Browsing by Author "Silva, Dina"
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- Amyloid-negative, neurodegeneration-negative amnestic mild cognitive impairmentPublication . Cardoso, Sandra; Guerreiro, Manuela; Montalvo, Alexandre; Silva, Dina; Alves, Luísa; Mendonça, Alexandre deBackground:The concept of amnestic mild cognitive impairment (aMCI) was developed to identify patients at an initial stage of Alzheimer's disease (AD). However, some patients with aMCI do not present biomarkers of amyloid pathology or neuronal injury.Objective:To know the natural history of amyloid-negative and neurodegeneration-negative patients with aMCI, namely to ascertain: 1) whether these patients remain cognitively stable or they present a slow decline in neuropsychological tests; 2) whether the memory complaints subside with the apparently benign clinical course of the disorder or if they persist along the time.Methods:Patients who fulfilled criteria for aMCI with no biomarkers of amyloid pathology or neuronal injury were selected from a large cohort of non-demented patients with cognitive complaints, and were followed with clinical and neuropsychological assessments.Results:Twenty-one amyloid-negative and neurodegeneration-negative aMCI patients were followed for 7.1 +/- 3.7 years. At the baseline they had more pronounced deficits in verbal learning (California Verbal Learning Test) and were also impaired in Word Recall and Logical Memory. However, they did not decline in any cognitive test during follow-up. The patients maintained a high level of subjective memory complaints from baseline (9.7 +/- 4.1) to the follow-up visit (9.2 +/- 4.1, a non-significant difference), in spite of a statistically significant decrease in the depressive symptoms, with Geriatric Depression Scale (15 items) score 4.9 +/- 2.8 at baseline and 3.2 +/- 1.8 at the follow-up visit. Conclusions: Amyloid-negative, neurodegeneration-negative aMCI is a chronic clinical condition characterized by the long-term persistence of cognitive deficits and distressing memory complaints. Adequate strategies to treat this condition are needed.
- Biomarker-based prognosis for people with mild cognitive impairment (ABIDE): a modelling studyPublication . van Maurik, Ingrid S.; Vos, Stephanie J.; Bos, Isabelle; Bouwman, Femke H.; Teunissen, Charlotte E.; Scheitens, Philip; Barkhof, Frederik; Frolich, Lutz; Kornhuber, Johannes; Wiftfang, Jens; Maier, Wolfgang; Peters, Oliver; ROther, Eckart; Nobili, Flavio; Frisoni, Giovanni B.; Spiru, Luiza; Freund-Levi, Yvonne; Wallin, Asa K.; Hampel, Harald; Soininen, Hilkka; Tsolaki, Magda; Verhey, Frans; Kloszewska, Iwona; Mecocci, Patrizia; Vellas, Bruno; Lovestone, Simon; Gailuzzi, Samantha; Herukka, Sanna-Kaisa; Santana, Isabel; Baldeiras, Ines; de Mendonca, Alexandre; Silva, Dina; Chetelat, Gael; Egret, Stephanie; Palmqvist, Sebastian; Hansson, Oskar; Visser, Pieter Jelle; Berkhof, Johannes; van der Flier, Wiesje M.Background Biomarker-based risk predictions of dementia in people with mild cognitive impairment are highly relevant for care planning and to select patients for treatment when disease-modifying drugs become available. We aimed to establish robust prediction models of disease progression in people at risk of dementia. Methods In this modelling study, we included people with mild cognitive impairment (MCI) from single-centre and multicentre cohorts in Europe and North America: the European Medical Information Framework for Alzheimer’s Disease (EMIF-AD; n=883), Alzheimer’s Disease Neuroimaging Initiative (ADNI; n=829), Amsterdam Dementia Cohort (ADC; n=666), and the Swedish BioFINDER study (n=233). Inclusion criteria were a baseline diagnosis of MCI, at least 6 months of follow-up, and availability of a baseline Mini-Mental State Examination (MMSE) and MRI or CSF biomarker assessment. The primary endpoint was clinical progression to any type of dementia. We evaluated performance of previously developed risk prediction models—a demographics model, a hippocampal volume model, and a CSF biomarkers model—by evaluating them across cohorts, incorporating different biomarker measurement methods, and determining prognostic performance with Harrell’s C statistic. We then updated the models by re-estimating parameters with and without centre-specific effects and evaluated model calibration by comparing observed and expected survival. Finally, we constructed a model combining markers for amyloid deposition, tauopathy, and neurodegeneration (ATN), in accordance with the National Institute on Aging and Alzheimer’s Association research framework. Findings We included all 2611 individuals with MCI in the four cohorts, 1007 (39%) of whom progressed to dementia. The validated demographics model (Harrell’s C 0·62, 95% CI 0·59–0·65), validated hippocampal volume model (0·67, 0·62–0·72), and updated CSF biomarkers model (0·72, 0·68–0·74) had adequate prognostic performance across cohorts and were well calibrated. The newly constructed ATN model had the highest performance (0·74, 0·71–0·76). Interpretation We generated risk models that are robust across cohorts, which adds to their potential clinical applicability. The models could aid clinicians in the interpretation of CSF biomarker and hippocampal volume results in individuals with MCI, and help research and clinical settings to prepare for a future of precision medicine in Alzheimer’s disease. Future research should focus on the clinical utility of the models, particularly if their use affects participants’ understanding, emotional wellbeing, and behaviour. Funding ZonMW-Memorabel.
