Motor, cognitive and mobility deficits in 1000 geriatric patients: protocol of a quantitative observational study before and after routine clinical geriatric treatment – the ComOn-study
BMC Geriatrics volume 20, Article number: 45 (2020)
Motor and cognitive deficits and consequently mobility problems are common in geriatric patients. The currently available methods for diagnosis and for the evaluation of treatment in this vulnerable cohort are limited. The aims of the ComOn (COgnitive and Motor interactions in the Older populatioN) study are (i) to define quantitative markers with clinical relevance for motor and cognitive deficits, (ii) to investigate the interaction between both motor and cognitive deficits and (iii) to assess health status as well as treatment outcome of 1000 geriatric inpatients in hospitals of Kiel (Germany), Brescia (Italy), Porto (Portugal), Curitiba (Brazil) and Bochum (Germany).
This is a prospective, explorative observational multi-center study. In addition to the comprehensive geriatric assessment, quantitative measures of reduced mobility and motor and cognitive deficits are performed before and after a two week’s inpatient stay. Components of the assessment are mobile technology-based assessments of gait, balance and transfer performance, neuropsychological tests, frailty, sarcopenia, autonomic dysfunction and sensation, and questionnaires to assess behavioral deficits, activities of daily living, quality of life, fear of falling and dysphagia. Structural MRI and an unsupervised 24/7 home assessment of mobility are performed in a subgroup of participants. The study will also investigate the minimal clinically relevant change of the investigated parameters.
This study will help form a better understanding of symptoms and their complex interactions and treatment effects in a large geriatric cohort.
The demographic changes associated with increased life-expectancy have led to a substantial increase in older people suffering from multimorbidity with age-related neurological diseases and functional impairment [1,2,3]. A target-oriented and specific geriatric treatment designed by a multiprofessional and –disciplinary team including neurological expertise, addressing both the clinical relevant functional deficits and the individual needs of the patients, is urgently needed [4, 5]. Impaired gait, balance, cognitive functions and, consequently, reduced mobility and falls are among the most relevant age-related functional impairments associated with multimorbidity. At 70 years, the prevalence of gait disorders is about 35% and increases further with age . About one third of people aged 65 years or above fall at least once a year . Interestingly, the prevalence of falls among neurological patients is nearly twice as high as in the general population . Of these patients, 5–10% develop serious injuries, e.g. fractures and head trauma [9, 10]. Delayed recovery from fall-related injury in geriatric patients often requires long-lasting inpatient stays with high resource costs [11,12,13] and the possibility of complications such as pneumonia. Moreover, long-term morbidity associated with fear of falling affect quality of life and mobility [14,15,16].
Cognition, particularly executive functions, are also often affected in older adults [17, 18] and can interfere with daily life activities and influence mortality rates. In an 8-year follow-up study , people with deficits in executive functions had a higher mortality rate than those without. One reason may be the reduced ability to manage multiple medical conditions . Executive dysfunctions even affect intervention outcomes. For example, a recent study showed that baseline executive function performance predicted performance on the mobility tests after training in older adults .
A growing amount of epidemiological and pathophysiological studies suggests that motor and cognitive deficits interact and amplify each other [14, 18, 21, 22]. The interaction is not surprising as: (i) recent neuroimaging studies indicate a strong involvement of, e.g. the thalamus, basal ganglia, cerebellum, mesiotemporal areas and the frontal cortex in gait and balance performance [23, 24], and (ii) lesions in these areas are associated with falls, e.g. for Parkinson patients [25,26,27].
Physical activity may depend on brain integrity and influences geriatric conditions, such as frailty. A recent study indicates that physical activity interventions can reduce the prevalence and severity of frailty in elderly people . A post-mortem study showed that white matter lesions of the brain explained 4% of the variance of physical frailty in 165 participants with a mean age at death of 88 years . However, the interaction between physical activity and age-associated functional impairment, such as motor and cognitive deficits and frailty, remain largely unexplained and need further investigation. Research and clinical routine commonly use qualitative measures for the assessment of mobility, and motor and cognitive deficits, and these tools improved our understanding of these symptoms. However, these tools have numerous disadvantages, such as inaccuracy, high time expenditure and investigator dependency . Due to the dynamic development in the fields of life sciences and technology, quantitative measures to evaluate impairment of gait, balance, cognitive functions and mobility –including mobile technology, so-called “wearables”- are increasingly available also for medical purposes. This technology can generate highly accurate outcome parameters for clinical studies and is even close to be implemented in the clinical routines [30,31,32,33].
The first mayor aim of this prospective, explorative observational multi-center study is therefore to explore quantitative markers of gait, balance and cognitive deficits in relation to routine clinical and specific geriatric parameters –as assessed with the comprehensive geriatric assessment (CGA)- in a large cohort of geriatric patients with predominantly chronic neurologic conditions. Detailed information beyond usual CGA parameters, e.g. gait variability, step characteristics, postural control and (semi-)quantitative cognitive parameters could substantially improve our understanding of geriatric conditions . We will also determine the minimal detectable and clinical relevant change of many of the parameters investigated.
The second mayor aim of the study is to examine the association between executive and attentional deficits and the identified quantitative motor parameters in this vulnerable clinical cohort. We hypothesize that these cognitive deficits have predictive value for certain gait and balance deficits. The third mayor main aim is to evaluate the efficacy of an individualized geriatric inpatient treatment. The large dimension and multifaceted construction of the dataset will also allow many additional hypotheses to be tested.
Novel aspects of this study are (i) the recruitment of a prospective and large geriatric cohort, (ii) the coverage of a broad range of clinically relevant parameters, (iii) the identification of stabile quantitative parameters with clinical relevance, (iv) the evaluation of treatment response, (v) the definition of the minimal clinically relevant change (MCRC) of the investigated parameters, (vi) the inclusion of newest mobile technology for the assessment of mobility, motor functions and balance aspects using validated algorithms, and (vii) the assessment of this vulnerable cohort at places beyond the clinical environment.
Ethical approvals have been obtained from the ethical committees of Kiel, Brescia, Porto, Curitiba and Bochum. The centres have submitted their proposals according to the principles of the Declaration of Helsinki. All participants will receive detailed oral and written information about the content and procedure of the study.
The study will include geriatric patients aged 70 years and older, with and without neurological conditions [34,35,36]. Patients aged between 50 and 69 years will also be considered if they suffer from at least two chronic conditions . Additional inclusion criteria are the ability to stand without personal aid for at least ten seconds and to walk at least three meters (walking aids permitted). Exclusion criteria are severe deficits in consciousness (clinical diagnosis), more than two falls during the previous week (fall risk during the assessment too high), five points or less in the Montreal Cognitive Assessment (MoCA) test [37, 38], history of or current drug abuse (except nicotine) and (corrected) visual acuity below 60% (assessed using a Sloan Letter Chart for three meter distance ). Magnetic Resonance Imaging (MRI) will be performed in a subset of patients having a clinical indication for this examination. Participants suffering from claustrophobia, or having pacemakers, defibrillators, targeted drug delivery systems, deep brain stimulation, vena cava filters, cochlear implants or any kind of ferromagnetic material within the body will not be considered. The cohort will include inpatients treated in University and General hospitals and geriatric rehabilitation centres.
This is a prospective, explorative observational multi-center study. Most of the participants will be recruited at admission. A subsample (n = 100) with a planned hospital stay (e.g. to evaluate new treatment options or to improve medication plans in severely affected patients that are at risk of losing functional independency) will be contacted via telephone, to ask them whether they would be interested to participate in a one week home-based assessment with wearables before and after the treatment phase. All participants will be assessed within the first two days (T1) and during the last two days before discharge (T2) of their inpatient stay. To determine the Minimal Detectable Change, an additional subgroup (n = 100) will undergo a visit (T0) 24 h before or after T1. Inpatient’s stay will be approximately 14–20 days. All participants will receive multidisciplinary care with an individually adapted set of therapeutic options depending on their needs during their inpatient treatment. Data obtained from T1 will be used to evaluate cross-sectional aspects of the study. Response to treatment will be evaluated by calculating the change between T1 and T2 after an approximately 14–20 days multidisciplinary treatment. Figure 1 illustrates the detailed study design.
