Development of machine learning models to predict cancer-related fatigue in Dutch breast cancer survivors up to 15 years after diagnosis.

PURPOSE: To prevent (chronic) cancer-related fatigue (CRF) after breast cancer, it is important to identify survivors at risk on time. In literature, factors related to CRF are identified, but not often linked to individual risks. Therefore, our aim was to predict individual risks for developing CRF. METHODS: Two pre-existing datasets were used. The Nivel-Primary Care Database and the Netherlands Cancer Registry (NCR) formed the Primary Secondary Cancer Care Registry (PSCCR). NCR data with Patient Reported Outcomes Following Initial treatment and Long-term Evaluation of Survivorship (PROFILES) data resulted in the PSCCR-PROFILES dataset. Predictors were patient, tumor and treatment characteristics, and pre-diagnosis health. Fatigue was GP-reported (PSCCR) or patient-reported (PSCCR-PROFILES). Machine learning models were developed, and performances compared using the C-statistic. RESULTS: In PSCCR, 2224/12813 (17%) experienced fatigue up to 7.6 ± 4.4 years after diagnosis. In PSCCR-PROFILES, 254 (65%) of 390 patients reported fatigue 3.4 ± 1.4 years after diagnosis. For both, models predicted fatigue poorly with best C-statistics of 0.561 ± 0.006 (PSCCR) and 0.669 ± 0.040 (PSCCR-PROFILES). CONCLUSION: Fatigue (GP-reported or patient-reported) could not be predicted accurately using available data of the PSCCR and PSCCR-PROFILES datasets. IMPLICATIONS FOR CANCER SURVIVORS: CRF is a common but underreported problem after breast cancer. We aimed to develop a model that could identify individuals with a high risk of developing CRF, ideally to help them prevent (chronic) CRF. As our models had poor predictive abilities, they cannot be used for this purpose yet. Adding patient-reported data as predictor could lead to improved results. Until then, awareness for CRF stays crucial.

A holistic profile for cancer-related fatigue for women with breast cancer - a qualitative study.

Objective: Cancer- related fatigue (CRF) is one of the most reported long-term effects after breast cancer and severely impacts quality of life. To come towards optimal treatment of multidimensional CRF, the first step is to use a holistic approach to develop a holistic patient profile including the patient's experience and impact of CRF on their life. Methods and measures: Four semi- structured focus groups with twenty- seven breast cancer patients and fourteen interviews with healthcare professionals (HCPs) were held. Reflexive thematic analysis was used to define (sub)themes for the holistic patient profile. The themes of the interviews and focus groups were compared for validity. Results: Breast cancer patients and HCPs described the same five major themes, consisting of experience of CRF, impact and consequences, coping, personality, and CRF treatment. Experience of CRF consists of cognitive, emotional, and physical aspects. Impact and consequences include work, family, partner relation, social contact and hobbies, body, and misunderstanding. Coping consists of twelve (mal)adaptive strategies. Personality and CRF treatment were summarised as themes. Conclusions: A first holistic patient profile was introduced for CRF for breast cancer. This profile can be conceptualized into a questionnaire to collect information for personalized treatment recommendations and monitoring of CRF over time.

Prediction of Physical Activity Patterns in Older Patients Rehabilitating After Hip Fracture Surgery: Exploratory Study.

BACKGROUND: Building up physical activity is a highly important aspect in an older patient's rehabilitation process after hip fracture surgery. The patterns of physical activity during rehabilitation are associated with the duration of rehabilitation stay. Predicting physical activity patterns early in the rehabilitation phase can provide patients and health care professionals an early indication of the duration of rehabilitation stay as well as insight into the degree of patients' recovery for timely adaptive interventions. OBJECTIVE: This study aims to explore the early prediction of physical activity patterns in older patients rehabilitating after hip fracture surgery at a skilled nursing home. METHODS: The physical activity of patients aged ≥70 years with surgically treated hip fracture was continuously monitored using an accelerometer during rehabilitation at a skilled nursing home. Physical activity patterns were described in our previous study, and the 2 most common patterns were used in this study for pattern prediction: the upward linear pattern (n=15) and the S-shape pattern (n=23). Features from the intensity of physical activity were calculated for time windows with different window sizes of the first 5, 6, 7, and 8 days to assess the early rehabilitation moment in which the patterns could be predicted most accurately. Those features were statistical features, amplitude features, and morphological features. Furthermore, the Barthel Index, Fracture Mobility Score, Functional Ambulation Categories, and the Montreal Cognitive Assessment score were used as clinical features. With the correlation-based feature selection method, relevant features were selected that were highly correlated with the physical activity patterns and uncorrelated with other features. Multiple classifiers were used: decision trees, discriminant analysis, logistic regression, support vector machines, nearest neighbors, and ensemble classifiers. The performance of the prediction models was assessed by calculating precision, recall, and F1-score (accuracy measure) for each individual physical activity pattern. Furthermore, the overall performance of the prediction model was calculated by calculating the F1-score for all physical activity patterns together. RESULTS: The amplitude feature describing the overall intensity of physical activity on the first day of rehabilitation and the morphological features describing the shape of the patterns were selected as relevant features for all time windows. Relevant features extracted from the first 7 days with a cosine k-nearest neighbor model reached the highest overall prediction performance (micro F1-score=1) and a 100% correct classification of the 2 most common physical activity patterns. CONCLUSIONS: Continuous monitoring of the physical activity of older patients in the first week of hip fracture rehabilitation results in an early physical activity pattern prediction. In the future, continuous physical activity monitoring can offer the possibility to predict the duration of rehabilitation stay, assess the recovery progress during hip fracture rehabilitation, and benefit health care organizations, health care professionals, and patients themselves.