- Can Subjective Memory Complaints Identify A beta Positive and A beta Negative Amnestic Mild Cognitive Impairment Patients?Publication . Mendes, Tiago; Cardoso, Sandra; Guerreiro, Manuela; Maroco, Joao; Silva, Dina; Alves, Luisa; Schmand, Ben; Gerardo, Bianca; Lima, Marisa; Santana, Isabel; de Mendonca, AlexandreBackground: The use of biomarkers, in particular amyloid-beta (A(beta) changes, has allowed the possibility to identify patients with subjective memory complaints (SMCs) and amnestic mild cognitive impairment (aMCI) who suffer from Alzheimer's disease (AD). Since it is unfeasible that all patients with aMCI could presently undergo biomarkers assessment, it would be important that SMCs might contribute to identify the aMCI patients who have AD amyloid pathology. Objectives: To know whether aMCI patients with amyloid biomarkers (A beta(+)) present greater SMCs as compared to those without amyloid biomarkers (A beta(-)). Methods: Participants were selected from a cohort of nondemented patients with cognitive complaints and a comprehensive neuropsychological evaluation, on the basis of 1) diagnosis of aMCI
- Delay discounting in mild cognitive impairmentPublication . Coelho, Sara; Guerreiro, Manuela; Chester, Catarina; Silva, Dina; Maroco, Joao; Paglieri, Fabio; de Mendonca, AlexandreIntroduction: Patients with mild cognitive impairment (MCI) may make suboptimal decisions particularly in complex situations, and this could be due to temporal discounting, the tendency to prefer immediate rewards over delayed but larger rewards. The present study proposes to evaluate intertemporal preferences in MCI patients as compared to healthy controls. Method: Fifty-five patients with MCI and 57 healthy controls underwent neuropsychological evaluation and a delay discounting questionnaire, which evaluates three parameters: hyperbolic discounting (k), the percentage of choices for delayed and later rewards (%LL), and response consistency (Acc). Results: No significant differences were found in the delay discounting questionnaire between MCI patients and controls for the three reward sizes considered, small, medium, and large, using both k and %LL parameters. There were also no differences in the response consistency, Acc, between the two groups. Conclusions: Patients with MCI perform similarly to healthy controls in a delay discounting task. Memory deficits do not notably affect intertemporal preferences.
- Memory awareness in patients with Major Depressive DisorderPublication . Mendes, Tiago; Cardoso, Sandra; Guerreiro, Manuela; Maroco, João; Silva, Dina; Alves, Luísa; Schmand, Ben; Simões do Couto, Frederico; Figueira, Maria Luísa; de Mendonça, AlexandreBackground: Subjective Memory Complaints (SMC) along with cognitive deficits are frequently observed in patients with Major Depressive Disorder (MDD). The relationship between SMC and objective memory performance in patients with MDD was evaluated, in comparison with patients with Mild Cognitive Impairment due to Alzheimer’s Disease (MCI-AD) and healthy controls (HC). Methods: Patients with MDD (n = 47), MCI-AD (n = 43) and HC (n = 45) were assessed with a self-report memory complaints scale (SMCS) and underwent a comprehensive clinical and neuropsychological assessment. A discrepancy score between the Logical Memory delayed recall and the SMCS total score was calculated as a measure of memory awareness. Results: Patients with MDD (12.5 ± 4.4) and patients with MCI-AD (10.9 ± 4.1) had not significantly different SMCS total scores, whereas HC showed significantly lower scores (4.0 ± 3.0). As much as 74.5% of patients with MDD patients and 65.1% of patients with MCI-AD reported prominent memory complaints, whereas only 4.4% of HC did. Patients with MDD had relatively preserved memory tests, resulting in a higher discrepancy score than both patients with MCI-AD and HC. The SMCS total score correlated positively with depressive symptoms in the 3 groups of participants. Conclusions: Patients with MDD showed inaccurate memory self-awareness as they under-estimated their memory functioning, a pattern distinct from both patients with MCI-AD and HC.
