There is a growing body of evidence that subtle deficits in instrumental activities of daily living (IADL) may be present in mild cognitive impairment (MCI). However, it is not clear if there are ...IADL domains that are consistently affected across patients with MCI. In this systematic review, therefore, we aimed to summarize research results regarding the performance of MCI patients in specific IADL (sub)domains compared with persons who are cognitively normal and/or patients with dementia.
The databases PsycINFO, PubMed and Web of Science were searched for relevant literature in December 2013. Publications from 1999 onward were considered for inclusion. Altogether, 497 articles were retrieved. Reference lists of selected articles were searched for potentially relevant articles. After screening the abstracts of these 497 articles, 37 articles were included in this review.
In 35 studies, IADL deficits (such as problems with medication intake, telephone use, keeping appointments, finding things at home and using everyday technology) were documented in patients with MCI. Financial capacity in patients with MCI was affected in the majority of studies. Effect sizes for group differences between patients with MCI and healthy controls were predominantly moderate to large. Performance-based instruments showed slight advantages (in terms of effect sizes) in detecting group differences in IADL functioning between patients with MCI, patients with Alzheimer's disease and healthy controls.
IADL requiring higher neuropsychological functioning seem to be most severely affected in patients with MCI. A reliable identification of such deficits is necessary, as patients with MCI with IADL deficits seem to have a higher risk of converting to dementia than patients with MCI without IADL deficits. The use of assessment tools specifically designed and validated for patients with MCI is therefore strongly recommended. Furthermore, the development of performance-based assessment instruments should be intensified, as they allow a valid and reliable assessment of subtle IADL deficits in MCI, even if a proxy is not available. Another important point to consider when designing new scales is the inclusion of technology-associated IADL. Novel instruments for clinical practice should be time-efficient and easy to administer.
•The performance of a deep learning model for visual ratings of atrophy was investigated in clinical out-of-distribution data.•Model is more robust on unseen clinical data when trained on more ...heterogeneous training data.•Model trained on research data with harmonized protocols perform well in cohorts where data is acquired with similar scanning parameters but fails in others.
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Deep learning (DL) methods have in recent years yielded impressive results in medical imaging, with the potential to function as clinical aid to radiologists. However, DL models in medical imaging are often trained on public research cohorts with images acquired with a single scanner or with strict protocol harmonization, which is not representative of a clinical setting. The aim of this study was to investigate how well a DL model performs in unseen clinical datasets–collected with different scanners, protocols and disease populations–and whether more heterogeneous training data improves generalization. In total, 3117 MRI scans of brains from multiple dementia research cohorts and memory clinics, that had been visually rated by a neuroradiologist according to Scheltens’ scale of medial temporal atrophy (MTA), were included in this study. By training multiple versions of a convolutional neural network on different subsets of this data to predict MTA ratings, we assessed the impact of including images from a wider distribution during training had on performance in external memory clinic data. Our results showed that our model generalized well to datasets acquired with similar protocols as the training data, but substantially worse in clinical cohorts with visibly different tissue contrasts in the images. This implies that future DL studies investigating performance in out-of-distribution (OOD) MRI data need to assess multiple external cohorts for reliable results. Further, by including data from a wider range of scanners and protocols the performance improved in OOD data, which suggests that more heterogeneous training data makes the model generalize better. To conclude, this is the most comprehensive study to date investigating the domain shift in deep learning on MRI data, and we advocate rigorous evaluation of DL models on clinical data prior to being certified for deployment.
Abstract This article presents recommendations, based on the Grading of Recommendations, Assessment, Development, and Evaluation method, for the clinical application of cerebrospinal fluid (CSF) ...amyloid-β1–42 , tau, and phosphorylated tau in the diagnostic evaluation of patients with dementia. The recommendations were developed by a multidisciplinary working group based on the available evidence and consensus from focused discussions for (i) identification of Alzheimer's disease (AD) as the cause of dementia, (ii) prediction of rate of decline, (iii) cost-effectiveness, and (iv) interpretation of results. The working group found sufficient evidence to support a recommendation to use CSF AD biomarkers as a supplement to clinical evaluation, particularly in uncertain and atypical cases, to identify or exclude AD as the cause of dementia. Because of insufficient evidence, it was uncertain whether CSF AD biomarkers outperform imaging biomarkers. Operational recommendations for the interpretation of ambiguous CSF biomarker results were also provided.