All participants will undergo an extensive and quantitatively oriented CGA, i.e. an assessment that collects information about all five relevant components of the International Classification of Functioning, Disability and Health (ICF) model . Furthermore, a detailed evaluation of mobility, and specific motor and cognitive function will be conducted. For measurements of motor and cognitive parameters, translated and validated test versions will be used as far as available. Clinical and demographical data and questionnaires will also be assessed in the required languages.
Clinical and demographic data
Clinical and demographic data –including age, gender, diagnosis, initial and current symptoms, concomitant diseases, activities of daily living (ADL, ), instrumental ADL (iADL, ), nutritional aspects and medication– will be collected from clinical records and also with a semi-standardized clinical interview. Neurological routine assessment will include evaluation of strength (grip force), muscular proprioceptive reflexes, pallaesthesia, signs of ataxia, and frontal lobe dysfunction. We will use the Geriatrie-Check, which is a screening tool for the identification of geriatric patients [43, 44] and assesses aspects of dementia, level of care, frailty, and the premorbid level. It has recently been validated . We will also use the geriatric screening according to Lachs et al.  to evaluate the functional aspects of vision, hearing, and urinary incontinence. Self-care and mobility skills (e.g. toilet use, eating, dressing, climbing stairs) will be appraised by the commonly used and reliable (kappa = 0.93) Barthel Index [46, 47]. Subjective improvement will be assessed using the Clinical Global Impression - Global Improvement - Scale (CGI-I, ).
Diagnoses and medication will be extracted from the medical reports. Extent of treatment and rehabilitation -as a covariate- will be evaluated using number and duration of therapeutic sessions as well as (change of) medication and medical aids.
Cognitive functions will be measured with standardized neuropsychological screening tools and tests. We will use the MoCA for the evaluation of global cognitive performance. The MoCA has been shown to be internally consistent (Cronbach’s alpha = 0.83) and highly sensitive in detecting Mild Cognitive Impairment (MCI, 90%) and Alzheimer’s Disease (100%). Normative and validation data are available for Brazilian, Italian, German and Portuguese populations [38, 49,50,51]. For the assessment of frontal-executive dysfunctions the required version of the Frontal Assessment Battery (FAB) will be used [52,53,54]. The FAB consists of six items, testing aspects of conceptualization, lexical fluency, motor programming, sensitivity to interference, inhibitory control and environmental autonomy.
The Trail Making Test (TMT, ) assesses visual scanning and processing speed (TMT part A) as well as mental flexibility and divided attention ((TMT part B, B-A). Construct validity of the TMT is good  and there are normative data available stratified by age and education for the required languages [57,58,59,60].
In order to gain the second study aim in more detail regarding specific cognitive functions, the Kiel centre will perform a detailed neuropsychological testing in this subcohort, including the following tests:
The Testbatterie zur Aufmerksamkeitsprüfung (TAP, ) is a computer-based assessment battery for attention. We will use the subtest “Alertness” to measure reaction time to a visual stimulus and the capability to inhibit reactions to a pre-stimulus.
The standardized Alters-Konzentrations-Test (AKT, ) provides information about vigilance, concentration and focused attention (the capacity to focus on a stimulus while suppressing imposed distractors). Retest-reliability is high (r = 0.75–0.89, ).
The Five-Point Test (FPT, ) is a standardized paper-pencil test for figural fluency and strategic thinking. The test consists of five-dot boxes in six rows on each sheet where participants produce as many different figures as possible by connecting the dots in each box within a defined time period. The FPT is a valid test that has excellent inter-rater (ICC = 0.99) and good test-retest reliability (ICC = 0.72–0.84, ).
The Regensburger Wortflüssigkeitstest (RWT, ) assesses verbal fluency and flexibility. Subjects have to name as many words as possible within two minutes that (i) belong to a certain category, (ii) have a defined starting letter, (iii) belong to two different categories (alternating naming) and (iv) have two defined starting letters (again alternating naming). Inter-rater reliability of the test is excellent (ICC = 0.99) and test-retest reliability good (rtt = 0.72 – rtt = 0.89, ).
The Nürnberger-Alters-Inventar (NAI, ), normed for people aged between 57 and 96 , provides information about cognitive and behavioural aspects. We will use the subtest Farb-Wort-Interferenz-Test (FWIT), based on the widely used Stroop-Test, to assess attention and cognitive flexibility during provision of conflicting stimuli.
To avoid learning effects in T2, parallel versions of the MoCA, the AKT and RWT will be provided.
Axial motor function
Gait, balance and transfer aspects will be measured in a supervised environment (e.g., the ward, Fig. 2) using a set of well-established tests (summarized in Table 1), which will all be instrumented with CE-certified wearable devices (Rehagait®, Hasomed GmbH, Magdeburg, Germany; sensors at the feet and on the lower back).
The protocol will include the Short Physical Performance Battery (SPPB, [67,68,69]). The SPPB measures balance (tandem, semi-tandem, and side-by-side stand), gait speed (walking twice four meters at a comfortable speed) and chair rise performance (5-Chair rise test, as fast as possible) which has been shown to be reliable in older adults (ICC = 0.83–0.89, ). Participants will also perform the above-mentioned balance tasks on a foam pad (Airex balance pad, 50x41x6 cm). This test has already been performed under instrumented conditions with test-retest reliability (ICC) between 0.41 and 0.81 .
Moreover, the Timed-up-and-Go test (TUG) will be used to assess mobility aspects and turning. Recent studies suggest that instrumentation of the TUG with wearable devices can provide useful additional and complementary information to the generally used total time [68, 72,73,74].
Participants will also perform straight walks (out of a standing position) over three meters and 20 m and circular walks around a 1.20 m circle (360°). Single task performance will be assessed during both walking conditions with self-selected and as-fast-as-possible pace, except for circular walking (self-selected pace starting with the right leg and then with left leg). Dual task performance (checking boxes and subtracting serial 7 s) will be assessed during circular walks in self-selected pace condition, straight walking dual-task performance in fast pace condition [75,76,77].
The functional reach (FR) test measures balance at the limits of stability in the anterior direction. It can identify fall risk and balance impairment in geriatric patients [78, 79]. We have recently published an instrumented version of the test . Participants will stand upright next to a wall with a yardstick and put their right arm in a stretched out position. Then they will reach forward as far as they are able to, and then be asked to keep this position for 15 s.
Part III of the revised version of the Unified Parkinson’s Disease Rating Scale (MDS UPDRS-III, ) will be used to assess axial deficits (e.g., via the postural instability and gait (PIGD) subscore) and parkinsonian signs. The Hoehn & Yahr scale will be used in patients with Parkinson’s disease (PD) to define disease severity .
The Falls Efficacy Scale (FES-I, ) consists of 16 questions about concerns regarding falling in specific activities of daily living (e.g., when getting dressed, when taking a shower or when shopping). The FES-I is a reliable instrument (Cronbach’s alpha = 0.79) and a strong association with previous as well as future falls has been found .
Fine motor function
The Functional Dexterity Test (FDT, pegboard test) is a reliable and valid instrument to measure finger and thumb movement . Participants will turn 16 pegs in a zigzag manner as fast as possible on a wooden board with holes, first with the dominant, then with the non-dominant hand.
The 20-Cents test assesses fine motor skills under daily life conditions and is validated for geriatric patients . Twenty 1-cent coins, spread over a white sheet of paper, will be picked up with each hand (first the dominant one, then the non-dominant one) and put into a box as fast as possible.