- Mental time travel in mild cognitive impairmentPublication . Coelho, Sara; Guerreiro, Manuela; Chester, Catarina; Silva, Dina; Maroco, Joao; Paglieri, Fabio; de Mendonca, AlexandreIntroduction: Mental Time Travel (MTT) is the people's ability to remember themselves in the past and to imagine themselves in the future, and influence important life domains such as making decisions and planning future actions. It is widely recognized that patients with aMCI have deficits in episodic memory, but they also show impairments in semantic memory. It has been controversial whether MTT tasks are disturbed in aMCI mainly in relation to internal details related to episodic information, or external details, representing semantic and other extraneous information. The present study assessed whether patients with aMCI are affected in MTT regarding generation of internal details and external details, in past and future dimensions. Furthermore, it analyzed production in individual detail categories (internal: event details, thought/emotion, place, time, perceptual
- Neuropsychological contribution to predict conversion to dementia in patients with mild cognitive impairment due to Alzheimer's diseasePublication . Silva, Dina; Cardoso, Sandra; Guerreiro, Manuela; Maroco, Joao; Mendes, Tiago; Alves, Luisa; Nogueira, Joana; Baldeiras, Ines; Santana, Isabel; de Mendonca, AlexandreBackground: Diagnosis of Alzheimer's disease (AD) confirmed by biomarkers allows the patient to make important life decisions. However, doubt about the fleetness of symptoms progression and future cognitive decline remains. Neuropsychological measures were extensively studied in prediction of time to conversion to dementia for mild cognitive impairment (MCI) patients in the absence of biomarker information. Similar neuropsychological measures might also be useful to predict the progression to dementia in patients with MCI due to AD. Objective: To study the contribution of neuropsychological measures to predict time to conversion to dementia in patients with MCI due to AD. Methods: Patients with MCI due toADwere enrolled from a clinical cohort and the effect of neuropsychological performance on time to conversion to dementia was analyzed. Results: At baseline, converters scored lower than non-converters at measures of verbal initiative, non-verbal reasoning, and episodic memory. The test of non-verbal reasoning was the only statistically significant predictor in a multivariate Cox regression model. A decrease of one standard deviation was associated with 29% of increase in the risk of conversion to dementia. Approximately 50% of patients with more than one standard deviation below the mean in the z score of that test had converted to dementia after 3 years of follow-up. Conclusion: In MCI due to AD, lower performance in a test of non-verbal reasoning was associated with time to conversion to dementia. This test, that reveals little decline in the earlier phases of AD, appears to convey important information concerning conversion to dementia.
- Neuropsychological predictors of conversion from mild cognitive impairment to Alzheimer’s disease: a feature selection ensemble combining stability and predictabilityPublication . Pereira, Telma; Ferreira, Francisco L.; Cardoso, Sandra; Silva, Dina; Mendonça, Alexandre de; Guerreiro, Manuela; Madeira, Sara C.Background Predicting progression from Mild Cognitive Impairment (MCI) to Alzheimer’s Disease (AD) is an utmost open issue in AD-related research. Neuropsychological assessment has proven to be useful in identifying MCI patients who are likely to convert to dementia. However, the large battery of neuropsychological tests (NPTs) performed in clinical practice and the limited number of training examples are challenge to machine learning when learning prognostic models. In this context, it is paramount to pursue approaches that effectively seek for reduced sets of relevant features. Subsets of NPTs from which prognostic models can be learnt should not only be good predictors, but also stable, promoting generalizable and explainable models. Methods We propose a feature selection (FS) ensemble combining stability and predictability to choose the most relevant NPTs for prognostic prediction in AD. First, we combine the outcome of multiple (filter and embedded) FS methods. Then, we use a wrapper-based approach optimizing both stability and predictability to compute the number of selected features. We use two large prospective studies (ADNI and the Portuguese Cognitive Complaints Cohort, CCC) to evaluate the approach and assess the predictive value of a large number of NPTs. Results The best subsets of features include approximately 30 and 20 (from the original 79 and 40) features, for ADNI and CCC data, respectively, yielding stability above 0.89 and 0.95, and AUC above 0.87 and 0.82. Most NPTs learnt using the proposed feature selection ensemble have been identified in the literature as strong predictors of conversion from MCI to AD. Conclusions The FS ensemble approach was able to 1) identify subsets of stable and relevant predictors from a consensus of multiple FS methods using baseline NPTs and 2) learn reliable prognostic models of conversion from MCI to AD using these subsets of features. The machine learning models learnt from these features outperformed the models trained without FS and achieved competitive results when compared to commonly used FS algorithms. Furthermore, the selected features are derived from a consensus of methods thus being more robust, while releasing users from choosing the most appropriate FS method to be used in their classification task.
