Older head and neck cancer patients are at increased risk for adverse health outcomes, but little is known about which geriatric assessment associates with poor outcome. The aim is to study the association of functional or cognitive impairment, social environment and frailty with adverse health outcomes in patients with head and neck cancer.
Four libraries were searched for studies reporting on an association of functional or cognitive impairment, social environment and frailty with adverse outcomes in head and neck cancer patients.
Of 4158 identified citations, 31 articles were included. The mean age was ⩾60years in twelve studies (39%). Geriatric conditions were prevalent: between 40 and 50% of the included participants were functional impaired, around 50% had depressive symptoms, and around 40% did not have a partner. Functional impairment was assessed in 18 studies, two studies reported on a cognitive test, eight studies examined mood and social status was depicted by 14 studies. None of the included studies addressed frailty or objectively measured physical capacity such as hand grip strength, gait speed or balance tests. In 64% of the reported associations, a decline in functional or cognitive impairment, mood or social environment was associated with adverse outcomes.
Functional and cognitive impairment, depressive symptoms and social isolation are highly prevalent in head and neck cancer patients and associate with high risk of adverse health outcomes. In the future, these measurements may guide decision-making and customize treatments, but more research is needed to further improve and firmly establish clinical usability.
Background: Older patients experience high rates of adverse outcomes after an emergency department (ED) visit. Early identification of those at high risk could guide preventive interventions and tailored treatment decisions, but available models perform poorly in discriminating those at highest risk. The present study aims to develop and validate a prediction model for functional decline and mortality in older patients presenting to the ED.
Methods: A prospective follow-up study in patients aged ≥ 70, attending the EDs of the LUMC, the Netherlands (derivation) and Alrijne Hospital, the Netherlands (validation) was conducted. A baseline assessment was performed and the main outcome, a composite of functional decline and mortality, was obtained after 90 days of follow-up.
Results: In total 751 patients were enrolled in the Leiden University Medical Center of whom 230 patients (30.6%) experienced the composite outcome and 71 patients (9.5%) died. The final model for the composite outcome resulted in an area under the curve (AUC) of 0.73 (95% CI 0.67-0.77) and was experienced in 69% of the patients at highest risk. For mortality the AUC was 0.79 (95% CI 0.73-0.85) and 36% of the patients at highest risk died. External validation in 881 patients of Alrijne Hospital showed an AUC of 0.71 (95% CI 0.67-0.75) for the composite outcome and 0.67 (95% CI 0.60-0.73) for mortality.
Conclusion: We successfully developed and validated prediction models for 90-day composite outcome and 90-day mortality in older emergency patients. The benefits for patient management by implementing these models with preventive interventions have to be investigated.
Background and objectives: Older patients reaching ESRD have a higher risk of adverse health outcomes. We aimed to determine the association of functional and cognitive impairment and frailty with adverse health outcomes in patients reaching ESRD. Understanding these associations could ultimately lead to prediction models to guide tailored treatment decisions or preventive interventions.
Design, setting, participants, & measurements: We searched MEDLINE, Embase, Web of Science, CENTRAL, CINAHL, PsycINFO, and COCHRANE for original studies published until February 8, 2016 reporting on the association of functional or cognitive impairment or frailty with adverse health outcome after follow-up in patients reaching ESRD either with or without RRT.
Results: Of 7451 identified citations, we included 30 articles that reported on 35 associations. Mean age was >60 years old in 73% of the studies, and geriatric conditions were highly prevalent. Twenty-four studies (80%) reported on functional impairment, seven (23%) reported on cognitive impairment, and four (13%) reported on frailty. Mortality was the main outcome measure in 29 studies (97%), and one study assessed functional status trajectory. In 34 of 35 (97%) associations reported, functional or cognitive impairment or frailty was significantly and independently associated with adverse health outcomes. The majority of studies (83%) were conducted in selected patient populations, mainly patients on incident dialysis.
Conclusions: Functional and cognitive impairment and frailty in patients reaching ESRD are highly prevalent and strongly and independently associated with adverse health outcomes, and they may, therefore, be useful for risk stratification. More research into their prognostic value is needed.
Background: Older people frequently attend the emergency department (ED) and have a high risk of poor outcome as compared to their younger counterparts. Our aim was to study routinely collected clinical parameters as predictors of 90-day mortality in older patients attending our ED.
Methods: We conducted a retrospective follow-up study at the Leiden University Medical Center (The Netherlands) among patients aged 70 years or older attending the ED in 2012. Predictors were age, gender, time and way of arrival, presenting complaint, consulting medical specialty, vital signs, pain score and laboratory testing. Cox regression analyses were performed to analyse the association between these predictors and 90-day mortality.
