Practice parameter: diagnosis of dementia (an evidence-based review). Report of the Quality Standards Subcommittee of the American Academy of Neurology

Handgrip Strength Is Related to Hippocampal and Lobar Brain Volumes in a Cohort of Cognitively Impaired Older Adults with Confirmed Amyloid Burden

BACKGROUND

Strength and mobility are essential for activities of daily living. With aging, weaker handgrip strength, mobility, and asymmetry predict poorer cognition. We therefore sought to quantify the relationship between handgrip metrics and volumes quantified on brain magnetic resonance imaging (MRI).

OBJECTIVE

To model the relationships between handgrip strength, mobility, and MRI volumetry.

METHODS

We selected 38 participants with Alzheimer's disease dementia: biomarker evidence of amyloidosis and impaired cognition. Handgrip strength on dominant and non-dominant hands was measured with a hand dynamometer. Handgrip asymmetry was calculated. Two-minute walk test (2MWT) mobility evaluation was combined with handgrip strength to identify non-frail versus frail persons. Brain MRI volumes were quantified with Neuroreader. Multiple regression adjusting for age, sex, education, handedness, body mass index, and head size modeled handgrip strength, asymmetry and 2MWT with brain volumes. We modeled non-frail versus frail status relationships with brain structures by analysis of covariance.

RESULTS

Higher non-dominant handgrip strength was associated with larger volumes in the hippocampus (p = 0.02). Dominant handgrip strength was related to higher frontal lobe volumes (p = 0.02). Higher 2MWT scores were associated with larger hippocampal (p = 0.04), frontal (p = 0.01), temporal (p = 0.03), parietal (p = 0.009), and occipital lobe (p = 0.005) volumes. Frailty was associated with reduced frontal, temporal, and parietal lobe volumes.

CONCLUSION

Greater handgrip strength and mobility were related to larger hippocampal and lobar brain volumes. Interventions focused on improving handgrip strength and mobility may seek to include quantified brain volumes on MR imaging as endpoints.

Fluids and flows in brain cancer and neurological disorders

Interstitial fluid (IF) and cerebrospinal fluid (CSF) are an integral part of the brain, serving to cushion and protect the brain parenchymal cells against damage and aid in their function. The brain IF contains various ions, nutrients, waste products, peptides, hormones, and neurotransmitters. IF moves primarily by pressure-dependent bulk flow through brain parenchyma, draining into the ventricular CSF. The brain ventricles and subarachnoid spaces are filled with CSF which circulates through the perivascular spaces. It also flows into the IF space regulated, in part, by aquaporin channels, removing waste solutes through a process of IF-CSF mixing. During disease development, the composition, flow, and volume of these fluids changes and can lead to brain cell dysfunction. With the improvement of imaging technology and the help of genomic profiling, more information has been and can be obtained from brain fluids; however, the role of CSF and IF in brain cancer and neurobiological disease is still limited. Here we outline recent advances of our knowledge of brain fluid flow in cancer and neurodegenerative disease based on our understanding of its dynamics and composition. This article is categorized under: Cancer > Biomedical Engineering Neurological Diseases > Biomedical Engineering.

Insulin Resistance and Cognitive Impairment: Evidence From Neuroimaging

Insulin is a peptide well known for its role in regulating glucose metabolism in peripheral tissues. Emerging evidence from human and animal studies indicate the multifactorial role of insulin in the brain, such as neuronal and glial metabolism, glucose regulation, and cognitive processes. Insulin resistance (IR), defined as reduced sensitivity to the action of insulin, has been consistently proposed as an important risk factor for developing neurodegeneration and cognitive impairment. Although the exact mechanism of IR-related cognitive impairment still awaits further elucidation, neuroimaging offers a versatile set of novel contrasts to reveal the subtle cerebral abnormalities in IR. These imaging contrasts, including but not limited to brain volume, white matter (WM) microstructure, neural function and brain metabolism, are expected to unravel the nature of the link between IR, cognitive decline, and brain abnormalities, and their changes over time. This review summarizes the current neuroimaging studies with multiparametric techniques, focusing on the cerebral abnormalities related to IR and therapeutic effects of IR-targeting treatments. According to the results, brain regions associated with IR pathophysiology include the medial temporal lobe, hippocampus, prefrontal lobe, cingulate cortex, precuneus, occipital lobe, and the WM tracts across the globe. Of these, alterations in the temporal lobe are highly reproducible across different imaging modalities. These structures have been known to be vulnerable to Alzheimer's disease (AD) pathology and are critical in cognitive processes such as memory and executive functioning. Comparing to asymptomatic subjects, results are more mixed in patients with metabolic disorders such as type 2 diabetes and obesity, which might be attributed to a multifactorial mechanism. Taken together, neuroimaging, especially MRI, is beneficial to reveal early abnormalities in cerebral structure and function in insulin-resistant brain, providing important evidence to unravel the underlying neuronal substrate that reflects the cognitive decline in IR. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 2.

The Alzheimer's Association appropriate use recommendations for blood biomarkers in Alzheimer's disease

Blood-based markers (BBMs) have recently shown promise to revolutionize the diagnostic and prognostic work-up of Alzheimer's disease (AD), as well as to improve the design of interventional trials. Here we discuss in detail further research needed to be performed before widespread use of BBMs. We already now recommend use of BBMs as (pre-)screeners to identify individuals likely to have AD pathological changes for inclusion in trials evaluating disease-modifying therapies, provided the AD status is confirmed with positron emission tomography (PET) or cerebrospinal fluid (CSF) testing. We also encourage studying longitudinal BBM changes in ongoing as well as future interventional trials. However, BBMs should not yet be used as primary endpoints in pivotal trials. Further, we recommend to cautiously start using BBMs in specialized memory clinics as part of the diagnostic work-up of patients with cognitive symptoms and the results should be confirmed whenever possible with CSF or PET. Additional data are needed before use of BBMs as stand-alone diagnostic AD markers, or before considering use in primary care.

Interpretable brain disease classification and relevance-guided deep learning

Deep neural networks are increasingly used for neurological disease classification by MRI, but the networks' decisions are not easily interpretable by humans. Heat mapping by deep Taylor decomposition revealed that (potentially misleading) image features even outside of the brain tissue are crucial for the classifier's decision. We propose a regularization technique to train convolutional neural network (CNN) classifiers utilizing relevance-guided heat maps calculated online during training. The method was applied using T1-weighted MR images from 128 subjects with Alzheimer's disease (mean age = 71.9 ± 8.5 years) and 290 control subjects (mean age = 71.3 ± 6.4 years). The developed relevance-guided framework achieves higher classification accuracies than conventional CNNs but more importantly, it relies on less but more relevant and physiological plausible voxels within brain tissue. Additionally, preprocessing effects from skull stripping and registration are mitigated. With the interpretability of the decision mechanisms underlying CNNs, these results challenge the notion that unprocessed T1-weighted brain MR images in standard CNNs yield higher classification accuracy in Alzheimer's disease than solely atrophy.

Moments of meeting: A case study of Shared Reading of poetry in a care home

There is a growing research interest in the value of participative arts-based strategies for enhancing wellbeing amongst adults living with dementia. One such intervention, centred around literature, is the group activity called Shared Reading. The purpose of this case study of weekly Shared Reading sessions of poetry in a care home in Merseyside is to investigate instances of how participants with mild to moderate dementia collaborate in processes of meaning-making that allow them shared experiences of being moved by poetry. An under-thematised aspect of psychological wellbeing is the capacity for being moved and for sharing such moments. This article addresses the following question: how can the specific multimodality of the text (participants have a copy of the text before them, the poem is read aloud and there may be use of non-verbal aids) in the Shared Reading model help to bring about such experiences? Using Stern’s concepts of Now Moments and Moments of Meeting, this case study discusses various instances of unpredictable, surprising and spontaneous intersubjective moments between participant and poem, participant and reader leader, participant and staff, participant and relative.

Diagnosis of Alzheimer’s disease: recommendations of the Scientific Department of Cognitive Neurology and Aging of the Brazilian Academy of Neurology

ABSTRACT This paper presents the consensus of the Scientific Department of Cognitive Neurology and Aging from the Brazilian Academy of Neurology on the diagnostic criteria for Alzheimer’s disease (AD) in Brazil. The authors conducted a literature review regarding clinical and research criteria for AD diagnosis and proposed protocols for use at primary, secondary, and tertiary care levels. Within this clinical scenario, the diagnostic criteria for typical and atypical AD are presented as well as clinical, cognitive, and functional assessment tools and complementary propaedeutics with laboratory and neuroimaging tests. The use of biomarkers is also discussed for both clinical diagnosis (in specific conditions) and research.