Early Warning Scores to Support Continuous Wireless Vital Sign Monitoring for Complication Prediction in Patients on Surgical Wards: Retrospective Observational Study.

BACKGROUND: Wireless vital sign sensors are increasingly being used to monitor patients on surgical wards. Although early warning scores (EWSs) are the current standard for the identification of patient deterioration in a ward setting, their usefulness for continuous monitoring is unknown. OBJECTIVE: This study aimed to explore the usability and predictive value of high-rate EWSs obtained from continuous vital sign recordings for early identification of postoperative complications and compares the performance of a sensor-based EWS alarm system with manual intermittent EWS measurements and threshold alarms applied to individual vital sign recordings (single-parameter alarms). METHODS: Continuous vital sign measurements (heart rate, respiratory rate, blood oxygen saturation, and axillary temperature) collected with wireless sensors in patients on surgical wards were used for retrospective simulation of EWSs (sensor EWSs) for different time windows (1-240 min), adopting criteria similar to EWSs based on manual vital signs measurements (nurse EWSs). Hourly sensor EWS measurements were compared between patients with (event group: 14/46, 30%) and without (control group: 32/46, 70%) postoperative complications. In addition, alarms were simulated for the sensor EWSs using a range of alarm thresholds (1-9) and compared with alarms based on nurse EWSs and single-parameter alarms. Alarm performance was evaluated using the sensitivity to predict complications within 24 hours, daily alarm rate, and false discovery rate (FDR). RESULTS: The hourly sensor EWSs of the event group (median 3.4, IQR 3.1-4.1) was significantly higher (P<.004) compared with the control group (median 2.8, IQR 2.4-3.2). The alarm sensitivity of the hourly sensor EWSs was the highest (80%-67%) for thresholds of 3 to 5, which was associated with alarm rates of 2 (FDR=85%) to 1.2 (FDR=83%) alarms per patient per day respectively. The sensitivity of sensor EWS-based alarms was higher than that of nurse EWS-based alarms (maximum=40%) but lower than that of single-parameter alarms (87%) for all thresholds. In contrast, the (false) alarm rates of sensor EWS-based alarms were higher than that of nurse EWS-based alarms (maximum=0.6 alarm/patient/d; FDR=80%) but lower than that of single-parameter alarms (2 alarms/patient/d; FDR=84%) for most thresholds. Alarm rates for sensor EWSs increased for shorter time windows, reaching 70 alarms per patient per day when calculated every minute. CONCLUSIONS: EWSs obtained using wireless vital sign sensors may contribute to the early recognition of postoperative complications in a ward setting, with higher alarm sensitivity compared with manual EWS measurements. Although hourly sensor EWSs provide fewer alarms compared with single-parameter alarms, high false alarm rates can be expected when calculated over shorter time spans. Further studies are recommended to optimize care escalation criteria for continuous monitoring of vital signs in a ward setting and to evaluate the effects on patient outcomes.

A Digital Coach (E-Supporter 1.0) to Support Physical Activity and a Healthy Diet in People With Type 2 Diabetes: Acceptability and Limited Efficacy Testing.

