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P3. Diagnosis

Detailed programme and abstracts

P3.1. Predictive testing for Alzheimer’s dementia: a German expert survey on disclosure practices and moral attitudes

SCHWEDA Mark, KÖGEL Anna, BARTELS Claudia, WILTFANG Jens, SCHNEIDER Anja, SCHICKTANZ Silke

It is increasingly acknowledged that Alzheimer’s disease (AD) pathology starts long before the onset of clinical symptoms and that a successful therapy should start in prodromal and even preclinical stages. While biomarker-supported prediction and diagnosis of preclinical Alzheimer’s disease (AD) already finds its way into clinical practice, professional attitudes towards disclosure practices and ethical issues are still unclear or controversial in many countries. Against this background, we investigated the current state of the art of early and predictive testing for late-onset dementia and AD in Germany. To this purpose, we conducted a comprehensive survey among medical professionals at German hospitals and memory clinics (n=108). The main foci of analysis were the practical criteria applied for prediction and diagnosis, the corresponding disclosure practice, the professionals’ attitudes towards ethical and legal issues, as well as required measures for the future. As our survey reveals, almost half of the respondents inform patients with MCI and pathological CSF biomarkers that they have or will soon develop Alzheimer’s dementia. 81% say there is a ‘right not to know’. However, 75% always communicate results. A majority agrees there is a benefit of prediction or later life planning (end-of-life, financial, family, housing (73-75%)) but also expects high psychological stress for patients (82%). As these results show, there is still considerable heterogeneity and insecurity among German professionals regarding predictive testing and early diagnosis of dementia and AD in Germany. Professionals use different criteria to communicate increased risks for AD. Some of them are in conflict with the current state of neuroscientific research or official guidelines, e.g., the pharmaceutical treatment of persons with MCI. We discuss these findings in view of their ethical implications and consider possibilities for improved information, training and standardization.

P3.2. A graduated detection and diagnosis strategy proposed by the European Joint Action “Act on Dementia”

KROLAK-SALMON Pierre, VANACORE Nicola, SELBAEK Geir, REJDAK Konrad, LATCHEZAR  Traykov, POLITIS Antonios, LEPERRE DESPLANQUES Armelle

In Europe, 40% to 50% of people with dementia remain undiagnosed. The diagnosis is mostly done lately at a stage of advanced autonomy loss or behavioural disorders. European surveys demonstrate the value of knowing diagnosis for people with dementia and their relatives. The first European Joint Action on Dementia “ALCOVE” recommends a timely diagnosis, available to all citizens who require it, at a stage when people first notice cognitive functions changes.

Poor diagnosis mainly relies on a lack of early cognitive detection in primary care, without available clear detection and diagnosis procedures. That is why the group dedicated to “Diagnosis and post-diagnosis supports” of the new European Joint Action “ACT ON DEMENTIA”, proposes a graduated strategy for neurocognitive disorder.

With that aim, a consensus has been adopted and discloses:

  • a neurocognitive detection step involving particularly general practitioners and nurses facing first patient or family complaints in primary care, leading to major or minor disorder determination
  • a first step of major disorder etiological diagnosis, aiming to identify typical Alzheimer’s disease and related disorders but also other possible aetiologies (metabolic disorders, subdural hematoma…)
  • a second step of major disorder etiological diagnosis for particularly complicated cases (focal atrophy, rapid dementia…)
  • a specific diagnosis pathway for people with a minor neurocognitive disorder, considering the person’s point of view after enlightened information on the possible evolution or not towards major disorder

At each step of the detection and diagnosis pathways are proposed:

  • an enlightened information to whom could benefit from or wants to access to clinical trials
  • post-diagnosis supports tailored to the patient-caregiver dyad profile and wills

This consensual European diagnosis strategy aims to enhance rates and quality of dementia diagnosis. First step of this strategy will be tested in primary care by the end of the Joint Action.

This abstract entitled “A graduated detection and diagnosis strategy proposed by the European Joint Action “Act on Dementia” is part of the joint action ‘678481 / DEM 2’ which has received fund from the European Union’s Health Programme (2016-2020).

P3.3. Assessing the educational needs of general practitioners around Alzheimer’s disease across Europe and Canada

DELL’AGNELLO Grazia, WILLIAMS, FRESCA, BOSSHARD-BECKER, HUNDEMER, MCRAE

Introduction/Background: To enable better patient management of Alzheimer’s disease(AD), timely diagnosis is essential but in practice is often delayed. A multidisciplinary working group of dementia specialists and general practitioners(GPs) hypothesized that a primary reason for a delay in timely detection and diagnosis/ referral stems from a knowledge gap among general practitioners.

