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Abstract Background Alzheimer’s disease (AD) and Parkinson’s disease (PD) are leading neurodegenerative disorders marked by protein aggregation, with AD featuring amyloid-beta (Aβ) and tau proteins, and PD alpha-synuclein (αSyn). Dementia with Lewy bodies (DLB) often presents with a mix of these pathologies. This study explores naturally occurring autoantibodies (nAbs), including Immunoglobulin (Ig)G, IgM, and IgA, which target αSyn, Aβ and tau to maintain homeostasis and were previously found altered in AD and PD patients, among others. Main text We extended this investigation across AD, PD and DLB patients investigating both the affinities of IgGs and levels of IgGs, IgMs and IgAs towards αSyn, Aβ and tau utilizing chemiluminescence assays. We confirmed that AD and PD patients exhibited lower levels of high-affinity anti-Aβ and anti-αSyn IgGs, respectively, than healthy controls. AD patients also showed diminished levels of high-affinity anti-αSyn IgGs, while anti-tau IgG affinities did not differ significantly across groups. However, DLB patients exhibited increased anti-αSyn IgG but decreased anti-αSyn IgM levels compared to controls and PD patients, with AD patients showing a similar pattern. Interestingly, AD patients had higher anti-Aβ IgG but lower anti-Aβ IgA levels than DLB patients. DLB patients had reduced anti-Aβ IgM levels compared to controls, and anti-tau IgG levels were lower in AD than PD patients, who had reduced anti-tau IgM levels compared to controls. AD patients uniquely showed higher anti-tau IgA levels. Significant correlations were observed between clinical measures and nAbs, with negative correlations between anti-αSyn IgG affinity and levels in DLB patients and a positive correlation with anti-αSyn IgA levels in PD patients. Disease-specific changes in nAb levels and affinity correlations were identified, highlighting altered immune responses. Conclusion This study reveals distinctive nAb profiles in AD, DLB, and PD, pinpointing specific immune deficiencies against pathological proteins. These insights into the autoreactive immune system’s role in neurodegeneration suggest nAbs as potential markers for vulnerability to protein aggregation, offering new avenues for understanding and possibly diagnosing these conditions.

Abstract Background Patients with young onset Alzheimer’s disease (YOAD) face long diagnostic delays. Prescription medication use may provide insights into early signs and symptoms, which may help facilitate timely diagnosis. Methods In a register-based nested case-control study, we examined medication use for everyone diagnosed with YOAD in a Danish memory clinic during 2016–2020 compared to cognitively healthy controls. Prescription medication use were grouped into 13 overall categories (alimentary tract and metabolism, blood and blood forming organs, cardiovascular system, dermatologicals, genitourinary system and sex hormones, systemic hormonal preparations, antiinfectives for systemic use, antineoplastic and immunomodulating agents, musculo-skeletal system, nervous system, antiparasitic products, respiratory system, and sensory organs). Further stratifications were done for predetermined subcategories with a use-prevalence of at least 5% in the study population. Conditional logistic regression produced odds ratios, which given the use of incidence-density matching is interpretable as incidence rate ratios (IRRs). The association between prescription medication use and subsequent YOAD diagnosis was examined in the entire 10-year study period and in three time-intervals. Results The study included 1745 YOAD cases and 5235 controls. In the main analysis, several overall categories showed significant associations with YOAD in one or more time-intervals, namely blood and blood forming organs and nervous system. Prescription medication use in the nervous system category was increased for YOAD cases compared to controls already 10->5 years prior to diagnosis (IRR 1.17, 95% CI 1.05–1.31), increasing to 1.57 (95% CI 1.39–1.78) in the year preceding diagnosis. This was largely driven by antidepressant and antipsychotic use, and especially prominent for first-time users. Conclusions In this study, medication use in several categories was associated with YOAD. Onset of treatment-requiring psychiatric symptoms such as depression or psychosis in mid-life may serve as potential early indicators of YOAD.

Abstract Background In epilepsy, the ictal phase leads to cerebral hyperperfusion while hypoperfusion is present in the interictal phases. Patients with Alzheimer’s disease (AD) have an increased prevalence of epileptiform discharges and a study using intracranial electrodes have shown that these are very frequent in the hippocampus. However, it is not known whether there is an association between hippocampal hyperexcitability and regional cerebral blood flow (rCBF). The objective of the study was to investigate the association between rCBF in hippocampus and epileptiform discharges as measured with ear-EEG in patients with Alzheimer’s disease. Our hypothesis was that increased spike frequency may be associated with increased rCBF in hippocampus. Methods A total of 24 patients with AD, and 15 HC were included in the analysis. Using linear regression, we investigated the association between rCBF as measured with arterial spin-labelling MRI (ASL-MRI) in the hippocampus and the number of spikes/sharp waves per 24 h as assessed by ear-EEG. Results No significant difference in hippocampal rCBF was found between AD and HC (p-value = 0.367). A significant linear association between spike frequency and normalized rCBF in the hippocampus was found for patients with AD (estimate: 0.109, t-value = 4.03, p-value

Abstract Easily applied diagnostic tools such as digital biomarkers for Alzheimer's disease (AD) are urgently needed due to the recent approval of disease‐modifying therapies. We aimed to determine the diagnostic performance of hand‐held, quantitative light reflex pupillometry (qLRP) in patients with AD in a proof‐of‐concept, cross‐sectional study. Participants underwent qLRP at a university memory clinic from August 2022 to October 2023. We fitted multivariable logistic regression models with qLRP, sex, and age as predictors evaluated with area under the receiver operating characteristics curve (AUROC). In total, 107 patients with AD, 44 patients with mixed AD and vascular cognitive dysfunction (VCD), 53 patients with dementia with Lewy bodies (DLB), and 50 healthy controls (HCs) were included. Our diagnostic models showed similar discriminatory ability (AUROC range 0.74‐0.81) when distinguishing patients with AD from HCs and other dementias. The qLRP seems promising as a bedside digital biomarker to aid in diagnosing AD. Highlights We demonstrated the diagnostic performance of qLRP in Alzheimer's disease. The diagnostic models were robust in sensitivity analyses. qLRP may assist in the bedside diagnostic evaluation of Alzheimer's disease.