Health-related quality of life, behavior, social participation, physical activity and pain
Health-Related Quality of Life (HrQoL, [85, 86]) is one of the most important factors regarding treatment decisions and outcome of treatment. Main dimensions of HrQoL are physical, mental, social and role functioning. The EuroQol questionnaire with five dimensions (EQ-5D-5 L, ) consists of a descriptive part and the EQ Visual Analogue Scale. For the descriptive part, participants rate the impact of mobility and its deficits, self-care, usual activities, pain/ discomfort and anxiety/ depression on HrQoL. The EQ Visual Analogue Scale allows the participant to rate today’s overall HrQoL on a scale of 0 (worst health they can imagine) to 100 (best health).
The Depression im Alter scale (DIA-S, ) assesses specific aspects of depression and consists of ten items. The test person is asked to focus on the previous 14 days. The DIA-S is reliable (Cronbach’s alpha = 0.84) and has been validated in geriatric patients .
Apathy, a common symptom in neurological and psychiatric diseases, will be assessed with the German version of the Apathy Evaluation Scale (AES-D, ). The AES-D includes cognitive and emotional aspects of goal-directed behaviour. A total of 18 items are rated on a four-point Likert scale by the participant (AES-D-S, self-rated) and by a relative (AES-D-I, informant). The AES-D is reliable (Cronbach’s alpha = 0.91–0.94) and has been shown to be valid in patients with diverse diseases and in healthy adults .
The reliable (ICC = 0.70–0.94) and valid Nürnberger-Alters-Alltagsaktivitäten-Skala (NAA), part of the NAI , is a 20-item questionnaire for the assessment of independency and participation in activities of daily living.
Physical activity (PA) will be assessed with the self-administered short version of the International Physical Activity Questionnaire (IPAQ, ). The participants are asked to estimate how much time in days per week and in hours per weekday they spend doing: (i) vigorous physical activities, (ii) moderate physical activities, (iii) walking, and (iv) sitting. Detailed information about reliability and validity are available for all versions from over twelve countries .
Pain will be assessed via the painDETECT Questionnaire (PD-Q), which is a reliable screening tool with high sensitivity, specificity and positive predictive accuracy .
Sarcopenia, frailty and malnutrition
The Jamar hydraulic hand dynamometer (AFH, Lügde, Germany) will be used to measure grip force . Lean body / muscle mass and total body water and fat will be quantitatively assessed with the validated bioelectrical impedance analysis (BIA, Akern Bia 101, SMT medical GmbH & Co. KG, Würzburg, Germany, [94, 95]). The BIA will be applied as instructed in the manual with four electrodes (two at the right foot, two on the right hand) in a lying position after a rest phase of about ten minutes . For the definition of sarcopenia we will follow the definition of the European consensus on definition and diagnosis for sarcopenia [97, 98].
Frailty will be assessed with the FRAIL-scale, a five-item questionnaire asking for fatigue, resistance, ambulation, illness and weight loss during the last three months. Usefulness for detecting frailty in elderly people has been proven [99,100,101].
The Swallowing Disturbance Questionnaire for Detecting Dysphagia (SDQ, ) is a 15-item questionnaire to detect dysphagia. The SDQ has been shown to be reliable (Cronbach’s alpha = 0.89) and useful to assess swallowing in PD.
Different aspects of malnutrition will be measured via interview using the Mini Nutritional Assessment (MNA, ), Malnutrition Universal Screening (MUST, ) and Subjective Global Assessment (SGA, ). The instruments assess nutritional status based on objective data (e.g. weight, height, Body-Mass-Index), physical examination and the participant’s self-report.
At the location of Kiel, heart rate variability (HRV) will be examined using computer-assisted equipment (ProSciCard III, MediSyst GmbH, Germany) during rest and controlled deep breathing (six respiratory cycles per minute). Coefficient of variation, root mean square of successive differences, mean circular resultant, expiration-inspiration difference and E/I-ratio as well as a spectral analysis of HRV will be quantified and compared to age-related normal ranges of 120 healthy subjects .
Blood pressure (BP) and heart rate (HR) during orthostatic exposition will be monitored after ten minutes of supine rest on a tilt table. Patients will then be moved to the erect position (65°) and BP and HR changes recorded at one, three, and five minutes of head-up tilt. A decrease of systolic BP > 20 mmHg and diastolic BP > 10 mmHg within three minutes of tilting is regarded as orthostatic hypotension .
Residual urine volume will be determined with the BladderScan BVI6100 (Verathon Medical BV, The Netherlands, ). Moreover, the reliable and validated Qualiveen  questionnaire will be used for the evaluation of HrQoL in patients with urinary disorders. It covers frequency and intensity of different aspects (limitations, constraints, fears, feelings) of urinary dysfunction.
The German version of the Female Sexual Function Index (FSFI-d, ) is a 19-item questionnaire for the assessment of six different domains of female sexuality: desire, arousal, lubrication, orgasm, satisfaction, and pain. Its internal consistency (Cronbach’s alpha = 0.75–0.95) is good to very good. The International Index of Erectile Function (IIEF, ) is a self-administered questionnaire for males and includes aspects of erectile function, orgasm function, sexual desire, intercourse satisfaction and overall satisfaction. The original version (Cronbach’s alpha> 0.9, ) and the German translation have been shown to be reliable (Cronbach’s alpha = 0.95, ). As sexual function is a sensible topic also in older adults, participants will be informed again explicitly that answering this questionnaire is voluntarily.
Participants will be asked to provide blood and stool samples for our established biobank . Material will be collected from the wards and directly brought to the technicians responsible for the pre-processing and storage of the material, to ensure highest quality standards of the biosamples. Blood samples will be used for blood counts and DNA isolation, whereas stool samples will be used for gut microbiome analysis.
We will analyse gradient echo T1-weighted sequences, as well as T2-weighted flair sequences, susceptibility-weighted imaging and DTI datasets collected with a standardized protocol on a 3-T MRI. In addition, participants will be asked to provide any existing MRI data for semi-quantitative analysis .
Those patients, who will undergo a planned inpatient stay from a former clinical contact, will be contacted by phone in advance. Patients interested in joining the home assessment will be visited at their homes by staff and introduced into this part of the study. During the home assessment, participants will wear three wearables (inertial measurement units IMUs, GaitUp SA, Lausanne, Switzerland) fixed at the lower back and at the more affected ankle and wrist (if both sides are equally affected they wear the sensors on the right). They will also be asked to keep a structured diary about their activities to ensure comparability of subjective evaluation with IMU-based data. Participants will be assessed 24 h per day over seven days before and after the inpatient stay. In case patients may have difficulties with the handling of the sensor system, relatives will be asked to support the measurement process.
Database and statistics
Study data will be collected and managed using REDCap electronic data capture tools hosted at Kiel University . Statistical analysis will be performed using established statistical programs (e.g. R version 3.5.0, The R Foundation; SPSS 24, SPSS Corp, Chicago IL, USA). We abstained from providing a detailed analysis plan and power analyses as the analysis plans will be substantially influenced by the type of research question, and power analyses depend on both, concrete study hypotheses (which are given here only to a certain extent) and at least preliminary effect sizes that are, to our best knowledge, not yet available for most of the Parameters collected in this specific cohort. The use of z-scores will ensure comparability between data sets of different centres and countries. Common descriptive and inferential statistics and equivalent nonparametric statistics will be used for baseline data analysis. Logistic regression will be used to evaluate confounding factors (e.g. age, gender). A pre-post comparison with correction for multiple testing will be conducted to evaluate changes in mobility, motor function and cognition between T2 and T1. To assess reliability and responsiveness of the assessments (T1 to T0), we will use t-test and Cohen’s d after testing for normal distribution, and extract Intra-Class-Correlation (ICC), Standard Error of Measurement (SEM) and Minimal Detectable Change . An explorative comparison of sensor-based data with clinical data and quantitative imaging parameters will be conducted by common descriptive and inferential statistics, (non-) parametric statistics and logistic regression.
