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Unravelling the potential mechanisms behind hospitalization-associated disability in older patients; the Hospital-Associated Disability and impact on daily Life (Hospital-ADL) cohort study protocol

  • Lucienne A. Reichardt1,
  • Jesse J. Aarden2, 3,
  • Rosanne van Seben1,
  • Marike van der Schaaf2, 3,
  • Raoul H. H. Engelbert2, 3,
  • Jos A. Bosch4,
  • Bianca M. Buurman1, 3Email author and
  • on behalf of the Hospital-ADL study group
BMC GeriatricsBMC series – open, inclusive and trusted201616:59

https://doi.org/10.1186/s12877-016-0232-3

Received: 5 October 2015

Accepted: 25 February 2016

Published: 5 March 2016

Abstract

Background

Over 30 % of older patients experience hospitalization-associated disability (HAD) (i.e., loss of independence in Activities of Daily Living (ADLs)) after an acute hospitalization. Despite its high prevalence, the mechanisms that underlie HAD remain elusive. This paper describes the protocol for the Hospital-Associated Disability and impact on daily Life (Hospital-ADL) study, which aims to unravel the potential mechanisms behind HAD from admission to three months post-discharge.

Methods/design

The Hospital-ADL study is a multicenter, observational, prospective cohort study aiming to recruit 400 patients aged ≥70 years that are acutely hospitalized at departments of Internal Medicine, Cardiology or Geriatrics, involving six hospitals in the Netherlands. Eligible are patients hospitalized for at least 48 h, without major cognitive impairment (Mini Mental State Examination score ≥15), who have a life expectancy of more than three months, and without disablement in all six ADLs. The study will assess possible cognitive, behavioral, psychosocial, physical, and biological factors of HAD. Data will be collected through: 1] medical and demographical data; 2] personal interviews, which includes assessment of cognitive impairment, behavioral and psychosocial functioning, physical functioning, and health care utilization; 3] physical performance tests, which includes gait speed, hand grip strength, balance, bioelectrical impedance analysis (BIA), and an activity tracker (Fitbit Flex), and; 4] analyses of blood samples to assess inflammatory and metabolic markers. The primary endpoint is additional disabilities in ADLs three months post-hospital discharge compared to ADL function two weeks prior to hospital admission. Secondary outcomes are health care utilization, health-related quality of life (HRQoL), physical performance tests, and mortality. There will be at least five data collection points; within 48 h after admission (H1), at discharge (H3), and at one (P1; home visit), two (P2; by telephone) and three months (P3; home visit) post-discharge. If the patient is admitted for more than five days, additional measurements will be planned during hospitalization on Monday, Wednesday, and Friday (H2).

Discussion

The Hospital-ADL study will provide information on cognitive, behavioral, psychosocial, physical, and biological factors associated with HAD and will be collected during and following hospitalization. These data may inform new interventions to prevent or restore hospitalization-associated disability.

Keywords

Acute hospitalization Hospitalization-associated disability Functional decline Older patients

Background

Studies have observed that at least 30 % of older patients hospitalized with an acute medical illness show a persistent decline in their ability to maintain Activities of Daily Living (ADLs) [15]. Such activities are prerequisites to self-care and independent living and include bathing, dressing, transferring out of bed, eating, toileting, and being mobile in and around the house. [1, 37]. This decline has been denoted hospitalization-associated disability (HAD), and is defined as the loss of ability to perform one or more of the basic ADLs [6].

HAD is an important problem; it is the leading cause of loss of independence at older age [4] and it is a complex and highly dynamic process with possible recurrent disability episodes in older patients [6, 8]. Research shows that older persons who have been hospitalized have a 60-fold increased risk to develop permanent disabilities [9]. The first month after hospital discharge has been identified as a critical period for recovery, after which disabilities have a high risk of becoming permanent [3]. Moreover, patients with new disabilities are at high risk for other adverse outcomes within three months post discharge: 20 % have readmissions [10], and post-discharge mortality is 25 % [1, 3, 11, 12]. In light of the high prevalence in older patients, and the rapid aging of western societies with a concomitant rise in hospitalizations, a better understanding of HAD is urgently needed.

Previous research has been able to identify a number of generic risk factors for hospitalization-associated disability such as older age [5], the severity of acute illness, geriatric conditions, cognitive impairment and delirium [1, 6, 13, 14]. However, a more fine-grained analyses and characterization of potentially modifiable risk factors is virtually absent from the literature. Little is known, for example, about: 1] the course of loss of muscle mass and strength, and the amount of physical activity older patients perform; 2] the association of cognitive, (psycho-)somatic, behavioral, and psychological restrictive symptoms with the onset and recovery from HAD within the critical period of three months post-discharge such as cognitive impairment, fatigue, pain, sleep quality, shortness of breath, dizziness, fear of falling, diminished self-efficacy, apathy, depression, and anxiety and; 3] the association of the inflammatory activity and related sickness behaviors with the onset and recovery from HAD. Moreover, most previous studies have utilized relatively long follow-up intervals (e.g., from admission to three months or more) [13, 15]. Thus information is lacking on events and processes that take place during the weeks after discharge, which are thought to be critical to recovery.

The current study – Hospital-Associated Disability and impact on daily Life (Hospital-ADL study) – aims to investigate cognitive, behavioral, psychosocial, physical, and biological factors that may be associated with HAD in acutely hospitalized older adults, performing frequent assessments to capture their dynamic development from hospital admission to three months post-discharge. This overall aim can be separated into the following five subordinate aims:
  1. (1)

    To study the temporal profile of HAD (i.e., loss of ADL) from hospitalization to three months post-discharge.

     
  2. (2)

    To investigate the course of physical functions that are essential to support ADL, such as muscle mass, muscle strength, and physical performance and spontaneous activity, and test its predictive value for the onset and recovery from HAD, health care utilization, and health-related quality of life (HRQoL) at three months post-discharge.

     
  3. (3)

    To study the prevalence, incidence and course of cognitive, (psycho-)somatic, behavioral, and psychological problems older patients experience from hospitalization up to three months post-discharge that might be restrictive in recovery from HAD post-discharge such as cognitive impairment, fatigue, pain, sleep quality, shortness of breath, dizziness, fear of falling, diminished self-efficacy, apathy, depression, and anxiety.

     
  4. (4)

    To study the association of aforementioned symptoms with HAD, health care utilization, and HRQoL.

     
  5. (5)

    To study the association of metabolic and proinflammatory factors, and physical and behavioral concomitants (e.g., sickness behaviors, loss of muscle mass) with the onset of and recovery from HAD, health care utilization, and HRQoL.

