COMPARATIVE ASSESSMENT OF PSYCHIATRIC COMORBIDITY, SUBSTANCE USE, QUALITY OF LIFE IN
PATIENTS WITH EARLY AND LATE ONSET DEMENTIA
Dissertation submitted for partial fulfillment of the rules and regulations
DOCTOR OF MEDICINE BRANCH – XVIII (PSYCHIATRY)
Reg. No. : 201728002
THE TAMILNADU
DR.M. G. R MEDICAL UNIVERSITY CHENNAI, TAMILNADU
MAY 2020
CERTIFICATE FROM THE DEAN
This is to certify that this dissertation entitled COMPARATIVE ASSESSMENT OF PSYCHIATRIC COMORBIDITY, SUBSTANCE USE,QUALITY OF LIFE IN PATIENTS WITH EARLY AND LATE ONSET DEMENTIA submitted by Dr. GOKULAN. E to The Tamilnadu Dr. M.G.R. Medical University, Chennai is in partial fulfillment of the requirement for the award of M.D. [PSYCHIATRY] and is a bonafide research work carried out by him under direct supervision and guidance.
This work has not previously formed the basis for the award of any degree or diploma.
Prof. Dr. R. JAYANTHI, M.D., FRCP (Glasg) Dean,
Rajiv Gandhi Government General Hospital, Chennai
BONAFIDE CERTIFICATE
This is to certify that this dissertation entitled
“COMPARATIVE ASSESSMENT OF PSYCHIATRIC COMORBIDITY, SUBSTANCE USE, QUALITY OF LIFE IN PATIENTS WITH EARLY AND LATE ONSET DEMENTIA” is a bonafide record work done by Dr. GOKULAN E under my direct supervision and guidance, submitted to The Tamilnadu Dr. M.G.R.
Medical University regulation for M.D Branch XVIII – Psychiatry.
Dr. P. POORNACHANDRIKA, D.C.H., M.D.
(Psychiatry),
Professor & Head of the Department, Department of Psychiatry,
Institute of Mental Health, Madras Medical College, Chennai.
CERTIFICATE FROM THE GUIDE
This is to certify that this dissertation entitled
“COMPARATIVE ASSESSMENT OF PSYCHIATRIC
COMORBIDITY, SUBSTANCE USE, QUALITY OF LIFE IN PATIENTS WITH EARLY AND LATE ONSET DEMENTIA” submitted by Dr. GOKULAN E to The Tamilnadu Dr. M.G.R. Medical University, Chennai is in partial fulfillment of the requirement for the award of M.D.
[PSYCHIATRY] and is a bonafide research work carried out by him under direct supervision and guidance. This work has not previously formed the basis for the award of any degree or diploma.
Dr. V. VENKATESH MATHAN KUMAR, M.D.
Professor,
Department of Psychiatry, Institute of Mental Health, Madras Medical College, Chennai.
DECLARATION
I, Dr. GOKULAN E, solemnly declare that dissertation entitled
“COMPARATIVE ASSESSMENT OF PSYCHIATRIC COMORBIDITY, SUBSTANCE USE,QUALITY OF LIFE IN PATIENTS
WITH EARLY AND LATE ONSET DEMENTIA” is a bonafide work done by me at the Institute of Mental Health under the guidance and supervision of Dr. V. VENKATESH MATHAN KUMAR, M.D. Professor of Psychiatry. It was not submitted by me or any other for any award, degree, diploma to any other university board either in India or abroad.
This dissertation is submitted to The Tamilnadu Dr. M.G.R.
Medical University, Chennai in partial fulfillment of the rules and regulations for the award M.D. Degree Branch – XVIII (Psychiatry) to be held in May 2020.
Place:
Date: Dr. GOKULAN E
(Reg. No. : 201728002)
ACKNOWLEDGEMENT
I sincerely thank The Dean Dr. R. JAYANTHI, M.D., FRCP (Glasg), Rajiv Gandhi government general hospital and Madras Medical College, Chennai for permitting me to do this study.
I sincerely thank Prof. Dr. P. Poornachandrika D.C.H., M.D., Head of the Department & Professor of Psychiatry, Institute of Mental Health, Madras Medical College, Chennai who has been a source of inspiration and for her immense guidance and help throughout the study.
I express my sincere thanks to my guide Dr. V. VENKATESH MATHAN KUMAR, M.D. Professor of Psychiatry, Institute of Mental Health, Madras Medical College, Chennai for lending out all possible help in the accomplishment of this study.
I am very grateful to my co-guide Asst. Professor Dr. D. SHANTHI MAHESHWARI, M.D., for her valuable support and guidance for the study.
I would like to express my sincere thanks to Prof. Dr. SHANTHI NAMBI, Former – Director of Institute of Mental Health, (Rtd.) and all my associate and assistant professors, Department of Psychiatry, Institute of Mental Health, Madras Medical College, who has guided me in literature search, developing protocol and
I would like to place on record, my gratitude to Dr. Arun, Dr Surendran V for helping me in statistical analysis.
I would fail in my duty if I don’t thank my colleagues and friends, Dr. Rizwana, Dr. Revathy, Dr. Vivek, Dr. Munivel, Dr. Subasree, Dr. Prabhavarani, Dr. Deepica Kumar, Dr. Priyamvadha, Dr. Kowsalya and Mr. Ramesh for their help and constant support especially during the process of research and writing of this thesis. This accomplishment would not have been possible without them. I would also like to thank all my juniors for helping me recruit cases and being supportive at all times.
Finally, I express my deepest love and affection to my father Mr. Ezhilan J, my mother Mrs. K. Sumathy and my sister and brother for providing me with unfailing support and constant encouragement throughout my years of study and especially during the process of research and writing of this thesis. This accomplishment would not have been possible without them.
INDEX
Sl. No. TOPIC Page Number
1 INTRODUCTION 1
2 REVIEW OF LITERATURE 7
3 AIMS AND OBJECTIVES 25
4 METHODOLOGY 26
5 RESULTS 35
6 DISCUSSION 63
7 CONCLUSION 71
8 LIMITATIONS 77
9 FUTURE DIRECTIONS 79
10 BIBLIOGRAPHY 80
11 APPENDIX
INTRODUCTION
According to the definition provided by the World Health Organization (WHO, 2017), dementia is “an umbrella term for several diseases affecting memory, other cognitive abilities and behaviour that interfere significantly with the ability to maintain daily living activities.
