versus 37%). In both cohorts, older age, male gender, lower socioeconomic position, and history of comorbidities were associated with shorter survival and higher risk of death. The associations of comorbidities with survival is weaker in the older age groups and people with AD. Hip fracture (adjusted HR 1.35, 95% CI 1.30–1.41), stroke (1.30, 1.27–1.34), and recent cancer treatment (1.29, 1.26–1.32) had the strongest associations in the AD cohort. Age modified the associations in both cohorts (weaker associations among older people). Conclusion Alzheimer’s disease is the major factor affecting survival, but comorbidities further decrease survival also in individuals with Alzheimer’s disease. Therefore, appropriate management of care of these comorbidities might affect not only survival but also the wellbeing of this vulnerable population.

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Survival time tool to guide care planning in people with dementia

Cited by 47 publications

References 36 publications

Examining hospital staff members' preferences for allocating a ventilator to a COVID-19 patient with and without Alzheimer's disease

Examining hospital staff members' preferences for allocating a ventilator to a COVID-19 patient with and without Alzheimer's disease

Mortality Risk Models for Persons with Dementia: A Systematic Review

The effect of comorbidities on survival in persons with Alzheimer’s disease: a matched cohort study

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