The purpose of the research we undertook for this Conference Paper was to investigate whether marketing campaigns for specific types of drinks could be directed towards age cohorts rather than towards intercultural differences between countries. We developed consumer profiles based on drinking motives and drinking behavior by age cohorts. We hypothesized that differences between countries in the youngest age groups are smaller than in the older age groups, where country specific tradition and culture still plays a more prominent role. We, therefore tested, from the data obtained by the COnsumer BEhaviouR Erasmus Network (COBEREN), the hypothesis that the extent to which the age specific profiles differ between countries increases with age. The results confirm our hypothesis that the extent to which drinking motives differ between countries increases with age. Our results suggest that marketing campaigns which are directed towards drinking motives, could best be tailored by age cohort, in particular when it concerns age group 18-37 and more particular for beer, spirits and especially premix drinks. Marketing campaigns for non-alcoholic beverages should be made specific for the British countries and the Western countries, but even more effectively be made specific for the age cohort 18-37.
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INTRODUCTION: Patients with COVID-19-related acute respiratory distress syndrome (ARDS) have been postulated to present with distinct respiratory subphenotypes. However, most phenotyping schema have been limited by sample size, disregard for temporal dynamics, and insufficient validation. We aimed to identify respiratory subphenotypes of COVID-19-related ARDS using unbiased data-driven approaches.METHODS: PRoVENT-COVID was an investigator-initiated, national, multicentre, prospective, observational cohort study at 22 intensive care units (ICUs) in the Netherlands. Consecutive patients who had received invasive mechanical ventilation for COVID-19 (aged 18 years or older) served as the derivation cohort, and similar patients from two ICUs in the USA served as the replication cohorts. COVID-19 was confirmed by positive RT-PCR. We used latent class analysis to identify subphenotypes using clinically available respiratory data cross-sectionally at baseline, and longitudinally using 8-hourly data from the first 4 days of invasive ventilation. We used group-based trajectory modelling to evaluate trajectories of individual variables and to facilitate potential clinical translation. The PRoVENT-COVID study is registered with ClinicalTrials.gov, NCT04346342.FINDINGS: Between March 1, 2020, and May 15, 2020, 1007 patients were admitted to participating ICUs in the Netherlands, and included in the derivation cohort. Data for 288 patients were included in replication cohort 1 and 326 in replication cohort 2. Cross-sectional latent class analysis did not identify any underlying subphenotypes. Longitudinal latent class analysis identified two distinct subphenotypes. Subphenotype 2 was characterised by higher mechanical power, minute ventilation, and ventilatory ratio over the first 4 days of invasive mechanical ventilation than subphenotype 1, but PaO2/FiO2, pH, and compliance of the respiratory system did not differ between the two subphenotypes. 185 (28%) of 671 patients with subphenotype 1 and 109 (32%) of 336 patients with subphenotype 2 had died at day 28 (p=0·10). However, patients with subphenotype 2 had fewer ventilator-free days at day 28 (median 0, IQR 0-15 vs 5, 0-17; p=0·016) and more frequent venous thrombotic events (109 [32%] of 336 patients vs 176 [26%] of 671 patients; p=0·048) compared with subphenotype 1. Group-based trajectory modelling revealed trajectories of ventilatory ratio and mechanical power with similar dynamics to those observed in latent class analysis-derived trajectory subphenotypes. The two trajectories were: a stable value for ventilatory ratio or mechanical power over the first 4 days of invasive mechanical ventilation (trajectory A) or an upward trajectory (trajectory B). However, upward trajectories were better independent prognosticators for 28-day mortality (OR 1·64, 95% CI 1·17-2·29 for ventilatory ratio; 1·82, 1·24-2·66 for mechanical power). The association between upward ventilatory ratio trajectories (trajectory B) and 28-day mortality was confirmed in the replication cohorts (OR 4·65, 95% CI 1·87-11·6 for ventilatory ratio in replication cohort 1; 1·89, 1·05-3·37 for ventilatory ratio in replication cohort 2).INTERPRETATION: At baseline, COVID-19-related ARDS has no consistent respiratory subphenotype. Patients diverged from a fairly homogenous to a more heterogeneous population, with trajectories of ventilatory ratio and mechanical power being the most discriminatory. Modelling these parameters alone provided prognostic value for duration of mechanical ventilation and mortality.