Diagnosis of Alzheimer's disease: recommendations of the Scientific Department of Cognitive Neurology and Aging of the Brazilian Academy of Neurology

This paper presents the consensus of the Scientific Department of Cognitive Neurology and Aging from the Brazilian Academy of Neurology on the diagnostic criteria for Alzheimer's disease (AD) in Brazil. The authors conducted a literature review regarding clinical and research criteria for AD diagnosis and proposed protocols for use at primary, secondary, and tertiary care levels. Within this clinical scenario, the diagnostic criteria for typical and atypical AD are presented as well as clinical, cognitive, and functional assessment tools and complementary propaedeutics with laboratory and neuroimaging tests. The use of biomarkers is also discussed for both clinical diagnosis (in specific conditions) and research.

Specific Challenges in Geriatric Cirrhosis and Hepatic Encephalopathy

As the world's population ages, diseases predominantly found in the elderly now overlap with diseases that were thought to be the purview of younger patients. This includes chronic liver disease, which affects more than 2 billion people worldwide. Owing to the obesity epidemic (and associated metabolic diseases), nonalcoholic fatty liver disease has become the most common cause of chronic liver disease and cirrhosis. A major complication of cirrhosis is hepatic encephalopathy (HE), which becomes challenging to diagnose in elderly patients. HE is usually included in the differential diagnosis of acute delirium but not of reversible dementias. To illustrate this point, we present 2 cases of older patients that were misdiagnosed as having dementia and Parkinson's disease or a parkinsonian syndrome but had contributions from cirrhosis. Both cognitive impairment and tremor resolved with treatment of HE.

The 5-Cog paradigm to improve detection of cognitive impairment and dementia: clinical trial protocol

Cognitive impairment related to dementia is under-diagnosed in primary care despite availability of numerous cognitive assessment tools; under-diagnosis is more prevalent for members of racial and ethnic minority groups. Clinical decision-support systems may improve rates of primary care providers responding to positive cognitive assessments with appropriate follow-up. The 5-Cog study is a randomized controlled trial in 1200 predominantly Black and Hispanic older adults from an urban underserved community who are presenting to primary care with cognitive concerns. The study will validate a novel 5-minute cognitive assessment coupled with an electronic medical record-embedded decision tree to overcome the barriers of current cognitive assessment paradigms in primary care and facilitate improved dementia care.

[18F]THK-5351 PET Patterns in Patients With Alzheimer's Disease and Negative Amyloid PET Findings

Background and Purpose

Alzheimer’s disease (AD) does not always mean amyloid positivity. [¹⁸F]THK-5351 has been shown to be able to detect reactive astrogliosis as well as tau accompanied by neurodegenerative changes. We evaluated the [¹⁸F]THK-5351 retention patterns in positron-emission tomography (PET) and the clinical characteristics of patients clinically diagnosed with AD dementia who had negative amyloid PET findings.

Methods

We performed 3.0-T magnetic resonance imaging, [¹⁸F]THK-5351 PET, and amyloid PET in 164 patients with AD dementia. Amyloid PET was visually scored as positive or negative. [¹⁸F]THK-5351 PET were visually classified as having an intratemporal or extratemporal spread pattern.

Results

The 164 patients included 23 (14.0%) who were amyloid-negative (age 74.9±8.3 years, mean±standard deviation; 9 males, 14 females). Amyloid-negative patients were older, had a higher prevalence of diabetes mellitus, and had better visuospatial and memory functions. The frequency of the apolipoprotein E ε4 allele was higher and the hippocampal volume was smaller in amyloid-positive patients. [¹⁸F]THK-5351 uptake patterns of the amyloid-negative patients were classified into intratemporal spread (n=10) and extratemporal spread (n=13). Neuropsychological test results did not differ significantly between these two groups. The standardized uptake value ratio of [¹⁸F]THK-5351 was higher in the extratemporal spread group (2.01±0.26 vs. 1.61±0.15, p=0.001). After 1 year, Mini Mental State Examination (MMSE) scores decreased significantly in the extratemporal spread group (-3.5±3.2, p=0.006) but not in the intratemporal spread group (-0.5±2.8, p=0.916). The diagnosis remained as AD (n=5, 50%) or changed to other diagnoses (n=5, 50%) in the intratemporal group, whereas it remained as AD (n=8, 61.5%) or changed to frontotemporal dementia (n=4, 30.8%) and other diagnoses (n=1, 7.7%) in the extratemporal spread group.

Conclusions

Approximately 70% of the patients with amyloid-negative AD showed abnormal [¹⁸F]THK-5351 retention. MMSE scores deteriorated rapidly in the patients with an extratemporal spread pattern.

Multimodal deep learning for Alzheimer's disease dementia assessment

Worldwide, there are nearly 10 million new cases of dementia annually, of which Alzheimer's disease (AD) is the most common. New measures are needed to improve the diagnosis of individuals with cognitive impairment due to various etiologies. Here, we report a deep learning framework that accomplishes multiple diagnostic steps in successive fashion to identify persons with normal cognition (NC), mild cognitive impairment (MCI), AD, and non-AD dementias (nADD). We demonstrate a range of models capable of accepting flexible combinations of routinely collected clinical information, including demographics, medical history, neuropsychological testing, neuroimaging, and functional assessments. We then show that these frameworks compare favorably with the diagnostic accuracy of practicing neurologists and neuroradiologists. Lastly, we apply interpretability methods in computer vision to show that disease-specific patterns detected by our models track distinct patterns of degenerative changes throughout the brain and correspond closely with the presence of neuropathological lesions on autopsy. Our work demonstrates methodologies for validating computational predictions with established standards of medical diagnosis.

Subclinical Hypothyroidism and Cognitive Impairment

BACKGROUND

Although thyroid dysfunction has been considered as a cause of reversible cognitive impairment, association between subclinical hypothyroidism and cognitive impairment is controversial.

OBJECTIVE

We compared cognitive profiles of patients in an euthyroid or subclinical hypothyroid (sHypo) state, as well as their disease progression from mild cognitive impairment (MCI) to dementia within 3 years.

METHODS

We included 2,181 patients in a euthyroid and 284 in a sHypo state over 60 years of age who underwent an extensive cognitive assessment at Seoul National University Bundang Hospital but were not prescribed levothyroxine, methimazole, carbimazole, or propylthiouracil. After propensity score matching for age, sex, and education level, 1,118 patients in a euthyroid and 283 patients in a sHypo state were included. Attention, language, memory, visuocontructive, and executive functions were compared between the groups using Student's t-test or the Mann-Whitney U test. To investigate the association between disease progression and subclinical hypothyroidism, a Cox regression analyses was performed in 1,265 patients with MCI. Patients with thyroid-stimulating hormone levels over 10 mlU/L was classified as the "sHypo10", and hazard ratios for sHypo or sHypo10 were assessed.

RESULTS

There was no difference in attention, language, memory, visuoconstructive, and executive functions between the patient groups. Progression from MCI to dementia was not associated with sHypo or sHypo10.

CONCLUSION

There was no difference in cognitive profile between euthyroid and sHypo patients, and no association between subclinical hypothyroidism and disease progression. This might suggest a clue of strategies regarding hormone therapy in subclinical hypothyroidism with cognitive impairment.

Atypical Alzheimer Disease Variants

PURPOSE OF REVIEW

This article discusses the clinical, neuroimaging, and biomarker profiles of sporadic atypical Alzheimer disease (AD) variants, including early-onset AD, posterior cortical atrophy, logopenic variant primary progressive aphasia, dysexecutive variant and behavioral variant AD, and corticobasal syndrome.

RECENT FINDINGS

Significant advances are being made in the recognition and characterization of the syndromically diverse AD variants. These variants are identified by the predominant cognitive and clinical features: early-onset amnestic syndrome, aphasia, visuospatial impairments, dysexecutive and behavioral disturbance, or motor symptoms. Although understanding of regional susceptibility to disease remains in its infancy, visualizing amyloid and tau pathology in vivo and CSF examination of amyloid-β and tau proteins are particularly useful in atypical AD, which can be otherwise prone to misdiagnosis. Large-scale research efforts, such as LEADS (the Longitudinal Early-Onset Alzheimer Disease Study), are currently ongoing and will continue to shed light on our understanding of these diverse presentations.