BACKGROUND: A healthy lifestyle, including regular physical activity and a healthy diet, is increasingly part of type 2 diabetes (T2D) management. As many people with T2D have difficulty living and maintaining a healthy lifestyle, there is a need for effective interventions. eHealth interventions that incorporate behavior change theories and tailoring are considered effective tools for supporting a healthy lifestyle. The E-Supporter 1.0 digital coach contains eHealth content for app-based eHealth interventions and offers tailored coaching regarding physical activity and a healthy diet for people with T2D. OBJECTIVE: This study aimed to assess the acceptability of E-Supporter 1.0 and explore its limited efficacy on physical activity, dietary behavior, the phase of behavior change, and self-efficacy levels. METHODS: Over a span of 9 weeks, 20 individuals with T2D received daily motivational messages and weekly feedback derived from behavioral change theories and determinants through E-Supporter 1.0. The acceptability of the intervention was assessed using telephone-conducted, semistructured interviews. The interview transcripts were coded using inductive thematic analysis. The limited efficacy of E-Supporter 1.0 was explored using the Fitbit Charge 2 to monitor step count to assess physical activity and questionnaires to assess dietary behavior (using the Dutch Healthy Diet index), phase of behavior change (using the single-question Self-Assessment Scale Stages of Change), and self-efficacy levels (using the Exercise Self-Efficacy Scale). RESULTS: In total, 5 main themes emerged from the interviews: perceptions regarding remote coaching, perceptions regarding the content, intervention intensity and duration, perceived effectiveness, and overall appreciation. The participants were predominantly positive about E-Supporter 1.0. Overall, they experienced E-Supporter 1.0 as a useful and easy-to-use intervention to support a better lifestyle. Participants expressed a preference for combining E-Supporter with face-to-face guidance from a health care professional. Many participants found the intensity and duration of the intervention to be acceptable, despite the coaching period appearing relatively short to facilitate long-term behavior maintenance. As expected, the degree of tailoring concerning the individual and external factors that influence a healthy lifestyle was perceived as limited. The limited efficacy testing showed a significant improvement in the daily step count (z=-2.040; P=.04) and self-efficacy levels (z=-1.997; P=.046) between baseline and postintervention. Diet was improved through better adherence to Dutch dietary guidelines. No significant improvement was found in the phase of behavior change (P=.17), as most participants were already in the maintenance phase at baseline. CONCLUSIONS: On the basis of this explorative feasibility study, we expect E-Supporter 1.0 to be an acceptable and potentially useful intervention to promote physical activity and a healthy diet in people with T2D. Additional work needs to be done to further tailor the E-Supporter content and evaluate its effects more extensively on lifestyle behaviors.

Patterns of physical activity over time in older patients rehabilitating after hip fracture surgery: a preliminary observational study.

BACKGROUND: To investigate patterns of continuously monitored physical activity in older patients rehabilitating after hip fracture surgery and the association with patient characteristics. METHODS: Physical activity of surgically treated hip fracture patients aged 70 years or older, who were rehabilitating at a skilled nursing home, was continuously monitored using a tri-axial accelerometer. The intensity of physical activity per day was calculated from the accelerometer signals to describe the daily physical activity levels of the enrolled patients. The patterns of three different aspects of physical activity were investigated: overall physical activity, overall variability, and day-to-day variability. Two experts in the geriatric rehabilitation field helped identifying unique physical activity patterns for each aspect based on visual analysis. Eighteen healthcare professionals independently classified each patient in one of the predefined patterns for each aspect. Differences between physical activity patterns and patient characteristics were assessed using a Kruskal-Wallis or Fisher's Exact Test. RESULTS: Physical activity data from 66 older patients were used in this preliminary study. A total of six unique patterns were identified for overall physical activity and overall variability, and five unique patterns for the day-to-day variability. The most common pattern found for the overall physical activity and day-to-day variability had a S-shape, which first slowly increased, then steeply increased, and subsequently flattened (n = 23, 34.8%). A N-shape pattern was found the most common pattern for overall variability, which first slowly increased, then steeply increased, then decreased and lastly increased (n = 14, 21.2%). The functionality at admission to rehabilitation, measured with the Barthel Index, and the duration of rehabilitation stay differed between the patterns of physical activity. CONCLUSIONS: Multiple patterns of physical activity among older patients during hip fracture rehabilitation were found in this preliminary study. The functionality at admission to rehabilitation and the duration of rehabilitation stay were associated with the different patterns found in this study. Results of this study highlight the importance of personalized hip fracture treatment.

Transparency in hip fracture recovery over institutional boundaries: The transmural monitoring pathway.

OBJECTIVES: To develop a transmural pathway for healthcare professionals across institutions to monitor the recovery of hip fracture patients. The secondary objectives were to evaluate the pathway's feasibility and initial outcomes. DESIGN: Prospective cohort study. METHOD: Stakeholders of the hospital and geriatric rehabilitation institutions implemented a transmural monitoring pathway in which different geriatric health domains were monitored during three phases: The in-hospital, inpatient rehabilitation, and outpatient follow-up phase. The outcomes for the first 291 patients and the feasibility of the pathway were evaluated. If the outcomes of the clinimetrics significantly improved over time, progress in functional recovery was assumed. Feasibility was assessed according to the rate of adherence to the clinimetric tests. RESULTS: During the in-hospital phase, patients showed a decline in functional level (the Katz index of independence in Activities of Daily Living (Katz-ADL) pre-fracture vs. discharge: 0 (0-2) vs. 4 (4-5), P < 0.001). Patients, in which 78.6% (n = 140) had cognitive impairment and 41.2% had malnutrition, showed the most progress (Katz-ADL 2 (1-3)) during the inpatient rehabilitation phase. In the outpatient follow-up phase, recovery remained ongoing, but most patients had not returned to their pre-fracture functional levels (Katz-ADL 1 (1-3)). The pathway feasibility during the first phase was excellent (>85%), whereas room for improvement existed during other phases (<85%). CONCLUSION: The transmural monitoring pathway provides insight into the entire recovery process for all involved healthcare professionals. Patients showed the most progress during the rehabilitation phase. The pathway feasibility was excellent during the in-hospital phase, but improvements could be made during other phases.