This article presents recommendations, based on the Grading of Recommendations, Assessment, Development, and Evaluation method, for the clinical application of cerebrospinal fluid (CSF) ...amyloid-β1–42, tau, and phosphorylated tau in the diagnostic evaluation of patients with mild cognitive impairment (MCI). The recommendations were developed by a multidisciplinary working group and based on the available evidence and consensus from focused group discussions for 1) prediction of clinical progression to Alzheimer's disease (AD) dementia, 2) cost-effectiveness, 3) interpretation of results, and 4) patient counseling. The working group recommended using CSF AD biomarkers in the diagnostic workup of MCI patients, after prebiomarker counseling, as an add-on to clinical evaluation to predict functional decline or conversion to AD dementia and to guide disease management. Because of insufficient evidence, it was uncertain whether CSF AD biomarkers outperform imaging biomarkers. Furthermore, the working group provided recommendations for interpretation of ambiguous CSF biomarker results and for pre- and post-biomarker counseling.
Cerebrospinal fluid (CSF) has been extensively studied to explore biochemical alterations in subjects with neurodegenerative disorders. In Alzheimer's disease, levels of increased CSF tau protein and ...decreased levels of β‐amyloid 1–42 (Aβ42) have been shown to correlate with brain plaque formation and tangle pathology. Intracellular Lewy inclusions containing aggregated α‐synuclein (α‐syn) represent a pathological hallmark of Parkinson's disease (PD). In most – but not all – studies published to date total CSF α‐syn concentrations have been found to be decreased in disorders related to α‐syn pathology, that is, PD, dementia with Lewy bodies and multiple system atrophy. However, these reports show extensive signal overlap among tested individuals, thereby diminishing its potential for routine use in clinical practice.
To investigate potential biological (i.e., non‐technical) confounders of reported CSF levels for α‐syn, Aβ42, and tau in PD and related disorders, we carried out a methodical review of known factors that underlie signal variability and speculate on those that have not yet been tested. We discuss several biological factors, such as neuropathology, demographics, clinical phenotype, progression and duration of disease, concomitant illnesses and, last but not least, pharmacotherapy, which in isolation or combination can substantially alter values for CSF proteins of interest. Enhanced implementation of standardized clinical protocols, streamlined operating procedures, and further progress in the development of validated assays for CSF proteins have the potential to (i) inform us as to the pathogenesis of disease, (ii) support the laboratory‐based diagnosis for symptomatic subjects in the future, and (iii) facilitate breakthrough therapies to alter the course of neurodegenerative disorders, such as PD and Alzheimer's disease.
Cerebrospinal fluid (CSF) has been extensively studied to explore biochemical alterations in subjects with neurodegenerative disorders. To investigate potential biological confounders of reported CSF levels for α‐synuclein (α‐Syn), amyloid‐β 1‐42(Aβ42) and tau protein in Parkinson's disease and related disorders, we reviewed the current literature for known factors that underlie signal variability and speculate on those that have not yet been tested.
This article is part of a special issue on Parkinson disease.
Cerebrospinal fluid (CSF) has been extensively studied to explore biochemical alterations in subjects with neurodegenerative disorders. To investigate potential biological confounders of reported CSF levels for α‐synuclein (α‐Syn), amyloid‐β 1‐42(Aβ42) and tau protein in Parkinson's disease and related disorders, we reviewed the current literature for known factors that underlie signal variability and speculate on those that have not yet been tested.
This article is part of a special issue on Parkinson disease.