- Predicting progression of mild cognitive impairment to dementia using neuropsychological data: a supervised learning approach using time windowsPublication . Pereira, Telma; Lemos, Luis; Cardoso, Sandra; Silva, Dina; Rodrigues, Ana; Santana, Isabel; de Mendonca, Alexandre; Guerreiro, Manuela; Madeira, Sara C.Background: Predicting progression from a stage of Mild Cognitive Impairment to dementia is a major pursuit in current research. It is broadly accepted that cognition declines with a continuum between MCI and dementia. As such, cohorts of MCI patients are usually heterogeneous, containing patients at different stages of the neurodegenerative process. This hampers the prognostic task. Nevertheless, when learning prognostic models, most studies use the entire cohort of MCI patients regardless of their disease stages. In this paper, we propose a Time Windows approach to predict conversion to dementia, learning with patients stratified using time windows, thus fine-tuning the prognosis regarding the time to conversion. Methods: In the proposed Time Windows approach, we grouped patients based on the clinical information of whether they converted (converter MCI) or remained MCI (stable MCI) within a specific time window. We tested time windows of 2, 3, 4 and 5 years. We developed a prognostic model for each time window using clinical and neuropsychological data and compared this approach with the commonly used in the literature, where all patients are used to learn the models, named as First Last approach. This enables to move from the traditional question "Will a MCI patient convert to dementia somewhere in the future" to the question "Will a MCI patient convert to dementia in a specific time window". Results: The proposed Time Windows approach outperformed the First Last approach. The results showed that we can predict conversion to dementia as early as 5 years before the event with an AUC of 0.88 in the cross-validation set and 0.76 in an independent validation set. Conclusions: Prognostic models using time windows have higher performance when predicting progression from MCI to dementia, when compared to the prognostic approach commonly used in the literature. Furthermore, the proposed Time Windows approach is more relevant from a clinical point of view, predicting conversion within a temporal interval rather than sometime in the future and allowing clinicians to timely adjust treatments and clinical appointments.
- The influence of planning and response inhibition on cognitive functioning of Non-Psychotic unipolar depressed suicide attemptersPublication . Moniz, Marco; Jesus, Saul Neves de; Pacheco, Andreia; Gonçalves, Eduardo; Viseu, J.; Brás, Marta; Silva, Dina; Batista, SilviaDepression is one of the main risk factors for suicide. However, little is known about the intricate relationships among depressive symptomatology in unipolar depression, suicide risk, and the characteristics of executive dysfunction in depressed patients. We compared 20 non-psychotic unipolar depressed suicide attempters to 20 matching depressed non-attempters and to 20 healthy controls to further investigate the possible differences in neuropsychological performance. Depressed subjects were controlled for current suicidal ideation, and their neuropsychological profile was assessed using a range of measures of executive functioning, attention, verbal memory, processing speed, and psychomotor speed. Depressed groups were outperformed by healthy controls. Depressed attempters presented more cognitive impairment than depressed non-attempters on a simple Go/No-go response inhibition task and performed better than non-attempters on the Tower of London planning task. Depressed attempters were clearly distinguished by a deficit in response inhibition (Go/No-go commission errors). The normative planning performance (Tower of London extra moves) of the suicide attempters was unexpected, and this unanticipated finding calls for further research. Normative planning may indicate an increased risk of suicidal behavior.