Although age is its strongest known risk factor, dementia is not a normal part of aging”. The associated brain diseases can cause a long-term, often gradual decrease in cognitive abilities, “emotional problems, language difficulties and decreased motivation”. The definition provided by the U.S. National Institute of Neurological Disorders and Stroke (NINDS, 2018) is more detailed in stating that dementia is “a group of symptoms caused by disorders that affect the brain. It is not a specific disease” and
“memory loss is a common symptom of dementia. However, memory loss by itself does not mean having dementia. People with dementia have serious problems with two or more brain functions, such as memory and language. Although dementia is common in very elderly people, it is not part of normal aging.1
Many different diseases can cause dementia, including Alzheimer disease (AD), frontotemporal dementia (FTD), Lewy body dementia (LBD), vascular dementia (VD), syphilitic dementia (SD), mixed dementia (MD), senility dementia (SD), or the combined effect of two or
more dementia types, and even stroke. About 10% of individuals present with Mixed Dementia, a usual combination of AD and another type of dementia such as FTD or VD. However, not being a specific disease, the above potential contributors do not reach to the primary cause of the disease. There lies our greatest shortcoming: unable to pinpoint the root cause of the disease, we are powerless in treating it. Sure, drugs are available to treat some of the symptoms of these contributing diseases but not the diseases themselves. Likewise, drugs available for dementia can also only alleviate its symptoms; they cannot cure it or repair brain damage. They may improve symptoms or at best slow down the disease.
Indeed, there is no known cure for dementia. This is a sad observation on the state of the situation. It stems from our incomplete understanding of the deep biology of the contributing diseases and associated epigenetic/
Eco genetic influences.2-5
Originally Dementia did not include older patients with “senile dementia.” and is meant to be a disorder of early-onset (EOD; <65 years of age) and In fact, the first reported patient with the dementia neuropathology appeared to have the onset of symptoms in her late 40’s, before being diagnosed with dementia at age 51. Her symptoms included memory loss, language impairment, and unpredictable, agitated, aggressive, confusion, and paranoid behaviour, and, on autopsy, she had
what we now recognize as the characteristic neuropathological markers of Dementia, extracellular amyloid-positive neuritic plaques and intracellular tau-positive neurofibrillary tangles (NFTs). Investigators subsequently broadened the diagnosis of Dementia to include the much more common late-onset Dementia (LOD) with the observation of similar neuropathology associated with cognitive decline in all age groups. In recent years, the main focus of interest and research has been on LOD;
however, like Auguste Deter, patients with EOD remain an important and impactful subgroup of patients with this disorder.6
Most common early-onset neurodegenerative dementia is EOD.
Vast majority of the cases are non-familial as indicated in few Epidemiological studies, making up about 4–6% of all Dementia, with an annual incidence rate of about 6.3/100,000 and a prevalence rate of about 24.2/100,000 in the 45–64 year age group, or between 220,000 and 640,000 Americans . As patients approach age 65 these incidence and prevalence rates rise exponentially. Since EOD is often atypical it is unfortunately missed often, leading to a 1.6-year average delay in diagnosis compared to older patients. Yet, EOD accounted for a more number of premature deaths among US adults aged 40–64 with many years of potential life lost as well as losses in productivity based on a mortality report from 1999 to 2010.7,8
Based on the greater extent of evaluation required for diagnosis EOD differs from LOD. The increased impact of dementia risk factors such as lower cognitive fitness and cardiovascular fitness, and the potentially increased consequence of traumatic brain injury lower the age of onset of dementia.9 Also there are psychosocial problems specific to early-onset dementia , such as the effects of grief with a sense of an “out- of-step” decline in midlife, unexpected loss of independence, difficulty juggling ongoing responsibilities, and relatively preserved insight with associated depression and anxiety. Since the autosomal dominant familial dementia tends to be of early onset, People belonging to the subgroups of EOD generally presents with higher rates of neurological symptoms and the risk of development of dementia is also greater in these subgroups compared to LOD. In contrast, compared to LOD, EOD patients have decreased overall comorbidities such as diabetes, obesity, and circulatory disorders .9,10
EOD patients differ from LOD patients on a number of clinical, neuropsychological, neuropathological, and neuroimaging variables.
Several studies indicate that the clinical course tends to be more aggressive in early-onset dementia patients. Compared to LOD, EOD presents less commonly with memory deficits and more frequently as focal cortical or phenotypic variants (described below). Overall, EOD
patients have better memory recognition scores and semantic memory, but they tend to have worse attention, executive functions, ideomotor praxis, and visuospatial skills compared to comparably impaired LOD patients.11,12 On magnetic resonance imaging (MRI), greater neocortical atrophy, particularly in parietal cortex, with less atrophy in the mesial temporal lobe (MTL) is seen in EOD patients .12
In patients with preserved hippocampal volumes MRI shows larger sulcal widths in the temporoparietal cortex among EOD patients relative to LOD. FDG-PET also suggests dysfunction in brain metabolic activity especially in the salience network among EOD patients with behavioral disturbances Resting state fluorodeoxy glucose (FDG) positron emission tomography (PET), shows greater parietal hypometabolism, worse on the left in one study, in EOD compared to greater bilateral temporal hypometabolism in LOD.13 Neuropathologically, both Early and Late onset dementia have temporoparietal-precuneus atrophy, but EOD patients have higher burdens of neuritic plaques and NFTs in these regions, and, to a lesser extent, frontal cortex, than Late onset dementia patients.13
Even though studies in various western countries have differentiated the differences between pathological and morphological changes in EOD and LOD, there are a dearth of studies in India profiling
the differences in risk factors for these two subtypes. With this background, the current research was done to determine the psychiatric morbidity, substance use, quality of life in persons with early onset and late onset dementia and to compare the differences in above factors between early onset and late onset dementia.
REVIEW OF LITERATURE
Psychiatric Co-morbidities and Dementia
Dementia is typically defined as a clinical syndrome of cognitive decline that is sufficiently severe to interfere with social or occupational functioning. It is an umbrella term for a group of cognitive disorders characterized by progressive decline in cognitive function interfering with independently carrying out activities of daily life due to brain damage or disease, but not related to delirium or depression.14.
Dementia is a neurodegenerative syndrome characterized by multidimensional progression consisting of three core dimensions:
cognitive, functional and psychiatric symptoms, with functional symptoms being defined as a decreased ability to independently perform daily life activities.2 Its prevalence is increasing rapidly due to aging of most societies, though incidence seems to decline in people with high educational levels in high income countries. According to Alzheimer’s association the term early onset dementia refers to first occurrence of dementia in a person under age 65 and can be caused by Alzheimer’s disease or any other conditions. Late onset dementia is dementia first occurring in a person after 65 years of age which can also be caused by Alzheimer’s disease or any other conditions.