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Purpose: There is growing international interest in the implementation of structured osteoarthritis management programs (OAMPs) to deliver best evidence osteoarthritis (OA) care. A consortium of researchers, clinicians and consumers concerned with optimising implementation of OAMPs have established the ‘Joint Effort’ Initiative (the Initiative), endorsed by the Osteoarthritis Research Society International (OARSI) in 2018. A priority action of the Initiative is to evaluate the outcomes and implementation of existing OAMPs.Marked differences between existing international OAMP models include treatments offered, settings and mode of delivery, intensity, duration and health disciplines involved. There is some evidence of effectiveness from randomised controlled trials (RCTs) and longitudinal cohort studies reporting outcomes from OAMPS in different real-world settings, however, this research is still in its infancy. The effects of different OAMP models have not been compared head-to-head and given the prohibitive costs and logistics associated with comparing OAMP models in RCTs, it is unlikely that these trials will take place. Instead, we will leverage research efforts and costs that have already been spent by combining data from existing cohort studies to compare the outcomes of different OAMP models.We aim to combine Individual Patient Data (IPD) from the existing international OAMP cohorts and use meta-analytic techniques to address the following objectives: 1) Compare the short-, medium- and long-term changes in pain, physical function, body weight, Quality of Life, fear of movement and goal achievement between different OAMPs. 2) Determine the short-, medium- and long-term overall effects of OAMPs on pain and physical function for people with knee and hip OA. 3) Examine the characteristics of OAMP participants who achieved/ did not achieve the Patient Acceptable Symptom State (PASS), OMERACT-OARSI responder criteria, and completers vs dropouts. 4) Describe the implementation evaluation outcomes of OAMPsMethods: We will use de-identified IPD from nine existing OAMP clinical cohorts from Australia, Norway, Sweden, Netherlands, UK, New Zealand and USA. Clinical cohorts will be eligible if they are derived from a hip/knee OAMP in a real-world setting with the following components: i) personalised OA care; ii) package of care with reassessment and progression; iii) minimum of two core treatments of education, exercise, and/or weight-loss, and; iv) optional adjunctive treatments. We will include both published and unpublished data.Based on scoping work on the outcomes measures and time points currently collected by each OAMP, our primary outcomes will be the difference in pain (numerical rating scale 0-10) and function (Western Ontario and McMasters Osteoarthritis Index function score (WOMAC)), at 12-weeks. Secondary outcomes will be changes in pain and function at 26- and 52-weeks. Other secondary outcomes at 12-, 26- and 52- weeks will be changes in: body weight; quality of life (EuroQol, Short Form 12); disease specific measures (Knee Injury and Osteoarthritis Outcome score, Hip Disability and Osteoarthritis Outcome score, WOMAC); functional performance (30-second chair stand test, six-minute walk test); fear of movement; and patient satisfaction. We will report against the PASS, OMERACT-OARSI definition of responders/non-responders and examine implementation outcomes where available including the Osteoarthritis Quality Indicator Questionnaire, uptake, reach and fidelity.The IPD will be harmonised and aggregated to create one large dataset. We will use descriptive statistics to compare the characteristics of participants across OAMPs. We will take a two-step approach to IPD meta-analytic techniques. First, we will estimate the change in outcomes for each OAMP (pain, function and other outcomes) with multivariable regression modelling. Second, we will weight and pool estimates using random-effects methods to determine the overall effects on pain and function, account for differences in effects across studies and examine prognostic effects and interactions of characteristics (e.g. baseline symptomatic severity, functional performance) of participants who achieved/did not achieve the PASS, OMERACT OARSI responder criteria and those who completed/dropped out of the OAMPs.Results: This study has received ethical approval from the NSLHD Human Research Ethics Committee (Australia). Ethical approval for use of other cohort data is being sought by researchers in their respective countries. We have performed extensive work with the stakeholders involved to identify appropriate co-collected outcomes and will collaborate with the OA Trial Bank to store and collate the cohort data, the first database of its kind.Conclusions: This project will be the first to compare patient and implementation outcomes across international OAMPs. It will address a priority of the Initiative and make recommendations on the “optimal” OAMP model/s to use.
