The Relation of Patient Dependence to Home Health Aide Use in Alzheimer's Disease

BACKGROUND: Although there has been much research devoted to understanding the predictors of nursing home placement (NHP) in Alzheimer's disease (AD) patients, there is currently a lack of research concerning the predictors of home health care. The objective of this study was to examine whether the Dependence Scale can predict home health aide (HHA) use. METHODS: The sample is drawn from the Predictors Study, a large, multicenter cohort of patients with probable AD, prospectively followed annually for up to 7 years in three university-based AD centers in the United States. Markov analyses (n=75) were used to calculate annual transition probabilities for the "new onset" of HHA use (instances where an HHA was absent at the previous visit, but present at the next visit) as a function of HHA presence at the preceding year's visit and dependence level at that preceding year's visit. RESULTS: The dependence level at the previous year's visit was a significant predictor of HHA use at the next year's visit. Three specific items of the Dependence Scale (needing household chores done for oneself, needing to be watched or kept company when awake, and needing to be escorted when outside) were significant predictors of the presence of an HHA. CONCLUSION: The Dependence Scale is a valuable tool for predicting HHA use in AD patients. Obtaining a better understanding of home health care in AD patients may help delay NHP and have a positive impact on the health and well-being of both the caregiver and the patient

Participation in Clinical Trials and Long-Term Outcomes in Alzheimer's Disease

The objective of this study was to determine whether participation in clinical trials affects long-term outcomes in Alzheimer's disease (AD). Participation in clinical trials for persons with dementia is often justified on the grounds that patients benefit from the medical oversight typical of trials, even when experimental agents do not demonstrate short-term benefits. This claim has not been rigorously assessed. Of 215 community-resident subjects enrolled in a prospective study of outcomes in AD, 101 participated in randomized clinical trials (RCTs) during the first 2 years of follow-up. These subjects were compared with subjects who met eligibility requirements for RCTs but did not participate (N = 57) and with subjects who were ineligible (N = 57), over a total of 3.5 years of follow-up. Survival analyses assessed risk of death, nursing home placement, and incident functional deficit end points, adjusting for baseline differences. Subjects who participated in RCTs were younger and more highly educated. Mortality, risk of hospitalization, number of medical examinations conducted by study physicians, and onset of severe functional deficit did not differ between the groups, but risk of nursing home admission was significantly lower among RCT participants compared with eligible nonparticipants and ineligible subjects (16.8% versus 36.8% and 31.6%, respectively [p = 0.01]). The difference in risk of nursing home placement may represent a long-term, drug-related benefit to patients, a selection effect (caregivers of patients who participate in RCTs differ from caregivers of patients who do not), or a positive effect on caregivers (greater contact with a medical service may be associated with better care-giving outcomes). Further research is required to assess these effects

Change in Body Mass Index before and after Alzheimer's Disease Onset

OBJECTIVES: A high body mass index (BMI) in middle-age or a decrease in BMI at late-age has been considered a predictor for the development of Alzheimer's disease (AD). However, little is known about the BMI change close to or after AD onset. METHODS: BMI of participants from three cohorts, the Washington Heights and Inwood Columbia Aging Project (WHICAP; population-based) and the Predictors Study (clinic-based), and National Alzheimer's Coordinating Center (NACC; clinic-based) were analyzed longitudinally. We used generalized estimating equations to test whether there were significant changes of BMI over time, adjusting for age, sex, education, race, and research center. Stratification analyses were run to determine whether BMI changes depended on baseline BMI status. RESULTS: BMI declined over time up to AD clinical onset, with an annual decrease of 0.21 (p=0.02) in WHICAP and 0.18 (p=0.04) kg/m2 in NACC. After clinical onset of AD, there was no significant decrease of BMI. BMI even increased (b=0.11, p=0.004) among prevalent AD participants in NACC. During the prodromal period, BMI decreased over time in overweight (BMI>/=25 and /=30) NACC participants. After AD onset, BMI tended to increase in underweight/normal weight (BMI<25) patients and decrease in obese patients in all three cohorts, although the results were significant in NACC study only. CONCLUSIONS: Our study suggests that while BMI declines before the clinical AD onset, it levels off after clinical AD onset, and might even increase in prevalent AD. The pattern of BMI change may also depend on the initial BMI

Clinical Characteristics and Longitudinal Changes of Informal Cost of Alzheimer's Disease in the Community

Most estimates of the cost of informal caregiving in patients with Alzheimer's disease (AD) remain cross-sectional. Longitudinal estimates of informal caregiving hours and costs are less frequent and are from assessments covering only short periods of time. The objectives of this study were to estimate long-term trajectories of the use and cost of informal caregiving for patients with AD and the effects of patient characteristics on the use and cost of informal caregiving. The sample is drawn from the Predictors Study, a large, multicenter cohort of patients with probable AD, prospectively followed annually for up to 7 years in three university-based AD centers in the United States (n=170). Generalized linear mixed models were used to estimate the effects of patient characteristics on use and cost of informal caregiving. Patients' clinical characteristics included cognitive status (Mini-Mental State Examination), functional capacity (Blessed Dementia Rating Scale (BDRS)), comorbidities, psychotic symptoms, behavioral problems, depressive symptoms, and extrapyramidal signs. Results show that rates of informal care use and caregiving hours (and costs) increased substantially over time but were related differently to patients' characteristics. Use of informal care was significantly associated with worse cognition, worse function, and higher comorbidities. Conditional on receiving informal care, informal caregiving hours (and costs) were mainly associated with worse function. Each additional point on the BDRS increased informal caregiving costs 5.4%. Average annual informal cost was estimated at $25,381 per patient, increasing from$20,589 at baseline to $43,030 in Year 4