This review focuses specifically on late-onset Dementia and Early onset dementia. Late onset Dementia (LOD), which is defined as dementia with an onset after 65 years of age. LOD is more prevalent and generally has a more slowly progressing course as compared to early- onset dementia (EOD).14,15
Currently it is impossible to provide patients and their families with a reliable prediction of the course of their disease, as there is substantial variability in rates of decline among individuals with LOD.
Knowing which factors are associated with decline would be useful for understanding and slowing disease progression, as well as for individual prognosis. Potentially influential factors are comorbidities. Comorbidity is defined as any additional co-existing ailment in a patient with a particular index disease, in this case LOD. It has been shown that comorbidities are more prevalent among individuals with LOD as compared to demographically-matched controls. In addition, a review indicated that comorbidity contributes to decline in LOD.15,16
However, it is unclear exactly how comorbidities affect the separate facets of LOD, since many studies merely report relations between comorbidity and one dimension of LOD, despite the multifaceted nature of the syndrome. In order to provide a multidimensional overview, this review investigates whether there is
evidence for an association between comorbid disease burden and cognitive, functional and psychiatric symptoms in individuals with LOD, both cross-sectionally and longitudinally.5,11,15
Worldwide, 35.6 million people are diagnosed with dementia, of whom 60% to 70% have Alzheimer disease (AD). The major risk factor for AD is advanced age, and by consequence, most dementia health care is focused on the elderly. In a minority of 2% to 10% of people with dementia, symptom onset occurs before the age of 65.1
The prevalence rates of this so-called young-onset dementia (EOD) range from 54 to 98 per 100,000 up to 156 in the 60 to 64 age group. In EOD and late-onset dementia (LOD), with symptom onset after the age of 65, AD is the most common diagnosis of dementia.4,16,17 The prevalence of AD in EOD ranges from 11.9% to 67.0%, and in LOD, the range is 50.0% to 70.0%. EOD is also characterized by a broader differential diagnosis compared with LOD. Alcohol dementia, the late presentation of metabolic disease, and sleep apnea are some of the examples of this differential diagnosis.
Comorbidity, which is any clinical condition that occurs during the course of an index disease, is frequently seen during the course of late onset AD (LOAD) and is usually associated with negative health outcomes. Currently, no studies on comorbidity in young-onset AD (YO-
AD) exist, although it is conceivable that these patients, having comorbidity, also experience negative health outcomes.4,9,16 The identification and treatment of comorbid disorders is an important strategy to reduce excess disability, maintain functional status, and to improve quality of life (QoL). Comorbid conditions may be underdiagnosed because of underreporting by people with AD.
The detection of symptoms of a possible disease/medical condition is challenging, especially in individuals with dementia, as they might be less able to sufficiently express symptoms and the associated discomfort.
Furthermore, when dealing with EOD, a severe health problem, physicians might overlook the possibility of comorbidity. When comorbidity is present or poorly controlled, it increases the burden of dementia caregivers with a subsequent risk of institutionalization of the patient with dementia.16,17
This higher risk of institutionalization is also seen in patients with dementia who suffer from neuropsychiatric symptoms, some of them resulting from comorbidity. In contrast to EOD, LOD is increasingly seen as a multifactorial syndrome, with heterogeneity in causes and presentation.
In this model, comorbidity is regarded as one of the factors leading to LOD. This differs from the amyloid hypothesis, in which the pathway to AD in EOD and LOD is the same; however, in EOD, the most common factor of the amyloid hypothesis, aging, is lacking.14 Therefore, knowledge on comorbidity can reveal to what extent this is important in EOD and may indicate the various aetiologies of AD in young and elderly patients. Furthermore, studying differences in clusters of comorbidity between EOD and LOD may provide additional information about this issue.17
Associations between alcohol use and the incidence of cognitive impairment/ dementia, including dose-response studies
The systematic reviews published after 2000 which studied the associations between alcohol use and the incidence of cognitive impairment or dementia were often coupled with meta-analytic summaries, typically based on cohort studies which primarily measured the effect of other modifiable risk factors, usually measured at baseline (including alcohol use), on the hazard or risk (or both) of being diagnosed with cognitive impairment or dementia or dying (or both) from dementia.
The majority of these systematic reviews indicated that there was a statistically significant association between light to moderate alcohol use and a lower risk of (i) being diagnosed with cognitive impairment and
different types of dementia and (ii) dying from dementia.18,19 However, two systematic reviews found inconsistent results. Furthermore, chronic heavy alcohol use (defined based on the World Health Organization/European Medicines Agency definitions as drinking more than 60 g of pure alcohol per day for men and more than 40 g of pure alcohol per day for women) was associated with an increased risk of being diagnosed with either cognitive impairment or dementia.19
There also was an association found between engaging in irregular heavy drinking and the risk of being diagnosed with either cognitive impairment or dementia. In several reviews, the potential of an interaction between alcohol use and the presence or absence of the apolipoprotein E ε4 allele (a known risk factor for AD and other types of dementia) and the resulting risk of either cognitive impairment or dementia was also examined, albeit based on a limited number of studies with substantial heterogeneity.18-21
The causality of the association between the volume and patterns of alcohol use and the development of cognitive impairment and dementia was assessed by Piazza-Gardner et al., who determined that there was not sufficient evidence of a causal relationship between light to moderate drinking and a decreased risk of dementia. Overall, the level of evidence and the methodological quality of the reviews were judged to be
only moderate. With respect to the positive association between light and moderate drinking and vascular dementia, the underlying protective mechanisms of these patterns of use for cardiovascular outcomes were mentioned (that is, having a favourable impact on lipid levels by, for example, increasing high-density lipoprotein, and affecting atherosclerosis and inflammation via decreases in fibrinogen levels and inflammation markers .21-24
All meta-analyses showed high levels of heterogeneity. The following limitations in assessing the relationship between alcohol use and the onset of cognitive impairment and dementia were highlighted in the systematic reviews and may explain, in part, the observed heterogeneity between studies:
Alcohol use was always self-reported and in almost all studies was assessed only once, at baseline. There was a lack of standardization of alcohol use and of level of use categories across studies; some reviews used only broad descriptive categories (that is, light, moderate, and heavy alcohol use) which varied widely because of different standard alcoholic drink sizes across countries and differences in the categorization of alcohol use volumes and patterns.25-27
There was inconsistent or no control for potential confounding variables, as different risk factors or confounding variables (or both)
were measured across cohort studies. Furthermore, interactions between alcohol and other risk factors, particularly tobacco smoking, may also exist but these interactions were not assessed.4,18,21
Former drinkers were usually grouped with lifetime abstainers to create a control group, leading to a lack of control for “sick quitters” (that is, people who quit drinking because of health problems. However, having conducted a meta-analysis of studies in which former drinkers were categorized separately, Neafsey and Collins still observed a statistically significant association between moderate drinking and a lower risk of cognitive impairment or dementia. Also, Reid et al.