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Abstract Objective: To describe changes in the health service delivery process experienced by professionals, patients and informal caregivers during implementation of a national programme to improve quality of care of geriatric rehabilitation by improving integration of health service delivery processes. Study setting: Sixteen skilled nursing facilities. Study design: Prospective study, comparing three consecutive cohorts. Data collection: Professionals (elderly care physicians, physiotherapists and nursing staff) rated four domains of health service delivery at admission and at discharge of 1075 patients. In addition, these patients [median age 79 (Interquartile range 71–85) years, 63% females] and their informal caregivers rated their experiences on these domains 4 weeks after discharge. Principal findings: During the three consecutive cohorts, professionals reported improvement on the domain team cooperation, including assessment for intensive treatment and information transfer among professionals. Fewer improvements were reported within the domains alignment with patients’ needs, care coordination and care quality. Between the cohorts, according to patients (n = 521) and informal caregivers (n = 319) there were no changes in the four domains of health service delivery. Conclusion: This national programme resulted in small improvements in team cooperation as reported by the professionals. No effects were found on patients’ and informal caregivers’ perceptions of health service delivery.
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This study contributes to the employability skills debate by investigating how students’ self-perceived 21st century skills relate to the self-perceived fit between their higher education curriculum and their future labor market for a sustainable entry to this labor market. Survey data from 4670 fourth-year students over a period of four years were analyzed. Furthermore, out of this group, 83 students were monitored longitudinally over their full educational student careers. Results showed a positive relationship between students’ self-perceived 21st century skills and their self-perceived “education-future labor market fit”. Among more recent cohorts, a significant improvement in their self-perceived 21st century skills was found. Overall, this study indicated that in order to deliver “employable” graduates, students need to be thoroughly trained in 21st century skills, and their development should be retained and expanded. This is one of the few studies that uses a vast amount of both cross-sectional and longitudinal data on skills and labor market perspectives among new graduates.
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Background: Early identification of older cardiac patients at high risk of readmission or mortality facilitates targeted deployment of preventive interventions. In the Netherlands, the frailty tool of the Dutch Safety Management System (DSMS-tool) consists of (the risk of) delirium, falling, functional impairment, and malnutrition and is currently used in all older hospitalised patients. However, its predictive performance in older cardiac patients is unknown. Aim: To estimate the performance of the DSMS-tool alone and combined with other predictors in predicting hospital readmission or mortality within 6 months in acutely hospitalised older cardiac patients. Methods: An individual patient data meta-analysis was performed on 529 acutely hospitalised cardiac patients ≥70 years from four prospective cohorts. Missing values for predictor and outcome variables were multiply imputed. We explored discrimination and calibration of: (1) the DSMS-tool alone; (2) the four components of the DSMS-tool and adding easily obtainable clinical predictors; (3) the four components of the DSMS-tool and more difficult to obtain predictors. Predictors in model 2 and 3 were selected using backward selection using a threshold of p = 0.157. We used shrunk c-statistics, calibration plots, regression slopes and Hosmer-Lemeshow p-values (PHL) to describe predictive performance in terms of discrimination and calibration. Results: The population mean age was 82 years, 52% were males and 51% were admitted for heart failure. DSMS-tool was positive in 45% for delirium, 41% for falling, 37% for functional impairments and 29% for malnutrition. The incidence of hospital readmission or mortality gradually increased from 37 to 60% with increasing DSMS scores. Overall, the DSMS-tool discriminated limited (c-statistic 0.61, 95% 0.56-0.66). The final model included the DSMS-tool, diagnosis at admission and Charlson Comorbidity Index and had a c-statistic of 0.69 (95% 0.63-0.73; PHL was 0.658). Discussion: The DSMS-tool alone has limited capacity to accurately estimate the risk of readmission or mortality in hospitalised older cardiac patients. Adding disease-specific risk factor information to the DSMS-tool resulted in a moderately performing model. To optimise the early identification of older hospitalised cardiac patients at high risk, the combination of geriatric and disease-specific predictors should be further explored.