Results: Three thousand two hundred one unique patients were eligible for inclusion. Ninety-day mortality was 10.5 % for the total group. Independent predictors of mortality were age (hazard ratio [HR] 1.06, 95 % confidence interval [95 % CI] 1.04-1.08), referral from another hospital (HR 2.74, 95 % CI 1.22-6.11), allocation to a non-surgical specialty (HR: 1.55, 95 % CI 1.13-2.14), increased respiration rate (HR up to 2.21, 95 % CI 1.25-3.92), low oxygen saturation (HR up to 1.96, 95 % CI 1.19-3.23), hypothermia (HR 2.27, 95 % CI 1.28-4.01), fever (HR 0.43, 95 % CI 0.24-0.75), high pain score (HR 1.55, 95 % CI 1.03-2.32) and the indication to perform laboratory testing (HR 3.44, 95 % CI 2.13-5.56).
Conclusions: Routinely collected parameters at the ED can predict 90-day mortality in older patients presenting to the ED. This study forms the first step towards creating a new and simple screening tool to predict and improve health outcome in acutely presenting older patients.
In epidemiology, the regression discontinuity design has received increasing attention recently and might be an alternative to randomized controlled trials (RCTs) to evaluate treatment effects. In regression discontinuity, treatment is assigned above a certain threshold of an assignment variable for which the treatment effect is adjusted in the analysis. We performed simulations and a validation study in which we used treatment effect estimates from an RCT as the reference for a prospectively performed regression discontinuity study. We estimated the treatment effect using linear regression adjusting for the assignment variable both as linear terms and restricted cubic spline and using local linear regression models. In the first validation study, the estimated treatment effect from a cardiovascular RCT was -4.0 mmHg blood pressure (95% confidence interval: -5.4, -2.6) at 2 years after inclusion. The estimated effect in regression discontinuity was -5.9 mmHg (95% confidence interval: -10.8, -1.0) with restricted cubic spline adjustment. Regression discontinuity showed different, local effects when analyzed with local linear regression. In the second RCT, regression discontinuity treatment effect estimates on total cholesterol level at 3 months after inclusion were similar to RCT estimates, but at least six times less precise. In conclusion, regression discontinuity may provide similar estimates of treatment effects to RCT estimates, but requires the assumption of a global treatment effect over the range of the assignment variable. In addition to a risk of bias due to wrong assumptions, researchers need to weigh better recruitment against the substantial loss in precision when considering a study with regression discontinuity versus RCT design.
Background: Mobile phone-assisted technologies provide the opportunity to optimize the feasibility of long-term blood pressure (BP) monitoring at home, with the potential of large-scale data collection.
Objective: In this proof-of-principle study, we evaluated the feasibility of home BP monitoring using mobile phone-assisted technology, by investigating (1) the association between study center and home BP measurements; (2) adherence to reminders on the mobile phone to perform home BP measurements; and (3) referrals, treatment consequences and BP reduction after a raised home BP was diagnosed.
Methods: We used iVitality, a research platform that comprises a Website, a mobile phone-based app, and health sensors, to measure BP and several other health characteristics during a 6-month period. BP was measured twice at baseline at the study center. Home BP was measured on 4 days during the first week, and thereafter, at semimonthly or monthly intervals, for which participants received reminders on their mobile phone. In the monthly protocol, measurements were performed during 2 consecutive days. In the semimonthly protocol, BP was measured at 1 day.
Results: We included 151 participants (mean age [standard deviation] 57.3 [5.3] years). BP measured at the study center was systematically higher when compared with home BP measurements (mean difference systolic BP [standard error] 8.72 [1.08] and diastolic BP 5.81 [0.68] mm Hg, respectively). Correlation of study center and home measurements of BP was high (R=0.72 for systolic BP and 0.72 for diastolic BP, both P<.001). Adherence was better in participants measuring semimonthly (71.4%) compared with participants performing monthly measurements (64.3%, P=.008). During the study, 41 (27.2%) participants were referred to their general practitioner because of a high BP. Referred participants had a decrease in their BP during follow-up (mean difference final and initial [standard error] −5.29 [1.92] for systolic BP and −2.93 [1.08] for diastolic BP, both P<.05).
Conclusion: Mobile phone-assisted technology is a reliable and promising method with good adherence to measure BP at home during a 6-month period. This provides a possibility for implementation in large-scale studies and can potentially contribute to BP reduction.
Background: Increasing physical activity is a viable strategy for improving both the health and quality of life of older adults.
Objective: The aim of this study was to assess if an Internet-based intervention aimed to increase physical activity was effective in improving quality of life of inactive older adults. In addition, we analyzed the effect of the intervention on quality of life among those participants who successfully reached their individually targeted increase in daily physical activity as indicated by the intervention program, as well as the dose-response effect of increasing physical activity on quality of life.
Methods: The intervention was tested in a randomized controlled trial and was comprised of an Internet program—DirectLife (Philips)—aimed at increasing physical activity using monitoring and feedback by accelerometry and feedback by digital coaching (n=119). The control group received no intervention (n=116). Participants were inactive 60-70-year-olds and were recruited from the general population. Quality of life and physical activity were measured at baseline and after 3 months using the Research ANd Development 36-item health survey (RAND-36) and wrist-worn triaxial accelerometer, respectively.
