A simple score to predict survival with dementia in the general population

Development and validation of a clinical prediction tool to estimate survival in community-dwelling adults living with dementia: a protocol

INTRODUCTION

A clinical prediction tool to estimate life expectancy in community-dwelling individuals living with dementia could inform healthcare decision-making and prompt future planning. An existing Ontario-based tool for community-dwelling elderly individuals does not perform well in people living with dementia specifically. This study seeks to develop and validate a clinical prediction tool to estimate survival in community-dwelling individuals living with dementia receiving home care in Ontario, Canada.

METHODS AND ANALYSIS

This will be a population-level retrospective cohort study that will use data in linked healthcare administrative databases at ICES. Specifically, data that are routinely collected from regularly administered assessments for home care will be used. Community-dwelling individuals living with dementia receiving home care at any point between April 2010 and March 2020 will be included (N≈200 000). The model will be developed in the derivation cohort (N≈140 000), which includes individuals with a randomly selected home care assessment between 2010 and 2017. The outcome variable will be survival time from index assessment. The selection of predictor variables will be fully prespecified and literature/expert-informed. The model will be estimated using a Cox proportional hazards model. The model's performance will be assessed in a temporally distinct validation cohort (N≈60 000), which includes individuals with an assessment between 2018 and 2020. Overall performance will be assessed using Nagelkerke's R2, discrimination using the concordance statistic and calibration using the calibration curve. Overfitting will be assessed visually and statistically. Model performance will be assessed in the validation cohort and in prespecified subgroups.

ETHICS AND DISSEMINATION

The study received research ethics board approval from the Sunnybrook Health Sciences Centre (SUN-6138). Abstracts of the project will be submitted to academic conferences, and a manuscript thereof will be submitted to a peer-reviewed journal for publication. The model will be disseminated on a publicly accessible website (www.projectbiglife.com).

TRIAL REGISTRATION NUMBER

NCT06266325 (clinicaltrials.gov).

Association between glycemic status and all-cause mortality among individuals with dementia: a nationwide cohort study

BACKGROUND

To examine the association between glycemic status and all-cause mortality risk among individuals with dementia.

METHODS

We enrolled 146,832 individuals aged 40 and older with dementia as identified through the Korean National Health Insurance Service health screening test between 2008 and 2016. Mortality status was evaluated at the end of 2019. Participants were classified into normoglycemia, prediabetes, or diabetes mellitus (DM) categories. The duration of diabetes was noted in those with DM. This study focused on the association between glycemic status and all-cause mortality.

RESULTS

The cohort, which was predominantly elderly (average age 75.1 years; 35.5% male), had a 35.2% mortality rate over an average 3.7-year follow-up. DM was linked with increased all-cause mortality risk (hazard ratio [HR] 1.34; 95% confidence interval [CI]: 1.32-1.37) compared to non-DM counterparts. The highest mortality risk was observed in long-term DM patients (≥ 5 years) (HR 1.43; 95% CI: 1.40-1.47), followed by newly diagnosed DM (HR 1.35; 95% CI: 1.30-1.40), shorter-term DM (< 5 years) (HR 1.17; 95% CI: 1.13-1.21), and prediabetes (HR 1.03; 95% CI: 1.01-1.05). These patterns persisted across Alzheimer's disease and vascular dementia, with more pronounced effects observed in younger patients.

CONCLUSIONS

Glucose dysregulation in dementia significantly increased mortality risk, particularly in newly diagnosed or long-standing DM. These findings suggest the potential benefits of maintaining normal glycemic levels in improving the survival of patients with dementia.

Developing a predictive model for mortality in patients with cognitive impairment

OBJECTIVES

We developed a predictive model for all-cause mortality and examined the risk factors for cause-specific mortality among people with cognitive impairment in a Japanese memory clinic-based cohort (2010-2018).

