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|Autori: ||Castellano, Sabrina|
|Titolo: ||Role of psychometric tools in the diagnosis and pharmacological treatment of Major Depression and Alzheimer s disease|
|Abstract: ||Psychometrics is the science of psychological measurement and is concerned with the objective measurement of skills and knowledge, abilities, attitudes, personality traits, and educational achievement. Efficacy trials with antidepressant drugs often fail to demonstrate beneficial effects, even though efficacious treatments are investigated, due, among other factors, to the lack of sensitivity of psychometric tools.
Affective disorders and particularly major depressive disorders (MDD) have been recently identified as new risk factors for the development of mild cognitive impairment and Alzheimer s disease (AD).
According to this clinical continuum between depression, MCI and AD new strategies of neuropsychological assessments should be explored by using multiple psychometric tools able to detect both affective and cognitive symptoms from depression and MCI to early AD.
Aim of the present Doctorate Thesis is to discuss recent evidence on the role of psychometric tools in the diagnosis of MDD and AD and in the evaluation of pharmacological treatment, focusing on a new combination of psychometric tools useful to detect early cognitive deficits both in MDD patients and MCI patients with an high risk to convert into AD.
The results presented in the PhD Thesis have been published in two articles on peer-reviewed journals, whereas a third study has been recently submitted for publication.
My first study demonstrated the efficacy of omega-3 in depressed patients and was based on psychometric data obtained with Hamilton Depression Rating Scale (HDRS) in published clinical studies. Omega-3 were also effective on bipolar disorder, although the evidence was weakened by the exclusion of three studies conducted on patients with MDD or on patients with depressive symptoms in which a lack of rigor in patients selection may lead to the inclusion of both normal emotional states and subthreshold depressed subjects, eventually affecting the results.
The study, in addition, highlights a number of methodological criticisms that mainly concern the inclusion criteria that should be more rigid and based on the score to psychometric tests rather than solely on clinical diagnosis. Psychometric instruments, in fact, represent an essential tool not only for a better diagnostic or for evaluating the efficacy of a treatment, but also for use inclusion criteria more rigid in order to improve the methodology in efficacy studies.
In the second study we critically reviewed the current literature on biological and neuropsychological markers in amnestic MCI patients who are at high risk to develop AD. A major conclusion of this study was that it is possible to identify a combination of neuropsychological tools (MMSE, MoCA, Rey s Test, FAB) and validated biological markers essential for an early diagnosis of AD and also for monitoring the response to disease modifying therapies in amnestic MCI patients who are at high risk to develop AD.
In the third study presented in this doctorate thesis we have adopted a new strategy of psychometric evaluation combining standard psychometric tools validated for the assessment of affective symptoms in MDD patients (HDRS and BDI-II) with neuropsychological tools such as MMSE, MoCA, FAB, Rey s 15 Words Test developed to detect cognitive deficits in mild cognitive impairment or in early AD.
The main finding of our observational study is that both SSRIs and SNRIs can improve cognitive symptoms independently from their clinical efficacy on affective symptoms.
As a neurobiological and clinical continuum exists between major depression, MCI, and dementia, we believe that our strategy of neuropsychological assessments can be applied to a wide range of patients from MDD to MCI/AD. This neuropsychological battery might represent a new tool to detect in future clinical studies affective symptoms and early cognitive deficits not only in MDD patients, but also in MCI patients with an high risk to convert into AD.|
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|CSTSRN84D70F158N-Tesi Castellano.pdf||Tesi Castellano||1,23 MB||Adobe PDF||Visualizza/apri
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