Abstract Objectives This study aims to evaluate the diagnostic accuracy and reliability of a new, brief questionnaire, ‘Brief Assessment of Impaired Cognition– Questionnaire’ (BASIC-Q) for detection of cognitive impairment, primarily developed for use in primary care. BASIC-Q has three components: Self-report, Informant report, and Orientation. Self-report and Orientation are completed by the individual and Informant report is answered by a close relative. Methods We included 275 participants ≥ 70 years, without a prior diagnosis of dementia, and with a close relative who agreed to participate as an informant. Participants were included prospectively in 14 general practices in urban and rural Denmark using a convenience sampling method. The Repeatable Battery for the Assessment of Neuropsychological Status (RBANS), the informant-completed Functional Activities Questionnaire (FAQ) and reported memory concern were used as a reference standard for the classification of the participants’ cognitive function. Results BASIC-Q demonstrated a fair to good diagnostic accuracy to differentiate between people with cognitive impairment and normal cognition with an area under the ROC curve (AUC) of 0.84 (95% CI 0.79–0.89) and a sensitivity and specificity of 0.80 (95% CI 0.72–0.87) and 0.71 (95% CI 0.63–0.78). A prorated BASIC-Q score derived from BASIC-Q without Informant report had significantly lower classification accuracy than the full BASIC-Q. The test-retest reliability of BASIC-Q was good with an intraclass correlation coefficient of 0.84. Conclusion BASIC-Q is a brief, easy-to-use questionnaire for identification of cognitive impairment in older adults. It demonstrated fair to good classification accuracy in a general practice setting and can be a useful case-finding tool when suspecting dementia in primary health care.

Abstract Introduction Significant mortality amongst vulnerable populations, such as people living with dementia, might go undetected during pandemic conditions due to refocus of care efforts. There is an urgent need to fully evaluate the pandemic impact on mortality amongst people living with dementia in order to facilitate future healthcare reforms and prevent deaths. The purpose of this study was to determine whether there was any significant difference in mortality amongst people with dementia without COVID-19 during the COVID-19 pandemic compared to previous years. Methods A literature search was conducted in 5 databases. The relative risk ratio and confidence interval was used to estimate the change in mortality rates amongst people with dementia during the COVID-19 pandemic. The I2 value was used to assess heterogeneity, publication bias, and sensitivity analyses were performed. Results Pooled analysis of 11 studies showed that mortality amongst people living with dementia was significantly increased during the COVID-19 pandemic for people with dementia without COVID-19. Mortality risk increased by 25% during the time period studied. Subgroup analysis was not performed due the low number of included studies. Conclusions The results of this study suggest that people with dementia had a significant increased mortality during the pandemic even if they did not have COVID-19. People with dementia should participate in efforts that reduce general social spread and pandemic impact on healthcare system such as vaccinations, mask mandates, and testing. These results have clinical implications as preventing direct COVID-19 infection is not enough to adequately protect people living with dementia from increased mortality. Measures to limit social spread of infections and help support patients should also be a focus for clinicians. Further research should focus on the identification of mechanisms and other explanations for increased mortality as well as contributing factors such as living in care homes and differences between countries with various pandemic strategies.

Abstract INTRODUCTION Early and accurate diagnosis of neurocognitive disorders including neurodegenerative dementia remains challenging. This study explores the impact of biological factors on serum neurofilament light chain (NfL) levels and clinical usefulness for the detection of neurocognitive disorders in a mixed memory clinic. METHODS Serum samples and clinical data were obtained from 1188 patients who underwent diagnostic investigations for memory complaints between January 2018 and September 2019. Serum NfL was measured using single molecule array technology. RESULTS NfL exhibited a moderate association with age, estimated glomerular filtration rate (eGFR), and Fazekas score. NfL was able to differentiate between patients with neurocognitive disorders and those without with a sensitivity and specificity of 80%. NfL could, however, not distinguish between different dementia etiologies. DISCUSSION Serum NfL could aid early diagnostic triage by identifying patients requiring further diagnostic procedures and therefore aid in a more focused use of health‐care resources.

Background: In patients with Alzheimer's disease (AD) without clinical seizures, up to half have epileptiform discharges on long-term in-patient electroencephalography (EEG) recordings. Long-term in-patient monitoring is obtrusive, and expensive as compared to outpatient monitoring. No studies have so far investigated if long-term outpatient EEG monitoring is able to identify epileptiform discharges in AD. Our aim is to investigate if epileptiform discharges as measured with ear-EEG are more common in patients with AD compared to healthy elderly controls (HC). Methods: In this longitudinal observational study, 24 patients with mild to moderate AD and 15 age-matched HC were included in the analysis. Patients with AD underwent up to three ear-EEG recordings, each lasting up to two days, within 6 months. Results: The first recording was defined as the baseline recording. At baseline, epileptiform discharges were detected in 75.0% of patients with AD and in 46.7% of HC (p-value = 0.073). The spike frequency (spikes or sharp waves/24 h) was significantly higher in patients with AD as compared to HC with a risk ratio of 2.90 (CI: 1.77–5.01, p

Summary: Lecanemab, an anti-amyloid antibody with effects on biomarker and clinical endpoints in early Alzheimer's Disease (AD), was granted accelerated approval by the FDA in 2023 and regulatory review in Europe is ongoing. We estimate the population potentially eligible for treatment with lecanemab in the 27 EU countries to 5.4 million individuals. Treatment costs would exceed 133 billion EUR per year if the drug is priced similarly as in the United States, amounting to over half of the total pharmaceutical expenditures in the EU. This pricing would be unsustainable; the ability to pay for high-priced therapies varies substantially across countries. Pricing similarly to what has been announced for the United States may place the drug out of reach for patients in some European countries. Disparities in access to novel amyloid-targeting agents may further deepen the inequalities across Europe in health outcomes. As representatives of the European Alzheimer's Disease Consortium Executive Committee, we call for pricing policies that allow eligible patients across Europe to access important innovations, but also continued investments in research and development. Infrastructure to follow up the usage of new therapies in routine care and new payment models may be needed to address affordability and inequalities in patient access.

IntroductionAerobic exercise has been shown to modify Alzheimer pathology in animal models, and in patients with multiple sclerosis to reduce neurofilament light (NfL), a biomarker of neurodegeneration.ObjectiveTo investigate whether a 16-week aerobic exercise program was able to reduce serum NfL in patients with mild Alzheimer’s disease (AD).MethodsThis is a secondary analysis of data from the multi-center Preserving Cognition, Quality of Life, Physical Health, and Functional Ability in Alzheimer’s disease: The Effect of Physical Exercise (ADEX) study. Participants were randomized to 16 weeks of moderate intensity aerobic exercise or usual care. Clinical assessment and measurement of serum NfL was done at baseline and after the intervention.ResultsA total of 136 participants were included in the analysis. Groups were comparable at baseline except for APOEε4 carriership which was higher in the usual care group (75.3 versus 60.2%; p = 0.04). There was no effect of the intervention on serum NfL [intervention: baseline NfL (pg/mL) 25.76, change from baseline 0.87; usual care: baseline 27.09, change from baseline −1.16, p = 0.09].ConclusionThe findings do not support an effect of the exercise intervention on a single measure of neurodegeneration in AD. Further studies are needed using other types and durations of exercise and other measures of neurodegeneration.Clinical trial registrationclinicaltrials.gov, identifier NCT01681602.