METHODS

This retrospective cohort study included people aged ≥65 years with mild cognitive impairment or dementia. The survival status was assessed based on the response of participants or their close relatives via a postal survey. Potential predictors including demographic and lifestyle-related factors, functional status, and behavioral and psychological status were assessed at the first visit at the memory clinic. A backward stepwise Cox regression model was used to select predictors, and a predictive model was developed using a regression coefficient-based scoring approach. The discrimination and calibration were assessed via Harrell's C-statistic and a calibration plot, respectively.

RESULTS

A total of 2610 patients aged ≥65 years (men, 38.3%) were analyzed. Over a mean follow-up of 4.1 years, 544 patients (20.8%) died. Nine predictors were selected from the sociodemographic and clinical variables: age, sex, body mass index, gait performance, physical activity, and ability for instrumental activities of daily living, cognitive function, and self-reported comorbidities (pulmonary disease and diabetes). The model showed good discrimination and calibration for 1-5-year mortality (Harrell's C-statistic, 0.739-0.779). Some predictors were specifically associated with cause-specific mortality.

CONCLUSIONS

This predictive model has good discriminative ability for 1- to 5-year mortality and can be easily implemented for people with mild cognitive impairment and all stages of dementia referred to a memory clinic.

Accuracy of two prognostic indexes to predict mortality in older adults with advanced dementia

Dementia is a cause of disability among older adults. Accessing advanced dementia prognosis is a challenge.

Mortality Risk Models for Persons with Dementia: A Systematic Review

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.

Five-year risk of admission to long-term care home and death for older adults given a new diagnosis of dementia: a population-based retrospective cohort study

BACKGROUND

After diagnosis of a health condition, information about survival and potential transition from community into institutional care can be helpful for patients and care providers. We sought to describe the association between a new diagnosis of dementia and risk of admission to a long-term care home and death at 5 years.

METHODS

We conducted a population-based retrospective cohort study using linked health administrative databases. We identified individuals aged 65 years or older, living in the community, with a first documented diagnosis of dementia between Jan. 1, 2010, and Dec. 31, 2012, in Ontario, Canada. Dementia diagnosis was captured using diagnostic codes from hospital discharges, physician billings, assessments conducted for home care and long-term care, and dispensed prescriptions for cholinesterase inhibitors. Our primary outcome measures were 5-year risk of death and placement in a long-term care home, adjusted for sociodemographic and clinical factors.

RESULTS

We identified 108 757 individuals in our study cohort. By the end of 5 years, 24.4% remained alive in the community and 20.5% were living in a long-term care home. Of the 55.1% who died, about half (27.9%) were admitted to a long-term care home before death. Three risk factors were associated with increased odds of death: older age (age ≥ 90 yr; odds ratio [OR] 9.5, 95% confidence interval [CI] 8.8-10.2 [reference: age 65-69 yr]), male sex (OR 1.7, 95% CI 1.6-1.7), and the presence of organ failure, including chronic obstructive pulmonary disease (OR 1.7, 95% CI 1.7-1.8), congestive heart failure (OR 2.0, 95% CI 1.9-2.0) and renal failure (OR 1.7, 95% CI 1.6-1.8). Groups formed by combinations of these 3 factors had an observed 5-year risk of death varying between 22% and 91%.

INTERPRETATION

Among community-dwelling older adults with newly identified dementia in Ontario, the majority died or were admitted to a long-term care home within 5 years. This information may be helpful for discussions on prognosis and need for admission to long-term care.

A prediction model for one- and three-year mortality in dementia: results from a nationwide hospital-based cohort of 50,993 patients in the Netherlands

Objective

to develop a model to predict one- and three-year mortality in patients with dementia attending a hospital, through hospital admission or day/memory clinic.

Design

we constructed a cohort of dementia patients through data linkage of three Dutch national registers: the hospital discharge register (HDR), the population register and the national cause of death register.

Subjects

patients with dementia in the HDR aged between 60 and 100 years registered between 1 January 2000 and 31 December 2010.

