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

Association of the Area Deprivation Index With Dementia Basic Workup and Diagnosis in Central and Western Virginia: A Cross-Sectional Study

Background and Objectives

The Area Deprivation Index (ADI) provides a validated and multidimensional metric of areal disadvantage. Our goals were to determine if the ADI influences the likelihood of receiving workup based on published guidelines and an etiologic diagnosis of dementia in Central and Western Virginia.

Methods

We collected deidentified data from the electronic health record of individuals aged 50-105 years diagnosed with dementia at the University of Virginia (UVA) Medical Center (2016-2021) and at Carillion Clinic (2018-2021). Visit-specific ICD-10 codes were used to classify each dementia diagnosis as "disease-specific" (e.g., Alzheimer disease) or "general" (e.g., unspecified dementia). Following the American Academy of Neurology guidelines, we considered the evaluation performed as "adequate" if patients had vitamin B12, thyroid-stimulating hormone, and brain CT or magnetic resonance imaging within 6 months of the initial diagnosis. Census tract ADI was linked to study participants using the unique census tract identifier derived from the participants' home addresses at the time of diagnosis. Statistical modeling occurred under a Bayesian paradigm implemented using a standard code in R.

Results

The study included 13,431 individuals diagnosed with dementia at UVA (n = 7,152) and Carillion Clinic (n = 6,279). Of those, 32.5% and 20.4% received "disease-specific" diagnoses at UVA and Carillion Clinic and 8.2% and 20.4% underwent "adequate" workup, respectively. The adjusted relationship between census tract ADI and the likelihood of a disease-specific diagnosis was U-shaped: Residence in moderately disadvantaged areas was associated with the lowest likelihood of disease-specific diagnosis.

Discussion

Most patients diagnosed with dementia did not receive an adequate evaluation or an etiologic diagnosis. Those living in locations just above the national median ADI levels had the lowest likelihood of receiving an etiologic diagnosis, lower than those in the least and most deprived areas. Renewed awareness efforts among providers are needed to increase compliance with diagnostic guidelines.

Insights from a 7-Year Dementia Cohort (VALCODIS): ApoE Genotype Evaluation

Background: The VALCODIS (Valencian Cognitive Diseases Study) cohort was designed and studied at the Hospital Universitari i Politècnic La Fe (Valencia, Spain) for the research of cognitive diseases, especially in the search for new biomarkers of Alzheimer's disease (AD). Methods: Participants in the VALCODIS cohort had cerebrospinal fluid (CSF) and blood samples, neuroimaging, and neuropsychological tests. The ApoE genotype was evaluated to identify its relationship with CSF biomarkers and neuropsychological tests in AD and non-AD participants. Results: A total of 1249 participants were included. They were mainly AD patients (n = 547) but also patients with other dementias (frontotemporal lobar dementia (n = 61), Lewy body dementia without AD CSF signature (n = 10), vascular dementia (n = 24) and other specific causes of cognitive impairment (n = 442), and patients with subjective memory complaints (n = 165)). In the ApoE genotype evaluation, significant differences were found for Aβ42 levels between genotypes in both AD and non-AD patients, as well as a negative correlation between tau values and a cognitive test in non-carriers and ε4 heterozygous. Conclusions: The VALCODIS cohort provides biologically diagnosed patients with demographical, clinical and biochemical data, and biological samples for further studies on early AD diagnosis. Also, the ApoE genotype evaluation showed correlations between CSF biomarkers and neuropsychological tests.

Thyroid Function and Cognitive Decline: A Narrative Review

OBJECTIVE

As the population of older adults in the United States continues to rise, understanding modifiable risk factors that contribute to cognitive decline and dementia becomes increasingly important. This narrative review summarizes existing literature on the association between thyroid function in the euthyroid range, hypothyroidism and hyperthyroidism, and cognitive outcomes in older adults.

METHODS

A comprehensive literature search of the PubMed and Ovid/Medline databases was conducted. Randomized controlled trials, systematic reviews, meta-analyses, and observational studies published in English between January 2000 and December 2023 were included.

RESULTS

Overall, existing studies yielded conflicting results, failing to delineate a concrete relationship between thyroid function and cognitive outcomes and/or dementia in older adults. There may be a possible association between higher thyroid stimulating hormone in the reference range and lower risk of incident dementia, which may be more pronounced in women. Majority of studies elucidated a possible association between low thyroid stimulating hormone and incident dementia, with suggestion that duration of hyperthyroidism may contribute to increasing dementia risk. Even though evidence on the association of hypothyroidism and cognitive decline are disparate, current data do not support treatment of subclinical hypothyroidism to improve cognitive outcomes in older adults.

CONCLUSION

Despite numerous studies, there is no conclusive evidence that supports a direct relationship between hyperthyroidism or hypothyroidism and cognitive decline. Study limitations include heterogeneity in study designs, measurement methodologies, and cognitive assessment tools. Future research is needed to better delineate whether an association exists and whether treatment of thyroid dysfunction ameliorates cognitive impairment.

A feature-aware multimodal framework with auto-fusion for Alzheimer's disease diagnosis

Alzheimer's disease (AD), one of the most common dementias, has about 4.6 million new cases yearly worldwide. Due to the significant amount of suspected AD patients, early screening for the disease has become particularly important. There are diversified types of AD diagnosis data, such as cognitive tests, images, and risk factors, many prior investigations have primarily concentrated on integrating only high-dimensional features and simple fusion concatenation, resulting in less-than-optimal outcomes for AD diagnosis. Therefore, We propose an enhanced multimodal AD diagnostic framework comprising a feature-aware module and an automatic model fusion strategy (AMFS). To preserve the correlation and significance features within a low-dimensional space, the feature-aware module employs a low-dimensional SHapley Additive exPlanation (SHAP) boosting feature selection as the initial step, following this analysis, diverse tiers of low-dimensional features are extracted from patients' biological data. Besides, in the high-dimensional stage, the feature-aware module integrates cross-modal attention mechanisms to capture subtle relationships among different cognitive domains, neuroimaging modalities, and risk factors. Subsequently, we integrate the aforementioned feature-aware module with graph convolutional networks (GCN) to address heterogeneous data in multimodal AD, while also possessing the capability to perceive relationships between different modalities. Lastly, our proposed AMFS autonomously learns optimal parameters for aligning two sub-models. The validation tests using two ADNI datasets show the high accuracies of 95.9% and 91.9% respectively, in AD diagnosis. The methods efficiently select features from multimodal AD data, optimizing model fusion for potential clinical assistance in diagnostics.

Post hoc analysis of the characteristics and treatment needs of patients with dementia with Lewy bodies (DLB) and their caregivers and their physicians' awareness of those treatment needs according to the duration after diagnosis of DLB

OBJECTIVES

To investigate the differences in patient/caregiver characteristics, their treatment needs, and the attending physician's understanding of those treatment needs according to the duration after diagnosis of dementia with Lewy bodies (DLB).

METHODS

This was a post hoc analysis of a multicenter, cross-sectional, questionnaire survey study. A total of 263 patient-caregiver pairs were reclassified into two groups according to the median duration after diagnosis of DLB as follows: short (<24 months; S-group) and long (≥24 months; L-group) post-DLB diagnosis duration. Treatment need was defined as the symptom domain that caused the patient or caregiver the most distress. Concordance rates between patient-physician and caregiver-physician were calculated for physicians' understanding of treatment needs.