Objective/Methods: The purpose of this research was to validate the hypothesis of the working group and to identify educational needs in AD management in primary care. Sixty telephone interviews were conducted with GPs across Canada, Germany, Sweden and the UK, with a further 75 interviews to be conducted in five other European countries (additional data will be available during the congress).

Results: GPs rated their current AD knowledge as average in the following areas: choosing and applying appropriate screening tools, treatment knowledge and patient management. GP’s are highly interested in improving their competence.  Educational needs were ranked by relevance to practice and interest in improving knowledge. The top ranked needs were: AD treatment approaches (4.43 out of 5); diagnostic process (4.40); differentiating AD from other causes of cognitive impairment (4.34); managing symptoms post-diagnosis (4.33); applying and choosing appropriate screening tools (4.32 and 4.30 respectively). GPs showed interest in attending Medical Education programs if clinical value could be provided to their patients.

Conclusions: GPs identified several unmet educational needs in AD detection, diagnosis and patient management and showed interest in improving their knowledge, especially in topics more relevant to daily practice, through specific Medical Education programs

P3.4. Gait as predictor of dementia risk

PÄRKKÄ Juha, MAHDIANI Shadi, BRUUN Marie, BARONI Marta, RHODIUS-MEESTER Hanneke, HERUKKA Sanna-Kaisa, GILS Mark van, HASSELBALCH Steen, MECOCCI Patrizia, FLIER Wiesje van der, REMES, Anne, SOININEN Hilkka, LÖTJÖNEN Jyrki

The disease pathology in dementias, e.g., in Alzheimer's disease, is known to start already decades before the first noticeable symptoms. The PredictND project is developing tools for early detection of people with high risk for dementia. One of these tools is the analysis of gait as a predictor of dementia risk.

Two walking measurements were successfully done with 315 patients in 4 memory clinics in Europe (Amsterdam, Copenhagen, Kuopio and Perugia). The mean patient age was 67±10 (mean±std) and MMSE 29±1,6 (mini-mental state examination). The WALK test consisted of standing up from a chair, walking 20m with 3 turns, and finally sitting down on a chair. The DUAL test contained the same, with simultaneously counting aloud backwards, starting from 100. Movements were measured with Actigraph GT3X-BT accelerometers.

Signal characteristics were computed offline, separately for WALK and DUAL tasks, using Matlab R2016a. Correlation between hip accelerometer data characteristics and MMSE total score are shown (Tables 1-2).Durationis the walking time in seconds.Varianceandrangeshow signal variance and range during the task. They are larger with stronger movements.Peak frequencyis the step rate, steps per second.PeakFreqValuedescribes the regularity of steps.SpecEntropydescribes the spectral entropy, thus irregularity of steps.

Table 1Correlation of MMSE total score and gait features during WALK task (statistically significant Pearson correlations: * p<0.05, ** p<0.001)

R

WALK duration

WALK variance

WALK range

WALK Peak Freqency

WALK PeakFreqValue

WALK SpecEntropy

MMSE

-0,056

0,204 **

0,088

-0,014

0,337 **

-0,325 **

Table 2Correlation of gait features and MMSE total score during DUAL task

R

DUAL duration

DUAL variance

DUAL range

DUAL Peak Frequency

DUAL PeakFreqValue

DUAL SpecEntropy

MMSE

-0,058

0,208 **

0,111

0,062

0,350 **

-0,357 **

The gait characteristic that had strongest correlation with MMSE was walking irregularity (SpecEntropy) during the DUAL task. Task duration (walking speed) did not have significant correlation with MMSE. The project continues and collects 12-month follow-up data, which will show if individual changes in gait provide more insight to predicting dementia risk using gait analysis.