Abstract Background Several factors may play a role in the ability of patients with Alzheimer’s disease to perform activities of daily living (ADL). The aim of this study was to examine the impact of different aspects of physical performance and cognitive functions on ADL in patients suffering from mild-to-moderate Alzheimer’s disease. Methods We conducted secondary analyses on cross-sectional baseline data from the randomized controlled multicentre study “Preserving quality of life, physical health and functional ability in Alzheimer’s Disease: The effect of physical exercise” (ADEX). In total, 185 AD patients (76 women and 109 men), with a mean age on 70,4 years, were included. Data from physical performance tests (Astrand cycle test, Timed up & Go (TUG), Sit to Stand test (STS)) and cognitive tests (Mini Mental Status Examination (MMSE), Symbol Digit Modalities Test (SDMT), Stroop Color and Word test (Stroop)) were used. Their associations with ADL, measured on the ADCS-ADL scale was assessed in multivariable regression analyses. Results SDMT and MMSE had significant, moderate correlations with total ADL (SDMT: r = 0.33, MMSE: r = 0.42) and instrumental ADL (SDMT: r = 0.31, MMSE: r = 0.42), but not with basic ADL. Adjusting for age and sex, the associations between SDMT and MMSE to total ADL and instrumental ADL persisted. No significant associations were found between Astrand, TUG, STS or Stroop and total ADL, basic ADL or instrumental ADL. Conclusion Total ADL and instrumental ADL are associated with cognitive functions, including executive function. No significant association between examined physical performance parameters and ADL functions was observed, and consequently does not support an impact of physical function on ADL functions in patients with mild-to-moderate Alzheimer’s disease and relatively well-preserved physical function. Strategies aimed to improve cognition may be better suited to improve ADL function in patients with mild-to-moderate Alzheimer’s disease. Trial registration NCT01681602 . Registered 10 September 2012, retrospectively registered.

Abstract Background Previous studies found an association between migraine and dementia, which are two leading causes of disability. However, these studies did not differentiate between migraine types and did not investigate all prevalent dementia subtypes. The main objective of this national register-based study was to investigate whether migraine was a risk factor for dementia. Additionally, we explored potential differences in dementia risk for migraine with and without aura. Methods We obtained data on birth cohorts born between 1935 and 1956 (n = 1,657,890) from Danish national registers. Individuals registered with migraine before age 59 (n = 18,135) were matched (1:5) on sex and birthdate with individuals without migraine (n = 1,378,346). Migraine was defined by International Classification of Diseases (ICD) diagnoses and dementia was defined by ICD diagnoses and anti-dementia medication. After matching, 62,578 individuals were eligible for analysis. For the statistical analyses, we used Cox regression models and adjusted for socio-demographic factors and several psychiatric and somatic morbidities. Results During a median follow-up time of 6.9 (IQR: 3.6–11.2) years, 207 individuals with migraine developed dementia. Compared with individuals without migraine, we found a 50% higher rate of dementia among individuals with migraine (HR = 1.50; 95% CI: 1.28–1.76). Individuals without aura had a 19% higher rate of dementia (HR = 1.19; 95% CI: 0.84–1.70), and individuals with aura had a two times higher rate of dementia (HR = 2.11; 95% CI: 1.48–3.00). Conclusions Our findings support the hypothesis that migraine is a midlife risk factor for dementia in later life. The higher rate of dementia in individuals with a hospital-based diagnosis of migraine with aura emphasizes the need for studies on pathological mechanisms and potential preventative measures. Furthermore, given that only hospital-based migraine diagnoses were included in this study, future research should also investigate migraine cases derived from the primary healthcare system to include less severe migraine cases.

Introduction A growing body of evidence suggests that hearing loss is a significant and potentially modifiable risk factor for cognitive impairment. Although the mechanisms underlying the associations between cognitive decline and hearing loss are unclear, listening effort has been posited as one of the mechanisms involved with cognitive decline in older age. To date, there has been a lack of research investigating this association, particularly among adults with mild cognitive impairment (MCI).Methods and analysis 15–25 cognitively healthy participants and 15–25 patients with MCI (age 40–85 years) will be recruited to participate in an exploratory study investigating the association between cognitive functioning and listening effort. Both behavioural and objective measures of listening effort will be investigated. The sentence-final word identification and recall (SWIR) test will be administered with single talker non-intelligible speech background noise while monitoring pupil dilation. Evaluation of cognitive function will be carried out in a clinical setting using a battery of neuropsychological tests. This study is considered exploratory and proof of concept, with information taken to help decide the validity of larger-scale trials.Ethics and dissemination Written approval exemption was obtained by the Scientific Ethics Committee in the central region of Denmark (De Videnskabsetiske Komiteer i Region Hovedstaden), reference 19042404, and the project is registered pre-results at clinicaltrials.gov, reference NCT04593290, Protocol ID 19042404. Study results will be disseminated in peer-reviewed journals and conferences.

A rare cause of inherited frontotemporal dementia (FTD) is a mutation in the CHMP2B gene on chromosome 3 leading to the autosomal dominantly inherited FTD (CHMP2B-FTD). Since CHMP2B-FTD is clinically well-characterized, and patients show a distinct pattern of executive dysfunction, the condition offers possible insight in the early electroencephalographic (EEG) changes in the cortical networks. Specifically, EEG microstate analysis parses the EEG signals into topographies believed to represent discrete network activations. We investigated the EEG dynamics in patients with symptomatic CHMP2B-FTD (n = 5) as well as pre-symptomatic mutation carriers (n = 5) compared to non-carrier family members (n = 6). The data was parsed into four archetypal microstates and global power was calculated. A trend was found for lower occurrence in microstate D in CHMP2B-FTD (p-value = 0.177, F-value = 2.036). Patients with recent symptom onset (2 years) showed decreased duration. Patients with CHMP2B-FTD present with executive dysfunction, and microstate D has previously been shown to be associated with the fronto-parietal network. The biphasic pattern may represent the pathophysiological changes in brain dynamics during neurodegeneration, which may apply to other neurodegenerative diseases.