RESULTS

In this analysis, 126 pairs (32 physicians) and 137 pairs (34 physicians) were classified as the S- and L-groups, respectively. Patient and caregiver characteristics were broadly similar between groups (mean age for patients 78.7 ± 6.6 vs. 79.8 ± 6.7, for caregivers 64.7 ± 12.9 vs. 64.9 ± 12.8; number of male/female for patients 61/65 vs. 67/70, for caregivers 34/92 vs. 38/99), but the prevalence of parkinsonism (82.5% vs. 66.7%) and autonomic dysfunction (49.6% vs. 33.3%), severity of parkinsonism (MDS-UPDRS Part III total scores, 29.2 ± 22.6 vs. 18.0 ± 16.4; Part II total score, 14.6 ± 12.0 vs. 7.6 ± 7.9), and caregiver burden (J-ZBI_8 score, 9.1 ± 6.7 vs. 7.5 ± 5.8) were higher in the L-group than the S-group. Regarding treatment needs, the invalid answer rates for patients were 34.9% and 46.8%, and those for caregivers were 28.6% and 34.9% in the S- and L groups, respectively. Patients' treatment needs did not significantly differ (p = 0.056), but S-group patients were more likely to select cognitive impairment (p = 0.045) as their treatment need, whereas L-group patients were more likely to select parkinsonism (p = 0.003). Caregivers' treatment needs significantly differed (p = 0.032) between groups. S-group caregivers were more likely to select cognitive impairment (p = 0.001), whereas L-group caregivers were more likely to select other symptom domains such as parkinsonism (S-group vs. L-group: 10.3% vs. 16.7%), psychiatric symptoms (20.6% vs. 24.6%), sleep-related disorder (4.0% vs. 7.1%), and autonomic dysfunction (4.8% vs. 9.5%). Concordance rates between patient-physician and caregiver-physician were low in both groups.

CONCLUSIONS

There were some differences in characteristics according to the duration after diagnosis of DLB. Cognitive dysfunction may be a particular concern for patients and caregivers soon after diagnosis of DLB. Treatment needs of patients and caregivers for parkinsonism, psychiatric symptoms, sleep-related disorder, or autonomic dysfunction were different according to the duration after diagnosis of DLB. Physicians' perception of patients'/caregivers' treatment needs was poor regardless of the duration after diagnosis of DLB.

CLINICAL TRIAL REGISTRATION

UMIN Clinical Trials Registry (UMIN000041844).

Resistance and Resilience to Alzheimer's Disease

Dementia is a significant public health crisis; the most common underlying cause of age-related cognitive decline and dementia is Alzheimer's disease neuropathologic change (ADNC). As such, there is an urgent need to identify novel therapeutic targets for the treatment and prevention of the underlying pathologic processes that contribute to the development of AD dementia. Although age is the top risk factor for dementia in general and AD specifically, these are not inevitable consequences of advanced age. Some individuals are able to live to advanced age without accumulating significant pathology (resistance to ADNC), whereas others are able to maintain cognitive function despite the presence of significant pathology (resilience to ADNC). Understanding mechanisms of resistance and resilience will inform therapeutic strategies to promote these processes to prevent or delay AD dementia. This article will highlight what is currently known about resistance and resilience to AD, including our current understanding of possible underlying mechanisms that may lead to candidate preventive and treatment interventions for this devastating neurodegenerative disease.

Tear Proteins Altered in Patients with Persistent Eye Pain after Refractive Surgery: Biomarker Candidate Discovery

Some patients develop persistent eye pain after refractive surgery, but factors that cause or sustain pain are unknown. We tested whether tear proteins of patients with pain 3 months after surgery differ from those of patients without pain. Patients undergoing refractive surgery (laser in situ keratomileusis or photorefractive keratectomy ) were recruited from 2 clinics, and tears were collected 3 months after surgery. Participants rated their eye pain using a numerical rating scale (NRS, 0-10; no pain-worst pain) at baseline, 1 day, and 3 months after surgery. Using tandem mass tag proteomic analysis, we examined tears from patients with pain [NRS ≥ 3 at 3 months (n = 16)] and patients with no pain [NRS ≤ 1 at 3 months (n = 32)] after surgery. A subset of proteins (83 of 2748 detected, 3.0%) were associated with pain 3 months after surgery. High-dimensional statistical models showed that the magnitude of differential expression was not the only important factor in classifying tear samples from pain patients. Models utilizing 3 or 4 proteins had better classification performance than single proteins and represented differences in both directions (higher or lower in pain). Thus, patterns of protein differences may serve as biomarkers of postsurgical eye pain as well as potential therapeutic targets.

AI-based differential diagnosis of dementia etiologies on multimodal data

Differential diagnosis of dementia remains a challenge in neurology due to symptom overlap across etiologies, yet it is crucial for formulating early, personalized management strategies. Here, we present an artificial intelligence (AI) model that harnesses a broad array of data, including demographics, individual and family medical history, medication use, neuropsychological assessments, functional evaluations and multimodal neuroimaging, to identify the etiologies contributing to dementia in individuals. The study, drawing on 51,269 participants across 9 independent, geographically diverse datasets, facilitated the identification of 10 distinct dementia etiologies. It aligns diagnoses with similar management strategies, ensuring robust predictions even with incomplete data. Our model achieved a microaveraged area under the receiver operating characteristic curve (AUROC) of 0.94 in classifying individuals with normal cognition, mild cognitive impairment and dementia. Also, the microaveraged AUROC was 0.96 in differentiating the dementia etiologies. Our model demonstrated proficiency in addressing mixed dementia cases, with a mean AUROC of 0.78 for two co-occurring pathologies. In a randomly selected subset of 100 cases, the AUROC of neurologist assessments augmented by our AI model exceeded neurologist-only evaluations by 26.25%. Furthermore, our model predictions aligned with biomarker evidence and its associations with different proteinopathies were substantiated through postmortem findings. Our framework has the potential to be integrated as a screening tool for dementia in clinical settings and drug trials. Further prospective studies are needed to confirm its ability to improve patient care.

A Framework for the Administration of Anti-amyloid Monoclonal Antibody Treatments in Early-Stage Alzheimer's Disease

The US Food and Drug Administration (FDA) approval of lecanemab for early-stage Alzheimer's disease (AD) represents an exciting new chapter in the management of neurodegenerative disease, but likewise presents numerous clinical, technical, and financial logistical challenges for both academic and non-academic medical institutions hoping to administer this drug. Minimal resources exist that provide guidance for establishing and maintaining a lecanemab treatment program at the institutional level. The current report aims to provide healthcare institutions a framework for the planning, onboarding, and longitudinal treatment of AD with anti-amyloid monoclonal antibody treatments. We present an implementation study involving three stages: (1) feasibility assessment, (2) operations and going live, and (3) monitoring assessment. We found that implementation of lecanemab in clinical practice was feasible due to the assignment of an enterprise-wide project manager to facilitate the planning phase, a cost analysis showing that lecanemab was financially sustainable, and the development of electronic medical record tools to support operational efficiency.

Clinical spectrum of late symptomatic neurosyphilis in China: an 11-year retrospective study

OBJECTIVES

This study aimed to describe the clinical features of neurosyphilis in Chinese patients in an attempt to find clinical features that are helpful for the early identification of neurosyphilis.