SUMMARY

Understanding the clinical, neuroimaging, and biomarker profiles of the heterogeneous group of atypical AD syndromes improves diagnostic accuracy in patients who are at increased risk of misdiagnosis. Earlier accurate identification facilitates access to important interventions, social services and disability assistance, and crucial patient and family education.

Impact of arterial hypertension and its management strategies on cognitive function and dementia: a comprehensive umbrella review

INTRODUCTION

Cognitive decline and dementia recognize multiple risk factors and pathophysiological mechanisms, often involved simultaneously with complex interactions. Several studies have shown that both arterial hypertension and hypotension are associated with a greater risk of cognitive decline and dementia, but clinical evidence on this point is conflicting. Our aim was to conduct an umbrella review on cognitive function, dementia, and blood pressure, with particular attention to epidemiological, prognostic and therapeutic aspects.

EVIDENCE ACQUISITION

We conducted a dedicated literature search on PubMed for systematic reviews and meta-analyses that focused on arterial pressure, hypertension, hypotension and similar conditions, and cognitive function, cognitive decline and dementia. The internal validity of systematic reviews and meta-analyses was formally analyzed using the OQAQ tool. The umbrella review was planned in accordance with current international recommendations and was described as specified by the PRISMA guidelines.

EVIDENCE SYNTHESIS

Seventeen systematic reviews (including 13 meta-analyses) were included, for a total of 675 clinical studies and over 1 million patients. Hypertension results to be associated with a lower risk of Alzheimer's dementia, greater risk of vascular dementia and greater risk of cognitive decline. Orthostatic hypotension seems to be associated with greater risk of Alzheimer's dementia, vascular dementia and dementia of Parkinson's disease. Therapy with acetylcholinesterase inhibitors produces lower risk of cardiovascular events, greater risk of hypertension and greater risk of bradycardia, while the anti-hypertensive therapy leads to a lower risk of dementia of all types and lower risk of cognitive decline.

CONCLUSIONS

To date, the evidence on the relationship between blood pressure, cognitive decline and dementia provides somewhat heterogeneous data. Further studies are clearly needed, with explicit inclusion criteria as objective as possible, adequate follow-up and precise characterization of implemented cardiovascular and cognitive treatments.

Alzheimer Disease

PURPOSE OF REVIEW

Alzheimer disease (AD) is the most common cause of dementia in adults (mid to late life), highlighting the importance of understanding the risk factors, clinical manifestations, and recent developments in diagnostic testing and therapeutics.

RECENT FINDINGS

Advances in fluid (CSF and blood-based) and imaging biomarkers are allowing for a more precise and earlier diagnosis of AD (relative to non-AD dementias) across the disease spectrum and in patients with atypical clinical features. Specifically, tau- and amyloid-related AD pathologic changes can now be measured by CSF, plasma, and positron emission tomography (PET) with good precision. Additionally, a better understanding of risk factors for AD has highlighted the need for clinicians to address comorbidities to maximize prevention of cognitive decline in those at risk or to slow decline in patients who are symptomatic. Recent clinical trials of amyloid-lowering drugs have provided not only some optimism that amyloid reduction or prevention may be beneficial but also a recognition that addressing additional targets will be necessary for significant disease modification.

SUMMARY

Recent developments in fluid and imaging biomarkers have led to the improved understanding of AD as a chronic condition with a protracted presymptomatic phase followed by the clinical stage traditionally recognized by neurologists. As clinical trials of potential disease-modifying therapies continue, important developments in the understanding of the disease will improve clinical care now and lead to more effective therapies in the near future.

Fluid Biomarkers in Dementia Diagnosis

PURPOSE OF REVIEW

This article discusses how fluid biomarkers can augment the routine dementia evaluation and improve diagnostic accuracy. The tests that are currently available and the indications for their use are described. Further, tests that are under development and likely to be used in the future are identified.

RECENT FINDINGS

Technical improvements in assay sensitivity and precision have led to the rapid development of blood-based biomarkers for Alzheimer disease (AD) over the past several years. Studies have found that the ratio of amyloid-β (Aβ) peptides (Aβ42/Aβ40) and concentrations of phosphorylated tau isoforms in plasma can identify individuals with AD brain pathology. Blood-based tests may enable much broader use of AD biomarkers in the evaluation of patients with cognitive impairment.

SUMMARY

Even after a detailed history, examination, routine laboratory testing, and brain imaging, the cause of dementia sometimes remains unclear. CSF and blood-based biomarkers can evaluate for a range of neurologic disorders that are associated with dementia, including AD. Integrating data from fluid biomarker tests and the routine dementia evaluation may improve the accuracy of dementia diagnosis.

Monoamine oxidase binding not expected to significantly affect [18F]flortaucipir PET interpretation

Purpose

[¹⁸F]-labeled positron emission tomography (PET) radioligands permit in vivo assessment of Alzheimer’s disease biomarkers, including aggregated neurofibrillary tau (NFT) with [¹⁸F]flortaucipir. Due to structural similarities of flortaucipir with some monoamine oxidase A (MAO-A) inhibitors, this study aimed to evaluate flortaucipir binding to MAO-A and MAO-B and any potential impact on PET interpretation.

Methods

[¹⁸F]Flortaucipir autoradiography was performed on frozen human brain tissue slices, and PET imaging was conducted in rats. Dissociation constants were determined by saturation binding, association and dissociation rates were measured by kinetic binding experiments, and IC₅₀ values were determined by competition binding.

Results

Under stringent wash conditions, specific [¹⁸F]flortaucipir binding was observed on tau NFT-rich Alzheimer’s disease tissue and not control tissue. In vivo PET experiments in rats revealed no evidence of [¹⁸F]flortaucipir binding to MAO-A; pre-treatment with MAO inhibitor pargyline did not impact uptake or wash-out of [¹⁸F]flortaucipir. [¹⁸F]Flortaucipir bound with low nanomolar affinity to human MAO-A in a microsomal preparation in vitro but with a fast dissociation rate relative to MAO-A ligand fluoroethyl-harmol, consistent with no observed in vivo binding in rats of [¹⁸F]flortaucipir to MAO-A. Direct binding of flortaucipir to human MAO-B was not detected in a microsomal preparation. A high concentration of flortaucipir (IC₅₀ of 1.3 μM) was found to block binding of the MAO-B ligand safinamide to MAO-B on microsomes suggesting that, at micromolar concentrations, flortaucipir weakly binds to MAO-B in vitro.

Conclusion

These data suggest neither MAO-A nor MAO-B binding will contribute significantly to the PET signal in cortical target areas relevant to the interpretation of [¹⁸F]flortaucipir.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00259-022-05822-9.

Diagnostic Accuracy of the Five-Word Test for Mild Cognitive Impairment Due to Alzheimer's Disease

New diagnostic methods have been developed for the early diagnosis of Alzheimer’s disease (AD) with the primary purpose of intercepting the transition-phase (mild cognitive impairment, MCI) between normal aging and dementia. We aimed to explore whether the five-word test (FWT) and the mini-mental state examination (MMSE) are predictive for the early diagnosis of MCI due to AD (AD-MCI). We computed ROC analyses to evaluate the sensitivity and specificity of MMSE and FWT in predicting abnormal CSF (t-Tau, p-Tau181, Aβ1−42) and amyloid-PET biomarkers. AD-MCI patients showed lower MMSE and FWT scores (all p < 0.001) than non-AD-MCI. The best predictor of amyloid plaques’ presence at amyloid-PET imaging was the encoding sub-score of the FWT (AUC = 0.84). Both FWT and MMSE had low/moderate accuracy for the detection of pathological CSF Aβ42, t-Tau and p-Tau181 values, with higher accuracy for the t-Tau/Aβ1−42 ratio. In conclusion, the FWT, as a single-domain cognitive screening test, seems to be prompt and moderately accurate tool for the identification of an underlying AD neuropathological process in patients with MCI, supporting the importance of associating biomarkers evaluation in the work-up of patients with dementing neurodegenerative disorders.