     

Methods/Design

Study design and setting

The Hospital-ADL study is a multicenter, observational, prospective cohort study designed by an interdisciplinary team of researchers in the field of geriatrics, nursing, psychology, physical therapy and rehabilitation. Six hospitals will participate: 1] the Academic Medical Center in Amsterdam (AMC), a 1002-bed university teaching hospital; 2] the Isala in Zwolle, a 994-bed regional teaching hospital; 3] the Tergooi in Blaricum, a regional teaching hospital (633-bed spread over two sites: Hilversum and Blaricum); 4] the Slotervaart Hospital in Amsterdam, a 310-bed regional teaching hospital; 5] the BovenIJ Hospital in Amsterdam, a 313-bed regional teaching hospital, and; 6] the Meander Medical Center in Amersfoort, a 543-bed regional teaching hospital. The study has started October 1, 2015 and will end after the last patient has been followed up for three months post-discharge. We expect the recruitment phase to be completed late 2016.

Patients

We aim to recruit 400 non-fully disabled adults aged ≥70 years. The following inclusion criteria apply: 1] acutely admitted at departments of Internal Medicine, Cardiology or Geriatrics for 48 h or more in one of the above mentioned hospitals; 2] 70 years and older; 3] have approval from the attending Medical Doctor for inclusion; 4] score of 15 or higher on the Mini-Mental State Examination; 5] Dutch language proficiency sufficient to complete questionnaires. Patients will be excluded if they: 1] have a life expectancy of three months or less as assessed by the attending Medical Doctor, or; 2] are disabled in all six basic ADL as determined by the Katz-ADL index [16].

Procedures

Eligible patients will be contacted, and the patient will be informed about the objectives of this study and the study procedures, upon which written informed consent is obtained. Furthermore, a legal representative of the patient will be contacted if the patient has a MMSE score between 15 and 20. Two mobile geriatric assessment teams will visit all six hospitals and will be present on Monday, Wednesday and Friday for consenting and to perform assessments. The mobile geriatric assessment teams consist of a psychologist, physical therapist, and/or a health scientist. The teams are trained in the study procedures of obtaining informed consent, to perform assessments and physical performance tests with adequate inter- and intra-rater reliability (>0.8), and completing the electronic case report form (eCRF).

Table 1 provides an overview of the location, content of assessment and duration of data collection per time point. There will be at least five data collection points; within 48 h after admission (H1), at discharge (H3), and at one (P1; home visit), two (P2; by telephone) and three months (P3; home visit) post-discharge. If the patient is admitted for more than five days, additional measurements will be planned during hospitalization on Monday, Wednesday, and Friday (i.e., the days that the mobile geriatric assessment team is present) (H2),
Table 1

Time, location, content of assessment and duration of the Hospital-ADL study

Time

Location

Content of assessment

Duration (minutes)

H1 (Within 48 h after admission)

Hospital

Medical & demographical data

60

 Socio-demographic characteristics

 Medical comorbidity

 Geriatric conditions

 Severity of acute illness (medical record)

Personal interview/self-report data

 Cognitive functioning

 ADL/physical functioning

 Behavioral & psychosocial functioning

 Health care utilization (medical record)

 Physical performance tests

Blood parameters

H2 (During hospital stay on Monday-Wednesday-Friday)

Hospital

Medical & demographical data

20–30

 Severity of acute illness (medical record)

Short personal interview/self-report data

Physical performance tests

Blood parameters

H3 (At hospital discharge)

Hospital

Personal interview/self-report data

40

 Cognitive functioning

 ADL/Physical functioning

 Behavioral and psychosocial functioning

Physical performance tests

Blood parameters

P1 (One month post-discharge)

Home visit

Medical & demographical data

60

 Socio-demographic characteristics

 Geriatric conditions

Personal interview/self-report data

 Cognitive functioning

 ADL/physical functioning

 Behavioral & psychosocial functioning

 Health care utilization

Physical performance tests

P2 (Two months post-discharge)

By telephone

Personal interview/self-report data

20

 ADL/physical functioning

 Behavioral and psychosocial functioning

 Health care utilization

P3 (Three months post-discharge)

Home visit

Medical & demographical data

60

 Socio-demographic characteristics

 Geriatric conditions

Personal interview/self-report data

 Cognitive functioning

 ADL/physical functioning

 Behavioral & psychosocial functioning

 Health care utilization

Physical performance tests

Mortality (medical record)

Data will be collected through: 1] medical and demographical data (e.g., socio-demographic characteristics, severity of acute illness, and geriatric-, and chronic conditions); 2] personal interviews (including cognitive, behavioral, psychosocial, and physical parameters, and health care utilization, see description of information collected below); 3] physical performance tests (e.g., gait speed, muscle strength, muscle mass, mobility and physical functioning, see below) and; 4] blood samples (e.g., to assess markers of inflammation).

The personal interviews will take place during hospitalization (H1, H2, and H3), at the participant’s home or residence (P1 and P3; one and three months post-discharge), and by telephone (P2; two months post-discharge). Physical performance data will be collected within 48 h after admission (H1), during hospitalization on Monday, Wednesday and Friday (H2), at discharge (H3), and at one and three months post-discharge (P1 and P3).

Primary outcome

The primary outcome is the level of ADL functioning three months post-discharge compared to premorbid functioning, which are measured with the 6-item Katz-ADL index score of the modified Katz-ADL index [17]. The Katz-ADL index score assesses the degree of independence in bathing, dressing, toileting, use of incontinence materials, transfer from bed-chair and eating [16].

Secondary outcomes

Secondary outcomes include:
  1. (1)

    Health care utilization (extension of the Minimal Dataset (MDS) [18] and Comprehensive Geriatric Assessment of the Transitional Care Bridge (TCB) [19], see below).

     
  2. (2)

    Quality of life as measured with the EuroQol-5D [20] and the three items of the MDS [18] (see description below).

     
  3. (3)

    Physical performance tests (see below for description of included tests).

     
  4. (4)

    Mortality.