METHODS

This retrospective study included people with syphilis who visited Shanghai Skin Disease Hospital between January 2010 and December 2020. Lumbar puncture was performed on those who met the inclusion and exclusion criteria. The diagnosis of neurosyphilis was based on clinical and laboratory findings. The parameters were analysed statistically.

RESULTS

Of the 3524 patients with neurosyphilis, 2111 (59.9%) and 1413 (40.1%) were asymptomatic and symptomatic neurosyphilis, respectively. General paresis was the most common type of symptomatic neurosyphilis (46.8%). The clinical manifestations of symptomatic neurosyphilis include psychiatric and neurotic symptoms, among which general paresis predominantly presented as psychiatric symptoms such as affective (66.7%) and memory disorder (72.9%). Tabes dorsalis is often presented as neurotic symptoms. One hundred fifty patients (10.6%) with symptomatic neurosyphilis presented candy signs, a rare and specific neurosyphilis symptom that is common in general paresis. Girdle sensation was presented in 13 patients, mainly with tabes dorsalis, which had not been reported in previous studies.

CONCLUSIONS

Notably, the candy sign is identified as a specific symptom of general paresis, while girdle sensations are highlighted as a particular symptom of tabes dorsalis. This is the largest study describing the clinical spectrum of neurosyphilis since the onset of the penicillin era and could help doctors learn more about the disease. A comprehensive description of the possible clinical manifestations of late symptomatic neurosyphilis, particularly highlighting rare symptoms, can identify suspicious patients and prevent diagnostic delays.

Cognitive Impairment in the Primary Care Clinic

Cognitive impairment is a common problem in the geriatric population and is characterized by variable symptoms of memory difficulties, executive dysfunction, language or visuospatial problems, and behavioral changes. It is imperative that primary care clinicians recognize and differentiate the variable symptoms associated with cognitive impairment from changes attributable to normal aging or secondary to other medical conditions. A thorough evaluation for potentially reversible causes of dementia is required before diagnosis with a neurodegenerative dementia. Other abnormal neurologic findings, rapid progression, or early age of onset are red flags that merit referral to neurology for more specialized evaluation and treatment.

Dementia with Lewy bodies: Primary care PAs can make this difficult diagnosis

ABSTRACT

Lewy body dementia is an umbrella term for dementia with Lewy bodies (DLB) and Parkinson disease dementia. These progressive, degenerative brain disorders link dementia with psychosis and parkinsonism and are difficult to diagnose. The diagnosis of DLB is challenging, especially in its early phase, because the presentation is variable. Relevant screening tools and a complete physical examination are essential. Making the correct diagnosis lets patients and caregivers make arrangements, have more timely access to services, improve patient quality of life, and lessen the burden on caregivers.

Differential atrophy along the longitudinal hippocampal axis in Alzheimer's disease

Alzheimer's disease (AD) is a progressive neurodegenerative disorder that primarily affects the hippocampus. Since hippocampal studies have highlighted a differential subregional regulation along its longitudinal axis, a more detailed analysis addressing subregional changes along the longitudinal hippocampal axis has the potential to provide new relevant biomarkers. This study included structural brain MRI data of 583 participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Cognitively normal (CN) subjects, mild cognitively impaired (MCI) subjects and AD patients were conveniently selected considering the age and sex match between clinical groups. Structural MRI acquisitions were pre-processed and analysed with a new longitudinal axis segmentation method, dividing the hippocampus in three subdivisions (anterior, intermediate, and posterior). When normalizing the volume of hippocampal sub-divisions to total hippocampus, the posterior hippocampus negatively correlates with age only in CN subjects (r = -.31). The longitudinal ratio of hippocampal atrophy (anterior sub-division divided by the posterior one) shows a significant increase with age only in CN (r = .25). Overall, in AD, the posterior hippocampus is predominantly atrophied early on. Consequently, the anterior/posterior hippocampal ratio is an AD differentiating metric at early disease stages with potential for diagnostic and prognostic applications.

Incidence and Prevalence of Dementia: A 2015-2020 Population-Based Study in the Campania Region of Italy

OBJECTIVE

The aims of this study were to provide population-based estimates of prevalence and incidence of any dementia and Alzheimer's dementia (AD) in the Campania region (South Italy) and to validate towards a clinical registry.

METHODS

This was a population-based study, using routinely collected healthcare data of individuals living in the Campania region (South Italy) from 2015 to 2020. We included individuals aged ≥65 years alive at the prevalence day (January 1, 2021) who had at least one administrative record for dementia and/or AD from 2015 to 2020. Age-and sex-standardised prevalence rates were calculated using direct standardisation method (European population in 2020 as the reference population). To estimate the incidence, we tested three possible algorithms, which differed for the duration of the time interval between study baseline (January 1, 2015) and index date (first record for dementia and/or AD in administrative databases). We employed a clinical database for the validation of our algorithms towards neuropsychological test results.

RESULTS

Among individuals aged over 65 years, 80,392 had dementia, of which 35,748 had AD. The age- and sex-standardised prevalence rates per 1,000 individuals for any dementia and AD were 77.64 (95% confidence interval [CI] = 77.57; 77.68) and 34.05 (95% CI = 34.01; 34.09), respectively. There were 82.10 incident cases of any dementia per 100,000 per year (0.79 sensitivity and 0.62 specificity) and 59.89 incident cases of AD per 100,000 per year (0.80 sensitivity and 0.59 specificity). The capture-recapture method showed a very low number of undetected cases (1.7% for any dementia and 3.0% for AD). Our algorithms showed acceptable performance with the area under the curve ranging from 0.59 to 0.72 and a double likelihood ratio of correctly identifying individuals above and below mini-mental status examination (MMSE) standard cut-offs (24 and 26).

CONCLUSIONS

Prevalence and incidence of any dementia and AD in the Campania region (South Italy) from 2015 to 2020 are in line with previous estimates from other countries. Our algorithm, integrating administrative and clinical data, holds potential for assessing dementia's epidemiological burden, identifying risk factors, planning healthcare access, and developing prevention strategies.

AI-based differential diagnosis of dementia etiologies on multimodal data

Differential diagnosis of dementia remains a challenge in neurology due to symptom overlap across etiologies, yet it is crucial for formulating early, personalized management strategies. Here, we present an AI model that harnesses a broad array of data, including demographics, individual and family medical history, medication use, neuropsychological assessments, functional evaluations, and multimodal neuroimaging, to identify the etiologies contributing to dementia in individuals. The study, drawing on 51,269 participants across 9 independent, geographically diverse datasets, facilitated the identification of 10 distinct dementia etiologies. It aligns diagnoses with similar management strategies, ensuring robust predictions even with incomplete data. Our model achieved a micro-averaged area under the receiver operating characteristic curve (AUROC) of 0.94 in classifying individuals with normal cognition, mild cognitive impairment and dementia. Also, the micro-averaged AUROC was 0.96 in differentiating the dementia etiologies. Our model demonstrated proficiency in addressing mixed dementia cases, with a mean AUROC of 0.78 for two co-occurring pathologies. In a randomly selected subset of 100 cases, the AUROC of neurologist assessments augmented by our AI model exceeded neurologist-only evaluations by 26.25%. Furthermore, our model predictions aligned with biomarker evidence and its associations with different proteinopathies were substantiated through postmortem findings. Our framework has the potential to be integrated as a screening tool for dementia in various clinical settings and drug trials, with promising implications for person-level management.