Serum NfL in Alzheimer Dementia: Results of the Prospective Dementia Registry Austria

Background and Objectives: The neurofilament light chain (NfL) is a biomarker for neuro-axonal injury in various acute and chronic neurological disorders, including Alzheimer’s disease (AD). We here investigated the cross-sectional and longitudinal associations between baseline serum NfL (sNfL) levels and cognitive, behavioural as well as MR volumetric findings in the Prospective Dementia Registry Austria (PRODEM-Austria). Materials and Methods: All participants were clinically diagnosed with AD according to NINCDS-ADRDA criteria and underwent a detailed clinical assessment, cognitive testing (including the Mini Mental State Examination (MMSE) and the Consortium to Establish a Registry for Alzheimer’s Disease (CERAD)), the neuropsychiatric inventory (NPI) and laboratory evaluation. A total of 237 patients were included in the study. Follow-up examinations were done at 6 months, 1 year and 2 years with 93.3% of patients undergoing at least one follow-up. We quantified sNfL by a single molecule array (Simoa). In a subgroup of 125 subjects, brain imaging data (1.5 or 3T MRI, with 1 mm isotropic resolution) were available. Brain volumetry was assessed using the FreeSurfer image analysis suite (v6.0). Results: Higher sNfL concentrations were associated with worse performance in cognitive tests at baseline, including CERAD (B = −10.084, SE = 2.999, p < 0.001) and MMSE (B = −3.014, SE = 1.293, p = 0.021). The sNfL levels also correlated with the presence of neuropsychiatric symptoms (NPI total score: r = 0.138, p = 0.041) and with smaller volumes of the temporal lobe (B = −0.012, SE = 0.003, p = 0.001), the hippocampus (B = −0.001, SE = 0.000201, p = 0.013), the entorhinal (B = −0.000308, SE = 0.000124, p = 0.014), and the parahippocampal cortex (B = −0.000316, SE = 0.000113, p = 0.006). The sNfL values predicted more pronounced cognitive decline over the mean follow-up period of 22 months, but there were no significant associations with respect to change in neuropsychiatric symptoms and brain volumetric measures. Conclusions: the sNfL levels relate to cognitive, behavioural, and imaging hallmarks of AD and predicts short term cognitive decline.

New Onset Dementia Among Survivors of Pneumonia Associated with Severe Acute Respiratory Syndrome Coronavirus 2 Infection

Background

Case series without control groups suggest that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection may result in cognitive deficits and dementia in the postinfectious period.

Methods

Adult pneumonia patients with SARS-CoV-2 infection (index hospitalization) and age-, gender-, and race/ethnicity-matched contemporary control pneumonia patients without SARS-CoV-2 infection were identified from 110 healthcare facilities in United States. The risk of new diagnosis of dementia following >30 days after the index hospitalization event without any previous history of dementia was identified using logistic regression analysis to adjust for potential confounders.

Results

Among 10 403 patients with pneumonia associated with SARS-CoV-2 infection, 312 patients (3% [95% confidence interval {CI}, 2.7%–3.4%]) developed new-onset dementia over a median period of 182 days (quartile 1 = 113 days, quartile 3 = 277 days). After adjustment for age, gender, race/ethnicity, hypertension, diabetes mellitus, hyperlipidemia, nicotine dependence/tobacco use, alcohol use/abuse, atrial fibrillation, previous stroke, and congestive heart failure, the risk of new-onset dementia was significantly higher with pneumonia associated with SARS-CoV-2 infection compared with pneumonia unrelated to SARS-CoV-2 infection (odds ratio [OR], 1.3 [95% CI, 1.1–1.5]). The association remained significant after further adjustment for occurrence of stroke, septic shock, and intubation/mechanical ventilation during index hospitalization (OR, 1.3 [95% CI, 1.1–1.5]).

Conclusions

Approximately 3% of patients with pneumonia associated with SARS-CoV-2 infection developed new-onset dementia, which was significantly higher than the rate seen with other pneumonias.

Quantified Brain Magnetic Resonance Imaging Volumes Differentiate Behavioral Variant Frontotemporal Dementia from Early-Onset Alzheimer's Disease

BACKGROUND

The differentiation of behavioral variant frontotemporal dementia (bvFTD) from early-onset Alzheimer's disease (EOAD) by clinical criteria can be inaccurate. The volumetric quantification of clinically available magnetic resonance (MR) brain scans may facilitate early diagnosis of these neurodegenerative dementias.

OBJECTIVE

To determine if volumetric quantification of brain MR imaging can identify persons with bvFTD from EOAD.

METHODS

3D T1 MR brain scans of 20 persons with bvFTD and 45 with EOAD were compared using Neuroreader to measure subcortical, and lobar volumes, and Volbrain for hippocampal subfields. Analyses included: 1) discriminant analysis with leave one out cross-validation; 2) input of predicted probabilities from this process into a receiver operator characteristic (ROC) analysis; and 3) Automated linear regression to identify predictive regions.

RESULTS

Both groups were comparable in age and sex with no statistically significant differences in symptom duration. bvFTD had lower volume percentiles in frontal lobes, thalamus, and putamen. EOAD had lower parietal lobe volumes. ROC analyses showed 99.3% accuracy with Neuroreader percentiles and 80.2% with subfields. The parietal lobe was the most predictive percentile. Although there were differences in hippocampal (particularly left CA2-CA3) subfields, it did not add to the discriminant analysis.

CONCLUSION

Percentiles from an MR based volumetric quantification can help differentiate between bvFTD from EOAD in routine clinical care. Use of hippocampal subfield volumes does not enhance the diagnostic separation of these two early-onset dementias.

Age Matching Is Essential for the Study of Cerebrospinal Fluid sTREM2 Levels and Alzheimer's Disease Risk: A Meta-Analysis

Background: Both the genetic and pathological studies link Alzheimer's disease (AD) to the triggering receptor expressed on myeloid cells 2 (TREM2). A large number of studies have explored the value of cerebrospinal fluid (CSF) soluble TREM2 (sTREM2) levels as a biomarker for the diagnosis and prediction of AD; however, the findings are inconsistent. We aimed to review the studies that investigated the association of CSF sTREM2 levels and AD risk, and to provide the recommendations for future research. Methods and Results: A systematic literature search was performed using the MEDLINE, EMBASE, and Web of Science (all databases) databases. The meta-analysis for the association between the CSF sTREM2 levels and AD risk included 15 studies (17 comparisons) with a total of 1,153 cases and 1,626 controls. The total results showed that the higher CSF sTREM2 levels and AD risk were associated [standardized mean difference (SMD) = 0.428, 95% CI (0.213, 0.643), I ² = 81.1%]. However, the analysis of the subgroup of "age difference ≤ 2 years" indicated that sTREM2 was not associated with AD [SMD = 0.090, 95% CI (-0.092, 0.272), I² = 27.4%] and had a significantly lower heterogeneity. Combining the results of the "age difference of 5-10 years" [SMD = 0.497, 95% CI (0.139, 0.855), I ² = 82.5%] and "age difference > 10 years" [SMD = 0.747, 95% CI (0.472, 1.023), I ² = 50.0%] subgroups showed that the difference in CSF sTREM2 between the AD and control groups was positively correlated with the age difference. A meta-regression analysis showed that the age difference can explain 33.4% of the between-study variance. By conducting further subgroup analyses of the five age-matched studies (495 cases and 364 controls) according to the measurement method, and whether inclusion criteria containing the requirement for pathological evidence of AD, no changes were observed in the corresponding pooled SMD or in the significance of the results. The meta-analysis result of "age difference ≤ 2 years" group was robust in the sensitivity analysis. Conclusion: The available high-quality evidence does not yet support an association between the CSF sTREM2 levels and AD risk. Age matching between the patients with AD and cognitively unimpaired controls was a major influencing factor in the results.

Clinical Approach to Cognitive and Neurobehavioral Symptoms

PURPOSE OF REVIEW

This article provides a framework for the approach to patients with cognitive or neurobehavioral concerns.

RECENT FINDINGS

Recent advances in structural neuroimaging, functional neuroimaging, and disease biomarkers have greatly expanded knowledge of brain-behavior relationships, neural networks and functional connectivity, and pathophysiologic processes leading to cognitive and neurobehavioral disorders. However, any one of these studies is subject to misinterpretation if not applied in the appropriate clinical context.

SUMMARY

A systematic approach to the history and examination in patients with cognitive and neurobehavioral symptoms is important in marrying clinical assessments with contemporary diagnostic studies and treatments.