Background: More than half of the people with dementia live in lower-middle income countries (LMIC), yet we lack research and evidence-based knowledge to guide health promotion and prevention strategies for cognitive decline. In the Philippines, the prevalence of mild cognitive impairment (MCI) and cardiovascular risk factors among older persons are high, making this population at high risk for developing dementia. This protocol describes a cluster randomized controlled trial that aims to investigate the efficacy of a multicomponent intervention to maintain cognitive performance among high-risk population.Methods: This is a cluster-randomized, two-arm, single-blind trial of a multicomponent intervention that combines dance called INDAK (Improving Neurocognition through Dance and Kinesthetics), nutrition counseling, and vascular risk management. The intervention arm will receive 12 months (1-h, twice per week) of INDAK and every 3 months of nutrition counseling and intensive vascular risk management and monitoring. The control group will receive the usual vascular care advice and referral. A total of 605 (20–25 clusters per arm) community-dwelling Filipino older adults aged ≥ 60 years old with MCI will participate in the study and will be assessed at baseline, 6th- and 12th-month follow-up. The primary outcome is cognitive performance assessed by the Alzheimer's Disease Assessment Scale—Cognitive (ADAS-Cog), Mnemonic Similarity Tasks (MST), and executive function composite (EFC). Secondary outcomes are functional connectivity assessed through brain imaging, and measures of behavioral, functional level, and quality of life.Discussion: The study aims to provide scientific evidence on a public health intervention that is contextualized in a community setting to reduce dementia risk among older adults with MCI. This model can be an ecological, low-cost, and effective program, thereby conducive to widespread implementation in the Philippines as well as in other low-resource settings with similar public health challenges. The pilot phase was underway with eight villages (clusters), but temporarily interrupted by the pandemic. The full study is anticipated to start after community restrictions are eased.

Abstract Background As biobank research has become increasingly widespread within biomedical research, study-specific consent to each study, a model derived from research involving traditional interventions on human subjects, has for the sake of feasibility gradually given way to alternative consent models which do not require consent for every new study. Besides broad consent these models include tiered, dynamic, and meta-consent. However, critics have pointed out that it is normally not known at the time of enrolment in what ways samples deposited in a biobank may be used in future research and that, for a consent to be informed, exactly this kind of knowledge is required. Therefore, there is an ongoing debate about the ethical acceptability of going for less than study-specific consent. Main text In light of this debate we address the question of how to best protect participants against relevant risks and violations of autonomy. We apply the central aims of the informed consent process to the unique circumstances of biobank research where samples and data in many cases are stored for long periods of time and reused in subsequent studies. Thereby we are able to formulate a set of criteria focusing both on the risk of informational harm and the potential violation of participants’ values. We compare existing models of consent based on their ability to satisfy the criteria, and we find that the broad consent model offers the best level of protection for participants, although, it suffers from a few important deficiencies with regards to protection against participant value violations and long-term protection of autonomy, if it is applied without qualifications. For this reason, we propose modifications to the current broad consent model, in order to ensure that it provides protection of autonomy and participant values through strong ethical review and continuous communication. Conclusion We conclude that a modified form of broad consent is ethically superior in biobank research, not only because it is most feasible but primarily because it offers the best available protection against the hazards facing research subjects in this form of research.

Background: Filipino normative data for neuropsychological tests are lacking. Objectives: This study aimed to determine the Filipino normative data for the Filipino Norming Project (FNP) Neuropsychological Battery, combining the Alzheimer’s Disease Assessment Scale – Cognitive (ADAS-Cog) and the Neuropsychological Test Battery from the Uniform Dataset of Alzheimer’s Disease Center (UDS-ADC). Methods: We recruited participants 60 years and older with normal cognition (MMSE score of 25 and above and did not fulfill criteria for dementia according to DSM-IV criteria). Psychologists administered the tests to the study participants. We conducted multivariate analyses to study the effect of age, gender, and education on test performance. Results: A total of 191 participants underwent the FNP Neuropsychological Test Battery. The mean age was 68.8 years (SD 5.4). The majority were female (84.1%). The mean score of ADAS-Cog was 9.98 (SD 4.74). The effect of education was prominent throughout the cognitive domains tested while the effect of age was limited to a few cognitive domains. The mean ADAS-Cog scores were 11.80 ± 4.40 for primary education, 9.93 ± 5.08 for secondary, and 8.15 ± 3.95 for tertiary. On average, women scored 2.75 points lower than men and performed better on the verbal components. Men performed better on the constructional praxis component. The same effect of education and gender was observed for the UDS-ADC. Conclusion: For the first time, normative data are available for the ADAS-Cog and UDS-ADC for a Filipino older population. This study stresses the importance of establishing population-specific normative data, taking into account the specific sociocultural and linguistic context of that population.

Abstract Background In clinical practice, it is often difficult to predict which patients with cognitive complaints or impairment will progress or remain stable. We assessed the impact of using a clinical decision support system, the PredictND tool, to predict progression in patients with subjective cognitive decline (SCD) and mild cognitive impairment (MCI) in memory clinics. Methods In this prospective multicenter study, we included 429 patients with SCD (n = 230) and MCI (n = 199) (female 54%, age 67 ± 9, MMSE 28 ± 2) and followed them for at least 12 months. Based on all available patient baseline data (demographics, cognitive tests, cerebrospinal fluid biomarkers, and MRI), the PredictND tool provides a comprehensive overview of the data and a classification defining the likelihood of progression. At baseline, a clinician defined an expected follow-up diagnosis and estimated the level of confidence in their prediction using a visual analogue scale (VAS, 0–100%), first without and subsequently with the PredictND tool. As outcome measure, we defined clinical progression as progression from SCD to MCI or dementia, and from MCI to dementia. Correspondence between the expected and the actual clinical progression at follow-up defined the prognostic accuracy. Results After a mean follow-up time of 1.7 ± 0.4 years, 21 (9%) SCD and 63 (32%) MCI had progressed. When using the PredictND tool, the overall prognostic accuracy was unaffected (0.4%, 95%CI − 3.0%; + 3.9%; p = 0.79). However, restricting the analysis to patients with more certain classifications (n = 203), we found an increase of 3% in the accuracy (95%CI − 0.6%; + 6.5%; p = 0.11). Furthermore, for this subgroup, the tool alone showed a statistically significant increase in the prognostic accuracy compared to the evaluation without tool (6.4%, 95%CI 2.1%; 10.7%; p = 0.004). Specifically, the negative predictive value was high. Moreover, confidence in the prediction increased significantly (∆VAS = 4%, p