Syphilis Serologies: A Practical Approach for the Primary Care Clinician

Syphilis serology interpretation can be challenging even for experienced providers. This article reviews the staging of syphilis and the principles of syphilis serology testing, the algorithms used in diagnosis, and guidance for their use in monitoring the response to treatment. The authors illustrate these principles through a series of clinical scenarios and describe the rationale behind the management approaches.

Non-indicated vitamin B12- and D-testing among Dutch hospital clinicians: a cross-sectional analysis in data registries

OBJECTIVES

To assess the extent of non-indicated vitamin B12- and D-testing among Dutch clinicians and its variation among hospitals.

DESIGN

Cross-sectional study using registration data from 2015 to 2019.

PARTICIPANTS

Patients aged between 18 and 70 years who received a vitamin B12- or D-test.

PRIMARY AND SECONDARY OUTCOME MEASURES

The proportion of non-indicated vitamin B12- and D-testing among Dutch clinicians and its variation between hospitals (n=68) over 2015-2019.

RESULTS

Between 2015 and 2019, at least 79.0% of all vitamin B12-tests and 82.0% of vitamin D-tests lacked a clear indication. The number of vitamin B12-tests increased by 2.0% over the examined period, while the number of D-tests increased by 12.2%. The proportion of the unexplained variation in non-indicated vitamin B12- and D-tests that can be ascribed to differences between hospitals remained low. Intraclass correlation coefficients ranged between 0.072 and 0.085 and 0.081 and 0.096 for non-indicated vitamin B12- and D-tests, respectively. The included casemix variables patient age, gender, socioeconomic status and hospital size only accounted for a small part of the unexplained variation in non-indicated testing. Additionally, a significant correlation was observed in non-indicated vitamin B12- and D-testing among the included hospitals.

CONCLUSION

Hospital clinicians order vitamin B12- and D-tests without a clear indication on a large scale. Only a small proportion of the unexplained variation could be attributed to differences between hospitals.

Association between plasma CTRPs with cognitive impairment and neurodegeneration of Alzheimer's disease

AIMS

Recent evidence indicated the biological basis of complement 1q (C1q)/tumor necrosis factor (TNF)-related protein (CTRP) 3, 4, and 14 for affecting brain structure and cognitive function. Thus, we aimed to investigate the association between plasma CTRPs with Alzheimer's disease (AD).

METHODS

A multicenter, cross-sectional study recruited patients with AD (n = 137) and cognitively normal (CN) controls (n = 140). After the data collection of demographic characteristics, lifestyle risk factors, and medical history, plasma levels of tau phosphorylated at threonine 217 (pT217), pT181, neurofilament light (NfL), CTRP3, 4, and 14 were examined and compared. Multivariate logistic regression analysis was applied to determine associations of plasma CTPRs with the presence of AD. The correlation analysis was used to explore correlations between plasma CTPRs with scores of Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), Activities of Daily Living (ADL) scale, and Clinical Dementia Rating Sum of Boxes (CDR-SB), and levels of plasma pT217, pT181, and NfL. Receiver-operating characteristic (ROC) analysis and Delong's test were used to determine the diagnostic power of plasma CTPRs.

RESULTS

Plasma levels of CTRP3, 4, and 14 were higher in AD group than those in CN group. After adjusting for conventional risk factors, CTRP3, CTRP4, and CTRP14 were associated with the presence of AD. In AD patients, CTRP3 was negatively correlated with scores of MMSE and MoCA, while positively correlated with ADL score, CDR-SB score, pT217, and pT181; CTRP4 was positively correlated with CDR-SB score, pT181, and NfL; CTRP14 was negatively correlated with MMSE score, while positively correlated with CDR-SB score, pT217, and NfL. An independent addition of CTRP3 and 4 to the basic model combining age, sex, years of education, APOE4 status, BMI, TG, and HDL-C led to a significant improvement in diagnostic power for AD, respectively.

CONCLUSIONS

All the findings preliminarily uncovered associations between plasma CTRPs and AD and suggested the potential of CTRPs as a blood-derived biomarker for AD.

Clinical parameter-based prediction model for neurosyphilis risk stratification

Accurately predicting neurosyphilis prior to a lumbar puncture (LP) is critical for the prompt management of neurosyphilis. However, a valid and reliable model for this purpose is still lacking. This study aimed to develop a nomogram for the accurate identification of neurosyphilis in patients with syphilis. The training cohort included 9,504 syphilis patients who underwent initial neurosyphilis evaluation between 2009 and 2020, while the validation cohort comprised 526 patients whose data were prospectively collected from January 2021 to September 2021. Neurosyphilis was observed in 35.8% (3,400/9,504) of the training cohort and 37.6% (198/526) of the validation cohort. The nomogram incorporated factors such as age, male gender, neurological and psychiatric symptoms, serum RPR, a mucous plaque of the larynx and nose, a history of other STD infections, and co-diabetes. The model exhibited good performance with concordance indexes of 0.84 (95% CI, 0.83-0.85) and 0.82 (95% CI, 0.78-0.86) in the training and validation cohorts, respectively, along with well-fitted calibration curves. This study developed a precise nomogram to predict neurosyphilis risk in syphilis patients, with potential implications for early detection prior to an LP.

T1 and FLAIR signal intensities are related to tau pathology in dominantly inherited Alzheimer disease

Carriers of mutations responsible for dominantly inherited Alzheimer disease provide a unique opportunity to study potential imaging biomarkers. Biomarkers based on routinely acquired clinical MR images, could supplement the extant invasive or logistically challenging) biomarker studies. We used 1104 longitudinal MR, 324 amyloid beta, and 87 tau positron emission tomography imaging sessions from 525 participants enrolled in the Dominantly Inherited Alzheimer Network Observational Study to extract novel imaging metrics representing the mean (μ) and standard deviation (σ) of standardized image intensities of T1-weighted and Fluid attenuated inversion recovery (FLAIR) MR scans. There was an exponential decrease in FLAIR-μ in mutation carriers and an increase in FLAIR and T1 signal heterogeneity (T1-σ and FLAIR-σ) as participants approached the symptom onset in both supramarginal, the right postcentral and right superior temporal gyri as well as both caudate nuclei, putamina, thalami, and amygdalae. After controlling for the effect of regional atrophy, FLAIR-μ decreased and T1-σ and FLAIR-σ increased with increasing amyloid beta and tau deposition in numerous cortical regions. In symptomatic mutation carriers and independent of the effect of regional atrophy, tau pathology demonstrated a stronger relationship with image intensity metrics, compared with amyloid pathology. We propose novel MR imaging intensity-based metrics using standard clinical T1 and FLAIR images which strongly associates with the progression of pathology in dominantly inherited Alzheimer disease. We suggest that tau pathology may be a key driver of the observed changes in this cohort of patients.