This study will include 1000 geriatric patients, and this number may be increased in the course of the ongoing recruitment due to the exploratory, prospective, modular, and observational study design. We are not aware of a comparable endeavor in this research field. Due to the large number of participants, data obtained from this study will also allow sub-analyses focusing on, e.g., presence and absence of geriatric and non-geriatric conditions and comparisons across centers.
We will collect data covering many aspects of body structure and function, but will –in line with the CGA- go beyond this usually well-assessed ICF component and collect data of all five components of this WHO-designed and most widely accepted model of health and dysfunction . The main asset of this study is in our view that as many as possible parameters of disability and symptomatology, from biofluid and neuroimaging, over quantitative geriatric syndrome assessment and parameters of autonomic and mobility dysfunctions will be collected on a quantitative level. The broad range of parameters will allow the use of novel analysis approaches and testing of hypotheses that can serve as an ideal starting point for the initiation of hypothesis-driven studies in the field of geriatrics.
This study will also evaluate treatment response through repeated assessment at the beginning and the end of multidisciplinary geriatric care programs. The programs will be comparable in the majority of participants and will encompass individual allied health training of at least 20 sessions, and re-evaluation and adaptation of medication (in the frame of, e.g., the early rehabilitation in geriatric medicine concept as applied in Germany [117, 118]). This approach will allow the definition of effective versus non-effective response-to-treatment parameters as well as the definition of predictive parameters for defined treatment approaches. This aspect is relevant especially at times when value-based healthcare [119, 120], precision medicine  and shared decision making  become increasingly important.
Moreover, we will evaluate test-retest reliability and minimal clinically relevant change through an additional T0 assessment. This approach is relevant in the light of the large number of assessments and inclusion of novel parameters in this study, to provide first evidence for the clinical meaningfulness of these parameters but also to provide information about the extent of noise that these parameters have during repeated assessments.
We will also use modern technology for the assessment of movement deficits, including but not limited to gait, balance, transfers, sleep and mobility. We will only apply algorithms that are validated for these populations for the extraction and appraisal of movement episodes and mobility patterns (e.g., [123,124,125,126]). It is expected that yet unknown symptoms will be detected that are not visible with the usual “clinical eye” . We will evaluate our participants not only in the hospitals but will collect daily-life data during a 24/7 assessment before and after the inpatient stay in a subgroup. This approach will give us access to an entirely new field of research, i.e. mobility, movement, and behavioral aspects in the natural environment of the participants. These measures will provide complementary aspects to the supervised assessments in the clinic, where measures mainly reflect functional capacity (“How well can you perform?”), as parameters collected in the usual environment rather reflect functional activity (“How do you regularly perform?”) [127, 128]. We have recently learned that “identical” behaviors and movements can substantially differ depending on whether they are collected in the clinical or the home environment . The home-based dataset will also allow evaluation of fluctuation in performance.
This study’s limitations include: firstly, the cohort includes old and frail people, and the assessment is somewhat exhaustive. Thus, it is possible that some participants lose motivation during the first assessment or between the first and second assessment. We will therefore split the respective assessments into parts and will allow adequate breaks (e.g. over lunch). This is possible as participants are investigated during an inpatient stay, and assessment times can be flexibly organized. Second, although the treatment is highly standardized at least in the German centers, this treatment is not comparable to standardized treatments as they are typically performed in clinical trials. Still, we feel that our approach is of value as this treatment reflects the “real life situation” in the participating centers and the high number of participants will most probably allow analyses in similarly treated subgroups. Third, the home assessment requires some technical understanding, which may not always be given in all participants. We will address this issue by asking spouses and other related people to help with the charging of the sensors, and by providing telephone contact in case technical issues occur. Fourth, use of novel technology always includes the risk of technical problems and potential data loss. We are confident that this is a little risk as we have long-lasting experience with the companies providing the sensors and constant communication and support is ensured by the manufacturers. Finally, our multi-center design requires an intense and regular interaction between respective principle investigators and study personnel, and highly standardized protocols. We address these aspects by providing all relevant documents in English, by performing personal visits at all cites to personally train the assessments and to solve any upcoming issues, and by regularly and randomly performed internal quality checks of the data.
This exploratory study investigates a large sample of geriatric patients. It uses a comprehensive, mainly quantitative and novel technology-oriented assessment protocol that is performed in the clinic and at home and thus goes beyond the already established CGA. This study design will allow evaluation of treatment effects. Taken together, this study has the potential to enhance our understanding of geriatric deficits and the intra-individual interaction of neurological age-related diseases. The dataset will also allow drawing new conclusions and hypotheses about disease and treatment effects in this vulnerable population.
Availability of data and materials
Activities of daily living
Apathy Evaluation Scale - German Version
Bioelectrical impedance analysis
Cognitive and Motor Interaction in the Older Population
Depression im Alter - Skala
- EQ-5D-5 L:
EuroQoL questionnaire (5 dimensions, 5 level of answers)
Frontal Assessment Battery
Functional Dexterity Test
Falls Efficacy Scale - International
Female Sexual Funtion Index – German version
Health-Related Quality of Life
Instrumental activities of daily living
International Index of Erectile Function
International Physical Activity Questionnaire
Montgomery-Asberg Depression Scale
Mild Cognitive Impairment
- MDS UPDRS:
Revised version of the Unified Parkinson’s Disease Rating Scale
Mini Nutritional Assessment
Montreal Cognitive Assessment
Magnetic resonance imaging
Malnutrition Universal Screening Tool
Postural instability and gait
Swallowing Disturbance Questionnaire
Standard error of measurement
Subjective Global Assessment
Short Physical Performance Battery
Time of assessment 0
Time of assessment 1
Time of assessment 2
Testbatterie zur Aufmerksamkeitsprüfung
Trail Making Test
Anderson GF, Hussey PS. Population Aging: A comparison among industrialized countries. Health Aff. 2000;19(3):191–203.
Lehnert T, Heider D, Leicht H, Heinrich S, Corrieri S, Luppa M, et al. Review: health care utilization and costs of elderly persons with multiple chronic conditions. Med Care Res Rev. 2011;68(4):387–420.
Synofzik M, Maetzler W. Gelingendes Altern: Was können Neurologie und Geriatrie beitragen? Nervenarzt. 2015;86(4):475–80.
Kane RL, Callahan CM, Morley J, Pacala JT. Marketing geriatrics. J Am Geriatr Soc. 2016;64(7):1405–7.
Tinetti M. Mainstream or extinction: can defining who we are save geriatrics? J Am Geriatr Soc. 2016;64(7):1400–4.
Verghese J, LeValley A, Hall CB, Katz MJ, Ambrose AF, Lipton RB. Epidemiology of gait disorders in community-residing older adults. J Am Geriatr Soc. 2006;54(2):255–61.
WHO. global report on falls prevention in older age. Geneva: World Health Organization; 2007.
Stolze H, Klebe S, Zechlin C, Baecker C, Friege L, Deuschl G. Falls in frequent neurological diseases: prevalence, risk factors and aetiology. J Neurol. 2004;251(1):79–84.
Nevitt MC, Cummings SR, Hudes ES. Risk factors for injurious falls: a prospective study. J Gerontol. 1991;46(5):M164–70.
Tinetti ME, Doucette J, Claus E, Marottoli R. Risk factors for serious injury during falls by older persons in the community. J Am Geriatr Soc. 1995;43(11):1214–21.
Rubenstein LZ. Falls in older people: Epidemiology, risk factors and strategies for prevention. Age Ageing. 2006;35(\).
Snijders AH, van de Warrenburg BP, Giladi N, Bloem BR. Neurological gait disorders in elderly people: clinical approach and classification. Lancet Neurol. 2007;6(1):63–74.