     

Scales and assessments

Table 2 gives a detailed overview of the primary and secondary outcomes at each time point.
Table 2

Summary of outcome measures and time points of assessment in Hospital-ADL study

 

Question or instrument

H1

H2

H3

P1

P2

P3

1. Medical & demographical data

       

 Age

Date of birth

×*

     

 Gender

 

×

     

 Postal code

 

×

     

 Date and time of admission

 

×*

     

 Education

(In accordance with Verhage, 1966 [57])

×

     

 Ethnicity

Country of birth patient and parents

×

     

 Marital status [18]

 

×

     

 Living arrangement [18, 19]

 

×

  

×

 

×

 Medical comorbidity

CCI [21]

×*

     

 Severity of acute illness

MEWS [22]

×*

×*

×*

   

 Admission diagnosis

 

×*

     

2. Personal interviews/self-report data

       

2.1 Cognitive functioning

       

 Cognitive impairment

MMSE [23]

×

 

×

×

 

×

 Delirium

CAM [24, 58]

×

     
 

Assessing whether: 1] the patient needs help with self-care; 2] the patient has previously undergone a delirium and; 3] the patient has a cognitive impairment [25]

×*

     

2.2 Behavioral & psychosocial functioning

       

 Fear of falling

NRS fear of falling

×

×

×

×

×

×

 Anxiety

STAI-6 [31]

×

 

×

×

×

×

 Apathy

GDS-15 [29]

×

 

×

×

×

×

 General self-efficacy

ALCOS-12 [34]

  

×

×

×

 

 Quality of life

1] In general, how is your quality of life?; 2] How would you grade your life at this moment, with a range between 0 and 10? and; 3] Compared to one year ago, how would you rate your health in general now? [18]

×

 

×

×

×

×

 

EQ-5D [20]

×

 

×

×

×

×

2.3 ADL/Physical functioning

       

 Disability in ADLs

Modified Katz Index Scale [16, 17]

×

 

×

×

×

×

 Independency in walking

FAC [42]

×

×

×

×

×

×

 Mobility

Could you walk outside for 5 minutes two weeks before admission/currently? And how often did/do you do physical activity two weeks before admission/currently? [19]

×

 

×

×

×

×

 Falls

Have you fallen once or more in the past (six) month(s)? If yes, how many times? [25]

×

 

×

×

×

×

 Pain

NRS pain [35]

×

×

×

×

×

×

 Fatigue

NRS fatigue [37]

×

×

×

×

×

×

 Impact of fatigue

MFIS-5 [38]

   

×

×

×

 Sleep quality

PSQI [39]

×

 

×

×

×

×

 Sleep medication

PSQI [39]

×

 

×

×

×

×

 Daytime sleepiness

Do you currently suffer from daytime sleepiness? If yes, does this affect your daily living?

×

×

×

×

×

×

 Polynocturia

Do you currently suffer from polynocturia? If yes, does this affect your daily living?

×

×

×

×

×

×

 Dizziness

Do you currently suffer from dizziness? If yes, does this affect your daily living?

×

×

×

×

×

×

 Shortness of breath

Do you currently suffer from shortness of breath? If yes, does this affect your daily living?

×

×

×

××

×

×

 Hearing impairment

Do you experience difficulties with hearing, despite the use of a hearing aid?

×

  

×

 

×

 Vision impairment

Do you experience difficulties with your vision, despite the use of glasses?

×

  

×

 

×

 Nutrition

SNAQ [25, 41]

×

 

×

×

×

×

 Dependency

Do you smoke? Do you use alcohol [19]?

×

  

×

 

×

 Polypharmacy

Do you use five or more different medications [19]?

×

  

×

 

×

2.4 Health care utilization

       

 Readmission

Have you been hospitalized in the last (six) month(s)? If yes, for how many days? [18]

×*

  

×

×

×

 Nursing home admission

Have you had a nursing home admission in the last month? If yes, for how many weeks totally? [18]

   

×

×

×

 Consult physiotherapist and/or occupational therapist

Have you had a consultation with your physiotherapist and/or occupational therapist in the last month? If yes, how many times?

   

×

×

×

 Consult general practitioner

Have you had a consultation with your general practitioner in the last month? If yes, in the evening, night or weekend and how many times totally? [19]

   

×

×

×

 Home care

Do you use home care? If yes, care assistance and/or domestic help and how many hours per week [19]

   

×

×

×

3. Physical performance tests

       

 Handgrip strength

Jamar® [5961]

×

×

×

×

 

×

 Mobility

DEMMI [45]

×

×

×

×

 

×

 Agility

CSR [47]

×

×

×

×

 

×

 Balance, strength, and gait

SPPB [46]

×

×

×

×

 

×

 Walking distance

2MWT [49]

×

×

×

×

 

×

 Body composition

BIA (Bodystat Quadscan 4000) [50]

×

×

×

×

 

×

 Activity tracker

Fitbit Flex [51]

×

×

×

×

 

×

 

Question or instrument

H1

H2/H3

P1

P2

P3

4. Blood parameters

      

 Inflammation markers

CRP [52]

×

×

   
 

WBC diff

×

×

   
 

TNF-α [5355]

×

×

   
 

IL-6 [5355]

×

×

   
 

IL-8 [55]

×

×

   

Mortality

Date of death

    

×*

Note: H1 = within 48 h after admission; H2 = during hospitalization on Monday, Wednesday, and/or Friday; H3 = at discharge; P1 = one month post-discharge (home visit); P2 = two months post-discharge (by telephone); P3 = three months post-discharge (home visit);

×* = Data will be obtained from medical record;

CCI Charlson Comorbidity Index, MEWS Modified Early Warning Score, MMSE Mini Mental State Examination, CAM Confusion Assessment Method, NRS Numeric Rating Scale, STAI-6 State Trait Anxiety Inventory-6, GDS-15 Geriatric Depression Scale-15, ALCOS-12 Algemene Competentie Schaal-12 (General Self-Efficacy Scale), EQ-5D EuroQol-5D, FAC Functional Ambulation Categories, MFIS-5 Modified Fatigue Impact Scale-5, PSQI Pittsburgh Sleep Quality Index, SNAQ Short Nutritional Assessment, DEMMI De Morton Mobility Index, CSR Chair Sit and Reach test, SPPB Short Physical Performance Battery, 2MWT 2 Minute Walking Test, BIA Bioelectrical Impedance Analysis, CRP C-Reactive Protein, WBC diff White Blood Cell Differential, TNF-α Tumor Necrosis Factor-α, IL-6 Interleukin-6, IL-8 Interleukin-8

  1. (1)

    Medical and demographical data

    Socio-demographic characteristics. Socio-demographic data include age, gender, date and time of admission, highest level of education, ethnicity, marital status and living arrangement.

    Geriatric conditions. A comprehensive geriatric assessment (CGA) will be collected, which will provide insight in the pre-illness determinants such as polypharmacy, substance use, incontinence, and vision- and hearing impairments.