Evaluation and treatment approaches for neurological post-acute sequelae of COVID-19: A consensus statement and scoping review from the global COVID-19 neuro research coalition

Post-acute neurological sequelae of COVID-19 affect millions of people worldwide, yet little data is available to guide treatment strategies for the most common symptoms. We conducted a scoping review of PubMed/Medline from 1/1/2020-4/1/2023 to identify studies addressing diagnosis and treatment of the most common post-acute neurological sequelae of COVID-19 including: cognitive impairment, sleep disorders, headache, dizziness/lightheadedness, fatigue, weakness, numbness/pain, anxiety, depression and post-traumatic stress disorder. Utilizing the available literature and international disease-specific society guidelines, we constructed symptom-based differential diagnoses, evaluation and management paradigms. This pragmatic, evidence-based consensus document may serve as a guide for a holistic approach to post-COVID neurological care and will complement future clinical trials by outlining best practices in the evaluation and treatment of post-acute neurological signs/symptoms.

Association between longitudinal changes in striatal dopamine transporter uptake and clinical features of dementia with Lewy bodies

BACKGROUND

It is widely known that there is low striatal 123 I-2β-Carbomethoxy-3β-(4-iodophenyl)-N-(3- fluoropropyl) nortropane (123 I-FP-CIT) dopamine transporter single photon emission tomography (DaT-SPECT) uptake in patients with dementia with Lewy bodies (DLB). No studies to date have analyzed the association between longitudinal changes of clinical features and DaT uptake in patients with Parkinson syndrome, particularly those with DLB. The aim of this study was to investigate the association between the longitudinal changes in DaT uptake and the severity of parkinsonism and cognitive function in DLB patients.

METHODS

A total of 35 outpatients with probable DLB who underwent DaT-SPECT twice (at the initial examination and the follow-up period) in the Memory Disorder Clinic at the Department of Geriatric Medicine, Tokyo Medical University, were enrolled in this study between April 2014 and September 2020. The correlation between annual changes in DaT uptake and clinical features (cognitive function decline and parkinsonism) of the patients was analyzed.

RESULTS

A significant correlation was detected between annual changes in parkinsonism symptom severity and DaT uptake in the left posterior putamen (r = -0.39, P = 0.03), and between Mini-Mental State Examination scores and DaT uptake in all regions except the right posterior putamen (P < 0.05) in patients with DLB.

CONCLUSIONS

Our results suggested that the pathway from the ventrolateral tier of the substantia nigra to the putamen might be more crucial for motor function than other pathways, not only in Parkinson's disease but also in DLB.

Cost-effectiveness of physical activity interventions for prevention and management of cognitive decline and dementia-a systematic review

BACKGROUND

Although increasing physical activity (PA) has been suggested to prevent and manage cognitive decline and dementia, its economic impact on healthcare systems and society is largely unknown. This study aimed to summarize evidence on the cost-effectiveness of PA interventions to prevent and manage cognitive decline and dementia.

METHODS

Electronic databases, including PubMed/MEDLINE, Embase, and ScienceDirect, were searched from January 2000 to July 2023. The search strategy was driven by a combination of subject-heading terms related to physical activity, cognitive function, dementia, and cost-effectiveness. Selected studies were included in narrative synthesis, and extracted data were presented in narrative and tabular forms. The risk of bias in each study was assessed using the Consolidated Health Economic Evaluation Reporting Standards and Consensus on Health Economic Criteria list.

RESULTS

Five of the 11 identified studies focused on individuals with existing dementia. Six of the 11 identified studies focused on individuals with no existing dementia, including 3 on those with mild cognitive impairment (MCI), and 3 on those with no existing MCI or dementia. PA interventions focused on individuals with no existing dementia were found to be cost-effective compared to the control group. Findings were mixed for PA interventions implemented in individuals with existing dementia.

CONCLUSIONS

PA interventions implemented before or during the early stage of cognitive impairment may be cost-effective in reducing the burden of dementia. More research is needed to investigate the cost-effectiveness of PA interventions in managing dementia. Most existing studies used short-term outcomes in evaluating the cost-effectiveness of PA interventions in the prevention and management of dementia; future research should consider adding long-term outcomes to strengthen the study design.

Navigating Early Alzheimer's Diagnosis: A Comprehensive Review of Diagnostic Innovations

The hunt for early Alzheimer's disease detection has created cutting-edge diagnostic instruments with enormous promise. This article examines the many facets of these developments, focusing on how they have revolutionised diagnosis and patient outcomes. These tools make it possible to detect tiny brain changes even before they give birth to clinical symptoms by combining cutting-edge biomarkers, neuroimaging methods, and machine-learning algorithms. A significant opportunity for therapies that can slow the course of the disease exists during this early detection stage. Additionally, these cutting-edge techniques improve diagnostic precision, objectivity, and accessibility. Liquid biopsies and blood-based biomarkers provide non-invasive alternatives, filling accessibility gaps in diagnosis. While issues with standardisation, ethics, and data integration continue, collaboration within research, clinical practice, and policy realms fuels positive developments. As technology advances, the way towards better Alzheimer's diagnosis becomes more evident, giving patients and families dealing with this difficult illness fresh hope. The synergy between scientific advancement and compassionate treatment is crucial for improving Alzheimer's disease diagnosis, as this paper emphasises.

Detection rate of contrast-enhanced brain magnetic resonance imaging in patients with cognitive impairment

INTRODUCTION

The number of brain MRI with contrast media performed in patients with cognitive impairment has increased without universal agreement. We aimed to evaluate the detection rate of contrast-enhanced brain MRI in patients with cognitive impairment.

MATERIALS AND METHODS

This single-institution, retrospective study included 4,838 patients who attended outpatient clinics for cognitive impairment evaluation and underwent brain MRI with or without contrast enhancement from December 2015 to February 2020. Patients who tested positive for cognitive impairment were followed-up to confirm whether the result was true-positive and provide follow-up management. Detection rate was defined as the proportion of patients with true-positive results and was compared between groups with and without contrast enhancement. Individual matching in a 1:2 ratio according to age, sex, and year of test was performed.

RESULTS

The overall detection rates of brain MRI with and without contrast media were 4.7% (57/1,203; 95% CI: 3.6%-6.1%) and 1.8% (65/3,635; 95% CI: 1.4%-2.3%), respectively (P<0.001); individual matching demonstrated similar results (4.7% and 1.9%). Among 1,203 patients with contrast media, 3.6% was only detectable with the aid of contrast media. The proportion of patients who underwent follow-up imaging or treatment for the detected lesions were significantly higher in the group with contrast media (2.0% and 0.6%, P < .001).

CONCLUSIONS

Detection rate of brain MRI for lesions only detectable with contrast media in patients with cognitive impairment was not high enough and further study is needed to identify whom would truly benefit with contrast media.

Impaired Sensitivity to Thyroid Hormones is Associated with Mild Cognitive Impairment in Euthyroid Patients with Type 2 Diabetes

Purpose

The prevalence of mild cognitive impairment (MCI) in patients with type 2 diabetes (T2D) is rapidly increasing. Thyroid hormones are key regulators of cognitive function in adults. The purpose of this study was to investigate the relationship between thyroid hormone sensitivity and MCI in euthyroid T2D patients.