IMPORTANCE: Cerebral amyloid-β aggregation is an early pathological event in Alzheimer disease (AD), starting decades before dementia onset. Estimates of the prevalence of amyloid pathology in ...persons without dementia are needed to understand the development of AD and to design prevention studies. OBJECTIVE: To use individual participant data meta-analysis to estimate the prevalence of amyloid pathology as measured with biomarkers in participants with normal cognition, subjective cognitive impairment (SCI), or mild cognitive impairment (MCI). DATA SOURCES: Relevant biomarker studies identified by searching studies published before April 2015 using the MEDLINE and Web of Science databases and through personal communication with investigators. STUDY SELECTION: Studies were included if they provided individual participant data for participants without dementia and used an a priori defined cutoff for amyloid positivity. DATA EXTRACTION AND SYNTHESIS: Individual records were provided for 2914 participants with normal cognition, 697 with SCI, and 3972 with MCI aged 18 to 100 years from 55 studies. MAIN OUTCOMES AND MEASURES: Prevalence of amyloid pathology on positron emission tomography or in cerebrospinal fluid according to AD risk factors (age, apolipoprotein E APOE genotype, sex, and education) estimated by generalized estimating equations. RESULTS: The prevalence of amyloid pathology increased from age 50 to 90 years from 10% (95% CI, 8%-13%) to 44% (95% CI, 37%-51%) among participants with normal cognition; from 12% (95% CI, 8%-18%) to 43% (95% CI, 32%-55%) among patients with SCI; and from 27% (95% CI, 23%-32%) to 71% (95% CI, 66%-76%) among patients with MCI. APOE-ε4 carriers had 2 to 3 times higher prevalence estimates than noncarriers. The age at which 15% of the participants with normal cognition were amyloid positive was approximately 40 years for APOE ε4ε4 carriers, 50 years for ε2ε4 carriers, 55 years for ε3ε4 carriers, 65 years for ε3ε3 carriers, and 95 years for ε2ε3 carriers. Amyloid positivity was more common in highly educated participants but not associated with sex or biomarker modality. CONCLUSIONS AND RELEVANCE: Among persons without dementia, the prevalence of cerebral amyloid pathology as determined by positron emission tomography or cerebrospinal fluid findings was associated with age, APOE genotype, and presence of cognitive impairment. These findings suggest a 20- to 30-year interval between first development of amyloid positivity and onset of dementia.
Concomitant Alzheimer's disease (AD) pathology is observed in Lewy body diseases (LBD), but the clinical impact is unknown. Only a few biomarker studies in LBD exist and have included small cohorts ...from single centers.
We aimed to evaluate the prevalence of abnormal cerebrospinal fluid (CSF) AD biomarkers across the spectrum of LBD in a large multicenter cohort and to assess whether an AD biomarker profile was associated with demographic and clinical differences in dementia with Lewy bodies (DLB).
We included 375 DLB patients, 164 Parkinson's disease (PD) patients without dementia, and 55 PD patients with dementia (PDD) from 10 centers. CSF amyloid-beta42 (Aβ42), total tau (t-tau), and phosphorylated tau (p-tau) values were dichotomized as abnormal or normal according to locally available cut-off values. A CSF AD profile was defined as abnormal Aβ42 combined with abnormal t-tau and/or p-tau.
A substantial proportion of DLB patients had abnormal values for CSF Aβ42, t-tau, and p-tau, while abnormal values were uncommon in PD without dementia. Patients with PDD had values in between. A CSF AD profile was observed in 25% of DLB patients, compared with only 9% of PDD and 3% of PD without dementia. Within DLB, patients with a CSF AD profile were older, more often female, performed worse on the Mini-Mental State Examination, and had shorter disease duration compared with patients with normal CSF.
A CSF AD profile is more common in DLB compared with PDD and PD, and is associated with more severe cognitive impairment in DLB.
This expert working group report proposes an updated approach to subtype definition of vascular parkinsonism (VaP) based on a review of the existing literature. The persistent lack of consensus on ...clear terminology and inconsistent conceptual definition of VaP formed the impetus for the current expert recommendation report. The updated diagnostic approach intends to provide a comprehensive tool for clinical practice. The preamble for this initiative is that VaP can be diagnosed in individual patients with possible prognostic and therapeutic consequences and therefore should be recognized as a clinical entity. The diagnosis of VaP is based on the presence of clinical parkinsonism, with variable motor and non-motor signs that are corroborated by clinical, anatomic or imaging findings of cerebrovascular disease. Three VaP subtypes are presented: (1) The acute or subacute post-stroke VaP subtype presents with acute or subacute onset of parkinsonism, which is typically asymmetric and responds to dopaminergic drugs; (2) The more frequent insidious onset VaP subtype presents with progressive parkinsonism with prominent postural instability, gait impairment, corticospinal, cerebellar, pseudobulbar, cognitive and urinary symptoms and poor responsiveness to dopaminergic drugs. A higher-level gait disorder occurs frequently as a dominant manifestation in the clinical spectrum of insidious onset VaP, and (3) With the emergence of molecular imaging biomarkers in clinical practice, our diagnostic approach also allows for the recognition of mixed or overlapping syndromes of VaP with Parkinson's disease or other neurodegenerative parkinsonisms. Directions for future research are also discussed.
•The diagnosis of VaP is based on convergence of parkinsonism with findings consistent with cerebrovascular disease.
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