explicitly included only studies which separated lifetime abstainers and former drinkers.21,22
Many studies lacked a quality assessment for various outcomes, with many different operationalizations for cognitive functioning, and lacked standardization for the diagnoses of different types of dementia.24
Some studies highlighted that the selection processes used in cohort studies may lead to underestimation of the associations between alcohol use and cognitive impairment or dementia. First, many cohort studies exclude heavier drinkers. Second, most of the studies on alcohol use and cognitive decline/dementia concerned older subjects. Therefore,
studies as they may have been more likely to have dementia at baseline or may have died prior to or before the end of the study because of other alcohol-attributable causes of death. In particular, there was an observed increase in the risk of an alcohol-attributable death at lower levels of use, such as 30 g of pure alcohol per day, and risk accelerated exponentially as average use increased.25,26
Survivor bias may also be an issue because of missing dementia information and this was not included in most reviews. Owing to these limitations, two systematic reviews refrained from conducting meta- analyses because of the lack of exposure or outcome comparability across studies or both.26
Associations between dimensions of alcohol use and specific brain functions
The systematic reviews that assessed the relationship between alcohol use and the resulting effects on brain structures and specific brain functioning assessed diverse associations. Verbaten tested the hypothesis that low to moderate drinking (about one to three standard alcoholic drinks) had beneficial effects on brain structure (through a review of seven magnetic resonance imaging (MRI) studies) and cognitive performance (through a review of six observational studies).
In the MRI studies, a linear negative association was observed between the volume of alcohol consumed and brain volume and grey matter, and a positive linear association was observed between the volume of alcohol consumed and white matter volumes (in men but not in women). However, when restricted to people aged 65 years and older, low to moderate alcohol use was related to grade of white matter integrity and cognition in a curvilinear manner (that is, U-shaped).27,28
A recently published large-scale study with a follow-up at 30 years, which measured alcohol use every 5 years and involved multiple MRI images and cognitive tests, concluded that alcohol use, even at light or moderate levels, was associated with adverse brain outcomes, including hippocampal atrophy, thereby corroborating the general results of the systematic review by Verbaten for people under 65 years of age.29
The systematic review by Montgomery et al. measured the association between heavy alcohol use in social drinkers and executive functioning. The findings of the underlying studies were heterogeneous, and, when these studies were combined, no significant relationship between heavy alcohol use and executive functioning was observed;
however, in a randomized control study by Montgomery et al., heavy alcohol use was significantly associated with all sub-measures of executive functioning except for memory updating.30 Therefore, the
detrimental effects of alcohol use may be mediated through a decrease in executive functioning.
Two other systematic reviews based on imaging studies found consistent detrimental effects of heavy alcohol use on brain structures and function. The structural effects have also been confirmed in autopsy studies. Both functional and structural impacts of heavy use have been corroborated in a number of additional narrative reviews.31,32
Alcohol-related and alcohol-induced dementia
Heavy alcohol use has been shown to be a contributory factor, as well as a necessary factor (where the disease would not exist in the absence of alcohol), in the development of multiple brain diseases and such use may cause alcohol-related brain damage in multiple ways.
First, ethanol and its metabolite acetaldehyde have a direct neurotoxic effect, leading to permanent structural and functional brain damage.
Second, chronic heavy alcohol use can result in thiamine deficiency by causing inadequate nutritional thiamine intake, decreased absorption of thiamine from the gastrointestinal tract, and impaired thiamine utilization in the cells, leading to Wernicke–Korsakoff syndrome.31,32
Treatment with administration of thiamine reverses many of the Wernicke–Korsakoff syndrome symptoms, although in some people certain chronic neuropsychiatric consequences of a previous thiamine deficiency persist even with appropriate treatment.
Third, heavy alcohol use is a risk factor for other conditions that can also damage the brain: hepatic encephalopathy in patients with cirrhotic liver disease, epilepsy, or head injury.33
Fourth, heavy alcohol use is indirectly associated with vascular dementia because of its associations with cardiovascular risk factors and diseases such as high blood pressure, ischemic heart disease, cardiomyopathy, atrial fibrillation, and stroke.
The above associations have been identified as causal and have been corroborated in studies of people with AUDs. Finally, heavy alcohol use is associated with lower levels of education, tobacco smoking, and depression, all of which are risk factors for dementia.34
Tobacco use and its effects on cognitive impairment and dementia Nicotine has been studied to improve cognitive function in adults with and without Alzheimer’s disease according to Rezvani and Levin due to its action on the cholinergic system, which has a significant role in the modulation of memory.35-36 But the role of chronic tobacco smoking
in improving cognitive abilities is still controversial. Ernst et al showed the cognitive performance, particularly working memory, of smokers unlike that of non-smokers did not benefit from the administration of oral nicotine37. Doll et al in his Cohort study also suggested a positive correlation between smoking and risk of Alzheimer’s disease38. This association is particularly strong in the presence of history of current smoking at the beginning of follow-up.
The European Community Concerted Action Epidemiology of Dementia (EURODEM) study comprising four smaller studies from Denmark, France, Netherland and the U.K., each with substantial cohorts, confirmed that smoking accelerates cognitive decline in older adults without dementia39. Smoking positively correlated with cognitive impairment and dementia is not surprising as smoking, in itself is a known risk factor for strokes and consequently, Vascular Dementia.40 In addition, smoking increases total plasma homocysteine which is in turn associated with an increased risk of strokes, dementia and Alzheimer’s Disease.41
Cannabis use and its effects on cognitive impairment and dementia Pope et al compared the cognitive performance of heavy cannabis users, former heavy users and controls and found that memory scores of current users were consistently lower than those of controls and also
concluded that, in spite of lack of sufficient strong evidence, heavy cannabis use has been found to be associated with cognitive decline by most of the recent studies.42-43 The duration of cannabis use were inversely correlated to cognitive performance according to Solowji et al.44 It was also noticed that the effects on cognition could be confounded by the use of other drugs affecting cognition by heavy cannabis users.