Validity and reliability of Eforto®, a system to (self-)monitor grip strength and muscle fatigability in older persons.

INTRODUCTION: We developed Eforto®, an innovative system for (self-)monitoring of grip strength (GS) and muscle fatigability (Fatigue Resistance (FR = time until GS decreased to 50% of maximum during sustained contraction) and grip work (GW = area under the strength-time curve)). The Eforto® system consists of a rubber bulb that is wirelessly connected to a smartphone-based application, and a telemonitoring platform. The aim was to evaluate the validity and reliability of Eforto® to measure muscle fatigability. METHODS: Community-dwelling older persons (n = 61), geriatric inpatients (n = 26) and hip fracture patients (n = 25) were evaluated for GS and muscle fatigability. In community dwellers fatigability was tested twice in the clinic (once with Eforto®, once with Martin Vigorimeter (MV), standard analog handgrip system) and for six consecutive days as a self-assessment at home with Eforto®. In hospitalized participants, fatigability was tested twice using Eforto®, once by a researcher and once by a health professional. RESULTS: Criterion validity was supported by good to excellent correlations between Eforto® and MV for GS (r = 0.95) and muscle fatigability (FR r = 0.81 and GW r = 0.73), and no significant differences in measurements between both systems. Inter-rater and intra-rater reliability for GW were moderate to excellent (intra-class correlation: 0.59-0.94). The standard error of measurement for GW was small for geriatric inpatients and hip fracture patients (224.5 and 386.5 kPa*s) and higher for community-dwellers (661.5 kPa*s). DISCUSSION/CONCLUSION: We established the criterion validity and reliability of Eforto® in older community-dwelling persons and hospitalized patients, supporting the implementation of Eforto® for (self-)monitoring of muscle fatigability.

A Digital Lifestyle Coach (E-Supporter 1.0) to Support People With Type 2 Diabetes: Participatory Development Study.

BACKGROUND: A healthy lifestyle, including regular physical activity and a healthy diet, is becoming increasingly important in the treatment of chronic diseases. eHealth interventions that incorporate behavior change techniques (BCTs) and dynamic tailoring strategies could effectively support a healthy lifestyle. E-Supporter 1.0 is an eCoach designed to support physical activity and a healthy diet in people with type 2 diabetes (T2D). OBJECTIVE: This paper aimed to describe the systematic development of E-Supporter 1.0. METHODS: Our systematic design process consisted of 3 phases. The definition phase included the selection of the target group and formulation of intervention objectives, and the identification of behavioral determinants based on which BCTs were selected to apply in the intervention. In the development phase, intervention content was developed by specifying tailoring variables, intervention options, and decision rules. In the last phase, E-Supporter 1.0 integrated in the Diameter app was evaluated using a usability test in 9 people with T2D to assess intervention usage and acceptability. RESULTS: The main intervention objectives were to stimulate light to moderate-vigorous physical activities or adherence to the Dutch dietary guidelines in people with T2D. The selection of behavioral determinants was informed by the health action process approach and theories explaining behavior maintenance. BCTs were included to address relevant behavioral determinants (eg, action control, self-efficacy, and coping planning). Development of the intervention resulted in 3 types of intervention options, consisting of motivational messages, behavioral feedback, and tailor-made supportive exercises. On the basis of IF-THEN rules, intervention options could be tailored to, among others, type of behavioral goal and (barriers to) goal achievement. Data on these variables could be collected using app data, activity tracker data, and daily ecological momentary assessments. Usability testing revealed that user experiences were predominantly positive, despite some problems in the fixed delivery of content. CONCLUSIONS: The systematic development approach resulted in a theory-based and dynamically tailored eCoach. Future work should focus on expanding intervention content to other chronic diseases and lifestyle behaviors, enhancing the degree of tailoring and evaluating intervention effects on acceptability, use, and cost-effectiveness.

Patient preference attributes in eHealth interventions for cancer-related fatigue: A scoping review.

