Bupropion SR in the naturalistic treatment of elderly patients with major depression

Steffens, David C.; Doraiswamy, P. Murali; McQuoid, Douglas R.

doi:10.1002/gps.424

Cited by 21 publications

(17 citation statements)

References 18 publications

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“…The statistics in Table 1 and Table 2 are derived on the basis of cumulative frequencies of any response (MADRS Ͻ16), of remission (MADRS Ͻ7), and relapse (MADRS Ͼ15) at fixed 3-month intervals up to 18 months. 24,25 We used Kaplan-Meier estimates to estimate the percentage of patients achieving remission. These definitions may differ from those suggested for use in controlled treatment trials.…”

Section: Discussionmentioning

confidence: 99%

Partial Response as a Predictor of Outcome in Geriatric Depression

Steffens

McQuoid

Krishnan

2003

The American Journal of Geriatric Psychiatry

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Section: Discussionmentioning

confidence: 99%

Partial Response as a Predictor of Outcome in Geriatric Depression

Steffens

McQuoid

Krishnan

2003

The American Journal of Geriatric Psychiatry

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“…Covariates were included to examine their contribution to associations between year and dementia prevalence. After reviewing large population-based studies and systematic reviews of risk factors and risk models for dementia (6,(15)(16)(17)(18)(19)(20)(21), the following covariates were included in the models based on their associations with dementia in previous studies and based on the data available in the dataset: age, sex, location (state) and reported health conditions (cerebrovascular disease including stroke, diabetes, hypertension, ischaemic heart disease, high cholesterol, obesity, malnutrition, depression, alcohol abuse/dependence and head injury).…”

Section: Covariatesmentioning

confidence: 99%

Trends in Prevalence of Dementia for People Accessing Aged Care Services in Australia

Harrison

Lang

Whitehead

et al. 2019

The Journals of Gerontology: Series A

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Background: Studies in some high-income countries have reported a potential decline in the prevalence of dementia. Improvements in cardiovascular health may be contributing to this decline. The objective was to examine trends in prevalence of dementia and survival with dementia for people accessing aged care in Australia. Methods: A retrospective study of older people who accessed long-term care 2008-2014 (n=348,311) and home care 2005-2014 (n=188,846) in Australia. The age-and sexstandardized prevalence for dementia by year of access to aged care were determined using direct standardization. Generalised linear models were used to determine change in the prevalence of dementia over time and change in one-year mortality for people who accessed long-term care. Results: The age-and sex-standardized prevalence (95% confidence interval) of dementia declined from 50.0% (49.6, 50.5) in 2008 to 46.6% (46.0, 47.2) in 2014 for people accessing long-term care (Absolute change 2008-2014: -3.8 (-4.6, -3.1)) and for people accessing home care from 25.9% (25.0, 26.5) in 2005 to 20.9% (20.2, 21.7) in 2014 (Absolute change 2005-2014: -5.2 (-6.2, -4. 1)). This decline in dementia occurred in concurrence with a decline in cerebrovascular disease in long-term care but despite the prevalence of hypertension, diabetes, high cholesterol, malnutrition, obesity, depression and head injury increasing. For people accessing long-term care, one-year mortality remained stable over time. Conclusions:The decline in prevalence of dementia for people accessing aged care services in Australia is critical to future projection estimates and for planning of services. Further research to determine contributing factors to the decline is needed.

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“…These mean scores represent all person observations for a particular time period, i.e., a subject may contribute more than one MADRS during a given time period. Relevant scores reported for the MADRS include a score below 15 to define a response, and a score below 7 to define remission (Bosworth et al, 2002;Steffens et al, 2001b).…”

Section: The Sample: Characteristics and Follow-upmentioning

confidence: 99%

Biological and social predictors of long-term geriatric depression outcome

Steffens

Pieper

Bosworth

et al. 2005

Int. Psychogeriatr.

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Objective: In this study, we examined 204 older depressed individuals for up to 64 months to determine factors related to depression outcome. We hypothesized that both presence of vascular brain lesions seen on baseline magnetic resonance imaging (MRI) scans and lower baseline social support measures would be related to worse depression outcome. Method: At study entry, all subjects were at least 59 years old, had a diagnosis of major depression, and were free of other major psychiatric illness and primary neurological illness, including dementia and stroke. Depression was diagnosed via structured interview and clinical assessment by a geriatric psychiatrist who completed a Montgomery Asberg Depression Rating Scale (MADRS) to determine severity of depression. Subjects provided self-report data on social support variables and ability to perform basic and instrumental activities of daily living (ADL, IADL). All subjects agreed to have a baseline standardized MRI brain scan. Ratings of severity of hyperintensities were determined for the periventricular white matter, deep white matter, and subcortical gray matter by two readers who decided by consensus. Treatment was provided by geropsychiatrists following clinical guidelines. Using mixed models to analyze the data, we determined the effect of a variety of demographic, social and imaging variables on the trajectory of MADRS score, the outcome variable of interest. Results: MADRS scores decreased steadily over time. In a final HLM model, in which time since entry, a baseline time indicator, age, gender, education

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Bupropion SR in the naturalistic treatment of elderly patients with major depression

Cited by 21 publications

References 18 publications

Partial Response as a Predictor of Outcome in Geriatric Depression

Partial Response as a Predictor of Outcome in Geriatric Depression

Trends in Prevalence of Dementia for People Accessing Aged Care Services in Australia

Biological and social predictors of long-term geriatric depression outcome

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