QUALITY OF LIFE IN EARLY AND LATE ONSET DEMENTIA
Quality of life is the general well being of individuals and societies, outlining negative and positive features of life, It observes life satisfaction, including everything from physical health, family, education, employment, wealth, safety, security to freedom, religious beliefs, and the environment. Health related quality of life is an assessment of how the individuals well being may be affected over time by a disease, disability or a disorder in our case Dementia. Chronic use of substance like alcohol, benzodiazepines, tobacco, cannabis has been associated with significant decline in cognitive function which is likely to have impact leading to various disorders thereby significantly impacting their quality of life as well as the quality of life of the care givers . Psychiatric morbidity is also more in people with dementia which affect the quality of life of the elderly people and their caregivers.
A cross sectional study done by Bakker et al45 in people with AD, VaD, FTD, MD and Dementia due to other diseases with sample size of n=215 carers in Netherlands in which QOL-AD administered to patients and the Dutch version of RAND-36 health survey and CANE (Camberwell Assessment for the need for the Elderly) administered to carers to investigate the relationship between HRQOL(Health related
quality of life) and unmet needs in YOD. The results obtained suggests that PWDs (People with Disabilities) QOL is not associated with unmet needs and there is a relationship between unmet needs of PWD and reduced caregiver QOL. Bakker et al conducted a longitudinal study in the same population of above mentioned study with CANE administered to investigate the needs of care and in its relationship to the severity of neuropsychiatric symptoms and the results of this study suggests that caregivers and PWD agreed on the areas in which needs occurred46. PWD experienced high levels of unmet needs in daytime activities, social company, intimate relationship and information.
Koopmans et al47 investigated PDU (Psychiatric decisions Unit) in Dutch community-dwelling people with YOD and the association between age, gender, dementia etiology and severity, symptoms of depression, disease awareness, unmet needs, and type of neuropsychiatric symptoms with 198 samples in Netherlands, they were assessed using Dutch version of the CANE and concluded that the majority of the sample had ≥3 unmet needs, there was no association between unmet needs and PDU. Hewitt et al48 studied the benefits of gardening program in people with YOD as a longitudinal study in the UK sample n=12 with AD,MD,FTD, Dementia with Lewy body who were given 2 gardening sessions per week for 1 year with multidisciplinary team assessed using
Bradford wellbeing profile and found there was a gradual increase in wellbeing indicators over the duration of the gardening project.
A cross sectional study by Rosness et al49 investigated QOL and depression in carers of people with AD,FTD,VD and Dementia with Lewy bodies in Norwegian population (n=49) to whom QOL-AD(Quality of Life-Alzheimer’s Disease) administered with results suggestive of carers ‘ QOL corresponds positively with increased age of carers and PWD’ insight.
Bakker et al50 studied the unmet needs of YOD individuals and care givers and explored the experiences of caregivers by following up a 59years old AD patient and his caregiver in Netherland using CANE and semi-structured interview. Allen et al51qualitatively analysed the interviews of children aged 13-23 years old of people with AD,FTD in UK(n=12) and concluded that there is a delay in diagnosis and difficulty of dealing with confused behaviours in agile, physically well adults are primary stressors which had major impact on children’s wellbeing.
Herrera et al found that mutation E280A in Gene Presenilin1 responsible for early onset presenile AD did not influence self assessment of QOL in carriers of this mutation52. Williams et al53 found that the wellbeing of two thirds of carers was poor or very poor which is in direct proportion to length of carrying.
Barca et al54 reported with lower quality of life was associated with major depression, low MMSE score ,impaired functions in daily living and female gender in a cross sectional study conducted in patients with dementia above 65 years of age . Bokberg et al concluded that quality of care helps in improving the quality of life by a community based cross sectional study with CLINT survey and QOL-AD55. H.C.Beerens et al explored the quality of life and care for people with dementia in 8 European countries and found that the presence of depressive symptoms was associated with low quality of life using QOL-AD scale.56
AIM & OBJECTIVES
AIM
• To determine the psychiatric morbidity, substance use, quality of life in persons with early onset and late onset dementia
• To compare the differences in above factors between early onset and late onset dementia.
METHODOLOGY Study context
The study was an analytical cross-sectional comparative study conducted in the Institute of Mental health, Chennai to determine the psychiatric morbidity, substance use, quality of life in persons with early onset and late onset dementia and to compare the differences in above factors between early onset and late onset dementia.
Study setting
The study was conducted among patients attending the Institue of Mental health, Madras Medical College, Chennai. Institute of Mental Health, Chennai is involved in Mental Health care for the past 206 Years.
Founded in 1794 as an asylum to manage 20 patients, it has grown into an Institute with bed strength of 1800 patients. It is no more an asylum for custodial care but a place for enhancing mental health and a training centre for mental health professionals. Today Institute of Mental Health is the second largest Institute in India, offering mental health services to a massive population of Tamil Nadu and Pondicherry.
The Institute is served by an army of trained professionals.
Psychiatrists, Psychiatric Social Workers, Clinical Psychologists, Occupational Therapists, Recreational Therapists, Special Education
Teacher, Skilled Training Staff, apart from Psychiatric Nurses are functioning, in co-ordination with each other contributing their own specific body of knowledge and skills to the benefit of mentally ill.
Study Duration
The data collection was carried over a period of one year after obtaining ethical clearance from the Institutional Human Ethical Committee (IHEC) of Madras Medical College, Chennai.
Study population
Patients diagnosed as dementia as per ICD-10 criteria.
Inclusion criteria
• Patient diagnosed as dementia as per ICD-10 criteria
• Patients and caregivers who give written and informed consent
• Both males and females
Exclusion criteria
• No reliable informant
• Not given informed consent
• Acute confusional state
• Cognitive impairment due to primary psychiatric illness
• Past history of any major psychiatric illness except substance use
Sample size
Total sample size = 60
30 early onset and 30 late onset dementia based on the age of onset.
Sampling Procedure
Patients newly diagnosed with dementia as per ICD -10 were continuously enrolled for the study after obtaining informed consent. The enrolment was continuous till the adequate sample size was achieved.
Necessary precautions were made to have a sample of 30 in early onset and 30 in late onset dementia types.
STUDY TOOLS
1. DEMENTIA SEVERITY RATING SCALE
It is usually completed by caregiver and rates the subject in 11 categories across 12 items in a multiple-choice format to obtain information about the subject’s ability to function in their home and environment. The categories involved in this scale are as follows
1) Memory, 2) orientation, 3) judgement,
4) social interaction, 5) home activities, 6) personal care, 7) language, 8) recognition, 9) eating,
10) incontinence, 11) mobility.