Results: After 3 months, a significant improvement in quality of life was seen in the intervention group compared to the control group for RAND-36 subscales on emotional and mental health (2.52 vs -0.72, respectively; P=.03) and health change (8.99 vs 2.03, respectively; P=.01). A total of 50 of the 119 participants (42.0%) in the intervention group successfully reached their physical activity target and showed a significant improvement in quality of life compared to the control group for subscales on emotional and mental health (4.31 vs -0.72, respectively; P=.009) and health change (11.06 vs 2.03, respectively; P=.004). The dose-response analysis showed that there was a significant association between increase in minutes spent in moderate-to-vigorous physical activity (MVPA) and increase in quality of life.
Conclusions: Our study shows that an Internet-based physical activity program was effective in improving quality of life in 60-70-year-olds after 3 months, particularly in participants that reached their individually targeted increase in daily physical activity.
Acutely hospitalized older patients have an increased risk of mortality, but at the moment of presentation this risk is difficult to assess. Early identification of patients at high risk might increase the awareness of the physician, and enable tailored decision-making. Existing screening instruments mainly use either geriatric factors or severity of disease for prognostication. Predictive performance of these instruments is moderate, which hampers successive interventions. We conducted a retrospective cohort study among all patients aged 70 years and over who were acutely hospitalized in the Acute Medical Unit of the Leiden University Medical Center, the Netherlands in 2012. We developed a prediction model for 90-day mortality that combines vital signs and laboratory test results reflecting severity of disease with geriatric factors, represented by comorbidities and number of medications. Among 517 patients, 94 patients (18.2 %) died within 90 days after admission. Six predictors of mortality were included in a model for mortality: oxygen saturation, Charlson comorbidity index, thrombocytes, urea, C-reactive protein and non-fasting glucose. The prediction model performs satisfactorily with an 0.738 (0.667–0.798). Using this model, 53 % of the patients in the highest risk decile (N = 51) were deceased within 90 days. In conclusion, we are able to predict 90-day mortality in acutely hospitalized older patients using a model with directly available clinical data describing disease severity and geriatric factors. After further validation, such a model might be used in clinical decision making in older patients.
Background: The iVitality online research platform has been developed to gain insight into the relationship between early risk factors (ie, poorly controlled hypertension, physical or mental inactivity) and onset and possibly prevention of dementia. iVitality consists of a website, a smartphone application, and sensors that can monitor these indicators at home. Before iVitality can be implemented, it should fit the needs and preferences of users, ie, offspring of patients with dementia. This study aimed to explore users’ motivation to participate in home-based health monitoring research, to formulate requirements based on users’ preferences to optimize iVitality, and to test usability of the smartphone application of iVitality.
Methods: We recruited 13 participants (aged 42-64 years, 85% female), who were offspring of patients with dementia. A user-centered methodology consisting of four iterative phases was used. Three semistructured interviews provided insight into motivation and acceptance of using iVitality (phase 1). A focus group with six participants elaborated on expectations and preferences regarding iVitality (phase 2). Findings from phase 1 and 2 were triangulated by two semistructured interviews (phase 3). Four participants assessed the usability of the smartphone application (phase 4) using a think aloud procedure and a questionnaire measuring ease and efficiency of use (scale 1-7; higher scores indicated better usability).
Results: All participants were highly motivated to contribute to dementia research. However, the frequency of home-based health monitoring should not be too high. Participants preferred to receive feedback about their measurements and information regarding the relationship between these measurements and dementia. Despite minor technical errors, iVitality was considered easy and efficient to use (mean score 5.50, standard deviation 1.71).
Conclusion: Offspring of patients with dementia are motivated to contribute to home-based monitoring research by using iVitality and are able to use the smartphone application. The formulated requirements will be embedded to optimize iVitality.
Evidence-based medicine (EBM) aims to integrate three elements in patient care: the patient situation, scientific evidence, and the doctors’ expertise. This review aims 1) to assess how these elements are systematically different in older patients and 2) to propose strategies how to improve EBM in older patients.
The ageing process systematically affects all three elements that constitute EBM. First, ageing changes the physiology of the older body, makes the patient more vulnerable with more multimorbidity and polypharmacy and affects somatic, psychological and social function. The heterogeneity of older patients may lead to overtreatment of vulnerable and undertreatment of fit older patients. Second, representative older patients are underrepresented in clinical studies and endpoints studied may not reflect the specific needs of older patients. Third, adequate clinical tools and schooling are lacking to aid physicians in clinical decision-making. Strategies to improve elements of EBM include: first systematically acknowledging that physical, mental and social function may reveal patients’ vulnerability and specific treatment goals. Second, clinical studies specifically targeting more representative older patients and studying endpoints relevant to older patients are warranted. Finally, teaching of physicians may increase their experience and expertise in treating older patients. In conclusion, in older patients the same elements constitute EBM, but the elements need tailoring to the older patient. In the clinic, a thorough assessment of individual patient preferences and physical, mental and social functioning in combination with increased level of experience of the doctor can increase the quality of EBM in older patients.