Methods

logistic regression analysis techniques were used to predict one- and three-year mortality after a first hospitalisation with dementia. The performance was assessed using the c-statistic and the Hosmer–Lemeshow test. Internal validation was performed using bootstrap resampling.

Results

50,993 patients were included in the cohort. Two models were constructed, which included age, sex, setting of care (hospitalised versus day clinic) and the presence of comorbidity using the Charlson comorbidity index. One model predicted one-year mortality and the other three-year mortality. Model discrimination according to the c-statistic for the models was 0.71 (95% CI 0.71–0.72) and 0.72 (95% CI 0.72–0.73), respectively.

Conclusion

both models display acceptable ability to predict mortality. An important advantage is that they are easy to apply in daily practise and thus are helpful for individual decision-making regarding diagnostic/therapeutic interventions and advance care planning.

Increased mortality and hospital readmission risk in patients with dementia and a history of cardiovascular disease: Results from a nationwide registry linkage study

OBJECTIVE

To evaluate the impact of cardiovascular disease (CVD) on mortality and readmission risk in patients with dementia.

METHODS

Prospective hospital-based cohort of 59 194 patients with dementia admitted to hospital or visiting a day-clinic between 2000 and 2010. Patients were divided in those with and without a history of CVD (ie, previous admission for CVD; coronary heart disease, heart failure, stroke, atrial fibrillation, or other CVD). Absolute mortality risks (ARs), median survival times, and hazard ratios (adjusted for age, sex, and comorbidity) were calculated.

RESULTS

Three-year ARs and HRs were higher, and survival times were shorter among patients visiting a day-clinic with a history of CVD than in those without. The differences were less pronounced for inpatients. Readmission risk was further increased in the presence of CVD in both day clinic and inpatients.

CONCLUSION

Clinicians need to be more aware of worse prognosis of the population with CVD and dementia.

Benefits of Occupational Therapy in Dementia Patients: Findings from a Real-World Observational Study

BACKGROUND

There is a growing interest in developing non-pharmacological approaches in dementia. Clinical efficacy of occupational therapy (OT) under routine care conditions has not been investigated yet.

OBJECTIVE

To analyze the short-term effects of OT in patients with dementia; and to identify factors related to greater benefit.

METHODS

Patients referred to OT were evaluated before starting a 3-month intervention and at 3 and 6 months later. Measures included: Mini-Mental State Examination (MMSE), Disability Assessment in Dementia (DAD), Neuropsychiatric Inventory (NPI) Questionnaire, patients' quality of life (EQ 5D-VAS), caregivers' burden (Zarit scale), and amount of informal care. Linear mixed models were used to analyze trajectories of outcomes. Logistic regressions with stepwise descending selection were used to study factors associated with benefits.

RESULTS

421 dementia patients benefited from OT (mean MMSE = 17.3). Patients remained cognitively stable over time. Functional performances also remained stable at 3 months and significantly decreased at 6 months (crude reduction of 2.8 points, p < 0.01). Behavioral troubles were significantly reduced over the intervention period and remained stable after (p < 0.01). Patients' quality of life increased over the 3-month intervention (p = 0.16) and significantly decreased thereafter. Caregivers' burden and informal care significantly decreased over the 3-month intervention and remained stable thereafter. Patients who benefited from OT with regard to function were less educated and had higher cognitive level.

CONCLUSION

OT may be an effective intervention to maintain cognition and functionality and to reduce psychiatric symptoms in dementia patients. Mild stages of dementia could gain more benefits from OT with regard to functional decline.

Effect of Vascular Risk Factors and Diseases on Mortality in Individuals with Dementia: A Systematic Review and Meta-Analysis

OBJECTIVES

To assess the effect of cardiovascular diseases and risk factors on mortality in individuals with dementia.

DESIGN

Systematic review and meta-analysis. English- and Dutch-language studies in PubMed, EMBASE, and PsycINFO databases were searched in April 2014 with hand-searching of in-text citations and no publication limitations. Inclusion criteria were original studies reporting on cardiovascular risk factors or diseases and their relationship with survival in individuals with dementia. The Quality In Prognosis Studies tool was used to appraise all included articles.