Interestingly Washington University Clinical Dementia Rating scale mirrors with the first 6 items of this scale. The care giver rates the subject according to the descriptions in increasing degree of severity from zero and the total score is derived from adding the numbers chosen from each category. Therefore, a score of zero indicates normal functioning and a maximally impaired person would score 51. It is most widely used because of its high reliability and better correlation with measures of overall severity and specific cognitive functions.
2. MINI PLUS SCALE- For diagnosing psychiatric comorbidity as per ICD-10 criteria & to asses substance use
For DSM-IV and ICD 10 psychiatric disorders psychiatrist and clinicians in the United States and Europe jointly developed a short structured diagnostic interview scale called M.I.N.I plus (Mini international Neuropsychiatric Interview) scale which can be administered within 15 minutes. It can be used as a first step in outcome tracking in non research setting and in epidemiology studies and multicenter clinical trials as it is designed to meet the need for an accurate but short structured psychiatric interview required in those settings.
Because of its good psychometric properties it is more widely used in psychiatry to support the diagnostics of more common psychiatric disorders according to ICD 10 and axis I DSM IV TR.
3. DEM-QOL (Quality of life) – patient version and proxy version Health related quality of life is assessed at all stages of dementia severity by means of DEMQOL and DEMQOL proxy on a 4 point Likert- type response scale. DEMQOL consists of 28 questions and DEMQOL- Proxy consists of 31 questions derived from five conceptual domain namely health and well being, cognitive functioning, daily activities, social relationships and self concept. It is administered by interviewer.
Apart from this there is also additional overall quality of life questions which is also answered on a 4 point likert scale which includes very good, good, fair, poor.
After completing all the questions according to standard algorithm the items are scored to produce overall score in which better health related quality of life is represented by higher scores. This scale is also designed to work across various dementia subtypes thereby establishing as disease specific instrument. This scale is also validated in a UK population and shows psychometric properties comparable with the best available instruments therefore most often used in the research studies like QoL-AD.
Data Collection procedure
• After obtaining permission from the Institutional Human Ethical Committee, written and informed consent from the eligible participants were obtained.
• As per sample size, 60 patients diagnosed with dementia according to ICD – 10 criteria were selected for the study
• Cases for the study were selected from newly diagnosed outpatients and in patients at Institute of mental health, MMC.
• Study sample had been grouped into two categories as early onset and late onset dementia (30+30) based on the age of onset (< 65)
• DEMENTIA SEVERITY RATING SCALE will be
administered to grade the severity of dementia
• Psychiatric comorbidity and substance use were assessed
using MINI PLUS INTERNATIONAL NEUROPSYCHIATRY INTERVIEW scale
• Quality of life was measured using DEMQOL & DEMQOL proxy scale
ETHICAL ISSUES
The study was approved by the Institutional Human Ethical Committee of the Institute of Mental health, Madras Medical College, Chennai. Written, informed consent was obtained from the participants before the survey. Privacy and confidentiality were maintained throughout the study period. An explicit participant information sheet had been prepared in both English and the regional language (Tamil). This document made the subjects understand all the details of the study before providing consent. The study neither required any invasive procedures nor involve any vulnerable population groups.
DATA ANALYSIS AND STATISTICAL TOOLS
The data obtained from the proforma were entered into Microsoft excel 2016 software and analysed using Statistical Package for Social Sciences (SPSS) version 16.108
Mean and standard deviation were calculated to summarize continuous variables such as age, DSRS scores and DEMQOL scores Number and percentage were used to present the categorical data pertaining to the following distribution of the various socio-demographic variables, types of psychiatric co-morbidities and dementia.
The association between categorical variables were studied using chi square test. In the associations, if the observed value in a cell was less than 5, Fisher’s Exact test was done to compute the p value. The distribution of continuous variables with normal distribution among the two patient groups were analysed using Independent t test. For those variables with continuous skewed distribution, association between two patient groups was studied using Mann- Whitney U test. Statistical significance was set at p value of less than or equal to 0.05.
RESULTS
Table 1: Distribution of the socio-demographic variables among the patients (n=60)
Socio-demographic variables Summary statistics
Age of patients, mean (±SD) 67.92 (8.25)
Gender, n(%)
Male 33 (55%)
Female 27 (45%)
Care taker, n(%)
Daughter 17 (28.3%)
Wife 23 (38.3%)
Daughter in law 5 (8.4%)
Husband 5 (8.3%)
Son 5 (8.3%)
Sister 3 (5%)
Warden 2 (3.4%)
The distribution of the socio-demographic characteristics sis shown in table 1. The average age of the participants was 67.92 (8.25 years). More than half (55%) were males. Majority of the patients were accompanied by their wife (38.3%) and daughter (17%).
Table 2: Distribution of the socio-demographic variables among the two patient groups
Socio-demographic variables Late onset dementia (n=30)
Early onset
Dementia (n=30) p value
Age of the patients, mean (±SD) 74.53 (5.70) 61.3 (3.92) <0.001*
Gender, n(%)
Male 14 (46.7%) 19 (63.3%)
0.194#
Female 16 (53.3%) 11 (36.7%)
Care taker, n(%)
Daughter 11 (36.7%) 6 (20%)
0.005#
Wife 7 (23.3%) 16 (53.3%)
Daughter in law 3 (10%) 2 (6.6%)
Husband 0 5 (16.7%)
Son 5 (16.7%) 0
Sister 3 (10%) 0
Warden 1 (3.3%) 1 (3.3%)
*p value by independent t test #p value by chi-square test
Table 2 shows the distribution of the socio-demographic characteristics among the two groups- early and late onset dementia.
The patients in late onset category were significantly older than the other group. However, majority of the patients in early onset were males (63.3%) and hence a little more half of the patients (53.3%) were accompanied by their wife.
Figure 1: Distribution of the onset of dementia among the patients (n=60)
Among the 60 patients studied, 30 (50%) belonged to early onset dementia and the remaining 50% belonged to late onset dementia. (Figure 1).