Bergman K, Papendick L. Falls in the neurologic illness population. J Trauma Nurs. 2014;21(4):182–5.
Rubenstein LZ, Josephson KR. Falls and their prevention in elderly people: what does the evidence show? Med Clin North Am. 2006;90(5):807–24.
Friedman SM, Munoz B, West SK, Ruben GS, Fried LP. Falls and fear of falling: which comes first? A longitudinal secondary prevention. J Am Geriatr Soc. 2002;50(8):1329–35.
Suzuki M, Ohyama N, Yamada K, Kanamori M. The relationship between fear of falling, activities of daily living and quality of life among elderly individuals. Nurs Health Sci. 2002;4(4):155–61.
Royall DR, Palmer R, Chiodo LK, Polk MJ. Declining executive control in Normal aging predicts change in functional status: the freedom house study. J Am Geriatr Soc. 2004;52(3):346–52.
Yogev G, Hausdorff JM, Giladi N, Yogev-Seligmann G, Hausdorff JM, Giladi N. The role of executive function and attention in gait. Mov Disord. 2008;23(3):329–42 quiz 472.
Vu LN, Dean MJ, Mwamburi M, Au R, Qiu WQ. Executive function and mortality in homebound elderly adults. J Am Geriatr Soc. 2013;61(12):2128–34.
Gothe NP, Fanning J, Awick E, Chung D, Wójcicki TR, Olson EA, et al. Executive function processes predict mobility outcomes in older adults. J Am Geriatr Soc. 2014;62(2):285–90.
Herman T, Mirelman A, Giladi N, Schweiger A, Hausdorff JM. Executive control deficits as a prodrome to falls in healthy older adults: A prospective study linking thinking, walking, and falling. J Gerontol A Biol Sci Med Sci. 2010;65 A(10):1086–92.
Verghese J, Lipton RB, Hall CB, Kuslansky G, Katz MJ, Buschke H. Abnormality of gait as a predictor of non-Alzheimer ’ S dementia. N Engl J Med. 2002;347(22):1761–8.
Sahyoun C, Floyer-Lea A, Johansen-Berg H, Matthews PM. Towards an understanding of gait control: brain activation during the anticipation, preparation and execution of foot movements. Neuroimage. 2004;21(2):568–75.
Jahn K, Deutschländer A, Stephan T, Strupp M, Wiesmann M, Brandt T. Brain activation patterns during imagined stance and locomotion in functional magnetic resonance imaging. Neuroimage. 2004;22(4):1722–31.
ten Harmsen BL, van Rumund A, Aerts MB, Bergkamp MI, Esselink RAJ, Richard E, et al. Clinical correlates of cerebral white matter abnormalities in patients with Parkinson’s disease. Park Relat Disord. 2018;49:28–33.
Ebersbach G, Sojer M, Müller J, Ransmayr G, Wenning G, Poewe W. Gleichgewichtsstörungen bei idiopathischer Parkinson-erkrankung: Der einfluss zerebrovaskulärer komorbidität. Nervenarzt. 2002;73(2):162–5.
Ciliz M, Sartor J, Lindig T, Pilotto A, Schäffer E, Weiss M, Scheltens P, Becker S, Hobert MA, Berg D, Liepelt-Scarfone I, Maetzler W. Brain-area specific white matter hyperintensities: Associations to falls in Parkinson’s disease. J Park Dis. 2018;8(3):455–62.
Cesari M, Vellas B, Hsu FC, Newman AB, Doss H, King AC, et al. A physical activity intervention to treat the frailty syndrome in older persons - results from the LIFE-P study. J Gerontol Ser A Biol Sci Med Sci. 2015;70(2):216–22.
Buchman AS, Schneider JA, Leurgans S, Bennett DA. Physical frailty in older persons is associated with Alzheimer disease pathology. Neurol. 2008;71(7):499–504.
Maetzler W, Klucken J, Horne M. A clinical view on the development of technology-based tools in managing Parkinson’s disease. Mov Disord. 2016;31(9):1263–71.
Dorsey ER, Glidden AM, Holloway MR, Birbeck GL, Schwamm LH. Teleneurology and mobile technologies: the future of neurological care. Nat Rev Neurol. 2018 Apr;14(5):285–97.
Austen K. What could derail the wearables revolution? Nat News. 2015;525(7567):22.
Gravitz L. Technology: monitoring gets personal. Nat. 2016;538(7626):S8–10.
Maetzler W, Grond M, AH J. No Title. In: Neurologie. Berlin Heidelber: Springer; 2016. p. 959–70.
Sieber CC. The elderly patient - who is that? Internist (Berl). 2007;48(1190):1192–4.
Johnston MC, Crilly M, Black C, Prescott GJ, Mercer SW. Defining and measuring multimorbidity: a systematic review of systematic reviews. Eur J Pub Health. 2018;29(1):182–9.
Lawton M, Kasten M, May MT, Mollenhauer B, Schaumburg M, Liepelt-Scarfone I, et al. Validation of conversion between mini-mental state examination and Montreal cognitive assessment. Mov Disord. 2016;31(4):593–6.
Nasreddine Z, Charbonneau S, Cummings JL. The Montreal cognitive assessment, MoCA: a brief screening tool for mild cognitive impairment. J Am Geriatr Soc. 2005;53(4):695–9.
Ashmore J, Russo R, Peoples J, Sloan J, Jackson BE, Bae S, et al. Chronic obstructive pulmonary disease self-management activation research trial (COPD-SMART): design and methods. Contemp Clin Trials. 2013;35(2):77–86.
World Health Organisation. International classification of functioning, Disability and Health. Geneva: ICF; 2001.
Katz S, Ford AB, Maskowitz RW, et al. Studies of illness in the aged. The index of ADL: a standardized measure of biological and psychological function. JAMA. 1963;185:914–9.
Lawton MP, Brody EM. Assessment of older people: self-maintaining and instrumental activities of daily living. Gerontolog. 1969;9:179–86.
Bellmann JK, Bleich SB-W, Doufrain MK-B gGmbH;, Al. E. Identifikation des geriatrischen Patienten. 2013.
Hobert M. Validierung des Geriatrie-Checks in einer Kohorte von stationären neurologischen. Z Gerontol Geriatr. 2019;52(2):172–78.
Lachs MS, Feinstein AR, Cooney LM, Drickamer MA, Marottoli RA, Pannill FC, et al. A simple procedure for general screening for functional disability in elderly patients. Ann Intern Med. 1990;112(9):699–706.
Heuschmann PU, Kolominsky-Rabas PL, Nolte CH, Hünermund G, Ruf HU, Laumeier I, et al. Untersuchung der reliabilität der Deutschen version des Barthel-Index sowie entwicklung einer postalischen und telefonischen fassung für den einsatz bei schlaganfall-patienten. Fortschritte der Neurol Psychiatr. 2005;73(2):74–82.
Lübke N, Meinck M. von Renteln–Kruse W. Der Barthel–Index in der Geriatrie. Eine Kontextanalyse zum Hamburger Einstufungsmanual. Z Gerontol Geriatr. 2004;37(4):316–26.
Busner J, Targum SD. The clinical global impressions scale: applying a research tool in clinical practice. Psychiatry (Edgmont). 2007;4(7):28–37.
Santangelo G, Siciliano M, Pedone R, Vitale C, Falco F, Bisogno R, et al. Normative data for the Montreal cognitive assessment in an Italian population sample. Neurol Sci. 2015;36(4):585–91.
Freitas S, Simões MR, Alves L, Santana I. Montreal cognitive assessment (MoCA): normative study for the Portuguese population. J Clin Exp Neuropsychol. 2011;33(9):989–96.