Background Biomarkers of neurodegeneration, e.g. MRI brain atrophy and [18F]FDG-PET hypometabolism, are often evaluated in patients suspected of neurodegenerative disease. Objective Our primary objective was to investigate prognostic properties of atrophy and hypometabolism. Methods From March 2015-June 2016, 149 patients referred to a university hospital memory clinic were included. The primary outcome was progression/stable disease course as assessed by a clinician at 12 months follow-up. Intracohort defined z-scores of baseline MRI automatic quantified volume and [18F]FDG-PET standardized uptake value ratios were calculated for all unilaterally defined brain lobes and dichotomized as pronounced atrophy (+A)/ pronounced hypometabolism (+H) at z-score

Abstract Introduction Large‐scale brain networks are disrupted in the early stages of Alzheimer's disease (AD). Electroencephalography microstate analysis, a promising method for studying brain networks, parses EEG signals into topographies representing discrete, sequential network activations. Prior studies indicate that patients with AD show a pattern of global microstate disorganization. We investigated whether any specific microstate changes could be found in patients with AD and mild cognitive impairment (MCI) compared to healthy controls (HC). Materials and methods Standard EEGs were obtained from 135 HC, 117 patients with MCI, and 117 patients with AD from six Nordic memory clinics. We parsed the data into four archetypal microstates. Results There was significantly increased duration, occurrence, and coverage of microstate A in patients with AD and MCI compared to HC. When looking at microstates in specific frequency bands, we found that microstate A was affected in delta (1–4 Hz), theta (4–8 Hz), and beta (13–30 Hz), while microstate D was affected only in the delta and theta bands. Microstate features were able to separate HC from AD with an accuracy of 69.8% and HC from MCI with an accuracy of 58.7%. Conclusions Further studies are needed to evaluate whether microstates represent a valuable disease classifier. Overall, patients with AD and MCI, as compared to HC, show specific microstate alterations, which are limited to specific frequency bands. These alterations suggest disruption of large‐scale cortical networks in AD and MCI, which may be limited to specific frequency bands.

Background: Exercise has been shown to alter brain plasticity and is explored as a therapeutic intervention in a wide variety of neurological diseases. Electroencephalography (EEG) offers an inexpensive method of studying brain electrocortical activity shortly after exercise and thus offers a way of exploring the influence of exercise on the brain. We conducted a systematic review to summarize the current body of evidence regarding methods of EEG analysis and the reported effects of exercise interventions on EEG.Methods: PubMed, Web of Science and EMBASE were searched for studies investigating resting state EEG in exercise intervention studies carried out in participants >17 years of age and with no history of epilepsy. Further, studies solely investigating event-related potentials as an outcome measure were excluded. Relevant data were extracted, and a risk-of-bias assessment was carried out using the Cochrane risk-of-bias tool. A qualitative synthesis of results was carried out. A protocol for the systematic review was uploaded to https://www.crd.york.ac.uk/PROSPERO/ (ID: CRD42019134570) and the Preferred Reporting Items for Systematic Reviews (PRISMA) statement was followed.Results: Out of 1,993 records screened, 54 studies were included in a final qualitative synthesis with a total of 1,445 participants. Our synthesis showed that studies were mainly carried out using frequency analysis as an analytical method. Generally, findings across studies were inconsistent and few were adjusted for multiple comparisons. Studies were mainly of low quality and usually carried out in small populations, lowering the significance of results reported.Conclusions: Changes in the EEG as a result of an exercise intervention are elusive and difficult to replicate. Future studies should provide biologically sound hypotheses underlying assumptions, include larger populations and use standardized EEG methods to increase replicability. EEG remains an interesting methodology to examine the effects of exercise on the brain.

Lifestyle factors have been shown to increase the risk of developing Alzheimer’s disease (AD) later in life. Specifically, an unfavorable cholesterol profile, and insulin resistance are associated with increased risk of developing AD. One way to non-pharmacologically affect the levels of plasma lipids is by exercise, which has been shown to be beneficial in cognitively healthy individuals. In this randomized controlled trial y, we therefore aimed to clarify the effect of physical exercise on the lipid profile, insulin and glucose in patients with AD. In addition, we investigated the effect of apolipoproteinE genotype on total cholesterol, high-density lipoprotein-cholesterol (HDL-C), low-density lipoprotein–cholesterol (LDL-C), and triglycerides (TG) in plasma from patients with AD. Plasma samples from 172 patients who underwent 16 weeks of moderate-to-high intensity exercise (n = 90) or treatment as usual (n = 82) were analyzed change from baseline for the levels of total cholesterol, LDL-C, HDL-C, TG, glucose, and insulin. In addition, we analyzed those from the exercise group who adhered to the protocol with an attendance of 2/3 or more of the exercise session and who followed the protocol of an intensity of 70% of the maximum heart rate. We found a significant increase in plasma HDL-C levels between the “high exercise sub-group” compared to control group. After intervention HDL-C was increased by 4.3% in the high-exercise group, and decreased by 0.7% in the control group, after adjustment for statin use. In conclusion, short term physical activity may be beneficial on the cholesterol profile in patients with AD.

Little evidence from the Arab region is available on dementia and its associated risk factors. This study is the first in Lebanon to examine the association between community older adults' socio-demographics and cardiovascular disease risk factors (CVDRF) and dementia in the aim of closing the knowledge gap. A cross-sectional household survey was conducted in 2013 in Beirut and two districts of Mount Lebanon with 502 older adults (65years and above) and their informants. Data was collected on CVDRF and socio-demographics using structured questionnaires and dementia was assessed using the 10/66 Dementia Research Group validated tools. Multivariable analysis was done using a generalized estimating equation to account for cluster effect. Being older and perceiving personal income as insufficient significantly increased the odds of dementia [OR75–84years=4.00 (95%CI=1.46, 10.95); OR85+years=7.07 (1.84, 27.03); ORinsufficient income=3.90 (1.58, 9.60)]. Having uncontrolled hypertension (versus no hypertension) was the only significant CVDRF that increased the odds of dementia [OR=6.35 (1.60, 25.10)]. Interventions targeting uncontrolled hypertension that aim to increase awareness about proper management of this chronic condition would contribute to the needed preventive efforts against CVDRFs in response to dementia risk. Further research on the association between income sufficiency – one indicator of low socio-economic status – and dementia is warranted. Keywords: Dementia, CVD risk factors, Uncontrolled hypertension, Income, Lebanon

Aims: We assessed the value of automated MRI quantification methods in the differential diagnosis of behavioral-variant frontotemporal dementia (bvFTD) from Alzheimer disease (AD), Lewy body dementia (LBD), and subjective memory complaints (SMC). We also examined the role of the C9ORF72-related genetic status in the differentiation sensitivity. Methods: The MRI scans of 50 patients with bvFTD (17 C9ORF72 expansion carriers) were analyzed using 6 quantification methods as follows: voxel-based morphometry (VBM), tensor-based morphometry, volumetry (VOL), manifold learning, grading, and white-matter hyperintensities. Each patient was then individually compared to an independent reference group in order to attain diagnostic suggestions. Results: Only VBM and VOL showed utility in correctly identifying bvFTD from our set of data. The overall classification sensitivity of bvFTD with VOL + VBM achieved a total sensitivity of 60%. Using VOL + VBM, 32% were misclassified as having LBD. There was a trend of higher values for classification sensitivity of the C9ORF72 expansion carriers than noncarriers. Conclusion: VOL, VBM, and their combination are effective in differential diagnostics between bvFTD and AD or SMC. However, MRI atrophy profiles for bvFTD and LBD are too similar for a reliable differentiation with the quantification methods tested in this study.