    Chronic conditions. The number and severity of comorbidities will be scored with the Charlson Comorbidity Index [21]. Depending on the risk of mortality, each condition is assigned a score of 1, 2, 3, or 6. Higher scores indicate a greater risk of mortality.

    Severity of acute illness. The severity of the acute illness will be measured with the Modified Early Warning Score (MEWS). The MEWS is based on 1] respiratory rate; 2] heart rate; 3] systolic and diastolic blood pressure; 4] level of consciousness; 5] temperature, and; 6] oxygen saturation [22].

    Personal interviews/self-report data

    (2.1) Cognitive functioning

    Cognitive impairments. The most commonly used Mini Mental State Examination (MMSE) will be applied to classify the severity of a cognitive impairment. It is a validated 23-item screening of cognitive impairment. The MMSE consists of a series of questions and tests, which assess different mental abilities, including memory, attention, language, and planning. Cognitive impairment is defined as a score of 23 or less on the MMSE [23].

    Delirium. The Confusion Assessment Method (CAM) will be used to identify the presence of delirium. The CAM consists of four features: 1] acute onset and fluctuating course; 2] inattention; 3] disorganized thinking, and 4] altered level of consciousness. The diagnosis of delirium requires the presence of both features 1 and 2, and the presence of either feature 3 or 4 [24]. Furthermore, we want to assess the risk for developing delirium with the following statements of the Dutch Safety Management Programme (Veiligheidsmanagementsysteem (VMS)): 1] the patient needs help with self-care, 2] the patient has previously undergone a delirium, and 3] the patient has a cognitive impairment such as dementia [25, 26].

    (2.2) Behavioral and psychosocial functioning

    Fear of falling. A Numeric Rating Scale (NRS) will be applied to measure fear of falling, in which a participant selects a whole number (0–10 integers). Zero represents no fear of falling and ten the worst possible fear of falling.

    Depression. The Geriatric Depression Scale-15 (GDS-15) will be used to measure symptoms of depression (Cronbach’s α = 0.75 [27]). The GDS-15 is a self-report scale of 15 items on a binary (yes/no) scale and assesses symptoms over the preceding week. The total score is the sum of the 15 items (range 0–15 points, higher scores indicating more depression). The following categories of the GDS-15 will be used: a score of 0 to 4 will be considered ‘normal’, a score of 5 to 8 a ‘mild depression’, 9 to 11 a ‘moderate depression’, and 12 to 15 a ‘severe depression’ [28].

    Apathy. Three items of the GDS-15 will be used to measure apathy (sensitivity of 69 % and specificity of 85 % [29]). The three apathy items include the following questions: 1] “Do you prefer to stay at home, rather than going out and doing new things?”; 2] “Have you dropped many of your activities and interests?” and; 3] “Do you feel full of energy? Higher scores indicate more apathy. A score of ≥2 points is indicative for apathy [29].

    Anxiety. The State-Trait Anxiety Inventory-6 (STAI-6) will be used to measure anxiety symptoms (Cronbach’s α = 0.79-0.81 [30]). The STAI-6 is a short-form of the 20-item state scale of the Spielberger State-Trait Anxiety Inventory (STAI) [31], that maintains results that are comparable with this full-form [30]. It consists of six items on a 4-point Likert scale (1] not at all/almost never; 2] somewhat/sometimes; 3] moderately so/often, and; 4] very much so/almost always). Furthermore, it remains sensitive to different levels of anxiety.

    Perceived self-efficacy. The General Self Efficacy Scale (In Dutch: Algemene Competentie Schaal (ALCOS-12)) will be used to measure general perceived self-efficacy (Cronbach’s α = 0.78 [32]). It is based on the Self-Efficacy Scale [33] and is a Dutch translated self-report rating scale of 12 items on a 5 point Likert scale (1] strongly disagree; 2] disagree; 3] no disagreement/agreement; 4] agree and; 5] strongly agree). The ALCOS-12 includes three subscales: competence (Cronbach’s α = 0.72), perseverance in adversity (Cronbach’s α = 0.67), and taking initiative (Cronbach’s α = 0.74) [32]. The total score is the sum of the 12 items (range 12–60), whereby the following categories of the ALCOS-12 will be used: a score of 12 to 38 will be defined as a ‘low competence level’, a score of 39 to 54 as ‘average’ and 55 to 60 as ‘high’ [34].

    Health-Related Quality of life. The EuroQol-5D (EQ-5D), a widely used preference based generic health-related quality of life (HRQoL) instrument with well-established psychometric properties will be administered [20]. The EQ-5D consists of five dimensions: 1] mobility; 2] self-care; 3] usual activities; 4] pain/discomfort and; 5] anxiety/depression. These dimensions have three response choices (no problems; some problems or; severe problems). Moreover, the following questions will be used to measure quality of life: 1] “In general, how is your quality of life (participants answer the item with one of five possible responses: excellent; very good; good; moderate or; bad)?”; 2] “How would you grade your life at this moment, with a range between 0 and 10?” and; 3] “Compared to one year ago, how would you rate your health in general now (five response choices: much better; slightly better; much the same; slightly worse or; much worse)?” [18].

    (2.3) Physical functioning

    Dizziness, polynocturia and shortness of breath. Symptoms of dizziness and shortness of breath will be assessed by asking: “Do you suffer from polynocturia/dizziness/shortness of breath at this moment? If yes, does this affect your daily functioning?”

    Pain. A gold standard of pain intensity measurements, the Numeric Rating Scale (NRS), will be applied to measure pain. The NRS for pain is a validated continuous scale with a score range between 0 and 10 (0 represents no pain and 10 the worst possible pain) [35, 36].

    Fatigue. The Numeric Rating Scale (NRS), will be used to measure fatigue. The NRS for fatigue is a continuous scale with a score range between zero and ten (zero represents no pain and ten the worst possible fatigue) [37].

    Impact of fatigue. The abbreviated version of the 21-item Modified Fatigue Impact Scale (MFIS) will be used to quantify the impact of fatigue. The short version consists of five items that are divided into three subscales: physical- (2 items), cognitive- (2 items), and psychosocial functioning (1 item) subscale. An example of a MFIS-5 statement is: “Because of my fatigue during the past four week, I have been less alert.” The total score of the MFIS-5 is the sum of the raw scores on a 5-point Likert scale (0] never; 1] rarely; 2] sometimes; 3] often, and; 4] almost always). Higher scores indicate greater fatigue [38].