Pinto TCC, Machado L, Bulgacov TM, Rodrigues-Júnior AL, Costa MLG, Ximenes RCC, et al. Influence of age and education on the performance of elderly in the Brazilian version of the Montreal cognitive assessment battery. Dement Geriatr Cogn Disord. 2018;45(5–6):290–9.
Benke T, Karner E, Delazer M. FAB-D: German version of the frontal assessment battery. J Neurol. 2013;260(8):2066–72.
Beato RG, Nitrini R, Formigoni AP, Caramelli P, Beato RG, Nitrini R, et al. Brazilian version of the frontal assessment battery (FAB): preliminary data on administration to healthy elderly. Dement Neuropsychol. 2007;1(1):59–65.
Appollonio I, Leone M, Isella V, Piamarta F, Consoli T, Villa ML, et al. The frontal assessment battery (FAB): normative values in an Italian population sample. Neurol Sci. 2005;26(2):108–16.
Strauss E, Sherman E, Spreen O. Trail making Test (TMT). In: Strauss E, Sherman E, Spreen O, editors. A compendium of neuropsychological tests administration, norms and commentary. 3rd ed. Oxford: Oxford University Press; 2006. p. 655–77.
Sánchez-Cubillo I, Periáñez JA, Adrover-Roig D, Rodríguez-Sánchez JM, Ríos-Lago M, Tirapu J, et al. Construct validity of the trail making Test: role of task-switching, working memory, inhibition/interference control, and visuomotor abilities. J Int Neuropsychol Soc. 2009;15(3):438–50.
Tombaugh TN. Trail making Test a and B: normative data stratified by age and education. Arch Clin Neuropsychol. 2004;19(2):203–14.
Amodio P, Wenin H, Del Piccolo F, Mapelli D, Montagnese S, Pellegrini A, et al. Variability of trail making Test, symbol digit Test and line trait Test in normal people. A normative study taking into account age-dependent decline and sociobiological variables. Aging Clin Exp Res. 2002;14(2):117–31.
Hamdan AC, Hamdan EMLR. Effects of age and education level on the trail making Test in a healthy Brazilian sample. Psychol Neurosci. 2009l;2(2):199–203.
Cavaco S, Goncalves A, Pinto C, Almeida E, Gomes F, Moreira I, et al. Trail making Test: regression-based norms for the Portuguese population. Arch Clin Neuropsychol. 2013;28(2):189–98.
Zimmermann P, Fimm B. Testbatterie zur Aufmerksamkeitsprüfung. Version 2.3. Psychologische Testsysteme; 2012.
Gatterer G. Alters-Konzentrations-Test. 2., überarbeitete und neu normierte Auflage. Göttingen: Hogrefe; 2007.
Morgenstern U, Ketelhut K, Rösler D. Konzentrationssteigerung zum Erhalt der Alltagskompetenz bei Demenz. Z Gerontol Geriatr. 2017;50(1):28–34.
Goebel S, Fischer R, Ferstl R, Mehdorn HM. Normative data and psychometric properties for qualitative and quantitative scoring criteria of the five-point Test. Clin Neuropsychol. 2009;23(4):675–90.
Aschenbrenner A, Tucha O, Lange K. Regensburger Wortflüssigkeitstest (RWT): Handanweisung. Göttingen: Hogrefe; 2000.
Oswald WD, Fleischmann UM. Nürnberger-Alter-Inventar NAI. 4.Auflage. Göttingen: Hogrefe; 1997.
Guralnik JM, Simonsick EM, Ferrucci L, Glynn RJ, Berkman LF, Blazer DG, et al. A short physical performance battery assessing lower extremity function: association with self-reported disability and prediction of mortality and nursing home admission. J Gerontol. 1994;49(2):M85–94.
da S PL, de L BL, da S MVRF, MMF G, Bachion MM, RL de M. Fatores associados a quedas em idosos com catarata. Cien Saude Colet. 2018;23(8):2503–14.
Vasunilashorn S, Coppin AK, Patel KV, Lauretani F, Ferrucci L, Bandinelli S, et al. Use of the short physical performance battery score to predict loss of ability to walk 400 meters: analysis from the InCHIANTI study. J Gerontol Ser A Biol Sci Med Sci. 2009;64A(2):223–9.
Freire AN, Guerra RO, Alvarado B, Guralnik JM, Zunzunegui MV. Validity and reliability of the short physical performance battery in two diverse older adult populations in Quebec and Brazil. J Aging Health. 2012;24(5):863–78.
Lin C-C, Roche JL, Steed DP, Musolino MC, Marchetti GF, Furman GR, et al. Test-retest reliability of postural stability on two different foam pads. J Nat Sci. 2015;1(2):e43.
Weiss A, Herman T, Plotnik M, Brozgol M, Maidan I, Giladi N, et al. Can an accelerometer enhance the utility of the timed up & go Test when evaluating patients with Parkinson’s disease? Med Eng Phys. 2010;32(2):119–25.
Al-Jawad A, Adame MR, Romanovas M, Hobert M, Maetzler W, Traechtler M, et al. Using multi-dimensional dynamic time warping for TUG test instrumentation with inertial sensors. IEEE Int Conf Multisens Fusion Integr Intell Syst. 2012;(September 2014):212–8.
Varalta V, Picelli A, Fonte C, Amato S, Melotti C, Zatezalo V, et al. Relationship between cognitive performance and motor dysfunction in patients with Parkinson’s disease: a pilot cross-sectional study. Biomed Res Int. 2015;2015:1–6.
Hobert MA, Niebler R, Meyer SI, Brockmann K, Becker C, Huber H, et al. Poor trail making test performance is directly associated with altered dual task prioritization in the elderly - baseline results from the trend study. PLoS One. 2011;6(11):e27831.
Salkovic D, Hobert MA, Bellut C, Funer F, Renno S, Haertner L, et al. Evidence for a Selectively Regulated Prioritization Shift Depending on Walking Situations in Older Adults. Front Aging Neurosci. 2017;9(APR).
Hobert MA, Meyer SI, Hasmann SE, Metzger FG, Suenkel U, Eschweiler GW, et al. Gait is associated with cognitive flexibility: A dual-tasking study in healthy older people. Front Aging Neurosci. 2017;9(MAY).
Duncan PW, Weiner DK, Chandler J, Studenski S. Functional reach: a new clinical measure of balance. J Gerontol. 1990;45(6):M192–7.
Hasmann SE, Berg D, Hobert MA, Weiss D, Lindemann U, Streffer J, et al. Instrumented functional reach Test differentiates individuals at high risk for Parkinsonâ€™s disease from controls. Front Aging Neurosci. 2014;6:286.
Goetz CG, Tilley BC, Shaftman SR, Stebbins GT, Fahn S, Martinez-Martin P, et al. Movement Disorder Society-sponsored revision of the unified Parkinson’s disease rating scale (MDS-UPDRS): scale presentation and clinimetric testing results. Mov Disord. 2008;23(15):2129–70.
Hoehn MM, Yahr MD. Parkinsonism: onset, progression and mortality. Neurol. 1967;17:427–42.
Delbaere K, Close JCT, Mikolaizak AS, Sachdev PS, Brodaty H, Lord SR. The falls efficacy scale international (FES-I). A comprehensive longitudinal validation study. Age Ageing. 2010;39(2):210–6.
Aaron DH, Stegink Jansen CW. Development of the functional dexterity Test (FDT): construction, validity, reliability, and normative data. J Hand Ther. 2003;16(1):12–21.
Krupp S, Kasper J, Balck F, Schnoor M, Eisemann N, Lohse K, et al. “Timed up and go” für die Finger in Form des 20-Cents-Tests. Z Gerontol Geriatr. 2015;48(2):121–7.
Wood-Dauphinee S. Assessing quality of life in clinical research: from where have we come and where are we going? J Clin Epidemiol. 1999;52(4):355–63.