Figure 2: Distribution of the age among the two patient groups (n=60)
The patients in early onset dementia were significantly younger on comparison with patients in late onset dementia as shown in the box and whisker plot. (Figure 2)
Majority of the patients in early onset dementia were males while in late onset dementia half of the patients were males as depicted by the clustered bar diagram. (Figure 3)
Since most of the patients in early onset were males, they were mostly accompanied by their wife. In late onset, due to the equal representation of males and females, most of them were accompanied by daughter and wife as depicted by the clustered bar diagram. (Figure 4)
Figure 3: Distribution of the gender among the two patient groups (n=60)
Figure 4: Distribution of the caretakers among the two patient groups (n=60)
Figure 5: Distribution of the duration of illness among the two patient groups (n=60)
Figure 5 shows the distribution of the duration of illness among the two patient groups. Both the groups had a median duration of illness of around 2 years. However, patients in late onset dementia had a wider range of duration of illness starting from few months to 8 years.
Table 3: Distribution of the Psychiatric Co-morbidity among the patients (n=60)
Psychiatric Co-morbidities Summary statistics, n
(%) F06.2 (Psychotic disorder due to general medical
condition) 3 (5%)
F06.2/F19.2 (Mental and behavioural disorders due to multiple drug use and use of other psychoactive substances-Dependence syndrome)
1 (1.7%)
F06.30 (Manic Episode due to general medical
condition) 1 (1.7%)
F06.32 (Mood disorder due to medical condition) 2 (3.3%) F10.2 (Mental and behavioural due to use of alcohol -
Dependence syndrome) 5 (8.3%)
F29.0 (Unspecified psychosis not due to a substance or
known physiological condition) 2 (3.3%)
F32.x (Major depressive episode- current) 5 (8.3%) F33.x3 (Major depressive disorder with psychotic
features) 1 (1.7%)
F41.1 (Generalized Anxiety disorder) 7 (11.7%)
F41.2 (Mixed anxiety and depressive disorder) 2 (3.3%)
Nil 31 (51.7%)
The distribution of the Psychiatric Co-morbidity among the patients is shown in table 3. The top three psychiatric co- morbidities among the patients were F41.1-Generalized Anxiety disorder (11.7%), F10.2-Mental and behavioural disorders due to use of alcohol - Dependence syndrome (8.3%) and F32.x-Major depressive episode- current (8.3%). More than half (51.7%) didn’t have any psychiatric co-morbidities.
Table 4: Distribution of Psychiatric Co-morbidity among the two patient groups
Variable Early onset
dementia (n=30)
Late onset
Dementia (n=30) p value
Psychiatric Co- morbidity , n(%)
F06.2 3 (10%) 0
0.274*
F06.2/F19.2 1 (3.3%) 0
F06.30 0 1 (3.3%)
F06.32 2 (6.7%) 0
F10.2 3 (10%) 2 (6.7%)
F29.0 0 2 (6.7%)
F32.x 1 (3.3%) 4 (13.3%)
F33.x3 1 (3.3%) 0
F41.1 3 (10%) 4 (13.3%)
F41.2 1 (3.3%) 1 (3.3%)
Nil 15 (50%) 16 (53.3%)
*p value by chi-square test
Table 4 and Figure 6 shows the distribution of the Psychiatric Co-morbidity among the two-patient group based on ICD 10 codes in Mini plus scale. Among those with early onset dementia, the leading psychiatric co-morbidities were F06.2-Psychotic disorder due to general medical condition (10%), F41.1-Generalized Anxiety disorder (10%) and F10.2-Mental and behavioural disorders due to use of alcohol -
psychiatric co-morbidities were F41.1-Generalized Anxiety disorder (13.3%) and F32.x-Major depressive episode- current (13.3%). The distribution of these psychiatric co-morbidities wasn’t statistically significant.
Figure 6: Distribution of Psychiatric
Co-morbidity among the two patient groups (n=60)
Table 5: Distribution of the Psychiatric comorbidities according to MINI plus modules among the patients (n=60)
Variable
Summary statistics, n (%)
MINI plus code
A (Major Depressive Episode) 9 (15%)
D (Manic Episode) 1 (1.7%)
K (Alcoholic Dependence) 5 (8.3%)
M (Psychotic Disorders) 4 (6.7%)
P (Generalized Anxiety Disorder) 7 (11.7%) Z (Mixed Anxiety-Depressive Disorder) 2 (3.3%)
A/K/L 1 (1.7%)
Nil 31 (51.7%)
The distribution of the psychiatric comorbidities as per the modules in MINI plus among the patients is shown in table 5. The top three MINI plus module psychiatric comorbidity among the patients were A -Major Depressive Episode (15%), P-Generalized Anxiety Disorder (11.7%) and K- Alcoholic Dependence (8.3%).
More than half (51.7%) didn’t have any psychiatric co-morbidities.
Table 6: Distribution of the MINI plus modules among the two patient groups
Variable Early onset
dementia (n=30)
Late onset
Dementia (n=30) p value
MINI plus module, n(%)
A 5 (16.7%) 4 (13.3%)
0.928*
A/K/L 1 (3.3%) 0
D 0 1 (3.3%)
K 3 (10%) 2 (6.7%)
M 2 (6.7%) 2 (6.7%)
P 3 (10%) 4 (13.3%)
Z 1 (3.3%) 1 (3.3%)
Nil 15 (50%) 16 (53.3%)
*p value by chi-square test
Table 6 and Figure 7 shows the distribution of psychiatric comorbidity as per the MINI plus module among the two-patient group. Among those with early onset dementia, the leading psychiatric co-morbidities (MINI plus module) were A -Major Depressive Episode (16.7%), P-Generalized Anxiety Disorder (10%) and K- Alcoholic Dependence (10%). In late onset dementia patients, the top MINI plus module psychiatric comorbidities were A -Major Depressive Episode (13.3%) and P-Generalized Anxiety Disorder (13.3%). The distribution of these MINI plus codes wasn’t statistically significant.
Figure 7: Distribution of MNI plus modules among the two patient groups (n=60)
Table 7: Distribution of Dementia types among the patients (n=60)
Dementia types with respect to ICD-10 Codes Summary statistics, n (%)
F00.0 (Dementia in Alzheimer’s disease with early onset) 15 (25%) F00.1 (Dementia in Alzheimer’s disease- late onset) 18 (30%) F01.0 (Vascular dementia of acute onset) 11 (18.3%)
F01.1 (Multiinfarct Dementia) 2 (3.3%)
F01.2 (Subcortical vascular dementia) 2 (3.3%)
F02.0 (Dementia in picks disease) 3 (5%)
F02.3 (Dementia in Parkinson's disease) 6 (10%)
F02.4 (Dementia in HIV disease) 1 (1.7%)
F02.8 (Dementia in Epilepsy) 2 (3.3%)
The distribution of the dementia types with respect to ICD- 10 Codes among the patients is shown in table 7. The top three dementia types among the patients were F00.1- Dementia in Alzheimer’s disease- late onset (30%), F00.0- Dementia in Alzheimer’s disease with early onset (25%) and F01.0- Vascular dementia of acute onset (18.3%).