    Sleep. The Pittsburgh Sleep Quality Index (PSQI) will be utilized to measure two components of sleep: sleep quality and sleep medication. Sleep quality will be quantified by asking: “During the past month, how would you rate your sleep quality overall?” Sleep medication will be measured by asking: “During the past month, how often have you taken medicine (prescribed or “over the counter”) to help you sleep?” The score of sleep quality and sleep medication have a range of 0 (better) to 3 (worse) [39]. In addition, we measure daily sleepiness on a binary scale (yes/no) with the following question: “Do you currently suffer from daytime sleepiness? If yes, does this affect your daily living?”

    Nutrition. The widely used Short Nutritional Assessment Questionnaire (SNAQ) will be applied to identify malnourished hospital patients (Cronbach’s alpha = 0.58 [40]) [25, 26]. The total score of the SNAQ is the sum of the raw scores, whereby the following categories of the SNAQ will be used: a score of 0 to 1 will be defined as ‘no malnutrition’, a score of 2 as ‘moderate malnutrition’ and a score of 3 as ‘severe malnutrition’ [41].

    ADL functioning. The 15 items modified Katz-ADL index will be used to measure physical functioning [16, 17]. The modified Katz-ADL index consists of statements of their independency in performing basic Activities of Daily Living (ADL) and Instrumental Activities of Daily Living (IADL) (formulated in two versions on a binary (yes/no) scale: two weeks before admission or currently).

    Mobility. The Functional Ambulation Categories (FAC) will be used to classify mobility, using six categories: a category of 1 will be defined as ‘independent unlimited’, a category of 2 as ‘independent limited’ and categories 3 to 5 as ‘dependent’. Allocation to these last categories is based on levels of assistance and supervision needed [42]. Furthermore, we will measure mobility with two questions in according to the Comprehensive Geriatric Assessment (CGA) of the Dutch Society of Clinical Geriatrics (NVKG, 2012): 1] “Were you able to walk outside the house for five minutes (formulated in two versions: two weeks before admission or currently)?”, and; 2] “How often did/do you perform physical activity two weeks before admission/currently [19]?”

    Falls. To measure the number of falls in the past (six) month(s) the following question of the VMS will be used: “Have you fallen once or more in the past (six) month(s)? If yes, how many times [25, 26]?”

    (2.4) Health care utilization

    (Re)admission(s). Any (re)admission(s) to the hospital will be measured. We will search the medical record for (re)admission(s) in the same hospital six months before hospitalization and during three months post-discharge, and we will also retrieve this information by self-report at P1-P3 with the following self-report question: “Have you been hospitalized in the last month? If yes, for how many days [18]?” Data that will be collected out of the hospital system are: date of admission and discharge for any readmission, whether the admission was planned or unplanned and the reason for the readmission.

    Nursing home admission(s). The amount of nursing home admission or whether they were admitted to the nursing home and the length of stay will be measured with the subsequent question: “Have you had a nursing home admission in the last month? If yes, for how many weeks totally [18]?”

    Consult of physical therapist and/or occupational therapist. The amount of consults of a physiotherapist and/or occupational therapist will be measured by asking: “Have you had a consultation with your physical therapist and/or occupational therapist in the last month? If yes, how many times?”

    Consult general practitioner. The amount of consults of a general practitioner will be measured by asking: “Have you had a consultation with your general practitioner in the last month? If yes, in the evening, night or weekend and how many times in total [19]?”

    Home care. The use of home care will be measured with the subsequent question: “Do you use home care? If yes, care assistance and/or domestic help and how many hours per week [19]?” A distinction will be made between household help from a nursing aid, and help from a registered nurse.

     
  2. (2)

    Physical performance tests

    Handgrip strength. The hand grip strength will be measured with the widely used Jamar® grip strength dynamometer (Lafayette Instrument Company, USA). The handgrip strength test is used to provide an objective index of general upper body strength. Handgrip strength is a reliable instrument (good to excellent test-retest reproducibility and excellent inter-rater reliability) to indicate skeletal muscle mass [43]. Participants will perform the task thrice with each hand. The highest score from either hand will be used and registered in the eCRF. Normative values of adults are described in a study of Mathiowetz [44].

    Mobility. To measure the mobility we will use the 15-item Morton Mobility Index (DEMMI). Subjects will be asked to perform several mobility tasks, in the order of bed, chair, stand, and walking activities to maximize patient safety, which will result in an ordinal raw score (range: 0–19). The ordinal raw score will be converted into a total interval DEMMI score (range: 0 to 100 points). Moreover, the DEMMI has a hierarchical structure, and thus each assessed participant can be evaluated. Higher scores indicate a better mobility performance [45].

    Balance, strength, and gait speed. The Short Physical Performance Battery (SPPB) will be applied to measure the balance, strength and gait speed. Participants will be asked to stand with their feet in various balance positions, walk a distance of four meter and to rise from a chair and return to the seated position five times as quickly as possible. Higher scores indicate a better performance [46].

    Back and hamstring flexibility. The Chair Sit and Reach (CSR) test will be used as a measure of flexibility. Participant will be asked to extend one leg as straight as possible, hands on top of each other, and then to reach to his/her foot as far as possible. Lower distances between the tip of his/her toes and their extended fingers indicating a higher back and hamstring flexibility [47, 48].

    Walking distance. The 2 Minute Walking West (2MWT) will be applied to measure the maximal walking distance in meters. Participants will be asked to walk back and forth along a premeasured corridor of 15 meter in two minutes. Longer walking distances indicating a better walking capacity [49].

    Body composition. The Bioelectrical Impedance Analysis (BIA) (Bodystat Quadscan 4000) will be used as method for estimating body composition, in particular fat-free mass (FFM) and high fat mass (FM). Electrodes will be attached to the ankle and wrist. A small electric signal will circulate, which measures the resistance and reactance of this electrical signal in the human body [50].

    Activity level. The Fitbit Flex will be applied to monitor the sleep quality, measure motion patterns, determine the calories burned, distance traveled, and steps taken [51]. Participants will be asked to wear the Fitbit Flex from hospital admission up to one and a half weeks post-discharge.

     
  3. (3)

    Blood parameters

    Inflammation markers. Inflammation markers, such as C-Reactive Protein (CRP) [52], Tumor Necrosis Factor-α (TNF-α), the interleukins IL-6 [5355] and IL-8) [55], and White Blood Cell Differential (WBC diff), will be determined from blood plasma and serum. Blood will be collected during the customary laboratory rounds during hospitalization. Venous blood will be collected in 4.5 ml EDTA and serum vacutainers. Samples will be centrifuged and stored at −80 C° until analysis. Sample handling and analyses will be performed according to ISO standards.