Abstract Introduction We studied, using a data‐driven approach, how different combinations of diagnostic tests contribute to the differential diagnosis of dementia. Methods In this multicenter study, we included 356 patients with Alzheimer's disease, 87 frontotemporal dementia, 61 dementia with Lewy bodies, 38 vascular dementia, and 302 controls. We used a classifier to assess accuracy for individual performance and combinations of cognitive tests, cerebrospinal fluid biomarkers, and automated magnetic resonance imaging features for pairwise differentiation between dementia types. Results Cognitive tests had good performance in separating any type of dementia from controls. Cerebrospinal fluid optimally contributed to identifying Alzheimer's disease, whereas magnetic resonance imaging features aided in separating vascular dementia, dementia with Lewy bodies, and frontotemporal dementia. Combining diagnostic tests increased the accuracy, with balanced accuracies ranging from 78% to 97%. Discussion Different diagnostic tests have their distinct roles in differential diagnostics of dementias. Our results indicate that combining different diagnostic tests may increase the accuracy further.

OBJECTIVES: The aim of this study was to investigate the effect of shift work and long working hours in midlife on the risk of dementia in old age. METHODS: The present study comprised 4766 participants from the Copenhagen Male Study. We used information on shift work (collected in 1970–1971 and 1985–1986), long working hours defined as >45 hours per week (collected in 1970–1971), socioeconomic status, sleep, stress, and cardiovascular risk factors. Information about dementia diagnoses was obtained from registers. Participants were followed until 2014 (mean length of follow-up was 17.8 years). We employed Poisson regression for the survival analyses and estimated incidence rate ratios (IRR) and their 95% confidence intervals (CI). RESULTS: We found no statistically significant association between shift work (IRR 0.86, 95% CI 0.70–1.05) or long working hours (IRR 0.97, 95% CI 0.79–1.19) and dementia. Adjustment for potential confounders and mediators did not change the estimates. Working shifts at both time points of exposure assessment was not associated with a higher incidence of dementia compared with non-shift workers at both time points (IRR 0.99, 95% CI 0.69–1.42). The lowest incidence of dementia was observed among participants who reported shift work at one time point (only in 1985–1986: IRR 0.44, 95% CI 0.16–1.23 and only in 1970–1971: IRR 0.58, 95% CI 0.31–1.11). CONCLUSION: We did not find positive evidence of an association between shift work or long working hours and the incidence of dementia, but the negative findings may reflect the crude assessment of shift work and long working hours, which is a major limitation of the present study.

Down syndrome (DS) is associated with development of dementia due to Alzheimer’s disease (AD). However, due to considerable heterogeneity in intellectual function among persons with DS, it is difficult to assess whether a person with DS has developed dementia due to AD (DS-AD). EEG spectral power has previously shown very promising results with increased slowing in DS-AD compared to DS. However, another technique called microstates may be used to assess whole-brain dynamics and has to our knowledge not previously been investigated in either DS or DS-AD. The aim of the current study was to assess whether microstates could be used to differentiate between adults with DS, and DS-AD. We included EEGs from 10 persons with DS and 15 persons with DS-AD in the analysis. For the microstate analyses, we calculated four global maps, which were then back-fitted to all the EEGs. Lastly, we extracted the duration, occurrence, and coverage for each of the microstates. Here, we found the four archetypical maps as has previously been reported in the literature. We did not find any significant difference between DS and DS-AD but the largest difference in microstate duration between DS and DS-AD was found in microstate A and D. These findings are in line with structural MR studies showing that both the frontal and temporal lobes are affected in persons with DS-AD. Microstates may potentially serve as a diagnostic marker, but larger studies are needed to confirm these findings.

Differentiating between different types of neurodegenerative diseases is not only crucial in clinical practice when treatment decisions have to be made, but also has a significant potential for the enrichment of clinical trials. The purpose of this study is to develop a classification framework for distinguishing the four most common neurodegenerative diseases, including Alzheimer's disease, frontotemporal lobe degeneration, Dementia with Lewy bodies and vascular dementia, as well as patients with subjective memory complaints. Different biomarkers including features from images (volume features, region-wise grading features) and non-imaging features (CSF measures) were extracted for each subject. In clinical practice, the prevalence of different dementia types is imbalanced, posing challenges for learning an effective classification model. Therefore, we propose the use of the RUSBoost algorithm in order to train classifiers and to handle the class imbalance training problem. Furthermore, a multi-class feature selection method based on sparsity is integrated into the proposed framework to improve the classification performance. It also provides a way for investigating the importance of different features and regions. Using a dataset of 500 subjects, the proposed framework achieved a high accuracy of 75.2% with a balanced accuracy of 69.3% for the five-class classification using ten-fold cross validation, which is significantly better than the results using support vector machine or random forest, demonstrating the feasibility of the proposed framework to support clinical decision making. Keywords: Neurodegenerative diseases, Differential diagnosis, MRI, Dementia, Imbalance learning, Multi-class feature selection

Alzheimer's disease (AD) is a progressive and irreversible neurodegenerative disease causing neural cell degeneration and brain atrophy and is considered to be the most common form of dementia. We previously generated an induced pluripotent stem cell (iPSC) line from an AD patient carrying an A79V mutation in PSEN1 as an in vitro disease model. Here we generated a gene-corrected version from this hiPSC line by substituting the point mutation with the wild-type sequence. The reported A79V-GC-iPSCs line is a very useful resource in combination with the A79V-iPSC line in order to study pathological cellular phenotypes related to this particular mutation.