RALBP1 in Oxidative Stress and Mitochondrial Dysfunction in Alzheimer's Disease

The purpose of our study is to understand the role of the RALBP1 gene in oxidative stress (OS), mitochondrial dysfunction and cognition in Alzheimer's disease (AD) pathogenesis. The RALPB1 gene encodes the 76 kDa protein RLIP76 (Rlip). Rlip functions as a stress-responsive/protective transporter of glutathione conjugates (GS-E) and xenobiotic toxins. We hypothesized that Rlip may play an important role in maintaining cognitive function. The aim of this study is to determine whether Rlip deficiency in mice is associated with AD-like cognitive and mitochondrial dysfunction. Brain tissue obtained from cohorts of wildtype (WT) and Rlip+/- mice were analyzed for OS markers, expression of genes that regulate mitochondrial fission/fusion, and synaptic integrity. We also examined mitochondrial ultrastructure in brains obtained from these mice and further analyzed the impact of Rlip deficiency on gene networks of AD, aging, stress response, mitochondrial function, and CREB signaling. Our studies revealed a significant increase in the levels of OS markers and alterations in the expression of genes and proteins involved in mitochondrial biogenesis, dynamics and synapses in brain tissues from these mice. Furthermore, we compared the cognitive function of WT and Rlip+/- mice. Behavioral, basic motor and sensory function tests in Rlip+/- mice revealed cognitive decline, similar to AD. Gene network analysis indicated dysregulation of stress-activated gene expression, mitochondrial function and CREB signaling genes in the Rlip+/- mouse brain. Our results suggest that Rlip deficiency-associated increases in OS and mitochondrial dysfunction could contribute to the development or progression of OS-related AD processes.

Association of Thyroid Dysfunction With Cognitive Function: An Individual Participant Data Analysis

IMPORTANCE

In clinical guidelines, overt and subclinical thyroid dysfunction are mentioned as causal and treatable factors for cognitive decline. However, the scientific literature on these associations shows inconsistent findings.

OBJECTIVE

To assess cross-sectional and longitudinal associations of baseline thyroid dysfunction with cognitive function and dementia.

DESIGN, SETTING, AND PARTICIPANTS

This multicohort individual participant data analysis assessed 114 267 person-years (median, 1.7-11.3 years) of follow-up for cognitive function and 525 222 person-years (median, 3.8-15.3 years) for dementia between 1989 and 2017. Analyses on cognitive function included 21 cohorts comprising 38 144 participants. Analyses on dementia included eight cohorts with a total of 2033 cases with dementia and 44 573 controls. Data analysis was performed from December 2016 to January 2021.

EXPOSURES

Thyroid function was classified as overt hyperthyroidism, subclinical hyperthyroidism, euthyroidism, subclinical hypothyroidism, and overt hypothyroidism based on uniform thyrotropin cutoff values and study-specific free thyroxine values.

MAIN OUTCOMES AND MEASURES

The primary outcome was global cognitive function, mostly measured using the Mini-Mental State Examination. Executive function, memory, and dementia were secondary outcomes. Analyses were first performed at study level using multivariable linear regression and multivariable Cox regression, respectively. The studies were combined with restricted maximum likelihood meta-analysis. To overcome the use of different scales, results were transformed to standardized mean differences. For incident dementia, hazard ratios were calculated.

RESULTS

Among 74 565 total participants, 66 567 (89.3%) participants had normal thyroid function, 577 (0.8%) had overt hyperthyroidism, 2557 (3.4%) had subclinical hyperthyroidism, 4167 (5.6%) had subclinical hypothyroidism, and 697 (0.9%) had overt hypothyroidism. The study-specific median age at baseline varied from 57 to 93 years; 42 847 (57.5%) participants were women. Thyroid dysfunction was not associated with global cognitive function; the largest differences were observed between overt hypothyroidism and euthyroidism-cross-sectionally (-0.06 standardized mean difference in score; 95% CI, -0.20 to 0.08; P = .40) and longitudinally (0.11 standardized mean difference higher decline per year; 95% CI, -0.01 to 0.23; P = .09). No consistent associations were observed between thyroid dysfunction and executive function, memory, or risk of dementia.

CONCLUSIONS AND RELEVANCE

In this individual participant data analysis of more than 74 000 adults, subclinical hypothyroidism and hyperthyroidism were not associated with cognitive function, cognitive decline, or incident dementia. No rigorous conclusions can be drawn regarding the role of overt thyroid dysfunction in risk of dementia. These findings do not support the practice of screening for subclinical thyroid dysfunction in the context of cognitive decline in older adults as recommended in current guidelines.

Amyloid and Tau in Alzheimer's Disease: Biomarkers or Molecular Targets for Therapy? Are We Shooting the Messenger?

Alzheimer's disease is a neuropsychiatric disorder with devastating clinical and socioeconomic consequences. Since the original description of the neuropathological correlates of the disorder, neuritic plaques and neurofibrillary tangles have been presumed to be critical to the underlying pathophysiology of the illness. The authors review the clinical and neuropathological origins of Alzheimer's disease and trace the evolution of modern biomarkers from their historical roots. They describe how technological innovations such as neuroimaging and biochemical assays have been used to measure and quantify key proteins and lipids in the brain, cerebrospinal fluid, and blood and advance their role as biomarkers of Alzheimer's disease. Together with genomics, these approaches have led to the development of a thematic and focused science in the area of degenerative disorders. The authors conclude by drawing distinctions between legitimate biomarkers of disease and molecular targets for therapeutic intervention and discuss future approaches to this complex neurobehavioral illness.

Early Impairment in the Ventral Visual Pathway Can Predict Conversion to Dementia in Patients With Amyloid-negative Amnestic Mild Cognitive Impairment

BACKGROUND

Around 15% to 20% of patients with clinically probable Alzheimer disease have been found to have no significant Alzheimer pathology on amyloid positron emission tomography. A previous study showed that conversion to dementia from amyloid-negative mild cognitive impairment (MCI) was observed in up to 11% of patients, drawing attention to this condition.

OBJECT

We gathered the detailed neuropsychological and neuroimaging data of this population to elucidate factors for conversion to dementia from amyloid-negative amnestic MCI.

METHODS

This study was a single-institutional, retrospective cohort study of amyloid-negative MCI patients over age 50 with at least 36 months of follow-up. All subjects underwent detailed neuropsychological testing, 3 tesla brain magnetic resonance imaging), and fluorine-18(18F)-florbetaben amyloid positron emission tomography scans.

RESULTS

During the follow-up period, 39 of 107 (36.4%) patients converted to dementia from amnestic MCI. The converter group had more severe impairment in all visual memory tasks. The volumetric analysis revealed that the converter group had significantly reduced total hippocampal volume on the right side, gray matter volume in the right lateral temporal, lingual gyri, and occipital pole.

CONCLUSION

Our study showed that reduced gray matter volume related to visual memory processing may predict clinical progression in this amyloid-negative MCI population.

Development and validation of the dialysis dementia risk score: A retrospective, population-based, nested case-control study

Background

Dementia is prevalent and underdiagnosed in the dialysis population. We aimed to develop and validate a simple dialysis dementia scoring system to facilitate identification of individuals who are at high risk for dementia.

Methods

We applied a retrospective, nested case‐control study design using a national dialysis cohort derived from the National Health Insurance Research Database in Taiwan. Patients aged between 40 and 80 years were included and 2940 patients with incident dementia were matched to 29,248 non‐dementia controls. All subjects were randomly divided into the derivation and validation sets with a ratio of 4:1. Conditional logistic regression models were used to identify factors contributing to the risk score. The cutoff value of the risk score was determined by Youden's J statistic and the graphic method.

Results

The dialysis dementia risk score (DDRS) finally included age and 10 comorbidities as risk predictors. The C‐statistic of the model was 0.71 (95% confidence interval [CI] 0.70–0.72). Calibration revealed a strong linear relationship between predicted and observed dementia risk (R² = 0.99). At a cutoff value of 50 points, the high‐risk patients had an approximately three‐fold increased risk of having dementia compared to those with low risk (odds ratio [OR] 3.03, 95% CI 2.78–3.31). The DDRS performance, including discrimination (C‐statistic 0.71, 95% CI 0.69–0.73) and calibration (p value of Hosmer−Lemeshow test for goodness of fit = 0.18), was acceptable during validation. The OR value (2.82, 95% CI 2.37–3.35) was similar to those in the derivation set.

Conclusion

The DDRS system has the potential to serve as an easily accessible screening tool to determine the high‐risk groups who deserve subsequent neurological evaluation in daily clinical practice.

Head-to-head comparison of cerebral blood flow single-photon emission computed tomography and 18 F-fluoro-2-deoxyglucose positron emission tomography in the diagnosis of Alzheimer disease

BACKGROUND

Clinical diagnosis of Alzheimer disease (AD) is only 70% accurate. Reduced cerebral blood flow (CBF) and metabolism in parieto-temporal and posterior cingulate cortex may assist diagnosis. While widely accepted that ¹⁸ F-fluoro-2-deoxyglucose positron emission tomography (¹⁸ F-FDG PET) has superior accuracy to CBF-SPECT for AD, there are very limited head-to-head data from clinically relevant populations and these studies relied on clinical diagnosis as the reference standard.