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Background: Poor motor skill competence may influence energy balance with childhood overweight as a result. Our aim was to investigate whether the age of motor milestone achievement has changed over the past decades and whether this change may contribute to the increasing trend observed in childhood overweight. Methods: Motor skill competence was assessed in children from the Young Netherlands Twin Register born between 1987 and 2007. Follow-up ranged from 4 up to 10 years. Weight and height were assessed at birth, 6 months, 14 months, and 2, 4, 7, and 10 years. Results: Babies born in later cohorts achieved their motor milestones ‘crawling’, ‘standing’, and ‘walkingunassisted’ later compared to babies born in earlier cohorts (N = 18,514, p <0.001). The prevalence of overweight at age 10 was higher in later cohorts (p = 0.033). The increase in overweight at age 10 was not explained by achieving motor milestones at a later age and this persisted after adjusting for gestational age, sex, and socioeconomic status. Conclusion: Comparing children born in 1987 to those born in 2007, we conclude that children nowadays achieve their motor milestones at a later age. This does not however, explain the increasing trend in childhood overweight.
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De publicatielijst bevat alle publicaties waar Harmen Bijwaard aan bijgedragen heeft in de periode 1998 - 2013
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Background: Pain assessment is a necessary step in pain management in older people in palliative care. In older people, pain assessment can be challenging due to underreporting and atypical pain manifestations by other distressing symptoms. Anxiety, fatigue, loss of appetite, nausea, insomnia, dyspnoea, and bowel problems correlate with pain in palliative care patients. Insight into these symptoms as predictors may help to identify the underlying presence of pain. This study aimed to develop and test a prediction model for pain in community-dwelling frail older people in palliative care. Methods: In this cross-sectional observational study, community-care nurses from multiple organizations across the Netherlands included eligible patients (life expectancy < 1 year, aged 65+, community-dwelling and frail). The outcome pain and symptoms were assessed by means of the Utrecht Symptom Diary. Also, demographic and illness information, including relevant covariates age, sex and living situation, was collected. Multivariable logistic regression and minimum Akaike Information Criterion(AIC) were used for model development and Receiver Operating Characteristics(ROC)-analysis for model performance. Additionally, predicted probability of pain are given for groups differing in age and sex. Results: A total of 157 patients were included. The final model consisted of insomnia(Odds Ratio[OR] = 2.13, 95% Confidence Interval[CI] = 1.01–1.30), fatigue(OR = 3.47, 95% CI = 1.11–1.43), sex(female)(OR = 3.83, 95% CI = 2.11–9.81) and age(OR=-1.59, 95% CI = 0.92–1.01) as predicting variables. There is an overall decreasing trend for age, older persons suffer less from pain and females have a higher probability of experiencing pain. Model performance was indicated as fair with a sensitivity of 0.74(95% CI = 0.64–0.83) and a positive predictive value of 0.80(95% CI = 0.70–0.88). Conclusions: Insomnia and fatigue are predicting symptoms for pain, especially in women and younger patients. Further testing of the model in external cohorts is needed before clinical adoption.
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This study aimed to identify simple rules for allocating chronic obstructive pulmonary disease (COPD) patients to clinical phenotypes identified by cluster analyses.Data from 2409 COPD patients of French/Belgian COPD cohorts were analysed using cluster analysis resulting in the identification of subgroups, for which clinical relevance was determined by comparing 3-year all-cause mortality. Classification and regression trees (CARTs) were used to develop an algorithm for allocating patients to these subgroups. This algorithm was tested in 3651 patients from the COPD Cohorts Collaborative International Assessment (3CIA) initiative.Cluster analysis identified five subgroups of COPD patients with different clinical characteristics (especially regarding severity of respiratory disease and the presence of cardiovascular comorbidities and diabetes). The CART-based algorithm indicated that the variables relevant for patient grouping differed markedly between patients with isolated respiratory disease (FEV1, dyspnoea grade) and those with multi-morbidity (dyspnoea grade, age, FEV1 and body mass index). Application of this algorithm to the 3CIA cohorts confirmed that it identified subgroups of patients with different clinical characteristics, mortality rates (median, from 4% to 27%) and age at death (median, from 68 to 76 years).A simple algorithm, integrating respiratory characteristics and comorbidities, allowed the identification of clinically relevant COPD phenotypes.
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