Longitudinal Study of Effects of Patient Characteristics on Direct Costs in Alzheimer Disease

OBJECTIVES: To estimate long-term trajectories of direct cost of caring for patients with Alzheimer disease (AD) and examine the effects of patients' characteristics on cost longitudinally. METHODS: The sample is drawn from the Predictors Study, a large, multicenter cohort of patients with probable AD, prospectively followed up annually for up to 7 years in three university-based AD centers in the United States. Random effects models estimated the effects of patients' clinical and sociodemographic characteristics on direct cost of care. Direct cost included cost associated with medical and nonmedical care. Clinical characteristics included cognitive status (measured by Mini-Mental State Examination), functional capacity (measured by Blessed Dementia Rating Scale [BDRS]), psychotic symptoms, behavioral problems, depressive symptoms, extrapyramidal signs, and comorbidities. The model also controlled for patients' sex, age, and living arrangements. RESULTS: Total direct cost increased from approximately 9,239 dollars per patient per year at baseline, when all patients were at the early stages of the disease, to 19,925 dollars by year 4. After controlling for other variables, a one-point increase in the BDRS score increased total direct cost by 7.7%. One more comorbid condition increased total direct cost by 14.3%. Total direct cost was 20.8% lower for patients living at home compared with those living in an institutional setting. CONCLUSIONS: Total direct cost of caring for patients with Alzheimer disease increased substantially over time. Much of the cost increases were explained by patients' clinical and demographic variables. Comorbidities and functional capacity were associated with higher direct cost over time

Clinical Features Associated with Costs in Early AD: Baseline Data from the Predictors Study

BACKGROUND: Few studies on cost of caring for patients with Alzheimer disease (AD) have simultaneously considered multiple dimensions of disease costs and detailed clinical characteristics. OBJECTIVE: To estimate empirically the incremental effects of patients' clinical characteristics on disease costs. METHODS: Data are derived from the baseline visit of 180 patients in the Predictors Study, a large, multicenter cohort of patients with probable AD followed from early stages of the disease. All patients initially lived at home, in retirement homes, or in assisted living facilities. Costs of direct medical care included hospitalizations, outpatient treatment and procedures, assistive devices, and medications. Costs of direct nonmedical care included home health aides, respite care, and adult day care. Indirect costs were measured by caregiving time. Patients' clinical characteristics included cognitive status, functional capacity, psychotic symptoms, behavioral problems, depressive symptoms, extrapyramidal signs, comorbidities, and duration of illness. RESULTS: A 1-point increase in the Blessed Dementia Rating Scale score was associated with a $1,411 increase in direct medical costs and a$2,718 increase in unpaid caregiving costs. Direct medical costs also were $3,777 higher among subjects with depressive symptoms than among those who were not depressed. CONCLUSIONS: Medical care costs and unpaid caregiving costs relate differently to patients' clinical characteristics. Poorer functional status is associated with higher medical care costs and unpaid caregiving costs. Interventions may be particularly useful if targeted in the areas of basic and instrumental activities of daily living

A New Algorithm for Predicting Time to Disease Endpoints in Alzheimer's Disease Patients

Background: The ability to predict the length of time to death and institutionalization has strong implications for Alzheimer's disease patients and caregivers, health policy, economics, and the design of intervention studies. Objective: To develop and validate a prediction algorithm that uses data from a single visit to estimate time to important disease endpoints for individual Alzheimer's disease patients. Method: Two separate study cohorts (Predictors 1, N = 252; Predictors 2, N = 254), all initially with mild Alzheimer's disease, were followed for 10 years at three research centers with semiannual assessments that included cognition, functional capacity, and medical, psychiatric, and neurologic information. The prediction algorithm was based on a longitudinal Grade of Membership model developed using the complete series of semiannually-collected Predictors 1 data. The algorithm was validated on the Predictors 2 data using data only from the initial assessment to predict separate survival curves for three outcomes. Results: For each of the three outcome measures, the predicted survival curves fell well within the 95% confidence intervals of the observed survival curves. Patients were also divided into quintiles for each endpoint to assess the calibration of the algorithm for extreme patient profiles. In all cases, the actual and predicted survival curves were statistically equivalent. Predictive accuracy was maintained even when key baseline variables were excluded, demonstrating the high resilience of the algorithm to missing data. Conclusion: The new prediction algorithm accurately predicts time to death, institutionalization, and need for full-time care in individual Alzheimer's disease patients; it can be readily adapted to predict other important disease endpoints. The algorithm will serve an unmet clinical, research, and public health need