Deuschl G, Schade-Brittinger C, Krack P, Volkmann J, Schäfer H, Bötzel K, et al. A randomized trial of deep-brain stimulation for Parkinson’s disease. N Engl J Med. 2006;355(9):896–908.
Herdman M, Gudex C, Lloyd A, Janssen M, Kind P, Parkin D, et al. Development and preliminary testing of the new five-level version of EQ-5D (EQ-5D-5L). Qual Life Res. 2011;20(10):1727–36.
Heidenblut S, Zank S. Entwicklung eines neuen Depressionsscreenings f??r den Einsatz in der Geriatrie: Die “Depression-im-Alter-Skala” (DIA-S). Z Gerontol Geriatr. 2010;43(3):170–6.
Montgomery SA, Asberg M. A new depression scale designed to be sensitive to change. Br J Psychiatry. 1979;134(4):382–9.
Lueken U, Seidl U, Schwarz M, Völker L, Naumann D, Mattes K, et al. Die apathy evaluation scale: Erste ergebnisse zu den psychometrischen eigenschaften einer Deutschsprachigen übersetzung der skala. Fortschritte der Neurol Psychiatr. 2006;74(12):714–22.
Craig CL, Marshall AL, Sjöström M, Bauman AE, Booth ML, Ainsworth BE, et al. International physical activity questionnaire: 12-country reliability and validity. Med Sci Sports Exerc. 2003;35(8):1381–95.
Freynhagen R, Baron R, Gockel U, Tölle TR. Pain DETECT : a new screening questionnaire to identify neuropathic components in patients with back pain. Curr Med Res Opin. 2006;22(10):1911–20.
Roberts HC, Denison HJ, Martin HJ, Patel HP, Syddall H, Cooper C, et al. A review of the measurement of grip strength in clinical and epidemiological studies: towards a standardised approach. Age Ageing. 2011;40(4):423–9.
Janssen I, Heymsfield S, Baumgartner R, Ross R. Estimation of skeletal muscle mass by bioelectrical impedance analysis. J Appl Physiol. 2000;89:465–71.
Drey M, Hasmann SE, Krenovsky JP, Hobert MA, Straub S, Elshehabi M, et al. Associations between early markers of Parkinson’s disease and sarcopenia. Front Aging Neurosci. 2017;9(MAR).
Reimers C, Mersch S, Müller-Nothmann S-D. Die Bioelektrische Impedanzanalyse (BIA). Methoden zur Messung der Körperkompartimente in der Ernährungsmedizin. Schweizerische Zeitschrift für Ganzheitsmedizin / Swiss J Integr Med. 2005;17(6):355–61.
Maetzler W, Drey M, Jacobs AH. Sarkopenie und Frailty in der Neurologie. Nervenarzt. 2015;86(4):420–30.
Cruz-Jentoft AJ, Bahat G, Bauer J, Boirie Y, Bruyère O, Cederholm T, et al. Sarcopenia: revised European consensus on definition and diagnosis. Age Ageing. 2019;13.
Díaz de León González E, Gutiérrez Hermosillo H, Martinez Beltran JA, JHM C, Palacios Corona R, Salinas Garza DP, et al. Validation of the FRAIL scale in Mexican elderly: results from the Mexican health and aging study. Aging Clin Exp Res. 2016;28(5):901–8.
Theou O, Brothers TD, Mitnitski A, Rockwood K. Operationalization of frailty using eight commonly used scales and comparison of their ability to predict all-cause mortality. J Am Geriatr Soc. 2013;61(9):1537–51.
Woo J, Yu R, Wong M, Yeung F, Wong M, Lum C. Frailty screening in the community using the FRAIL scale. J Am Med Dir Assoc. 2015;16(5):412–9.
Manor Y, Giladi N, Cohen A, Fliss DM, Cohen JT. Validation of a swallowing disturbance questionnaire for detecting dysphagia in patients with Parkinson’s disease. Mov Disord. 2007;22(13):1917–21.
Vellas B, Guigoz Y, Garry PJ, Nourhashemi F, Bennahum D, Lauque S, et al. The mini nutritional assessment (MNA) and its use in grading the nutritional state of elderly patients. Nutr. 1999;15(2):116–22.
Elia M. The “MUST” report. Nutritional screening for adults: a multidisciplinary responsibility. Development and use of the “Malnutrition Universal Screening Tool” (MUST) for adults: British Association for Parenteral and Enteral Nutrition (BAPEN); 2003.
a S D, JR ML, Baker JP, Johnston N, Whittaker S, R a M, et al. What is subjective global assessment of nutritional status? JPEN J Parenter Enteral Nutr. 1987;11(1):8–13.
Ziegler D, Laux G, Dannehl K, Spüler M, Mühlen H, Mayer P, et al. Assessment of cardiovascular autonomic function: age-related normal ranges and reproducibility of spectral analysis, vector analysis, and standard tests of heart rate variation and blood pressure responses. Diabet Med. 1992 Mar;9(2):166–75.
Schatz IJ, Bannister R, Freeman RL, Jankovic J, Koller WC, Low, PA, et al. Consensus statement on the definition of orthostatic hypotension, pure autonomic failure, and multiple system atrophy. J Neurol Sci. 1996;144(1–2):218–9.
Park YH, Ku JH, Oh SJ. Accuracy of post-void residual urine volume measurement using a portable ultrasound bladder scanner with real-time pre-scan imaging. Neurourol Urodyn. 2011;30(3):335–8.
Costa P, Perrouin-Verbe B, Colvez A, Didier J, Marquis P, Marrel A, et al. quality of life in spinal cord injury patients with urinary difficulties. Development and validation of qualiveen. Eur Urol. 2001;39(1):107–13.
Berner MM, Kriston L, Zahradnik HP, Härter M, Rohde A. Überprüfung der Gültigkeit und Zuverlässigkeit des Deutschen Female Sexual Function Index (FSFI-d). Geburtshilfe Frauenheilkd. 2004;64(3):293–303.
Rosen RC, Riley A, Wagner G, Osterloh IH, Kirkpatrick J, Mishra A. The international index of erectile function (IIEF): a multidimensional scale for assessment of erectile dysfunction. Urol. 1997;49(6):822–30.
Wiltink J, Hauck EW, Phädayanon M, Weidner W, Beutel ME. Validation of the German version of the international index of erectile function (IIEF) in patients with erectile dysfunction, Peyronie’s disease and controls. Int J Impot Res. 2003;15(3):192–7.
Richter G, Krawczak M, Lieb W, Wolff L, Schreiber S, Buyx A. Broad consent for health care-embedded biobanking: understanding and reasons to donate in a large patient sample. Genet Med. 2018;20(1):76–82.
Fazekas F, Chawluk JB, Alavi A, Hurtig HI, Zimmerman RA. Mr signal abnormalities at 1.5-T in Alzheimer dementia and Normal aging. Am J Roentgenol. 1987;149(2):351–6.
Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)-a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009;42(2):377–81.
Weir JP. Quantifying test-retest reliability using the intraclass correlation coefficient and the SEM. J Strength Cond Res. 2005 Feb;19(1):231–40.
Kolb G, Breuninger K, Gronemeyer S, van den Heuvel D, Lübke N, Lüttje D, et al. 10 Jahre geriatrische frührehabilitative Komplexbehandlung im DRG-System. Z Gerontol Geriatr. 2014;47(1):6–12.
Swoboda W, Sieber CC. Rehabilitation in der Geriatrie. Internist. 2010;51(10):1254–61.
Elf M, Flink M, Nilsson M, Tistad M, Von Koch L, Ytterberg C. The case of value-based healthcare for people living with complex long-term conditions. BMC Health Serv Res. 2017;17(1):1–6.
Porter ME. A strategy for health care reform — toward a value-based system. N Engl J Med. 2009;361(2):109–12.