SETTING

Population-, hospital-, and nursing home-based.

PARTICIPANTS

Community-dwelling, hospitalized individuals and nursing home residents with dementia.

MEASUREMENTS

A random-effects meta-analysis was performed to investigate the effect of several cardiovascular diseases and risk factors on overall mortality.

RESULTS

Twelve studies with 235,865 participants were included. In pooled analyses, male sex (hazard ratio (HR)=1.67, 95% confidence interval (CI)=1.56-1.78), diabetes mellitus (DM) (HR=1.49, 95% CI=1.33-1.68), smoking (ever vs never) (HR=1.37, 95% CI=1.17-1.61), coronary heart disease (CHD) (HR=1.21, 95% CI=1.02-1.44) and congestive heart failure (CHF) (HR=1.37, 95% CI=1.18-1.59) were associated with mortality. Stroke, high blood pressure, being overweight, and hypercholesterolemia were not statistically significantly related to mortality.

CONCLUSION

Individuals with dementia and DM, smoking, CHD, and CHF have a greater risk of death than individuals with dementia without these risk factors or diseases.

Mortality in incident dementia - results from the German Study on Aging, Cognition, and Dementia in Primary Care Patients

OBJECTIVE

Dementia is known to increase mortality, but the relative loss of life years and contributing factors are not well established. Thus, we aimed to investigate mortality in incident dementia from disease onset.

METHOD

Data were derived from the prospective longitudinal German AgeCoDe study. We used proportional hazards models to assess the impact of sociodemographic and health characteristics on mortality after dementia onset, Kaplan-Meier method for median survival times.

RESULTS

Of 3214 subjects at risk, 523 (16.3%) developed incident dementia during a 9-year follow-up period. Median survival time after onset was 3.2 years (95% CI = 2.8-3.7) at a mean age of 85.0 (SD = 4.0) years (≥2.6 life years lost compared with the general German population). Survival was shorter in older age, males other dementias than Alzheimer's, and in the absence of subjective memory complaints (SMC).

CONCLUSION

Our findings emphasize that dementia substantially shortens life expectancy. Future studies should further investigate the potential impact of SMC on mortality in dementia.

Latent classes of course in Alzheimer's disease and predictors: the Cache County Dementia Progression Study

OBJECTIVE

Several longitudinal studies of Alzheimer's disease (AD) report heterogeneity in progression. We sought to identify groups (classes) of progression trajectories in the population-based Cache County Dementia Progression Study (N = 328) and to identify baseline predictors of membership for each group.

METHODS

We used parallel-process growth mixture models to identify latent classes of trajectories on the basis of Mini-Mental State Exam (MMSE) and Clinical Dementia Rating sum of boxes scores over time. We then used bias-corrected multinomial logistic regression to model baseline predictors of latent class membership. We constructed receiver operating characteristic curves to demonstrate relative predictive utility of successive sets of predictors.

RESULTS

We fit four latent classes; class 1 was the largest (72%) and had the slowest progression. Classes 2 (8%), 3 (11%), and 4 (8%) had more rapid worsening. In univariate analyses, longer dementia duration, presence of psychosis, and worse baseline MMSE and Clinical Dementia Rating sum of boxes were associated with membership in class 2, relative to class 1. Lower education was associated with membership in class 3. In the multivariate model, only MMSE remained a statistically significant predictor of class membership. Receiver operating characteristic areas under the curve were 0.98, 0.88, and 0.67, for classes 2, 3, and 4 relative to class 1.

CONCLUSIONS

Heterogeneity in AD course can be usefully characterized using growth mixture models. The majority belonged to a class characterized by slower decline than is typically reported in clinical samples. Class membership could be predicted using baseline covariates. Further study may advance our prediction of AD course at the population level and in turn shed light on the pathophysiology of progression.