Skin fibroblasts were obtained from a 46-year-old symptomatic man carrying a M146I mutation in the presenilin 1 gene (PSEN1), responsible for causing Alzheimer's disease (AD). Induced pluripotent stem cells (iPSCs) were derived via transfection with episomal vectors carrying hOCT4, hSOX2, hKLF2, hL-MYC, hLIN28 and shTP53 genes. M146I-iPSCs were free of genomically integrated reprogramming genes, had the specific mutation but no additional genomic aberrancies, expressed the expected pluripotency markers and displayed in vitro differentiation potential to the three germ layers. The reported M146I-iPSCs line may be a useful resource for in vitro modeling of familial AD.

Skin fibroblasts were obtained from a 48-year-old presymptomatic woman carrying a A79V mutation in the presenilin 1 gene (PSEN1), causing Alzheimer's disease (AD). Induced pluripotent stem cell (iPSCs) were derived via transfection with episomal vectors carrying hOCT4, hSOX2, hKLF2, hL-MYC, hLIN28 and shTP53 genes. A79V-iPSCs were free of genomically integrated reprogramming genes, had the specific mutation but no additional genomic aberrancies, expressed the expected pluripotency markers and displayed in vitro differentiation potential to the three germ layers. The reported A79V-iPSCs line may be a useful resource for in vitro modeling of familial AD.

The burden on and mental well-being of family carers for the elderly, especially those with dementia, has been well studied in high-income countries and to a lesser extent in the Arab region. Our study of Lebanese carers highlights the importance of considering the psychological well-being of the family carer, and the role of dementia and depression in increasing the burden of care. Psychosocial interventions have produced equivocal results and therefore customised and contextualised interventions need to be researched. Greater understanding of the coping mechanisms used by carers is required and an examination of the positive aspects of caring is warranted.

Background: Diagnosing frontotemporal dementia may be challenging. New methods for analysis of regional brain atrophy patterns on magnetic resonance imaging (MRI) could add to the diagnostic assessment. Therefore, we aimed to develop automated imaging biomarkers for differentiating frontotemporal dementia subtypes from other diagnostic groups, and from one another. Methods: In this retrospective multicenter cohort study, we included 1213 patients (age 67 ± 9, 48% females) from two memory clinic cohorts: 116 frontotemporal dementia, 341 Alzheimer's disease, 66 Dementia with Lewy bodies, 40 vascular dementia, 104 other dementias, 229 mild cognitive impairment, and 317 subjective cognitive decline. Three MRI atrophy biomarkers were derived from the normalized volumes of automatically segmented cortical regions: 1) the anterior vs. posterior index, 2) the asymmetry index, and 3) the temporal pole left index. We used the following performance metrics: area under the receiver operating characteristic curve (AUC), sensitivity, and specificity. To account for the low prevalence of frontotemporal dementia we pursued a high specificity of 95%. Cross-validation was used in assessing the performance. The generalizability was assessed in an independent cohort (n = 200). Results: The anterior vs. posterior index performed with an AUC of 83% for differentiation of frontotemporal dementia from all other diagnostic groups (Sensitivity = 59%, Specificity = 95%, positive likelihood ratio = 11.8, negative likelihood ratio = 0.4). The asymmetry index showed highest performance for separation of primary progressive aphasia and behavioral variant frontotemporal dementia (AUC = 85%, Sensitivity = 79%, Specificity = 92%, positive likelihood ratio = 9.9, negative likelihood ratio = 0.2), whereas the temporal pole left index was specific for detection of semantic variant primary progressive aphasia (AUC = 85%, Sensitivity = 82%, Specificity = 80%, positive likelihood ratio = 4.1, negative likelihood ratio = 0.2). The validation cohort provided corresponding results for the anterior vs. posterior index and temporal pole left index. Conclusion: This study presents three quantitative MRI biomarkers, which could provide additional information to the diagnostic assessment and assist clinicians in diagnosing frontotemporal dementia. Keywords: Dementia, Frontotemporal lobar degeneration, Differential diagnosis, Behavioral variant frontotemporal dementia, Primary progressive aphasia, MRI

Clinical decision support systems (CDSSs) hold potential for the differential diagnosis of neurodegenerative diseases. We developed a novel CDSS, the PredictND tool, designed for differential diagnosis of different types of dementia. It combines information obtained from multiple diagnostic tests such as neuropsychological tests, MRI and cerebrospinal fluid samples. Here we evaluated how the classifier used in it performs in differentiating between controls with subjective cognitive decline, dementia due to Alzheimer’s disease, vascular dementia, frontotemporal lobar degeneration and dementia with Lewy bodies. We used the multiclass Disease State Index classifier, which is the classifier used by the PredictND tool, to differentiate between controls and patients with the four different types of dementia. The multiclass Disease State Index classifier is an extension of a previously developed two-class Disease State Index classifier. As the two-class Disease State Index classifier, the multiclass Disease State Index classifier also offers a visualization of its decision making process, which makes it especially suitable for medical decision support where interpretability of the results is highly important. A subset of the Amsterdam Dementia cohort, consisting of 504 patients (age 65 ± 8 years, 44% females) with data from neuropsychological tests, cerebrospinal fluid samples and both automatic and visual MRI quantifications, was used for the evaluation. The Disease State Index classifier was highly accurate in separating the five classes from each other (balanced accuracy 82.3%). Accuracy was highest for vascular dementia and lowest for dementia with Lewy bodies. For the 50% of patients for which the classifier was most confident on the classification the balanced accuracy was 93.6%. Data-driven CDSSs can be of aid in differential diagnosis in clinical practice. The decision support system tested in this study was highly accurate in separating the different dementias and controls from each other. In addition to the predicted class, it also provides a confidence measure for the classification.

Different neurodegenerative diseases can cause memory disorders and other cognitive impairments. The early detection and the stratification of patients according to the underlying disease are essential for an efficient approach to this healthcare challenge. This emphasizes the importance of differential diagnostics. Most studies compare patients and controls, or Alzheimer's disease with one other type of dementia. Such a bilateral comparison does not resemble clinical practice, where a clinician is faced with a number of different possible types of dementia. Here we studied which features in structural magnetic resonance imaging (MRI) scans could best distinguish four types of dementia, Alzheimer's disease, frontotemporal dementia, vascular dementia, and dementia with Lewy bodies, and control subjects. We extracted an extensive set of features quantifying volumetric and morphometric characteristics from T1 images, and vascular characteristics from FLAIR images. Classification was performed using a multi-class classifier based on Disease State Index methodology. The classifier provided continuous probability indices for each disease to support clinical decision making. A dataset of 504 individuals was used for evaluation. The cross-validated classification accuracy was 70.6% and balanced accuracy was 69.1% for the five disease groups using only automatically determined MRI features. Vascular dementia patients could be detected with high sensitivity (96%) using features from FLAIR images. Controls (sensitivity 82%) and Alzheimer's disease patients (sensitivity 74%) could be accurately classified using T1-based features, whereas the most difficult group was the dementia with Lewy bodies (sensitivity 32%). These results were notable better than the classification accuracies obtained with visual MRI ratings (accuracy 44.6%, balanced accuracy 51.6%). Different quantification methods provided complementary information, and consequently, the best results were obtained by utilizing several quantification methods. The results prove that automatic quantification methods and computerized decision support methods are feasible for clinical practice and provide comprehensive information that may help clinicians in the diagnosis making.