Patients and Methods

A total of 400 euthyroid T2D patients were enrolled in this cross-sectional study, including 218 patients with normal cognition and 182 MCI patients. The Montreal Cognitive Assessment (MoCA) was used to evaluate cognitive function. The free triiodothyronine to free thyroxine (FT3/FT4) ratio was calculated as a measure of peripheral sensitivity to thyroid hormones; the thyroid-stimulating hormone index (TSHI), thyrotrophic thyroxine resistance index (TT4RI) and thyroid feedback quantile-based index (TFQI) were calculated as measures of central sensitivity to thyroid hormones. Linear regression analysis and logistic regression analysis were performed to explore the relationships between these indices of thyroid hormone sensitivity and the MoCA score and MCI, respectively.

Results

Compared with the normal cognitive function group, patients in the MCI group had higher TSHI, TT4RI and TFQI but a lower FT3/FT4 ratio (P<0.05). The MoCA score was positively correlated with the FT3/FT4 ratio but negatively correlated with TSHI, TT4RI and TFQI (P< 0.05). Multivariate logistic regression analysis showed that a low FT3/FT4 ratio and high TSHI, TT4RI and TFQI were independently associated with MCI (P<0.05). After adjustment for confounding factors, the odds ratio (OR) for the association between MCI and the highest tertile of the FT3/FT4 was 0.455 (95% CI: 0.264-0.785), for the highest tertile of TSHI, the OR was 2.380 (95% CI: 1.376-4.119), for the highest tertile of TT4RI, the OR was 2.342 (95% CI:1.353-4.054), and for the highest tertile of TFQI, the OR was 2.536 (95% CI: 1.466-4.387) (P< 0.05).

Conclusion

Impaired sensitivity to thyroid hormones is associated with MCI in euthyroid T2D patients.

Charting the Next Road Map for CSF Biomarkers in Alzheimer's Disease and Related Dementias

Clinical prediction of underlying pathologic substrates in people with Alzheimer's disease (AD) dementia or related dementia syndromes (ADRD) has limited accuracy. Etiologic biomarkers - including cerebrospinal fluid (CSF) levels of AD proteins and cerebral amyloid PET imaging - have greatly modernized disease-modifying clinical trials in AD, but their integration into medical practice has been slow. Beyond core CSF AD biomarkers (including beta-amyloid 1-42, total tau, and tau phosphorylated at threonine 181), novel biomarkers have been interrogated in single- and multi-centered studies with uneven rigor. Here, we review early expectations for ideal AD/ADRD biomarkers, assess these goals' future applicability, and propose study designs and performance thresholds for meeting these ideals with a focus on CSF biomarkers. We further propose three new characteristics: equity (oversampling of diverse populations in the design and testing of biomarkers), access (reasonable availability to 80% of people at risk for disease, along with pre- and post-biomarker processes), and reliability (thorough evaluation of pre-analytical and analytical factors influencing measurements and performance). Finally, we urge biomarker scientists to balance the desire and evidence for a biomarker to reflect its namesake function, indulge data- as well as theory-driven associations, re-visit the subset of rigorously measured CSF biomarkers in large datasets (such as Alzheimer's disease neuroimaging initiative), and resist the temptation to favor ease over fail-safe in the development phase. This shift from discovery to application, and from suspended disbelief to cogent ingenuity, should allow the AD/ADRD biomarker field to live up to its billing during the next phase of neurodegenerative disease research.

Alzheimer Disease and Related Cognitive Impairment in Older Adults: A Narrative Review of Screening, Prevention, and Management for Manual Therapy Providers

Objective

The aim of this narrative review was to review literature relevant to manual therapists about cognitive impairment, together with screening, potential treatment, and prevention modalities.

Methods

A literature search of AMED (Allied and Complementary Medicine Database), CINAHL (Cumulative Index of Nursing and Allied Health Literature), PubMed, and MEDLINE was conducted with the search terms "cognitive decline," "cognitive impairment," "screening," and "prevention." We reviewed current screening practices, including functional exams, imaging, and laboratory testing. We reviewed current potential preventive measures and treatments being implemented in practice.

Results

We selected 49 resources for this narrative summary. The Montreal Cognitive Assessment and Mini-Mental State Exam are recommended screening tools. Imaging and laboratory testing are not recommended in screening for cognitive decline. Promotion of healthy, active living through physical and mental activities may assist with prevention of cognitive decline.

Conclusion

Cognitive decline affects a large proportion of the US population. Recognizing signs and symptoms of this condition starts with individuals, caretakers, family members, and health care providers. Health care providers should utilize the most appropriate screening tools to assess the presence of cognitive conditions.

Developing Biomarkers for the Skin: Biomarkers for the Diagnosis and Prediction of Treatment Outcomes of Alzheimer's Disease

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by memory decline and cognitive impairment. Research on biomarkers can aid in early diagnosis, monitoring disease progression, evaluating treatment efficacy, and advancing fundamental research. We conducted a cross-sectional longitudinal study to see if there is an association between AD patients and age-matched healthy controls for their physiologic skin characteristics, such as pH, hydration, transepidermal water loss (TEWL), elasticity, microcirculation, and ApoE genotyping. The study used the Mini-Mental State Examination (MMSE) and Clinical Dementia Rating-Sum of the Boxes (CDR-SB) scales as references to quantify the presence of disease, if any. Our findings demonstrate that AD patients have a dominantly neutral pH, greater skin hydration, and less elasticity compared to the control subjects. At baseline, the tortuous capillary percentage negatively correlated with MMSE scores in AD patients. However, AD patients who carry the ApoE E4 allele and exhibit a high percentage of tortuous capillaries and capillary tortuous numbers have shown better treatment outcomes at six months. Therefore, we believe that physiologic skin testing is a rapid and effective way to screen, monitor progression, and ultimately guide the most appropriate treatment for AD patients.

Assessing cognitive impairment in an ethnically diverse cohort of oldest-old: the life after 90 study

BACKGROUND

Though dementia rates vary by racial or ethnic groups, it is unknown if these disparities remain among those aged 90 or older.

AIMS

To test this hypothesis, we used baseline clinical evaluation of 541 ethnically and racially diverse individuals participating in the LifeAfter90 Study to assess how associations between core demographic characteristics and measures of physical and cognitive performance differ across the racial/ethnic groups.

METHODS

Participants in this study were long-term non-demented members of Kaiser Permanente Northern California. They were clinically evaluated and diagnosed with normal or impaired cognition (mild cognitive impairment and dementia) through an in-person comprehensive clinical assessment consisting of a detailed medical history, physical and neurological examination, functional, and cognitive tests.

RESULTS

The average age at enrollment was 93.0 ± 2.6 years, 62.4% female and 34.2% non-Hispanic White. At initial evaluation 301 participants had normal cognition and 165 had mild cognitive impairment (MCI) and despite screening, 69 participants were determined to have dementia. Age, education, 3MS, FAQ and CDR scores were significantly associated with cognitive impairment (normal versus MCI and dementia), but not gender. There was a significant univariate association between race/ethnicity and cognitive impairment (p < 0.02) being highest among Black (57.4%) and lowest among Asian (32.7%) individuals. After adjustment for age, gender, and education, however, prevalence of cognitive impairment was not influenced by race or ethnicity.

CONCLUSION

Our results confirm the ability to reliably assess clinical diagnosis in a diverse sample of very old individuals.