AIMS

To compare directly the accuracy of CBF-SPECT and ¹⁸ F-FDG PET in patients referred for diagnostic studies in detecting β-amyloid PET confirmed AD.

METHODS

A total of 126 patients, 56% with mild cognitive impairment and 44% with dementia, completed both CBF-SPECT and ¹⁸ F-FDG PET as part of their diagnostic assessment, and subsequently underwent β-amyloid PET for research purposes. Transaxial slices and Neurostat 3D-SSP analyses of ¹⁸ F-FDG PET and CBF-SPECT scans were independently reviewed by five nuclear medicine clinicians blinded to all other data. Operators selected the most likely diagnosis and their diagnostic confidence. Accuracy analysis used final diagnosis incorporating β-amyloid PET as the reference standard.

RESULTS

Clinicians reported high diagnostic confidence in 83% of ¹⁸ F-FDG PET compared to 67% for CBF-SPECT (P = 0.001). All reviewers showed individually higher accuracy using ¹⁸ F-FDG PET. Based on majority read, the combined area under the receiver operating characteristic curve in diagnosing AD was 0.71 for ¹⁸ F-FDG PET and 0.61 for CBF-SPECT (P = 0.02). The sensitivity of ¹⁸ F-FDG PET and CBF-SPECT was 76% versus 43% (P < 0.001), while specificity was 74% versus 83% (P = 0.45).

CONCLUSIONS

¹⁸ F-FDG PET is superior to CBF-SPECT in detecting AD among patients referred for the assessment of cognitive impairment.

Lacsogram: A New EEG Tool to Diagnose Alzheimer's Disease

This work proposes the application of a new electroencephalogram (EEG) signal processing tool - the lacsogram - to characterize the Alzheimer's disease (AD) activity and to assist on its diagnosis at different stages: Mild Cognitive Impairment (MCI), Mild and Moderate AD (ADM) and Advanced AD (ADA). Statistical analyzes are performed to lacstral distances between conventional EEG subbands to find measures capable of discriminating AD in all stages and characterizing the AD activity in each electrode. Cepstral distances are used for comparison. Comparing all AD stages and Controls (C), the most important significances are the lacstral distances between subbands θ and α ( p = 0.0014 0.05). The topographic maps show significant differences in parietal, temporal and frontal regions as AD progresses. Machine learning models with a leave-one-out cross-validation process are applied to lacstral/cepstral distances to develop an automatic method for diagnosing AD. The following classification accuracies are obtained with an artificial neural network: 95.55% for All vs All, 98.06% for C vs MCI, 95.99% for C vs ADM, 93.85% for MCI vs ADM-ADA. In C vs MCI, C vs ADM and MCI vs ADM-ADA, the proposed method outperforms the state-of-art methods by 5%, 1%, and 2%, respectively. In All vs All, it outperforms the state-of-art EEG and non-EEG methods by 6% and 2%, respectively. These results indicate that the proposed method represents an improvement in diagnosing AD.

A novel CT-based automated analysis method provides comparable results with MRI in measuring brain atrophy and white matter lesions

Purpose

Automated analysis of neuroimaging data is commonly based on magnetic resonance imaging (MRI), but sometimes the availability is limited or a patient might have contradictions to MRI. Therefore, automated analyses of computed tomography (CT) images would be beneficial.

Methods

We developed an automated method to evaluate medial temporal lobe atrophy (MTA), global cortical atrophy (GCA), and the severity of white matter lesions (WMLs) from a CT scan and compared the results to those obtained from MRI in a cohort of 214 subjects gathered from Kuopio and Helsinki University Hospital registers from 2005 - 2016.

Results

The correlation coefficients of computational measures between CT and MRI were 0.9 (MTA), 0.82 (GCA), and 0.86 (Fazekas). CT-based measures were identical to MRI-based measures in 60% (MTA), 62% (GCA) and 60% (Fazekas) of cases when the measures were rounded to the nearest full grade variable. However, the difference in measures was 1 or less in 97–98% of cases. Similar results were obtained for cortical atrophy ratings, especially in the frontal and temporal lobes, when assessing the brain lobes separately. Bland–Altman plots and weighted kappa values demonstrated high agreement regarding measures based on CT and MRI.

Conclusions

MTA, GCA, and Fazekas grades can also be assessed reliably from a CT scan with our method. Even though the measures obtained with the different imaging modalities were not identical in a relatively extensive cohort, the differences were minor. This expands the possibility of using this automated analysis method when MRI is inaccessible or contraindicated.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00234-021-02761-4.

Interrater agreement in dementia diagnosis: A systematic review and meta-analysis

OBJECTIVES

Dementia remains a clinical diagnosis with a degree of subjective assessment and potential for interrater disagreement. We described interrater agreement of clinical dementia diagnosis for various diagnostic criteria.

METHODS

We conducted a PROSPERO-registered (CRD42020168245) systematic review and meta-analysis. We searched multiple cross-disciplinary databases from inception until April 2020 for relevant papers, extracted data and described study quality in duplicate. Study quality was assessed using the Guidelines for Reporting Reliability and Agreement Studies. We used random-effects models to obtain summary estimates of interrater agreement using kappa and, where possible, Gwet's AC1/2 coefficients.

RESULTS

We found 7577 titles and 22 eligible studies. Meta-analysis was possible for all-cause dementia using the Diagnostic and Statistical Manual of Mental Disorders third edition revised (DSM-III-R) criteria (kappa = 0.66, 95% CI = [0.53,0.78]), Alzheimer's disease using the National Institute of Neurological and Communicative Disorders and Stroke and the Alzheimer's disease and Related Disorders Association (NINCDS-ADRDA) criteria (kappa = 0.71, 95% CI = [0.65,0.77] for presence/absence and AC2 = 0.61, 95% CI = [0.53,0.70] when distinguishing probable/possible cases), and vascular dementia using the International Classification of Diseases version 10 (ICD-10) criteria kappa = 0.79 (95% CI = [0.70,0.87]). Data was more limited for other criteria and dementia types. AC1/2 coefficients generally indicated higher agreement. One study was rated as high quality.

CONCLUSIONS

Diagnostic criteria for clinical dementia may have good but imperfect agreement. This has important implications for clinical practice and research studies, which frequently assume these criteria are perfect tests, such as diagnostic test accuracy studies frequently conducted for biomarkers and neuropsychological tests, and for trials where incident dementia is the outcome.

Physiological separation of Alzheimer's disease and Alzheimer's disease with significant levels of cerebrovascular symptomology and healthy controls

Most dementia patients with a mixed dementia (MxD) diagnosis have a mix of Alzheimer's disease (AD) and vascular dementia. Electrovestibulography (EVestG) records vestibuloacoustic afferent activity. We hypothesize EVestG recordings of AD and MxD patients are different. All patients were assessed with the Montreal cognitive assessment (MoCA) and Hachinski ischemic scale (HIS) (> 4 HIS score < 7 is representative of MxD cerebrovascular symptomology). EVestG recordings were made from 26 AD, 21 MxD and 44 healthy (control) participants. Features were derived from the EVestG recordings of the average field potential and field potential interval histogram to classify the AD, MxD and control groups. Multivariate analysis was used to test the features' significance. Using a leave-one-out cross-validated linear discriminant analysis with 3 EVestG features yielded accuracies > 80% for separating pairs of AD/MxD/control. Using the MoCA assessment and 2 EVestG features, a best accuracy of 81 to 91% depending on the classifier was obtained for the 3-way identification of AD, MxD and controls. EVestG measures provide a physiological basis for identifying AD from MxD. EVestG measures are hypothesized to be partly related to channelopathies and changes in the descending input to the vestibular periphery. Four of the five AD or MxD versus control features used had significant correlations with the MoCA. This supports assertions that the pathologic changes associated with AD impact the vestibular system and further are suggestive that the postulated physiological changes behind these features have an association with cognitive decline severity.

Mini-Cog for the detection of dementia within a secondary care setting

BACKGROUND

The diagnosis of Alzheimer's disease dementia and other dementias relies on clinical assessment. There is a high prevalence of cognitive disorders, including undiagnosed dementia in secondary care settings. Short cognitive tests can be helpful in identifying those who require further specialist diagnostic assessment; however, there is a lack of consensus around the optimal tools to use in clinical practice. The Mini-Cog is a short cognitive test comprising three-item recall and a clock-drawing test that is used in secondary care settings.