P3.5. Computer assisted differential diagnosis of dementia disorders: The PredictND validation study

BRUUN Marie, GJERUM Le, FREDERIKSEN Kristian, RHODIUS-MEESTER Hanneke, BARONI Marta, LEMSTRA Evelien, BREMER Jonne, REMES Anne, URHEMAA Timo, TOLONEN Antti, TONG Tong, GUERRERO Ricardo, RUECKERT Daniel, WALDEMAR Gunhild, SOININEN Hilkka, MECOCCI Patrizia, VAN DER FLIER Wiesje, LÖTJÖNEN Jyrki, HASSELBALCH Steen

Background: Defining the underlying cause for dementia disorders is challenging. In the PredictND validation study, we study whether a computer-based clinical decision support tool (PredictND tool) can assist the clinician in achieving more accurate diagnostic assessments. Preliminary results of the ongoing prospective multicenter study are presented in this abstract.

Methods: The PredictND tool uses reference data from individuals with subjective memory complaints (used as controls), Alzheimer’s disease, dementia with Lewy bodies, frontotemporal dementia and vascular dementia to provide for new patients a probability of belonging to one of the 4 dementia groups. In total, 783 individuals were included from four memory clinics; Amsterdam, Copenhagen, Kuopio and Perugia. (Table 1). Individuals suspected of having a dementia disorder with MMSE ≥18, Clinical Dementia Rating ≤1.0 and T1-weighted MRI (≥1.5 Tesla) were eligible for inclusion. The exclusion criteria were psychiatric disorder, alcohol or substance abuse and other brain disorder explaining the cognitive problems. Each individual underwent a baseline investigation including demographic data, neurological and physical examination, functional and psychological scales, neuropsychological testing, blood screening and MRI. A diagnosis and the level of confidence in the diagnosis were determined by clinicians first without the PredictND tool and later with the tool for all included subjects.

Results: Description of the cohort is presented in Table 1. Table 2 shows the distribution of clinical baseline diagnoses without and with the PredictND tool. Our results show that the syndrome diagnosis (dementia/MCI/healthy) was changed in 4 % of cases and the diagnosis of the underlying cause in 23 % of cases.

Conclusion: Our preliminary results indicate that especially the diagnosis of the underlying cause of cognitive dysfunction is challenging and influenced by the tool. Analysis on the added-value of the PredictND tool will be performed when the reference diagnoses from ongoing 12-month follow-ups become available.

P3.6. AD related determinants, not co-morbidity, are associated with mortality in young AD patients

RHODIUS- MEESTER Hanneke, LIEDES Hilkka, KOENE Ted, LEMSTRA Afina, TEUNISSEN Charlotte, BARKHOF Frederik, SCHELTENS Philip, VAN GILS Mark, LŐTJŐNEN Jyrki, VAN DER FLIER Wiesje

Background: Average survival after dementia diagnosis varies considerably. We aimed to identify clinical measures that are associated with risk of mortality in patients with dementia due to Alzheimer’s disease (AD). To combine multiple determinants and to facilitate use in clinical practice, we used a clinical decision support system (CDSS) based on the disease state index (DSI) classifier.

Methods: We included 616 patients (50% female, mean age 67±8 years, mean MMSE 22±3) with dementia due to AD from the Amsterdam Dementia Cohort. Information on mortality was obtained from the Dutch Municipal Register. We assessed associations of baseline clinical data, including co-morbidity, neuropsychology, MRI and cerebrospinal fluid (CSF) biomarkers, with mortality. In addition, we built a multivariate model based on the DSI to provide a prognosis of mortality.

Results: After a mean of 4.9±2.0 years, 213(35%) patients had died. Cox proportional hazards models showed that higher age and male gender, and after adjustment for age and sex, worse scores on neuropsychological tests for memory and executive functioning and more severe atrophy on MRI were associated with increased risk of mortality. Effect sizes ranged from HR (95%CI) 1.1 (1.0-1.3) to 2.4 (1.6-3.5). APOE e4, co-morbidity and CSF biomarkers were not associated with mortality. When we used the DSI classifier to combine these determinants, classification was modest with a receiver operating characteristics curve of 0.64±0.04. Moreover, the DSI classifier provided visualization of how each variable contributes to the prediction.

Conclusion: In this memory clinic cohort, AD-related determinants were associated with mortality. A CDSS was instrumental in translating these findings to clinical practice by integrating and visualizing available data.

 

 
 

Last Updated: Monday 23 October 2017

 

 
  • Acknowledgements

    The 27th AE Conference in Berlin received funding under an operating grant from the European Union’s Health Programme (2014-2020). Alzheimer Europe and Deutsche Alzheimer Gesellschaft e.V. gratefully acknowledge the support of all conference sponsors.
  • European Union
  • Roche
 
 

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