INTRODUCTION: Cancer-related fatigue (CRF) is one of the most reported long-term effects breast cancer patients experience after diagnosis. Many interventions for CRF are effective, however, not for every individual. Therefore, intervention advice should be adjusted to patients' preferences and characteristics. Our aim was to develop an overview of eHealth interventions and their (preference sensitive) attributes. METHODS: eHealth interventions were identified using a scoping review approach. Eligible studies included breast cancer patients and assessed CRF as outcome. Interventions were categorised as physical activity, mind-body, psychological, 'other' or 'combination'. Information was extracted on various (preference sensitive) attributes, like duration, intensity, peer support and costs. RESULTS: Thirty-five interventions were included and divided over the intervention categories. (Preference sensitive) attributes varied both within and between these categories. Duration varied from 4 weeks to 6 months, intensity from daily to own pace. Peer support was present in seven interventions and costs were known for six. CONCLUSION: eHealth interventions exist in various categories, additionally, there is much variation in (preference sensitive) attributes. This provides opportunities to implement our overview for personalised treatment recommendations for breast cancer patients struggling with CRF. Taking into account patients' preferences and characteristics suits the complexity of CRF and heterogeneity of patients.

An ideographic study into physiology, alcohol craving and lapses during one hundred days of daily life monitoring.

Introduction: Alcohol craving is a highly challenging obstacle to achieve long-term abstinence. Making alcohol use disorder patients timely aware of high-risk craving situations may protect them against relapse by prompting them to mobilize their coping resources. Current advances in wearable and smart-phone technology provide novel opportunities for the development of detecting these situations of heightened risk of craving, by enabling continuous tracking of fluctuations in psychological and physiological parameters. The present study therefore aims to determine the association between self-reported craving and relapses, and between heightened physiological activity. Specifically, we measured cardiovascular and electrodermal activity, and self-reported craving during one hundred days in the daily life of people trying to recover from alcoholism. The secondary aim is to study whether the association between physiology and craving can be strengthened by the inclusion of context related psychological parameters. Methods: An intensive repeated and continuous measures in naturalistic settings case-study design was employed. Ten participants were monitored with wearable bio-sensors and answered multiple questions every three hours on a smartphone app about craving, lapsing and multiple evidence based contextual variables. The association between physiology, craving and lapses was explored using Matthews correlation coefficients both with a current and 3 h lagged design. The contextual variables were included in a decision tree together with the physiological parameters to explore the added effect on the correlation of these contextual variables. Results: The association between lapses and craving was highly different across individuals, varying between a weak to a strong association. The association between cardiovascular activity and heightened self-reported craving was negligible to weak, however with a high specificity, meaning that most craving events were accompanied by increase heart rate. However, the association between electrodermal activity and craving was lower than with cardiovascular activity for most participants, both prior (lagged) and during craving. For two of the participants the association between physiology and craving improved by adding contextual variables, however, precision was too low. Conclusions: People differ strongly in their bodily reactions and psychological experiences during the first months of their addiction treatment. No individual in our study had unique one-to-one mappings between on the one hand physiological or psychological precursors, and on the other hand craving and (re)lapses. Therefore, detecting high risk craving situations with both physiological activity measured with wearables and psychological precursors to alert people specifically for an imminent (re)lapse, does not seem viable on the basis of the current results. We do see an added benefit of using physiology during treatment, as physiology can help start the conversation about possible high risk craving situations during that week. This would also help the counselor to gain added insights into the fluctuating states of the clients, and help to ameliorate the recall bias of clients. The present study showed the possibility and paved the way for future intensive longitudinal designs integrating both physiological, psychological and contextual factors during the challenging and lengthy recovery from addiction.

The Need for Objective Physical Activity Measurements in Routine Bariatric Care.

PURPOSE: This study aims to (1) quantify physical behavior through self-reports and sensor-based measures, (2) examine the correlation between self-reported and sensor-based physical activity (PA) and (3) assess whether bariatric patients adhere to PA guidelines. METHODS: A Fitbit accelerometer was used to collect minute-to-minute step count and heart rate data for 14 consecutive days. Total physical activity levels (PAL), moderate-to-vigorous intensity physical activity (MVPA) and sedentary behavior (SB) were used to quantify physical behavior. Self-reported PA was assessed with the International Physical Activity Questionnaire (IPAQ). To analyze the association between sensor-based and self-reported PA, Spearman's correlation was used. A minimum of 150 MVPA minutes per week was considered as compliance with the PA guidelines. RESULTS: Fitbit data of 37 pre- and 18 post-surgery patients was analyzed. Participants averaged 7403 ± 3243 steps/day and spent most of their time sedentary (832 min, IQR: 749 - 879), especially in prolonged periods of ≥ 30 min (525, IQR: 419 - 641). Median MVPA time was 5.6 min/day (IQR: 1.7 - 10.6). Correlations between self-reported and sensor-based MVPA and SB were respectively 0.072 and 0.455. Only 17.1% was objectively adherent to MVPA guidelines ≥ 150 min/week, while 94.3% met the guidelines in case of self-reports. CONCLUSION: PA quantification confirmed that bariatric patients are highly sedentary and rarely engage in MVPA, despite a relatively high daily step count. Moreover, bariatric patients are not able to assess MVPA and moderately their SB by self-reports. Our results indicate the need for sensor-based PA monitoring in routine bariatric care.