     

Planned statistical analyses

Data will be analyzed in accordance with the research questions outlined in the introduction, applying appropriate General Linear Models (e.g., linear regression, repeated measures ANOVA/ANCOVA) as well as log-linear models (e.g., logistic regression in case of binary outcomes). Mortality, a (censored) numerical outcome, will be tested using survival analysis. The global α level will be set at 0.05 with hypothesis-wise adjustment for multiple testing. All analyses will be performed using SPSS version 22.0 [56]. Castor Electronic Data Capture (EDC) will be used to build electronic Case Report Forms (eCRFs) for save and valid data collection.

Primary endpoint in the study will be HAD as measured with the Katz-ADL index score. For multivariable analyses (General Linear models and log-linear models) a custom 10:1 case-to-outcome ratio is utilized as a maximum. Utilizing a repeated measures design, power calculations imputing a conservative α level of 0.01 yielded a power of 95 % for associations of a small effect-size (Cohen’s f = 0.069), whereas a power of 80 % was established for associations with an effect-size of 0.058 (Cohen’s f).

Discussion

More than 30 % of the older patients experience hospitalization-associated disability (HAD) after acute hospitalization [1, 3, 4], which implies the loss of ability to perform one or more of the basic ADLs [6]. HAD is the leading cause of functional decline at older age [4]. With a higher number of older persons and an increasing life expectancy, there is an urgent need to unravel the potential mechanisms behind HAD as well as how the mechanisms can be influenced. To our knowledge, the Hospital-ADL study is the first study that investigates cognitive, behavioral, psychosocial, physical, and biological factors simultaneously. The current study will provide novel information regarding possible underlying mechanisms behind HAD within the critical period of three months post hospitalization, which is expected to lead to the development of interventions that can prevent or restore HAD.

Ethics approval and consent to participate

The study is approved by the Institutional Review board of the Academic Medical Center (AMC) in The Netherlands (Protocol ID: AMC2015_150). Written informed consent is obtained from all participants before inclusion. The research is performed according to the Dutch Medical Research Involving Human Subjects Act and principles of the Declaration of Helsinki (1964).

Abbreviations

2MWT: 

2 min walking test

ADL: 

activities of daily living

ALCOS-12: 

Algemene Competentie Schaal-12 (Perceived Self-Efficacy)

BIA: 

bioelectrical impedance analysis

CAM: 

confusion assessment method

CCI: 

Charlson comorbidity index

CGA: 

comprehensive geriatric assessment

CRF: 

case report form

CRP: 

C-Reactive Protein

CSR: 

Chair Sit an Reach test

DEMMI: 

De Morton Mobility Index

EQ-5D: 

EuroQoL-5D

FAC: 

functional ambulation categories

GDS-15: 

geriatric depression scale-15

HAD: 

hospitalization-associated disability

Hospital-ADL study: 

Hospital-Associated Disability and impact on daily Life study

IADL: 

instrumental activities of daily living

IL- 8: 

interleukin- 8

IL-6: 

interleukin- 6

MDS: 

minimal dataset

MEWS: 

modified early warning score

MFIS-5: 

modified fatigue impact scale-5

MMSE: 

mini mental state examination

NRS: 

numeric rating scale

PSQI: 

Pittsburgh Sleep Quality Index

SNAQ: 

short nutritional assessment

SPPB: 

short physical performance battery

STAI-6: 

state trait anxiety inventory-6

TCB: 

transitional care bridge

TNF-α: 

tumor necrosis factor-α

VMS: 

safety management programme (In Dutch: Veiligheidsmanagementsysteem)

WBC diff: 

white blood cell differential

Declarations

Acknowledgements

This work was supported by the Netherlands Organization for Health Research and Development (NWO-ZonMw) [grant number 16156071].

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
Department of Internal Medicine, Section of Geriatric Medicine, Academic Medical Center
(2)
Department of Rehabilitation, Academic Medical Center
(3)
Amsterdam Center for Innovative Health Practice (ACHIEVE), Faculty of Health, Amsterdam University of Applied Sciences
(4)
Department of Clinical Psychology, University of Amsterdam