OBJECTIVES

The primary objective was to determine the accuracy of the Mini-Cog for detecting dementia in a secondary care setting. The secondary objectives were to investigate the heterogeneity of test accuracy in the included studies and potential sources of heterogeneity. These potential sources of heterogeneity will include the baseline prevalence of dementia in study samples, thresholds used to determine positive test results, the type of dementia (Alzheimer's disease dementia or all causes of dementia), and aspects of study design related to study quality.

SEARCH METHODS

We searched the following sources in September 2012, with an update to 12 March 2019: Cochrane Dementia Group Register of Diagnostic Test Accuracy Studies, MEDLINE (OvidSP), Embase (OvidSP), BIOSIS Previews (Web of Knowledge), Science Citation Index (ISI Web of Knowledge), PsycINFO (OvidSP), and LILACS (BIREME). We made no exclusions with regard to language of Mini-Cog administration or language of publication, using translation services where necessary.

SELECTION CRITERIA

We included cross-sectional studies and excluded case-control designs, due to the risk of bias. We selected those studies that included the Mini-Cog as an index test to diagnose dementia where dementia diagnosis was confirmed with reference standard clinical assessment using standardised dementia diagnostic criteria. We only included studies in secondary care settings (including inpatient and outpatient hospital participants).

DATA COLLECTION AND ANALYSIS

We screened all titles and abstracts generated by the electronic database searches. Two review authors independently checked full papers for eligibility and extracted data. We determined quality assessment (risk of bias and applicability) using the QUADAS-2 tool. We extracted data into two-by-two tables to allow calculation of accuracy metrics for individual studies, reporting the sensitivity, specificity, and 95% confidence intervals of these measures, summarising them graphically using forest plots.

MAIN RESULTS

Three studies with a total of 2560 participants fulfilled the inclusion criteria, set in neuropsychology outpatient referrals, outpatients attending a general medicine clinic, and referrals to a memory clinic. Only n = 1415 (55.3%) of participants were included in the analysis to inform evaluation of Mini-Cog test accuracy, due to the selective use of available data by study authors. There were concerns related to high risk of bias with respect to patient selection, and unclear risk of bias and high concerns related to index test conduct and applicability. In all studies, the Mini-Cog was retrospectively derived from historic data sets. No studies included acute general hospital inpatients. The prevalence of dementia ranged from 32.2% to 87.3%. The sensitivities of the Mini-Cog in the individual studies were reported as 0.67 (95% confidence interval (CI) 0.63 to 0.71), 0.60 (95% CI 0.48 to 0.72), and 0.87 (95% CI 0.83 to 0.90). The specificity of the Mini-Cog for each individual study was 0.87 (95% CI 0.81 to 0.92), 0.65 (95% CI 0.57 to 0.73), and 1.00 (95% CI 0.94 to 1.00). We did not perform meta-analysis due to concerns related to risk of bias and heterogeneity.

AUTHORS' CONCLUSIONS

This review identified only a limited number of diagnostic test accuracy studies using Mini-Cog in secondary care settings. Those identified were at high risk of bias related to patient selection and high concerns related to index test conduct and applicability. The evidence was indirect, as all studies evaluated Mini-Cog differently from the review question, where it was anticipated that studies would conduct Mini-Cog and independently but contemporaneously perform a reference standard assessment to diagnose dementia. The pattern of test accuracy varied across the three studies. Future research should evaluate Mini-Cog as a test in itself, rather than derived from other neuropsychological assessments. There is also a need for evaluation of the feasibility of the Mini-Cog for the detection of dementia to help adequately determine its role in the clinical pathway.

Mini-Cog for the detection of dementia within a community setting

BACKGROUND

Alzheimer's disease and related forms of dementia are becoming increasingly prevalent with the aging of many populations. The diagnosis of Alzheimer's disease relies on tests to evaluate cognition and discriminate between individuals with dementia and those without dementia. The Mini-Cog is a brief, cognitive screening test that is frequently used to evaluate cognition in older adults in various settings.

OBJECTIVES

The primary objective of this review was to determine the accuracy of the Mini-Cog for detecting dementia in a community setting. Secondary objectives included investigations of the heterogeneity of test accuracy in the included studies and potential sources of heterogeneity. These potential sources of heterogeneity included the baseline prevalence of dementia in study samples, thresholds used to determine positive test results, the type of dementia (Alzheimer's disease dementia or all causes of dementia), and aspects of study design related to study quality. Overall, the goals of this review were to determine if the Mini-Cog is a cognitive screening test that could be recommended to screen for cognitive impairment in community settings.

SEARCH METHODS

We searched MEDLINE (OvidSP), EMBASE (OvidSP), PsycINFO (Ovid SP), Science Citation Index (Web of Science), BIOSIS previews (Web of Science), LILACS (BIREME), and the Cochrane Dementia Group's developing register of diagnostic test accuracy studies to March 2013. We used citation tracking (using the database's 'related articles' feature, where available) as an additional search method and contacted authors of eligible studies for unpublished data.

SELECTION CRITERIA

We included all cross-sectional studies that utilized the Mini-Cog as an index test for the diagnosis of dementia when compared to a reference standard diagnosis of dementia using standardized dementia diagnostic criteria. For the current review we only included studies that were conducted on samples from community settings, and excluded studies that were conducted in primary care or secondary care settings. We considered studies to be conducted in a community setting where participants were sampled from the general population.

DATA COLLECTION AND ANALYSIS

Information from studies meeting the inclusion criteria were extracted including information on the characteristics of participants in the studies. The quality of the studies was assessed using the QUADAS-2 criteria and summarized using risk of bias applicability and summary graphs. We extracted information on the diagnostic test accuracy of studies including the sensitivity, specificity, and 95% confidence intervals of these measures and summarized the findings using forest plots. Study specific sensitivities and specificities were also plotted in receiver operating curve space.

MAIN RESULTS

Three studies met the inclusion criteria, with a total of 1620 participants. The sensitivities of the Mini-Cog in the individual studies were reported as 0.99, 0.76 and 0.99. The specificity of the Mini-Cog varied in the individual studies and was 0.93, 0.89 and 0.83. There was clinical and methodological heterogeneity between the studies which precluded a pooled meta-analysis of the results. Methodological limitations were present in all the studies introducing potential sources of bias, specifically with respect to the methods for participant selection.

AUTHORS' CONCLUSIONS

There are currently few studies assessing the diagnostic test accuracy of the Mini-Cog in community settings. The limited number of studies and the methodological limitations that are present in the current studies make it difficult to provide recommendations for or against the use of the Mini-Cog as a cognitive screening test in community settings. Additional well-designed studies comparing the Mini-Cog to other brief cognitive screening tests are required in order to determine the accuracy and utility of the Mini-Cog in community based settings.

Mini-Cog for the detection of dementia within a primary care setting

BACKGROUND

Alzheimer's disease and other forms of dementia are becoming increasingly common with the aging of most populations. The majority of individuals with dementia will first present for care and assessment in primary care settings. There is a need for brief dementia screening instruments that can accurately detect dementia in primary care settings. The Mini-Cog is a brief, cognitive screening test that is frequently used to evaluate cognition in older adults in various settings.

OBJECTIVES

To determine the accuracy of the Mini-Cog for detecting dementia in a primary care setting.

SEARCH METHODS

We searched the Cochrane Dementia and Cognitive Improvement Register of Diagnostic Test Accuracy Studies, MEDLINE, Embase and four other databases, initially to September 2012. Since then, four updates to the search were performed using the same search methods, and the most recent was January 2017. We used citation tracking (using the databases' 'related articles' feature, where available) as an additional search method and contacted authors of eligible studies for unpublished data.

SELECTION CRITERIA

We only included studies that evaluated the Mini-Cog as an index test for the diagnosis of Alzheimer's disease dementia or related forms of dementia when compared to a reference standard using validated criteria for dementia. We only included studies that were conducted in primary care populations.

DATA COLLECTION AND ANALYSIS

We extracted and described information on the characteristics of the study participants and study setting. Using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) criteria we evaluated the quality of studies, and we assessed risk of bias and applicability of each study for each domain in QUADAS-2. Two review authors independently extracted information on the true positives, true negatives, false positives, and false negatives and entered the data into Review Manager 5 (RevMan 5). We then used RevMan 5 to determine the sensitivity, specificity, and 95% confidence intervals. We summarized the sensitivity and specificity of the Mini-Cog in the individual studies in forest plots and also plotted them in a receiver operating characteristic plot. We also created a 'Risk of bias' and applicability concerns graph to summarize information related to the quality of included studies.