Sex Differences in Alzheimer's Disease

Reviewing the research presented in this article, it is evident that from an epidemiological perspective, it is important to evaluate the extent to which findings of sex and gender differences in Alzheimer's dementia (AD) are due to differences in longevity, survival bias, and comorbidities. Medical, genetic, psychosocial, and behavioral factors, in addition to hormonal factors, can differentially affect the risk and progression of AD in women versus men. Further, evaluation of sex differences in AD progression and the trajectory of change in cognitive function, neuroimaging, cerebrospinal fluid (CSF), and blood-based biomarkers of AD is needed. Finally, identifying sex differences in AD biomarkers and change across the lifespan is critical for the planning of prevention trials to reduce the risk of developing AD.

HEBP1 - An early trigger for neuronal cell death and circuit dysfunction in Alzheimer's disease

Alzheimer's Disease (AD) is a progressive neurodegenerative disorder that gradually impairs memory, cognition and the ability to perform simple daily tasks. It is the most prevalent form of dementia in the elderly and its incidence increases exponentially with age. Neuronal and synapse loss, key hallmarks of the disorder, are widely regarded to occur early during the onset of AD, and the extent of this loss closely correlates with the progression of cognitive decline and dysfunction of the underlying neuronal circuity. Nevertheless, the mechanisms driving neuronal and synapse loss during early AD remains poorly understood. This review focuses on Heme-binding protein 1 (HEBP1), a mitochondrial-associated protein that has recently emerged as an important mediator of neuronal cell death during early AD pathogenesis. Acting downstream of Aβ and heme, HEBP1-mediated apoptosis contributes to neuronal loss and neuronal circuit dysfunction. Deleting HEBP1 expression in neurons protects them from heme- and Aβ-induced apoptosis, both of which are mechanisms implicated in neurodegeneration. HEBP1 participates in heme metabolism and binds to heme to modulate mitochondrial dynamics vital to the maintenance of neural circuitry that is affected in AD. HEBP1 elevation is also associated with AGE/RAGE-related neuronal damage, further implicating its involvement in neuronal loss during early AD. Moreover, F2L, a cleavage product of HEBP1 modulates inflammation. Collectively, these findings highlight the importance of HEBP1 in the disruption of neural circuits during early AD.

Psychological Problem Diagnosis and Management in the Geriatric Age Group

The definition of geriatrics is very complex to explain though it can be written as the treatment and care provided by healthcare and medical systems primarily to more venerable and senior citizens group of the population. The age group considered to be entering the old group is believed to be those who have reached their sixth decade of life. However, most of the global geriatric population doesn't need treatment until their seventh decade. Bodily impairment, both physical and mental, due to various reasons, for example, financial or personal reasons or feeling ignored, is reasonable for clinicians to anticipate caring for a growing proportion of older patients with complicated medical and psychosocial concerns. Complex ethical quandaries could develop as a result of these difficulties and problems. Who should anticipate ethical challenges faced by doctors early during management? We offer practical recommendations for improving communication because ineffective patient-clinician communication might result in moral dilemmas. Physical impairment, hopelessness, and cognitive decline are all more prevalent as people age. Politicians and healthcare providers of nations should step in to search for a measure to reduce the uprising of the condition; otherwise, it will lead to an uprising of the cases in an exponential manner. It is necessary to increase the financial challenges faced by the elderly. In addition, awareness should be increased, as well as programs aimed at enhancing their standard of living.

Multimodality neuroimaging in vascular mild cognitive impairment: A narrative review of current evidence

The vascular mild cognitive impairment (VaMCI) is generally accepted as the premonition stage of vascular dementia (VaD). However, most studies are focused mainly on VaD as a diagnosis in patients, thus neglecting the VaMCI stage. VaMCI stage, though, is easily diagnosed by vascular injuries and represents a high-risk period for the future decline of patients’ cognitive functions. The existing studies in China and abroad have found that magnetic resonance imaging technology can provide imaging markers related to the occurrence and development of VaMCI, which is an important tool for detecting the changes in microstructure and function of VaMCI patients. Nevertheless, most of the existing studies evaluate the information of a single modal image. Due to the different imaging principles, the data provided by a single modal image are limited. In contrast, multi-modal magnetic resonance imaging research can provide multiple comprehensive data such as tissue anatomy and function. Here, a narrative review of published articles on multimodality neuroimaging in VaMCI diagnosis was conducted，and the utilization of certain neuroimaging bio-markers in clinical applications was narrated. These markers include evaluation of vascular dysfunction before tissue damages and quantification of the extent of network connectivity disruption. We further provide recommendations for early detection, progress, prompt treatment response of VaMCI, as well as optimization of the personalized treatment plan.

Association of thyroid disease with risks of dementia and cognitive impairment: A meta-analysis and systematic review

Introduction

It is still uncertain whether the risk of dementia and cognitive impairment is related to thyroid disease. we carried out a meta-analysis and systematic review (PROSPERO: CRD42021290105) on the associations between thyroid disease and the risks of dementia and cognitive impairment.

Methods

We searched PubMed, Embase, and Cochrane Library for studies published up to August 2022. The overall relative risk (RRs) and its 95% confidence interval (CIs) were calculated in the random-effects models. Subgroup analyses and meta-regression were conducted to explore the potential source of heterogeneity among studies. We tested and corrected for publication bias by funnel plot-based methods. The Newcastle-Ottawa Scale (NOS) or Agency for Healthcare Research and Quality (AHRQ) scale were used to evaluate the study quality of longitudinal studies and cross-sectional studies, respectively.

Results

A total of 15 studies were included in our meta-analysis. Our meta-analysis showed that hyperthyroidism (RR = 1.14, 95% CI = 1.09–1.19) and subclinical hyperthyroidism (RR = 1.56, 95% CI = 1.26–1.93) might be associated with an elevated risk for dementia, while hypothyroidism (RR = 0.93, 95% CI = 0.80–1.08) and subclinical hypothyroidism (RR = 0.84, 95% CI = 0.70–1.01) did not affect the risk.

Discussion

Hyperthyroidism and subclinical hyperthyroidism are predictors of dementia.

Systematic review registration

PROSPERO, Identifier: CRD42021290105.

Chemokines in patients with Alzheimer's disease: A meta-analysis

Background

Alzheimer's disease (AD) is the most common neurodegenerative disease in elderly people. Many researches have reported that neuroinflammation is related to AD. Chemokines are a class of small cytokines that play important roles in cell migration and cell communication, which involved in neuroinflammation. Up to now there is no meta-analysis to explore the difference of chemokines between AD patients and healthy elderly individuals.

Method

We searched PubMed, Web of science, Cochrane library, EMBASE and Scopus databases from inception to January 2022. Data were extracted by two independent reviewers, and the Review Manager 5.3 was used for the meta-analysis.

Result

Thirty-two articles were included and analyzed. The total number of participants in the included study was 3,331. We found that the levels of CCL5 (SMD = 2.56, 95% CI: 1.91–3.21), CCL15 (SMD = 3.30, 95% CI: 1.48–5.13) and IP-10 (SMD = 3.88, 95% CI: 1.84–5.91) in the plasma of AD patients were higher than healthy people. MCP-1 protein (SMD = 0.67, 95% CI: 0.29–1.05) in the AD patients' CSF was higher than healthy controls.

Conclusion

These results suggested that chemokines may play an important role in AD. These findings could provide evidences for the diagnosis and treatment of AD.

Systematic review registration

https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021278736, identifier: CRD42021278736.