What web-based intervention for chronic cancer-related fatigue works best for whom? Explorative moderation analyses of a randomized controlled trial.

PURPOSE: Approximately 25% of cancer patients suffer from chronic cancer-related fatigue (CCRF), which is a complex, multifactorial condition. While there are evidence-based interventions, it remains unclear what treatment works best for the individual patient. This study explored whether baseline characteristics moderated the effect of web-based mindfulness-based cognitive therapy (eMBCT) versus ambulant activity feedback (AAF) and a psycho-education control group (PE) on fatigue in patients suffering from CCRF. METHODS: In a randomized controlled trial, participant suffering from CCRF participated in either eMBCT, AAF, or PE. Complete data of the treatment-adherent sample (≥ 6 sessions) was used to explore whether sociodemographic, clinical, and psychological characteristics at baseline moderated the intervention effect on fatigue severity at 6 months. RESULTS: A trend showed that baseline fatigue severity and fatigue catastrophizing moderated the intervention effect. That is, at low levels of fatigue severity and catastrophizing, patients benefited more from AAF than from eMBCT and at high levels of fatigue severity and catastrophizing, patients benefited more from eMBCT than from PE. CONCLUSIONS: This study found some preliminary evidence on what treatment works best for the individual suffering from CCRF. These findings emphasize the potential gain in effectiveness of personalizing treatment. An alternative approach that might help us further in answering the question "what treatment works best for whom?" is discussed.

Early identification of frailty: Developing an international delphi consensus on pre-frailty.

BACKGROUND: Frailty is associated with a prodromal stage called pre-frailty, a potentially reversible and highly prevalent intermediate state before frailty becomes established. Despite being widely-used in the literature and increasingly in clinical practice, it is poorly understood. OBJECTIVE: To establish consensus on the construct and approaches to diagnose and manage pre-frailty. METHODS: We conducted a modified (electronic, two-round) Delphi consensus study. The questionnaire included statements concerning the concept, aspects and causes, types, mechanism, assessment, consequences, prevention and management of pre-frailty. Qualitative and quantitative analysis methods were employed. An agreement level of 70% was applied. RESULTS: Twenty-three experts with different backgrounds from 12 countries participated. In total, 70 statements were circulated in Round 1. Of these, 52.8% were accepted. Following comments, 51 statements were re-circulated in Round 2 and 92.1% were accepted. It was agreed that physical and non-physical factors including psychological and social capacity are involved in the development of pre-frailty, potentially adversely affecting health and health-related quality of life. Experts considered pre-frailty to be an age-associated multi-factorial, multi-dimensional, and non-linear process that does not inevitably lead to frailty. It can be reversed or attenuated by targeted interventions. Brief, feasible, and validated tools and multidimensional assessment are recommended to identify pre-frailty. CONCLUSIONS: Consensus suggests that pre-frailty lies along the frailty continuum. It is a multidimensional risk-state associated with one or more of physical impairment, cognitive decline, nutritional deficiencies and socioeconomic disadvantages, predisposing to the development of frailty. More research is needed to agree an operational definition and optimal management strategies.

Patient compliance with postoperative precautions in an unrestricted and a supine sleeping position following posterolateral total hip arthroplasty: a randomized controlled trial.

PURPOSE: To evaluate compliance with the precaution to sleep in a supine position following total hip arthroplasty (THA) and its impact on the other precautions. MATERIALS AND METHODS: Single-center, parallel-group, stratified, randomized trial. Patients were allocated to a Restricted Group or an Unrestricted Group. This study focuses on compliance with the precaution to sleep in a supine position, compliance with the remaining set of precautions and the burden of restricted sleeping. Measurements were made using a self-administered diary and questionnaires. Trial registration number: NCT02107248. RESULTS: During the first 2 weeks, 81% of the patients in the restricted group were compliant with sleeping in a supine position.Patients in the Unrestricted Group significantly kept sleeping fewer days per week in a supine position than patients in the Restricted Group (p = 0.000). No significant differences between the two groups were found regarding compliance with the remaining set of precautions. The burden of the sleeping restriction is significantly lowered in the Unrestricted Group (p = 0.000). CONCLUSIONS: Compliance with restricting patients to sleep in a supine position is high. Removing this precaution has a significant decrease in burden for patients without affecting compliance with the remaining set of precautions. TRIAL REGISTRATION NUMBER: ClinicalTrials.gov NCT02107248 - https://clinicaltrials.gov/ct2/show/NCT02107248?term=anil+peters&draw=2&rank=1IMPLICATIONS FOR REHABILITATIONSleeping precautions cause a high rate of burden to patients, whereas movement precautions do not.By removing sleeping precautions, the burden is significantly reduced without affecting the remaining set of precautions.Compliance with movement precautions is high compared to other more functional precautions.