Table 8: Comparison of Dementia types among the two patient groups
Variable Early onset
dementia (n=30)
Late onset
Dementia (n=30) p value
Dementia types with respect to ICD- 10 Codes, n (%)
F00.0 15 (50%) 0
<0.001*
F00.1 0 18 (60%)
F01.0 9 (30%) 2 (6.7%)
F01.1 0 2 (6.7%)
F01.2 0 2 (6.6%)
F02.0 1 (3.3%) 2 (6.7%)
F02.3 2 (6.7%) 4 (13.3%)
F02.4 1 (3.3%) 0
F02.8 2 (6.7%) 0
*p value by chi-square test
Table 8 and Figure 8 shows the distribution of the dementia types with respect to ICD-10 Codes among the two-patient groups.
Among those with early onset dementia, the leading dementia types were F00.0 Dementia in Alzheimer’s disease with early onset (50%), F01.0-Vascular dementia of acute onset (30%), F02.3- Dementia in Parkinson's disease (6.7%) and F02.8- Dementia in Epilepsy (6.7%).
In late onset dementia patients, the top dementia types were F00.1 (Dementia in Alzheimer’s disease- late onset (60%) and F02.3- Dementia in Parkinson's disease (13.3%). The distribution of these dementia types with respect to ICD-10 codes was statistically
Figure 8: Distribution of Dementia types among the two patient groups
Table 9: Distribution of substance abuse among the patients (n=60)
Variable Summary statistics
Substance abuse, n(%)
Alcohol only 9 (15%)
Tobacco Only 7 (11.7%)
Alcohol & Tobacco 8 (13.3%) Alcohol, Tobacco &
Cannabis
1 (1.7%)
Nil 35 (58.3%)
The Distribution of substance abuse among the patients is given in table 9. More than half (58.3%) of the patients didn’t have any substance abuse. About 15% consumed alcohol, 11.7%
tobacco and 13.3% both alcohol and tobacco.
Table 10: Distribution of the substance abuse among the two patient groups
Variable Early onset
dementia (n=30)
Late onset
Dementia (n=30) p value
Substance abuse, n(%)
Alcohol only 5 (16.7%) 4 (13.3%)
0.367*
Tobacco Only 5 (16.7%) 2 (6.7%)
Alcohol & Tobacco 5 (16.7%) 3 (10%) Alcohol, Tobacco &
Cannabis 1 (3.3%) 0
Nil 14 (46.7%) 21 (70%)
*p value by chi-square test
Table 10 shows the distribution of the substance abuse among the two patient groups. Among patients with early onset dementia, an equal proportion (16.7%) of patients consumed alcohol, tobacco and both. In patients with late onset dementia, about 15% consumed alcohol, 11.7% tobacco and 13.3% both alcohol and tobacco.
Table 11: Comparison of the alcohol use among the two patient groups
Variable
Early onset dementia (n=30)
Late onset Dementia (n=30)
p value
Alcohol use, n(%)
Yes 11 (36.7%) 7 (23.3%)
0.260*
No 19 (63.3%) 23 (76.7%)
*p value by chi-square test
Figure 9: Distribution of alcohol use among the two patient groups (n=60)
Table 11 and Figure 9 shows the distribution and comparison of alcohol use among the two-patient groups. About 36.7% consumed alcohol in early onset dementia group while 23.3% consumed alcohol in late onset dementia group. The distribution of the alcohol use wasn’t statistically significant.
Table 12: Comparison of the tobacco use among the two patient groups
Variable Early onset
dementia (n=30)
Late onset
Dementia (n=30) p value
Tobacco use, n(%)
Yes 11 (36.7%) 5 (16.7%)
0.080*
No 19 (63.3%) 25 (83.3%)
*p value by chi-square test
Figure 10: Distribution of tobacco use among the two patient groups (n=60)
Table 12 and Figure 10 shows the distribution and comparison of tobacco use among the two patient groups. About 36.7% consumed tobacco in early onset dementia group while
16.7% consumed tobacco in late onset dementia group. The distribution of the tobacco use wasn’t statistically significant.
Table 13: Comparison of the cannabis use among the two patient groups
Variable Early onset
dementia (n=30)
Late onset
Dementia (n=30) p value
Cannabis use, n(%)
Yes 1 (3.33%) 0
0.260*
No 29 (96.7%) 30 (100%)
*p value by chi-square test- Fischer’s exact correction
Figure 11: Distribution of cannabis abuse among the two patient groups (n=60)
Table 13 and Figure 11 shows the distribution and comparison of cannabis use among the two-patient groups. Only a single patient in the early dementia group consumed cannabis.
Table 14: Comparison of DSRS scores among the two patient groups
DSRS scores, mean (±SD)
Onset of Dementia
p value*
Early (n=30) Late (n=30)
Scores 31.60 (±10.334) 25.83 (±8.355) 0.021
*p value by independent t test
Figure 12: Distribution of DSRS scores among the two patient groups (n=60)
Table 14 and Figure 12 shows the distribution and comparison of DSRS scores among the two-patient groups. The mean score in early onset group was 31.60 (±10.334) while in late onset group was 25.83 (±8.355). There was statistically significant higher DSRS scores (p=0.021) among those in early onset group on comparison with the late onset group.
Table 15: Comparison of DEMQOL scores among the two patient groups
DEMQOL, mean (±SD)
Onset of Dementia
p value*
Early (n=30) Late (n=30)
Feelings scores 22.83 (±3.752) 25.83 (±3.687) 0.002
Memory scores 13.70 (±2.277) 15.30 (±3.109) 0.027
Everyday life scores 18.33 (±2.309) 20.20 (±3.605) 0.021
Overall scores 1.93 (±0.740) 1.93 (±0.785) 0.016#
Total 57.10 (±7.308) 61.57 (±8.128) 0.029
*p value by independent t test #- p value by Mann Whitney U test
Table 15 and Figure 13-17 shows the distribution and comparison of DEMQOL scale and subscale scores among the two-patient groups.
For the feeling subscores, the mean score in early onset group was 22.83 (±3.752) while in late onset group was 25.83 (±3.687). For the memory subscores, the mean score in early onset group was 13.70 (±2.277) while in late onset group was 15.30 (±3.109). Similarly, for