Diagnostic performance of magnetic resonance imaging-based machine learning in Alzheimer's disease detection: a meta-analysis

PURPOSE

Advanced machine learning (ML) algorithms can assist rapid medical image recognition and realize automatic, efficient, noninvasive, and convenient diagnosis. We aim to further evaluate the diagnostic performance of ML to distinguish patients with probable Alzheimer's disease (AD) from normal older adults based on structural magnetic resonance imaging (MRI).

METHODS

The Medline, Embase, and Cochrane Library databases were searched for relevant literature published up until July 2021. We used the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool and Checklist for Artificial Intelligence in Medical Imaging (CLAIM) to evaluate all included studies' quality and potential bias. Random-effects models were used to calculate pooled sensitivity and specificity, and the Deeks' test was used to assess publication bias.

RESULTS

We included 24 models based on different brain features extracted by ML algorithms in 19 papers. The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio, and area under the summary receiver operating characteristic curve for ML in detecting AD were 0.85 (95%CI 0.81-0.89), 0.88 (95%CI 0.84-0.91), 7.15 (95%CI 5.40-9.47), 0.17 (95%CI 0.12-0.22), 43.34 (95%CI 26.89-69.84), and 0.93 (95%CI 0.91-0.95).

CONCLUSION

ML using structural MRI data performed well in diagnosing probable AD patients and normal elderly. However, more high-quality, large-scale prospective studies are needed to further enhance the reliability and generalizability of ML for clinical applications before it can be introduced into clinical practice.

Validity Assessment of an Automated Brain Morphometry Tool for Patients with De Novo Memory Symptoms

BACKGROUND AND PURPOSE

Automated volumetric analysis of structural MR imaging allows quantitative assessment of brain atrophy in neurodegenerative disorders. We compared the brain segmentation performance of the AI-Rad Companion brain MR imaging software against an in-house FreeSurfer 7.1.1/Individual Longitudinal Participant pipeline.

MATERIALS AND METHODS

T1-weighted images of 45 participants with de novo memory symptoms were selected from the OASIS-4 database and analyzed through the AI-Rad Companion brain MR imaging tool and the FreeSurfer 7.1.1/Individual Longitudinal Participant pipeline. Correlation, agreement, and consistency between the 2 tools were compared among the absolute, normalized, and standardized volumes. Final reports generated by each tool were used to compare the rates of detection of abnormality and the compatibility of radiologic impressions made using each tool, compared with the clinical diagnoses.

RESULTS

We observed strong correlation, moderate consistency, and poor agreement between absolute volumes of the main cortical lobes and subcortical structures measured by the AI-Rad Companion brain MR imaging tool compared with FreeSurfer. The strength of the correlations increased after normalizing the measurements to the total intracranial volume. Standardized measurements differed significantly between the 2 tools, likely owing to differences in the normative data sets used to calibrate each tool. When considering the FreeSurfer 7.1.1/Individual Longitudinal Participant pipeline as a reference standard, the AI-Rad Companion brain MR imaging tool had a specificity of 90.6%-100% and a sensitivity of 64.3%-100% in detecting volumetric abnormalities. There was no difference between the rate of compatibility of radiologic and clinical impressions when using the 2 tools.

CONCLUSIONS

The AI-Rad Companion brain MR imaging tool reliably detects atrophy in cortical and subcortical regions implicated in the differential diagnosis of dementia.

Assessment of clinical features and coexisting geriatric syndromes in newly diagnosed dementia with Lewy bodies: a retrospective study in a tertiary geriatrics setting in Turkey

PURPOSE

Identifying the associated clinical conditions in patients with newly diagnosed dementia with Lewy bodies (DLB) may contribute to the disease management. This study aimed to examine the clinical features and coexisting geriatric syndromes of patients with newly diagnosed DLB.

METHOD

This cross-sectional study included newly diagnosed DLB participants who were admitted to a tertiary geriatric outpatient clinic. Of the 857 patients with dementia, 116 DLB diagnoses were eligible for analysis. The core and supportive clinical features of DLB were recorded. Geriatric syndromes including polypharmacy, depression, insomnia, dependency, a history of delirium, falls, malnutrition, urinary incontinence, functional impairment, and living alone, were assessed and recorded at baseline.

RESULTS

The mean age was 79.0 ± 6.9 years, and 50.9% of the participants were female. The majority (63.8%) had mild dementia, 31.9% had moderate, and 4.3% had severe disease. Cognitive fluctuations (78.4%), visual hallucinations (77.6%), and Parkinsonism (73.3%) were the most common clinical features. Functional impairment (59.5%) and urinary incontinence (59.5%) were the leading geriatric syndromes, followed by polypharmacy (56.9%), depressive symptoms (54.7%), falls (52.6%), insomnia (49.1%), malnutrition (24.3%), and delirium (6.0%). Women had more functional impairment and depressive symptoms than men.

CONCLUSION

Although most patients had mild dementia, three-quarters of the DLB cohort had hallucinations, and nearly two-thirds were functionally impaired. The proportion of other serious health conditions also increased, indicating a high comorbidity and geriatric syndrome burden. Comprehensive geriatric assessment is strongly recommended for DLB patients from the time of diagnosis until death to reduce disability and comorbidities.

THE CLINICAL TRIAL REGISTRATION NUMBER

NCT05052450.

Challenges in the pharmacological treatment of patients under suspicion of chronic traumatic encephalopathy: A review

Chronic traumatic encephalopathy (CTE) is caused by progressive neurodegeneration associated with repetitive head impacts. This disease is more common in professionals who practice contact sports, resulting in a concussion and subconcussive trauma. CTE is characterized by the accumulation of hyperphosphorylated tau protein in neurons, astrocytes, and frontotemporal lobe degeneration. Symptoms are usually nonspecific and overlap with other neurodegenerative diseases, such as Alzheimer's disease and frontotemporal dementia, making it difficult to provide drug treatment for patients with this comorbidity. Therefore, the objective of this article is to present an updated review of the pharmacological treatment of chronic traumatic encephalopathy and its challenges.

The Morphology of the Pituitary Gland: A Meta-Analysis with Implications for Diagnostic Imaging

The objective of this meta-analysis was to present transparent data on the morphology of the pituitary gland (PG) using the available data in the literature. The main online medical databases, such as PubMed, Embase, Scopus, and Web of Science, were searched to gather all relevant studies regarding PG morphology. The mean overall volume of the PG was found to be 597.23 mm³ (SE = 28.81). The mean overall height of the PG was established to be 5.64 mm (SE = 0.11). The mean overall length of the PG was found to be 9.98 mm (SE = 0.26). In the present study, the PG's overall morphology and morphometric features were analyzed. Our results showed that, on average, females from Asia have the highest volume of PG (706.69 mm³), and males from Europe have the lowest (456.42 mm³). These values are crucial to be aware of because they represent the normal average properties of the PG, which may be used as reference points when trying to diagnose potential pathologies of this gland. Furthermore, the present study's results prove how the PG's size decreases with age. The results of the present study may be helpful for physicians, especially surgeons, performing procedures on the PG.

[Diagnosis and treatment of early forms of cognitive impairment: possibilities of influencing neuronal energy metabolism. Resolution of the Council of Experts]

Diagnosis and treatment of early forms of cognitive impairment: possibilities of influencing neuronal energy metabolism. Resolution of the Council of Experts.

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.