Background: Assessment of dementia in individuals with intellectual disability is complex due to great inter-individual variability in cognitive function prior to dementia and a lack of standardized instruments. Studies have indicated that quantitative electroencephalography (qEEG) results may be used as a diagnostic marker for dementia. The aim of this study was to examine the value of qEEG in the diagnostic evaluation of dementia in patients with Down syndrome (DS). Method: The study included 21 patients with DS and mild-to-moderate dementia due to Alzheimer's disease (DS-AD) and 16 age-matched adults with DS without cognitive deterioration assessed by the informant-based Dementia Screening Questionnaire in Intellectual Disability (DSQIID). Conventional EEG was performed and analysed quantitatively using fast Fourier transformation. Outcomes were centroid frequency, peak frequency, absolute power, and relative power. Results: In several regions of the brain, a significant decrease in the theta-1 band (4-7 Hz) was identified for the centroid frequency. A significant negative correlation was demonstrated between the mean of the centroid frequency of the theta-1 band and the total DSQIID score. Conclusion: We found that qEEG can detect a significant decrease in centroid frequency in a sample of patients with DS-AD as compared to a sample of adults with DS and no cognitive deterioration.

Background: Establishing a diagnosis of dementia in young patients may be complex and have significant implications for the patient. The aim of this study was to evaluate the quality of the diagnostic work-up in young patients diagnosed with dementia in the clinical routine. Methods: Two hundred patients were randomly selected from 891 patients aged ≤65 years registered with a diagnosis of dementia for the first time in 2008 in Danish hospitals, and 159 medical records were available for review. Three raters evaluated their medical records for the completeness of the diagnostic work-up on which the diagnosis of dementia had been based, using evidence-based guidelines for the diagnostic evaluation of dementia as reference standards. Results: According to the rater review, only 111 (70%) patients met the clinical criteria for dementia. An acceptable diagnostic work-up including all items of recommended basic diagnostic evaluation was performed in only 24%, although more often (28%) in the subgroup of patients where dementia was confirmed by raters. Conclusion: This first nationwide study of unselected young patients registered with a diagnosis of dementia indicated that the concept of dementia may be misinterpreted by clinicians and that a diagnosis of dementia in the young is only rarely based on a complete basic diagnostic work-up, calling for increased competency.

Depression and dementia are commonly concurrent and are both associated with increased mortality among older people. However, little is known about whether home-dwelling patients newly diagnosed with mild dementia coexisting with depressive symptoms have excess mortality. We conducted a post hoc analysis based on data from the Danish Alzheimer’s Intervention Study of 330 individuals who were diagnosed with mild dementia within the past 12 months. Thirty-four patients were identified with major depressive symptoms (MD-S) at baseline. During the 3-year follow-up period, 56 patients died, and, among them, 12 were with MD-S at baseline. Multivariable analysis adjusting for the potential confounders (age, sex, smoking status, alcohol consumption, education, BMI, household status, MMSE, CCI, QoL-AD, NPIQ, ADSC-ADL, medication, and RCT allocation) showed that patients with MD-S had a 2.5-fold higher mortality as compared to the patients without or with only few depressive symptoms. Our result revealed that depression is possibly associated with increased mortality in patients with mild dementia. Given that depression is treatable, screening for depression and treatment of depression can be important already in the earliest stage of dementia to reduce mortality.

PURPOSE:To compare the accuracies of predicting AD conversion by using a decision support system (PredictAD tool) and current research criteria of prodromal AD as identified by combinations of episodic memory impairment of hippocampal type and visual assessment of medial temporal lobe atrophy (MTA) on MRI and CSF biomarkers. METHODS:Altogether 391 MCI cases (158 AD converters) were selected from the ADNI cohort. All the cases had baseline cognitive tests, MRI and/or CSF levels of Aβ1-42 and Tau. Using baseline data, the status of MCI patients (AD or MCI) three years later was predicted using current diagnostic research guidelines and the PredictAD software tool designed for supporting clinical diagnostics. The data used were 1) clinical criteria for episodic memory loss of the hippocampal type, 2) visual MTA, 3) positive CSF markers, 4) their combinations, and 5) when the PredictAD tool was applied, automatically computed MRI measures were used instead of the visual MTA results. The accuracies of diagnosis were evaluated with the diagnosis made 3 years later. RESULTS:The PredictAD tool achieved the overall accuracy of 72% (sensitivity 73%, specificity 71%) in predicting the AD diagnosis. The corresponding number for a clinician's prediction with the assistance of the PredictAD tool was 71% (sensitivity 75%, specificity 68%). Diagnosis with the PredictAD tool was significantly better than diagnosis by biomarkers alone or the combinations of clinical diagnosis of hippocampal pattern for the memory loss and biomarkers (p≤0.037). CONCLUSION:With the assistance of PredictAD tool, the clinician can predict AD conversion more accurately than the current diagnostic criteria.

The aim of this study was to investigate a possible link between cellular telephone use and risks for various diseases of the central nervous system (CNS). We conducted a large nationwide cohort study of 420 095 persons whose first cellular telephone subscription was between 1982 and 1995, who were followed through 2003 for hospital contacts for a diagnosis of a CNS disorder. Standardized hospitalization ratios (SHRs) were derived by dividing the number of hospital contacts in the cohort by the number expected in the Danish population. The SHRs were increased by 10-20% for migraine and vertigo. No associations were seen for amyotrophic lateral sclerosis, multiple sclerosis or epilepsy in women. SHRs decreased by 30-40% were observed for dementia (Alzheimer disease, vascular and other dementia), Parkinson disease and epilepsy among men. In analyses restricted to subscribers of 10 years or more, the SHRs remained similarly increased for migraine and vertigo and similarly decreased for Alzheimer disease and other dementia and epilepsy (in men); the other SHRs were close to unity. In conclusion, the excesses of migraine and vertigo observed in this first study on cellular telephones and CNS disease deserve further attention. An interplay of a healthy cohort effect and reversed causation bias due to prodromal symptoms impedes detection of a possible association with dementia and Parkinson disease. Identification of the factors that result in a healthy cohort might be of interest for elucidation of the etiology of these diseases.