Mirnezami R, Nicholson J, Darzi A. Preparing for precision medicine. N Engl J Med. 2012;366(6):489–91.
Barry MJ, Edgman-Levitan S. Shared decision making — the pinnacle of patient-centered care. N Engl J Med. 2012;366(9):780–1.
Pham MH, Elshehabi M, Haertner L, Heger T, Hobert MA, Faber GS, et al. Algorithm for turning detection and analysis validated under home-like conditions in patients with Parkinson’s disease and older adults using a 6 degree-of-freedom inertial measurement unit at the lower Back. Front Neurol. 2017;8:135.
Pham MH, Elshehabi M, Haertner L, Del Din S, Srulijes K, Heger T, et al. Validation of a step detection algorithm during straight walking and turning in patients with Parkinson’s disease and older adults using an inertial measurement unit at the lower Back. Front Neurol. 2017;8:457.
Del Din S, Godfrey A, Rochester L. Validation of an accelerometer to quantify a comprehensive battery of gait characteristics in healthy older adults and Parkinson’s disease: toward clinical and at home use. IEEE J Biomed Heal Informatics. 2016;20(3):838–47.
Ramsperger R, Meckler S, Heger T, van Uem J, Hucker S, Braatz U, et al. Continuous leg dyskinesia assessment in Parkinson’s disease -clinical validity and ecological effect. Park Relat Disord. 2016;26:41–6.
Haertner L, Elshehabi M, Zaunbrecher L, Pham MH, Maetzler C, van Uem JMT, et al. Effect of fear of falling on turning performance in Parkinson’s disease in the lab and at home. Front Aging Neurosci. 2018;10(MAR).
Artusi CA, Mishra M, Latimer P, Vizcarra JA, Lopiano L, Maetzler W, et al. Integration of technology-based outcome measures in clinical trials of Parkinson and other neurodegenerative diseases. Park Relat Disord. 2018;46:S53–6.
van Lummel RC, Walgaard S, Pijnappels M, Elders PJM, Garcia-Aymerich J, van Dieën JH, et al. Physical performance and physical activity in older adults: associated but separate domains of physical function in old age. PLoS One. 2015;10(12):e0144048.
JoGe, SM, ME, CH, and WM made substantial contributions to the conception and design of all parts of the study, trained and supervised the examiners of all centers, and were responsible for acquisition, analysis and interpretation of data and in drafting as well as revising the manuscript. AnPi, MCR, BB, AlPa made substantial contributions to the conception and design for their center in Brescia (Italy) and were responsible for acquisition, analysis and interpretation of data. AnPi also revised the manuscript critically for important intellectual content. LFM, NV-C and MFC made substantial contributions to the conception and design for their center in Porto (Portugal), were responsible for acquisition, analysis and interpretation of data and revised the manuscript critically for important intellectual content. MM and IB made substantial contributions to the conception and design for their center in Curitiba (Brazil), were responsible for acquisition, analysis and interpretation of data and revised the manuscript critically for important intellectual content. LT and AM made substantial contributions to the conception and design for their center in Bochum (Germany), were responsible for acquisition, analysis and interpretation of data and revised the manuscript critically for important intellectual content. CM and OG were responsible for the implementation of the database and organization of data. MH JSB, SP, and MW made substantial contributions to the conception and design regarding clinical data for their involved Department of Neurology in Kiel (Germany) and revised the manuscript critically for important intellectual content. MW and OG, together with CR, MK and EMS, were also involved in the design, acquisition, analysis and interpretation of MRI data in the center of Kiel. MK, EMS as well as, MKH, LK, JK, CTO, FR, AW, KN, LMB and SF were also involved in acquisition, analysis and interpretation of data (demographical, neuropsychological and motoric test data) in the center of Kiel. CTO was also involved in the acquisition, analysis and interpretation of the data from T1 and T0 for validation purposes. LMB and SF were also involved in the acquisition, analysis and interpretation of the home assessment data. Together with AndFra, CB, GK and FL, KN also made substantial contributions to the conception and design regarding the biofluid data and were involved in the acquisition, analysis and interpretation of these data in the center of Kiel (Germany). AA, MR and SiSa were involved in acquisition and interpretation of medical data for their involved Department of Neurology in Kiel. CG, MD, TW and KK made substantial contributions to the conception and design regarding data for sarcopenia, frailty and nutrition for the center of Kiel and revised the manuscript critically for important intellectual content. KK was also involved in the acquisition, analysis and interpretation of these data in the center of Kiel.RB, PH and JaGe made substantial contributions to the conception and design for autonomic dysfunction (blood pressure, pain) data and revised the manuscript critically for important intellectual content. StK made substantial contributions to the conception and design for autonomic dysfunction (urinal aspects) data. All of them were involved in the acquisition, analysis and interpretation of these data in the center of Kiel. PB made substantial contributions to the conception and design regarding clinical data for his participating Department for Internal Medicine in Kiel (Germany). He was also involved in acquisition and interpretation of this data, and revised the manuscript critically for important intellectual content. TP made substantial contributions to the conception and design for clinical data for his participating Department for Cardiac and Vascular Surgery in Kiel and revised the manuscript critically for important intellectual content. Together with LS he was also involved in acquisition, analysis and interpretation of these data. MT, SU and BJ made substantial contributions to the conception and design for their participating Departments at the Städtisches Krankenhaus Kiel in Kiel (Germany) and revised the manuscript critically for important intellectual content. BJ was also responsible for the acquisition, analysis and interpretation of these data. SoKr made substantial contributions to the conception and design regarding the fine motoric tests, was involved in analysis and interpretation of this data and revised the manuscript critically for important intellectual content. MH and AS were involved in the conceptualization of the sensor-based motoric assessment, programming of the assessment application for this assessment and gave technical and IT-support. MHP and EW were involved in development of algorithms for the sensor-based data and in analyzing and interpreting these data. SH and AnjFr made substantial contributions to the statistical design analyses and were involved in analysis and interpretation of the study data. JW was substantially involved in the quality check, statistical analysis and interpretation of the study data and revised the manuscript critically for important intellectual content. MS was involved in organizing the data was well as in drafting and revising the manuscript. DB, TB, RK, SiSt, RB-M, JJF, PPU, PN made substantial contributions to the conception and design of the study and revised the manuscript critically for important intellectual content. All authors have given their final approval of the version to be published. Each author has participated sufficiently in the work and takes public responsibility for appropriate portions of the content and agrees to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. All authors read and approved the final manuscript.
The study does not receive any external funding.
Ethics approval and consent to participate
Ethical approval has been obtained from the ethical committee of Kiel (reference number: D427/17), Bochum (reference number: 19–6659-MPG), Brescia (reference number: NP 1471), Porto (reference number: 2018.087 (076-DEFI/076-CES)) and Curibitia (reference number: 2–686.426). In Bochum, the protocol of this study is implemented in the larger Project “Automatisierte Erfassung von Bewegungsprofilen bei Patienten mit Parkinson Syndromen (PARK-MOVE study)”. In Brescia, the protocol of this study is implemented in the larger Project “Clinical studies of adult movement disorders- DMA study”. In Porto, the protocol of this study is implemented in the larger Project “Keep Control - How does peripheral neuropathy relevantly influences gait and balance in PD”. The centres have submitted their proposals according to the principles of the Declaration of Helsinki. All participants will receive detailed oral and written information about the content and procedure of the study. Verbal and written consent of participation has to be granted by all participants.
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Geritz, J., Maetzold, S., Steffen, M. et al. Motor, cognitive and mobility deficits in 1000 geriatric patients: protocol of a quantitative observational study before and after routine clinical geriatric treatment – the ComOn-study. BMC Geriatr 20, 45 (2020). https://doi.org/10.1186/s12877-020-1445-z
- Body-worn sensors
- Comprehensive geriatric assessment
- Executive function
- Older adults
- Quantitative assessment