References

  1. Buurman BM, Hoogerduijn JG, de Haan RJ, Abu-Hanna A, Lagaay AM, Verhaar HJ, Schuurmans MJ, Levi M, de Rooij SE. Geriatric conditions in acutely hospitalized older patients: prevalence and one-year survival and functional decline. PLoS ONE. 2011;6(11), e26951.Google Scholar
  2. Boyd CM, Ricks M, Fried LP, Guralnik JM, Xue QL, Bandeen-Roche K. Functional Decline and Recovery of Activities of Daily Living among Hospitalized, Disabled Older Women: The Women’s Health and Aging Study I. J Am Geriatr Soc. 2009;57(10):1757–66.View ArticlePubMedPubMed CentralGoogle Scholar
  3. Boyd CM, Landefeld CS, Counsell SR, Palmer RM, Fortinsky RH, Kresevic D, Burant C, Covinsky KE. Recovery of activities of daily living in older adults after hospitalization for acute medical illness. J Am Geriatr Soc. 2008;56(12):2171–9.View ArticlePubMedPubMed CentralGoogle Scholar
  4. Gill TM, Allore HG, Gahbauer EA, Murphy TE. Change in disability after hospitalization or restricted activity in older persons. JAMA. 2010;304(17):1919–28.View ArticlePubMedPubMed CentralGoogle Scholar
  5. Covinsky KE, Palmer RM, Fortinsky RH, Counsell SR, Stewart AL, Kresevic D, Burant CJ, Landefeld CS. Loss of independence in activities of daily living in older adults hospitalized with medical illnesses: increased vulnerability with age. J Am Geriatr Soc. 2003;51(4):451–8.Google Scholar
  6. Covinsky KE, Pierluissi E, Johnston CB. Hospitalization-associated disability: “She was probably able to ambulate, but I’m not sure”. JAMA. 2011;306(16):1782–93.View ArticlePubMedGoogle Scholar
  7. Buurman BM, De Rooij SE. Functieverlies ouderen bij acute opname in ziekenhuis. Ned Tijdschr Geneeskd. 2015;159:A8185.PubMedGoogle Scholar
  8. Hardy SE, Dubin JA, Holford TR, Gill TM. Transitions between states of disability and independence among older persons. Am J Epidemiol. 2005;161(6):575–84.View ArticlePubMedGoogle Scholar
  9. Gill TM, Allore HG, Holford TR, Guo Z. Hospitalization, restricted activity, and the development of disability among older persons. JAMA. 2004;292(17):2115–24.View ArticlePubMedGoogle Scholar
  10. Kansagara D, Englander H, Salanitro A, Kagen D, Theobald C, Freeman M, Kripalani S. Risk prediction models for hospital readmission: a systematic review. JAMA. 2011;306(15):1688–98.Google Scholar
  11. Buurman BM, van Munster BC, Korevaar JC, Abu-Hanna A, Levi M, de Rooij SE. Prognostication in acutely admitted older patients by nurses and physicians. J Gen Intern Med. 2008;23(11):1883–9.View ArticlePubMedPubMed CentralGoogle Scholar
  12. Walter LC, Brand RJ, Counsell SR, Palmer RM, Landefeld CS, Fortinsky RH, Covinsky KE. Development and validation of a prognostic index for 1-year mortality in older adults after hospitalization. JAMA. 2001;285(23):2987–94.Google Scholar
  13. Inouye SK, Charpentier PA. Precipitating factors for delirium in hospitalized elderly persons. Predictive model and interrelationship with baseline vulnerability. JAMA. 1996;275(11):852–7.View ArticlePubMedGoogle Scholar
  14. Sands LP, Yaffe K, Covinsky K, Chren MM, Counsell S, Palmer R, Landefeld CS. Cognitive screening predicts magnitude of functional recovery from admission to 3 months after discharge in hospitalized elders. J Gerontol Ser A Biol Med Sci. 2003;58(1):37–45.Google Scholar
  15. Sager MA, Franke T, Inouye SK, Landefeld CS, Morgan TM, Rudberg MA, Sebens H, Winograd CH. Functional outcomes of acute medical illness and hospitalization in older persons. Arch Intern Med. 1996;156(6):645–52.Google Scholar
  16. Katz S, Downs TD, Cash HR, Grotz RC. Progress in development of the index of ADL. The Gerontologist. 1970;10(1):20–30.View ArticlePubMedGoogle Scholar
  17. Laan W, Zuithoff NP, Drubbel I, Bleijenberg N, Numans ME, de Wit NJ, Schuurmans MJ. Validity and reliability of the Katz-15 scale to measure unfavorable health outcomes in community-dwelling older people. J Nutr Health Aging. 2014;18(9):848–54.Google Scholar
  18. Minimale Data Set Zorgvrager Basismeting [http://topics-mds.eu/?page_id=366].
  19. Compleet Geriatrisch Assessment TZB [http://www.effectieveouderenzorg.nl/zorgmodel/downloadformulieren.aspx].
  20. Group. EuroQol - a new facility for the measurement of health-related quality of life. Health Policy. 1990;16(3):199–208.View ArticleGoogle Scholar
  21. Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40(5):373–83.View ArticlePubMedGoogle Scholar
  22. Subbe CP, Kruger M, Rutherford P, Gemmel L. Validation of a modified Early Warning Score in medical admissions. QJM. 2001;94(10):521–6.View ArticlePubMedGoogle Scholar
  23. Folstein MF, Folstein SE, McHugh PR. “Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. 1975;12(3):189–98.View ArticlePubMedGoogle Scholar
  24. Inouye SK, van Dyck CH, Alessi CA, Balkin S, Siegal AP, Horwitz RI. Clarifying confusion: the confusion assessment method. A new method for detection of delirium. Ann Intern Med. 1990;113(12):941–8.View ArticlePubMedGoogle Scholar
  25. VMS. Praktijkgids ‘Kwetsbare Ouderen’, VMS veiligheidsprogramma. 2009. 978-94-90101-04-6.Google Scholar
  26. Heim N, van Fenema EM, Weverling-Rijnsburger AW, Tuijl JP, Jue P, Oleksik AM, Verschuur MJ, Haverkamp JS, Blauw GJ, van der Mast RC et al. Optimal screening for increased risk for adverse outcomes in hospitalised older adults. Age Ageing. 2015;44(2):239–44.View ArticlePubMedPubMed CentralGoogle Scholar
  27. Friedman B, Heisel MJ, Delavan RL. Psychometric properties of the 15-item geriatric depression scale in functionally impaired, cognitively intact, community-dwelling elderly primary care patients. J Am Geriatr Soc. 2005;53(9):1570–6.View ArticlePubMedGoogle Scholar
  28. Kok RM, Heeren TJ, van Hemert AM. De Geriatric Depression Scale. Tijdschrift voor de Psychiatrie. 1993;35:416–21.Google Scholar
  29. van der Mast RC, Vinkers DJ, Stek ML, Bek MC, Westendorp RG, Gussekloo J, de Craen AJ. Vascular disease and apathy in old age. The Leiden 85-Plus Study. Int J Geriatr Psychiatry. 2008;23(3):266–71.Google Scholar
  30. Tluczek A, Henriques JB, Brown RL. Support for the Reliability and Validity of a Six-Item State Anxiety Scale Derived From the State-Trait Anxiety Inventory. J Nurs Meas. 2009;17(1):19–28.View ArticlePubMedPubMed CentralGoogle Scholar
  31. Chlan L, Savik K, Weinert C. Development of a shortened state anxiety scale from the Spielberger State-Trait Anxiety Inventory (STAI) for patients receiving mechanical ventilatory support. J Nurs Meas. 2003;11(3):283–93.View ArticlePubMedGoogle Scholar