[Are the older patients with a hip fracture better off with a multidisciplinary approach?] / Is de oudere patiënt met heupfractuur beter af door multidisciplinaire behandeling?

Integrated orthogeriatric treatment, led by a nurse practitioner, is an important step forward in the improvement of care for older people with a hip fracture. In this paper we reflect on the study of Van Leendert et al. Their main findings are similar to the literature with a significantly reduced 1-year mortality rate in the orthogeriatric group compared to the standard care group. However, there are some remarks to be made regarding the patient characteristics that are unbalanced in favor of the orthogeriatric group, with an overrepresentation of a certain type of fracture, indicating potentially more vulnerable patients in the standard care group. Although a significant step forward, we also address that still face major challenges, that technology might be an enabler for further improvement but that it might also be time to introduce a new perspective on recovery that makes better use of the dynamics of the system.

Glucose Regulation Beyond HbA1c in Type 2 Diabetes Treated With Insulin: Real-World Evidence From the DIALECT-2 Cohort.

OBJECTIVE: To investigate glucose variations associated with glycated hemoglobin (HbA1c) in insulin-treated patients with type 2 diabetes. RESEARCH DESIGN AND METHODS: Patients included in Diabetes and Lifestyle Cohort Twente (DIALECT)-2 (n = 79) were grouped into three HbA1c categories: low, intermediate, and high (≤53, 54-62, and ≥63 mmol/mol or ≤7, 7.1-7.8, and ≥7.9%, respectively). Blood glucose time in range (TIR), time below range (TBR), time above range (TAR), glucose variability parameters, day and night duration, and frequency of TBR and TAR episodes were determined by continuous glucose monitoring (CGM) using the FreeStyle Libre sensor and compared between HbA1c categories. RESULTS: CGM was performed for a median (interquartile range) of 10 (7-12) days/patient. TIR was not different for low and intermediate HbA1c categories (76.8% [68.3-88.2] vs. 76.0% [72.5.0-80.1]), whereas in the low category, TBR was higher and TAR lower (7.7% [2.4-19.1] vs. 0.7% [0.3-6.1] and 8.2% [5.7-17.6] vs. 20.4% [11.6-27.0], respectively, P < 0.05). Patients in the highest HbA1c category had lower TIR (52.7% [40.9-67.3]) and higher TAR (44.1% [27.8-57.0]) than the other HbA1c categories (P < 0.05), but did not have less TBR during the night. All patients had more (0.06 ± 0.06/h vs. 0.03 ± 0.03/h; P = 0.002) and longer (88.0 [45.0-195.5] vs. 53.4 [34.4-82.8] minutes; P < 0.001) TBR episodes during the night than during the day. CONCLUSIONS: In this study, a high HbA1c did not reduce the occurrence of nocturnal hypoglycemia, and low HbA1c was not associated with the highest TIR. Optimal personalization of glycemic control requires the use of newer tools, including CGM-derived parameters.

Early Predictors for Discharge to Geriatric Rehabilitation after Hip Fracture Treatment of Older Patients.

OBJECTIVE: To investigate early predictors for discharge to a geriatric rehabilitation department at a skilled nursing home in older patients after hospitalization for hip fracture surgery. DESIGN: Retrospective cohort study. SETTING AND PARTICIPANTS: Data from 21,176 patients with hip fracture aged ≥70 years, who were registered in the Dutch Hip Fracture Audit database between January 1, 2017, and December 31, 2019, were included. METHODS: Patients were categorized into 3 discharge groups: home (n=7326), rehabilitation (n=11,738), and nursing home (n=2112). Age, gender, Pre-Fracture Mobility Score (PFMS), premorbid Katz index of independence in Activities of Daily Living (Katz-ADL), history of dementia, American Society of Anesthesiologists physical status classification (ASA score), type of anesthesia, fracture type, surgical treatment, and cotreatment by a geriatrician were gathered. Multinomial regression analysis was used to assess for early predictors. RESULTS: Higher age, poor premorbid mobility, lower premorbid Katz-ADL, no history of dementia, ASA score 3-5, general anesthesia, intramedullary implant, and cotreatment by a geriatrician were independent predictors for discharge to geriatric rehabilitation vs discharge home. Identical predictors were found for discharge to a nursing home vs discharge home. History of dementia and premorbid Katz-ADL were distinguishing factors; a higher premorbid Katz-ADL and a history of dementia were associated with a higher risk of discharge to a nursing home vs discharge home. The multinomial regression model correctly predicted 86%, 38.6%, and 2.4% of the patients in the rehabilitation group, home group, and nursing home group, respectively. CONCLUSIONS AND IMPLICATIONS: This study showed that age, PFMS, premorbid Katz-ADL, surgical treatment, ASA score, type of anesthesia, history of dementia, and cotreatment by a geriatrician were independent early predictors for discharge to geriatric rehabilitation vs discharge home in older patients after hip fracture surgery. Identical predictors were found as predictors for discharge to a nursing home vs discharge home, except for history of dementia and premorbid Katz-ADL.