MAIN RESULTS

There were a total of four studies that met our inclusion criteria, including a total of 1517 total participants. The sensitivity of the Mini-Cog varied between 0.76 to 1.00 in studies while the specificity varied between 0.27 to 0.85. The included studies displayed significant heterogeneity in both methodologies and clinical populations, which did not allow for a meta-analysis to be completed. Only one study (Holsinger 2012) was found to be at low risk of bias on all methodological domains. The results of this study reported that the sensitivity of the Mini-Cog was 0.76 and the specificity was 0.73. We found the quality of all other included studies to be low due to a high risk of bias with methodological limitations primarily in their selection of participants.

AUTHORS' CONCLUSIONS

There is a limited number of studies evaluating the accuracy of the Mini-Cog for the diagnosis of dementia in primary care settings. Given the small number of studies, the wide range in estimates of the accuracy of the Mini-Cog, and methodological limitations identified in most of the studies, at the present time there is insufficient evidence to recommend that the Mini-Cog be used as a screening test for dementia in primary care. Further studies are required to determine the accuracy of Mini-Cog in primary care and whether this tool has sufficient diagnostic test accuracy to be useful as a screening test in this setting.

Machine learning for modeling the progression of Alzheimer disease dementia using clinical data: a systematic literature review

OBJECTIVE

Alzheimer disease (AD) is the most common cause of dementia, a syndrome characterized by cognitive impairment severe enough to interfere with activities of daily life. We aimed to conduct a systematic literature review (SLR) of studies that applied machine learning (ML) methods to clinical data derived from electronic health records in order to model risk for progression of AD dementia.

MATERIALS AND METHODS

We searched for articles published between January 1, 2010, and May 31, 2020, in PubMed, Scopus, ScienceDirect, IEEE Explore Digital Library, Association for Computing Machinery Digital Library, and arXiv. We used predefined criteria to select relevant articles and summarized them according to key components of ML analysis such as data characteristics, computational algorithms, and research focus.

RESULTS

There has been a considerable rise over the past 5 years in the number of research papers using ML-based analysis for AD dementia modeling. We reviewed 64 relevant articles in our SLR. The results suggest that majority of existing research has focused on predicting progression of AD dementia using publicly available datasets containing both neuroimaging and clinical data (neurobehavioral status exam scores, patient demographics, neuroimaging data, and laboratory test values).

DISCUSSION

Identifying individuals at risk for progression of AD dementia could potentially help to personalize disease management to plan future care. Clinical data consisting of both structured data tables and clinical notes can be effectively used in ML-based approaches to model risk for AD dementia progression. Data sharing and reproducibility of results can enhance the impact, adaptation, and generalizability of this research.

Diagnostic and Prognostic Laboratory Testing for Alzheimer Disease

This article focuses on current clinical laboratory testing to diagnose Alzheimer disease and monitor its progression throughout its disease course. Several clinically available tests focus on analysis of amyloid and tau levels in cerebrospinal fluid as well as autosomal dominant and risk factor genes. Although the current armament of clinical laboratory testing is limited by invasiveness of cerebrospinal fluid collection, rarity of autosomal dominant genetic mutations, and uncertainties of risk inherent in nonpenetrant genes, the field is poised to advance the clinical repertoire of laboratory diagnostic testing.

The Role of Brief Global Cognitive Tests and Neuropsychological Expertise in the Detection and Differential Diagnosis of Dementia

Dementia is a global public health problem and its impact is bound to increase in the next decades, with a rapidly aging world population. Dementia is by no means an obligatory outcome of aging, although its incidence increases exponentially in old age, and its onset may be insidious. In the absence of unequivocal biomarkers, the accuracy of cognitive profiling plays a fundamental role in the diagnosis of this condition. In this Perspective article, we highlight the utility of brief global cognitive tests in the diagnostic process, from the initial detection stage for which they are designed, through the differential diagnosis of dementia. We also argue that neuropsychological training and expertise are critical in order for the information gathered from these omnibus cognitive tests to be used in an efficient and effective way, and thus, ultimately, for them to fulfill their potential.

Biomarkers for neurodegenerative diseases

Biomarkers for neurodegenerative diseases are needed to improve the diagnostic workup in the clinic but also to facilitate the development and monitoring of effective disease-modifying therapies. Positron emission tomography methods detecting amyloid-β and tau pathology in Alzheimer's disease have been increasingly used to improve the design of clinical trials and observational studies. In recent years, easily accessible and cost-effective blood-based biomarkers detecting the same Alzheimer's disease pathologies have been developed, which might revolutionize the diagnostic workup of Alzheimer's disease globally. Relevant biomarkers for α-synuclein pathology in Parkinson's disease are also emerging, as well as blood-based markers of general neurodegeneration and glial activation. This review presents an overview of the latest advances in the field of biomarkers for neurodegenerative diseases. Future directions are discussed regarding implementation of novel biomarkers in clinical practice and trials.

Resting-state electroencephalographic biomarkers of Alzheimer's disease

OBJECTIVE

We evaluated the value of resting-state EEG source biomarkers to characterize mild cognitive impairment (MCI) subjects with an Alzheimer's disease (AD)-like cerebrospinal fluid (CSF) profile and to track neurodegeneration throughout the AD continuum. We further applied a resting-state functional MRI (fMRI)-driven model of source reconstruction and tested its advantage in terms of AD diagnostic accuracy.

METHODS

Thirty-nine consecutive patients with AD dementia (ADD), 86 amnestic MCI, and 33 healthy subjects enter the EEG study. All ADD subjects, 37 out of 86 MCI patients and a distinct group of 53 healthy controls further entered the fMRI study. MCI subjects were divided according to the CSF phosphorylated tau/β amyloid-42 ratio (MCIpos: ≥ 0.13, MCIneg: < 0.13). Using Exact low-resolution brain electromagnetic tomography (eLORETA), EEG lobar current densities were estimated at fixed frequencies and analyzed. To combine the two imaging techniques, networks mostly affected by AD pathology were identified using Independent Component Analysis applied to fMRI data of ADD subjects. Current density EEG analysis within ICA-based networks at selected frequency bands was performed. Afterwards, graph analysis was applied to EEG and fMRI data at ICA-based network level.

RESULTS

ADD patients showed a widespread slowing of spectral density. At a lobar level, MCIpos subjects showed a widespread higher theta density than MCIneg and healthy subjects; a lower beta2 density than healthy subjects was also found in parietal and occipital lobes. Evaluating EEG sources within the ICA-based networks, alpha2 band distinguished MCIpos from MCIneg, ADD and healthy subjects with good accuracy. Graph analysis on EEG data showed an alteration of connectome configuration at theta frequency in ADD and MCIpos patients and a progressive disruption of connectivity at alpha2 frequency throughout the AD continuum.

CONCLUSIONS

Theta frequency is the earliest and most sensitive EEG marker of AD pathology. Furthermore, EEG/fMRI integration highlighted the role of alpha2 band as potential neurodegeneration biomarker.

[Predictive Diagnosis of Alzheimer's Dementia]

Expanding technologies of early disease detection allow to identify Alzheimer's disease (AD) long before symptom onset. Hence, patients are increasingly demanding for these diagnostic procedures. Biomarker-based early detection of AD is therefore increasingly important in the clinical work-up. This article gives an overview of predictive procedures in the field of Alzheimer's dementia.

Brain SPECT as a Biomarker of Neurodegeneration in Dementia in the Era of Molecular Imaging: Still a Valid Option?

Biomarkers are playing a progressively leading role in both clinical practice and scientific research in dementia. Although amyloid and tau biomarkers have gained ground in the clinical community in recent years, neurodegeneration biomarkers continue to play a key role due to their ability to identify different patterns of brain involvement that sign the transition between asymptomatic and symptomatic stages of the disease with high sensitivity and specificity. Both ¹⁸F-FDG positron emission tomography (PET) and perfusion single photon emission computed tomography (SPECT) have proved useful to reveal the functional alterations underlying various neurodegenerative diseases. Although the focus of nuclear neuroimaging has shifted to PET, the lower cost and wider availability of SPECT make it a still valid alternative for the study of patients with dementia. This review discusses the principles of both techniques, compares their diagnostic performance for the diagnosis of neurodegenerative diseases and highlights the role of SPECT to characterize patients from low- and middle-income countries, where special care of additional costs is particularly needed to meet the new recommendations for the diagnosis and characterization of patients with dementia.