  32. Bosscher RJ, Smit JH, Kempen GIJM. Algemene competentieverwachtingen bij ouderen: Een onderzoek naar de psychometrische kenmerken van de Algemene Competentieschaal (ALCOS)./Global expectations of self-efficacy in the elderly: An investigation of psychometric characteristics of the General Self-Efficacy Scale. Ned Tijdschr Psychol. 1997;52:239–48.Google Scholar
  33. Sherer M, Maddux JE, Mercandante B, Prentice-Dunn S, Jacobs B, Rogers RW. The self-efficacy scale : Construction and validation. Psychol Rep. 1982;51:663–71.View ArticleGoogle Scholar
  34. Bosscher RJ, Laurijssen L, Boer E. Competence at later age: An explorative study. (Competentie op latere leeftijd: Een exploratieve studie.). Bewegen Hulpverlening. 1992;9:225–65.Google Scholar
  35. McCaffery M, Beebe A. Pain: clinical manual for nursing practice. C.V. Mosby: St. Louis; 1989.Google Scholar
  36. Puntillo KA, Neighbor ML. Two methods of assessing pain intensity in English-speaking and Spanish-speaking emergency department patients. J Emerg Nurs. 1997;23(6):597–601.View ArticlePubMedGoogle Scholar
  37. Hwang SS, Chang VT, Cogswell J, Kasimis BS. Clinical relevance of fatigue levels in cancer patients at a Veterans Administration Medical Center. Cancer. 2002;94(9):2481–9.View ArticlePubMedGoogle Scholar
  38. Fisk JD, Ritvo PG, Ross L, Haase DA, Marrie TJ, Schlech WF. Measuring the functional impact of fatigue: initial validation of the fatigue impact scale. Clin Infect Dis. 1994;18 Suppl 1:S79–83.View ArticlePubMedGoogle Scholar
  39. Buysse DJ, Reynolds 3rd CF, Monk TH, Berman SR, Kupfer DJ. The Pittsburgh Sleep Quality Index: a new instrument for psychiatric practice and research. Psychiatry Res. 1989;28(2):193–213.View ArticlePubMedGoogle Scholar
  40. Hanisah R, Suzana S, Lee FS. Validation of screening tools to assess appetite among geriatric patients. J Nutr Health Aging. 2012;16(7):660–5.View ArticlePubMedGoogle Scholar
  41. Kruizenga HM, Seidell JC, de Vet HC, Wierdsma NJ, van Bokhorst-de van der Schueren MA. Development and validation of a hospital screening tool for malnutrition: the short nutritional assessment questionnaire (SNAQ). Clin Nutr (Edinburgh, Scotland). 2005;24(1):75–82.View ArticleGoogle Scholar
  42. Holden MK, Gill KM, Magliozzi MR, Nathan J, Piehl-Baker L. Clinical gait assessment in the neurologically impaired. Reliability and meaningfulness. Phys Ther. 1984;64(1):35–40.PubMedGoogle Scholar
  43. Roberts HC, Denison HJ, Martin HJ, Patel HP, Syddall H, Cooper C, Sayer AA. A review of the measurement of grip strength in clinical and epidemiological studies: towards a standardised approach. Age Ageing. 2011;40(4):423–9.Google Scholar
  44. Mathiowetz V, Kashman N, Volland G, Weber K, Dowe M, Rogers S. Grip and pinch strength: normative data for adults. Arch Phys Med Rehabil. 1985;66(2):69–74.PubMedGoogle Scholar
  45. de Morton NA, Davidson M, Keating JL. The de Morton Mobility Index (DEMMI): an essential health index for an ageing world. Health Qual Life Outcomes. 2008;6:63.View ArticlePubMedPubMed CentralGoogle Scholar
  46. Guralnik JM, Simonsick EM, Ferrucci L, Glynn RJ, Berkman LF, Blazer DG, Scherr PA, Wallace RB. 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.Google Scholar
  47. Jones CJ, Rikli RE, Max J, Noffal G. The reliability and validity of a chair sit-and-reach test as a measure of hamstring flexibility in older adults. Res Q Exerc Sport. 1998;69(4):338–43.View ArticlePubMedGoogle Scholar
  48. Dewhurst S, Bampouras TM. Intraday reliability and sensitivity of four functional ability tests in older women. Am J Phys Med Rehabil. 2014;93(8):703–7.View ArticlePubMedGoogle Scholar
  49. Butland RJ, Pang J, Gross ER, Woodcock AA, Geddes DM. Two-, six-, and 12-minute walking tests in respiratory disease. Br Med J (Clin Res Ed). 1982;284(6329):1607–8.View ArticleGoogle Scholar
  50. Haverkort EB, Binnekade JM, de van der Schueren MA, Gouma DJ, de Haan RJ. Estimation of body composition depends on applied device in patients undergoing major abdominal surgery. Nutr Clin Pract. 2015;30(2):249–56.View ArticlePubMedGoogle Scholar
  51. Bai Y, Welk GJ, Nam YH, Lee JA, Lee JM, Kim Y. Meier NF. Comparison of Consumer and Research Monitors under Semistructured Settings. Medicine and science in sports and exercise: Dixon PM; 2015.Google Scholar
  52. Wium-Andersen M, Ørsted D, Nielsen S, Nordestgaard B. ELevated c-reactive protein levels, psychological distress, and depression in 73 131 individuals. JAMA Psychiatry. 2013;70(2):176–84.View ArticlePubMedGoogle Scholar
  53. Dantzer R. Cytokine, Sickness Behavior, and Depression. Immunol Allergy Clin N Am. 2009;29(2):247–64.View ArticleGoogle Scholar
  54. Dantzer R, O’Connor JC, Freund GG, Johnson RW, Kelley KW. From inflammation to sickness and depression: when the immune system subjugates the brain. Nat Rev Neurosci. 2008;9(1):46–56.View ArticlePubMedPubMed CentralGoogle Scholar
  55. Poon DC, Ho YS, Chiu K, Chang RC. Cytokines: how important are they in mediating sickness? Neurosci Biobehav Rev. 2013;37(1):1–10.View ArticlePubMedGoogle Scholar
  56. Corp I. IBM SPSS Statistics for Windows. 220th ed. Armonk: IBM Corp; 2013.Google Scholar
  57. Verhage F. Intelligentie en leeftijd: Onderzoek bij Nederlanders van twaalf tot zevenenzeventig jaar. Proefschrift. Van Gorcum: Assen; 1964.Google Scholar
  58. Heeren TJ, Kat MG, Stek ML. Handboek ouderenpsychiatrie (tweede druk). 2002. De Tijdstroom.Google Scholar
  59. Timmerman H, de Groot JF, Hulzebos HJ, de Knikker R, Kerkkamp HE, van Meeteren NL. Feasibility and preliminary effectiveness of preoperative therapeutic exercise in patients with cancer: a pragmatic study. Physiother Theory Pract. 2011;27(2):117–24.View ArticlePubMedGoogle Scholar
  60. Trutschnigg B, Kilgour RD, Reinglas J, Rosenthall L, Hornby L, Morais JA, Vigano A. Precision and reliability of strength (Jamar vs. Biodex handgrip) and body composition (dual-energy X-ray absorptiometry vs. bioimpedance analysis) measurements in advanced cancer patients. Appl Physiol Nutr Metab. 2008;33(6):1232–9.Google Scholar
  61. van Waart H, Stuiver MM, van Harten WH, Sonke GS, Aaronson NK. Design of the Physical exercise during Adjuvant Chemotherapy Effectiveness Study (PACES): a randomized controlled trial to evaluate effectiveness and cost-effectiveness of physical exercise in improving physical fitness and reducing fatigue. BMC Cancer. 2010;10:673.View ArticlePubMedPubMed CentralGoogle Scholar

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© Reichardt et al. 2016