Embodiment of Wearable Technology: Qualitative Longitudinal Study.

BACKGROUND: Current technology innovations, such as wearables, have caused surprising reactions and feelings of deep connection to devices. Some researchers are calling mobile and wearable technologies cognitive prostheses, which are intrinsically connected to individuals as if they are part of the body, similar to a physical prosthesis. Additionally, while several studies have been performed on the phenomenology of receiving and wearing a physical prosthesis, it is unknown whether similar subjective experiences arise with technology. OBJECTIVE: In one of the first qualitative studies to track wearables in a longitudinal investigation, we explore whether a wearable can be embodied similar to a physical prosthesis. We hoped to gain insights and compare the phases of embodiment (ie, initial adjustment to the prosthesis) and the psychological responses (ie, accept the prosthesis as part of their body) between wearables and limb prostheses. This approach allowed us to find out whether this pattern was part of a cyclical (ie, period of different usage intensity) or asymptotic (ie, abandonment of the technology) pattern. METHODS: We adapted a limb prosthesis methodological framework to be applied to wearables and conducted semistructured interviews over a span of several months to assess if, how, and to what extent individuals come to embody wearables similar to prosthetic devices. Twelve individuals wore fitness trackers for 9 months, during which time interviews were conducted in the following three phases: after 3 months, after 6 months, and at the end of the study after 9 months. A deductive thematic analysis based on Murray's work was combined with an inductive approach in which new themes were discovered. RESULTS: Overall, the individuals experienced technology embodiment similar to limb embodiment in terms of adjustment, wearability, awareness, and body extension. Furthermore, we discovered two additional themes of engagement/reengagement and comparison to another device or person. Interestingly, many participants experienced a rarely reported phenomenon in longitudinal studies where the feedback from the device was counterintuitive to their own beliefs. This created a blurring of self-perception and a dilemma of "whom" to believe, the machine or one's self. CONCLUSIONS: There are many similarities between the embodiment of a limb prosthesis and a wearable. The large overlap between limb and wearable embodiment would suggest that insights from physical prostheses can be applied to wearables and vice versa. This is especially interesting as we are seeing the traditionally "dumb" body prosthesis becoming smarter and thus a natural merging of technology and body. Future longitudinal studies could focus on the dilemma people might experience of whether to believe the information of the device over their own thoughts and feelings. These studies might take into account constructs, such as technology reliance, autonomy, and levels of self-awareness.

Low Physical Activity in Patients with Complicated Type 2 Diabetes Mellitus Is Associated with Low Muscle Mass and Low Protein Intake.

OBJECTIVE: In order to promote physical activity (PA) in patients with complicated type 2 diabetes, a better understanding of daily movement is required. We (1) objectively assessed PA in patients with type 2 diabetes, and (2) studied the association between muscle mass, dietary protein intake, and PA. Methods: We performed cross-sectional analyses in all patients included in the Diabetes and Lifestyle Cohort Twente (DIALECT) between November 2016 and November 2018. Patients were divided into four groups: <5000, 5000-6999, 7000-9999, ≥ 10,000 steps/day. We studied the association between muscle mass (24 h urinary creatinine excretion rate, CER) and protein intake (by Maroni formula), and the main outcome variable PA (steps/day, Fitbit Flex device) using multivariate linear regression analyses. RESULTS: In the 217 included patients, the median steps/day were 6118 (4115-8638). Of these patients, 48 patients (22%) took 7000-9999 steps/day, 37 patients (17%) took ≥ 10,000 steps/day, and 78 patients (36%) took <5000 steps/day. Patients with <5000 steps/day had, in comparison to patients who took ≥10,000 steps/day, a higher body mass index (BMI) (33 ± 6 vs. 30 ± 5 kg/m2, p = 0.009), lower CER (11.7 ± 4.8 vs. 14.8 ± 3.8 mmol/24 h, p = 0.001), and lower protein intake (0.84 ± 0.29 vs. 1.08 ± 0.22 g/kg/day, p < 0.001). Both creatinine excretion (ß = 0.26, p < 0.001) and dietary protein intake (ß = 0.31, p < 0.001) were strongly associated with PA, which remained unchanged after adjustment for potential confounders. CONCLUSIONS: Prevalent insufficient protein intake and low muscle mass co-exist in obese patients with low physical activity. Dedicated intervention studies are needed to study the role of sufficient protein intake and physical activity in increasing or maintaining muscle mass in patients with type 2 diabetes.